text:
Mark Andrew Twitchell (born July 4, 1979) is a Canadian filmmaker convicted of first-degree murder in April 2011 for the murder of John Brian Altinger. His trial attracted particular media attention because Twitchell had allegedly been inspired by the fictional character Dexter Morgan.

Early life and filmmaking ambitions
Born in Edmonton, Alberta, Twitchell dreamed of making blockbuster films and graduated from the Radio and Television Arts program at the Northern Alberta Institute of Technology in 2000. In 2001, Twitchell married an American woman and moved to Illinois, but they divorced in 2004.

In 2007, Twitchell directed Star Wars: Secrets of the Rebellion, a full-length fan film prequel set a few days prior to Star Wars Episode IV: A New Hope. Secrets of the Rebellion included a cameo by Jeremy Bulloch, a British actor best known for his role as bounty hunter Boba Fett in the original Star Wars films. The film, still in post-production, never saw release. Twitchell also scripted Day Players, a buddy comedy. In September 2008, he shot a short horror film entitled House of Cards at a garage he rented in the south end of Edmonton.

Murder of Johnny Altinger
In October 2008, John Brian Altinger, 38-year-old former White Rock, B.C., oilfield equipment manufacturer known to his friends as Johnny, unknowingly interacted with Twitchell on dating website Plenty of Fish. On October 10, 2008, Altinger informed his friends of his plans to meet a woman with whom he had been chatting.  Altinger discovered too late that Twitchell had posed as the woman online in order to lure him into a "kill room" set up in a rented garage being used as a film-studio. Twitchell bludgeoned and stabbed Altinger, before cutting him apart, partially burning him, and then dumping his remains in garbage bags into a storm sewer.

Altinger's friends became concerned after they received emails supposedly from Altinger claiming that his date had taken him on an extended vacation to Costa Rica. At work, a resignation letter arrived by email, but there was no response to a request for a forwarding address for sending a final paycheck. Altinger's friends broke into his condominium, where they found his passport, dirty dishes, and no indication of his having packed for a trip. A homicide investigation was soon launched by the Edmonton Police Service.

Twitchell related an improbable account to police of having met Altinger before his trip to Costa Rica. According to Twitchell, Altinger sold his Mazda 6 to Twitchell for 40 CAD, all the cash Twitchell had on hand. The police, not believing this story, impounded Twitchell's laptop and car, and found Altinger's blood in the car's trunk. Police arrested Twitchell on October 31, 2008, and, on the same day, charged him with the first-degree murder of Altinger.

Trial and sentencing
The key piece of evidence presented by the Crown at Twitchell's first-degree murder trial was a document, entitled "SKConfessions", which stood for "Serial Killer Confessions". The document had been recovered from Twitchell's laptop, despite having been deleted. The document begins with the passage: This story is based on true events. The names and events were altered slightly to protect the guilty. This is the story of my progression into becoming a serial killer. It presented an account of its narrator's planning, failed first attempt, and successful second attempt to lure a man to his garage and murder him, with fake online dating profiles used as bait. It went on to describe the process of dismembering the body and attempts to dispose of the remains.

During his trial, Twitchell admitted to killing Altinger and authoring the document, but claimed he had acted in self-defense. He described the document as fiction based on fact, as if he had planned Altinger's death deliberately, in order to craft a compelling story.

During the trial, Twitchell's interest in the television series Dexter was noted repeatedly, and his personal identification with its lead character, Dexter Morgan, a vigilante serial killer, prompted several media outlets to refer to him as the "Dexter Killer."

Another document found on Twitchell's laptop did not make its way into the evidence file for the jury to read during his trial. Entitled "A Profile of a Psychopath", and believed by investigators to have been written by Twitchell, it is a detailed self-analysis of personality and behavior.
On April 12, 2011, Twitchell was convicted of first-degree murder for the death of Altinger, and sentenced to life in prison without possibility for parole for 25 years.

Attempted murder charge
Twitchell still faced an attempted murder charge for his alleged attack on Gilles Tetreault, a computer company contractor. Tetreault testified that he was lured using the website Plenty of Fish, expecting a date with a young woman named Sheena, only to be attacked by a man in a hockey mask with a stun baton when he arrived at the garage in Edmonton rented by Twitchell. After a violent struggle, Tetreault escaped, but did not report the attack to police. Tetreault claims that he did not report the attack because he was embarrassed. Tetreault was nicknamed 'The One Who Got Away' by several media outlets.

Crown prosecutors considered pursuing a charge of attempted murder after securing a conviction of first-degree murder. Detectives were adamant that they had gathered a mountain of evidence – much of it revealed during the murder trial – while even Twitchell himself admitted on the witness stand to committing the attack. In preparing the case for trial, the Crown had argued in court for the attempted murder and first-degree murder charges to be heard simultaneously as they were part of the same "transaction" of his attempt to become a serial killer. Under Canadian law, charges can only be heard together if they are linked in some way. Court of Queen's Bench Justice Terry Clackson was not convinced by the prosecution's argument that the attack on Gilles Tetreault and the murder of Johnny Altinger were part of the same transaction. He ordered the charges to be severed and heard separately. "The offences are related and connected, but remain discrete," Justice Clackson wrote in his reasons for the decision, "As a result, the attempted murder charge cannot stand on the same indictment as the charge of murder because they are different transactions." On June 17, 2011, an attempted murder charge against Twitchell was stayed in the Court of Queen's Bench of Alberta, meaning that Crown prosecutors could resurrect the charge within a one-year period. Since his conviction of first-degree murder secured a maximum sentence — life in prison with no parole eligibility for 25 years — there was no need to proceed with more charges, and the attempted murder charge against Twitchell was eventually dropped.

Media coverage during trial
Extensive media coverage of the case created debate both inside and outside of the courtroom. Observers argued for and against the media's reporting on the more sensational details of the crime.

Prior to the criminal trial, Crown prosecutors and the defense sought vast publication bans and sealing orders over the police evidence, preventing the media from reporting on the details of the case until the jury would hear it during the future trial. The media fought the application, but the judge agreed to both a sealing order and publication ban, stating in his ruling that "there is a real risk that pretrial publicity will undermine the accused's constitutionally protected right to a fair trial." The jury pool was then polled through a "challenge for cause" procedure to determine if a potential juror had been influenced by the media coverage prior to the publication bans taking effect. When the bans were lifted, a large media presence attended and reported on the trial, including American television programs Dateline NBC and 48 Hours.

Following his first-degree murder conviction, Twitchell used the extensive media coverage of his case as grounds for an appeal. He argued in his notice of appeal that "the media attention surrounding my case was so extensive, so blatant and so overtly sensationalized that it is unreasonable to expect any unsequestered jury to have remained uninfluenced by it, regardless of judges' instructions in the charge." He abandoned his appeal in 2012.

Post-trial media coverage
In December 2012, Michael C. Hall, the actor who played Dexter Morgan, was interviewed by Jian Ghomeshi on the Canadian radio show Q. Hall stated that he did not think Dexter glamorized serial killers. "I would hope that people's appreciation was more than some sort of fetishization with the kill scenes," he said. Ghomeshi brought up Twitchell and Hall said, "I wouldn't stop making Dexter because someone was fascinated by it only in that way. I try to tell myself that their fixated nature would have done it one way or the other, but it seems that Dexter had something to do with it. It's horrifying."

In May 2013, it was reported that Twitchell had purchased a television for his prison cell. Twitchell stated that he had caught up on every Dexter episode that he missed since he was arrested and convicted of first-degree murder.

Twitchell's case was featured in the American magazine Crime Watch Daily on May 1, 2017. Much of that day's program focused on Twitchell's methods and featured interviews with Gilles Tetrault, his first intended victim, and Steve Lillebuen, author of the book The Devil's Cinema, which focused on the case. Part of the report included a return trip by Tetreault to the garage in which the incident had taken place.

Tetreault made several media appearances related to his experience, including Dateline NBC, 48 Hours Mystery, The Fifth Estate, I Survived... on Biography Channel, Dates from Hell on Investigation Discovery, and The Security Brief on REELZ.

Books about the case
 The Devil's Cinema (2012) by Steve Lillebuen, a true crime account of the case and trial, written with the cooperation of Twitchell.
 The One Who Got Away (2015) by Gilles Tetreault, a personal account by the original intended target of Twitchell. 1st Edition. Triplicity Publishing. ; 2nd Edition. CreateSpace Independent Publishing Platform.

See also
 Internet homicide
 Murder of Jun Lin

References

External links

 48 Hours: "Screenplay for Murder" (2012)
 SKConfessions Manuscript
Mark Twitchell's Profile of a Psychopath
 Email exchange between Altinger and Twitchell posing as a dating woman

1979 births
Living people
Film directors from Edmonton
Prisoners sentenced to life imprisonment by Canada
Canadian prisoners sentenced to life imprisonment
Canadian people convicted of murder
People convicted of murder by Canada
Crime in Edmonton
21st-century Canadian criminals
Canadian male criminals
Dexter (series)


The Board of Review handles disputes over the assessment of property, while allowing citizens to discuss possible errors in the assessment of property. An appearance at the local Board of Review is a prerequisite to further appeal to the Michigan Tax Tribunal.
The Downtown Development Authority Mission, as established by Public Act 197 of 1975 is: To correct and prevent deterioration in the established DDA district, to encourage historic preservation, to acquire and dispose of interests in real and personal property, to create and implement development plans in the district, and to promote the economic growth of the district. The goal of the DDA is to implement positive economic and aesthetic changes in downtown Evart.
The Evart Local Development Finance Authority helps seek and assist new industrial business for The City of Evart.
The Library Board's obligation to work toward improvement in library services through well-trained staff and efficient use of funds; to support adequate funding for good library service; and to promote the best possible use of all library resources.
The duties of the Recreation Advisory Board are: Consider and study the reasonable needs of the City recreation program; Serve in an advisory capacity when so required; Act as a recommending body to the City Council on matters of general recreation policy; and formulate and report its findings from time to time to the City Council.
Guide redevelopment of the community in a manner that fosters excellence in the quality of life for all Evart residents and is consistent with sound planning principles and practices.
The Water and Sewer Commission makes monitors city water rates, infrastructure, and preventative maintenance projects. The goal of the Water and Sewer Commission is to provide an adequate uninterrupted, high-quality supply of water to our customers, to collect and treat wastewater, and return clean water to the environment.
The Zoning Board of Appeals approves or denies requests for variances from the City's Zoning Ordinance. They hear appeals on the Building Inspector or Official's decisions as to the interpretations of the Zoning Ordinance.


text:
\section{CONCLUSION \& SUMMARY}\label{sec:conclusion}

Three \gls{dof} floating platforms are a good way of partially emulating microgravity environments as they are present in space applications.
This work introduces a controller for one of the heaviest floating platforms in Europe located within the \gls{orl} at ESTEC, \gls{esa}.

First, this work proposes a dynamic model of the overall system, actuated by eight solenoid-valve thrusters and one \gls{rw}.
Said controller consists of two main components: the trajectory planner and the trajectory follower.
The former pre-computes optimal trajectories that connect two arbitrary states while minimizing the force exerted by the thrusters.
The trajectory follower computes continuous control actions to follow these and any other physically feasible trajectory using a \gls{tvlqr} formulation.
To abide by the binary nature of the thrusters, it uses $\Sigma\Delta$-modulation to transfer the continuous force command onto the thrusters.
Finally, a \gls{kf} estimates the system state, providing feedback for the control architecture.

This work further develops a simulation of the overall system that takes measurement noise and the unevenness of the floor into account.
When testing the control architecture in this simulation, the controller achieves at least \SI{16}{\centi\meter} average Euclidean and \SI{5}{\degree} average angular error.
The controller proves to be robust to arbitrary initial poses on the flat-floor.
In a Monte-Carlo simulation where the robot is spawned at arbitrary initial poses and tasked with finding and following optimal trajectories to the origin, the controller achieves a 100\% success rate.

The controller is further evaluated on the physical system.
A straight-line trajectory is also followed successfully but experiences a drop in performance compared to the simulation.
The average euclidean error approximately doubles, and the angular error increases by one order of magnitude.
The increase in error is mostly attributed to a lack of precise system identification and control authority.

A thorough system identification, including a more precise characterization of individual thrusters and their thrust vectors, will improve the system's performance in the future.
This improved model is helpful in two domains: the output trajectories of the planner will be more representative of the physical system, and the controller will follow these better.
Redesigning some system components to increase control authority will also help to improve accuracy.
The two most promising options are decreasing the overall weight and inertia of the system and increasing the reaction wheel inertia.

Further work at the \gls{orl} intends to implement, test, and compare multiple implementations based on the software framework developed in this work.
More specifically, the future work will include improving the state estimation by adding additional sensors such as a \gls{imu} and eventually decoupling it from the global positioning system.
One approach to improve the control will also be to solve the trajectory optimization problem online and control the system in a \gls{mpc} fashion, increasing resilience to disturbances.

\section{CONTROLLER}\label{sec:controller}

\subsection{Overview}

The block diagram in Figure~\ref{fig:controlstructure} gives an overview of the entire control architecture.
The system consists of two main modules: the trajectory planner and the trajectory tracker.
The planner computes an optimal trajectory a-priori, given system constraints specified by the user.
The resulting trajectory has the form of $N$ knot-points, each comprised of a state and a control vector, which in combination satisfy the dynamics of the system and the specified constraints if physically feasible.
The trajectory tracker then tries to follow the trajectory using three sub-modules: the continuous feedback controller, the modulator, and the observer.
The feedback controller computes the optimal, continuous force required to follow the trajectory, using \gls{tvlqr}~\cite{bertsekas2012dynamic,Underactuated}.
The modulator then chooses opening times for the on/off thrusters to match the continuous force best using a $\Sigma\Delta$-Modulation scheme~\cite{Zappulla2017ExperimentalEM}.
A motor encoder and a \gls{mocap} system provide measurements of the \gls{rw} velocity and the system pose, respectively.
The observer uses the most recent measurements available at the sensors and the commanded control input to optimally estimate the current system state.
The state estimates and the torque commands are computed at \SI{100}{\hertz} while the force command is calculated at a slower \SI{10}{\hertz} to better abide by the physical limitations of the thrusters.
Further, the trajectory follower can follow the previously computed optimal trajectory and any other admissible (physically feasible) trajectory.

\begin{figure}
  \centering
	\includegraphics[width=0.49\textwidth, trim={0 11.05cm 0cm 0cm}, clip]{images/drawIO/ControlStructure}
	\caption{Block diagram of the control architecture, consisting of a trajectory planner and follower (\gls{tvlqr}, a $\Sigma\Delta$-Modulator, and an Observer).}
	\label{fig:controlstructure}
\end{figure}

\subsection{Trajectory Planner: Optimizing over Discrete States and Control Inputs}
\subsubsection{Cost Function}
The cost function $J$ is the main factor determining the shape of the resulting trajectory.
The two qualitative criteria that should be optimized are propellant efficiency and trajectory duration.
Given the actuator limits, there is a minimal time for the system to reach the final state.
This trajectory is called time-optimal.
On the other hand, if the desired finishing time is infinite, the most propellant-efficient action is to do nothing.
In order to find a trajectory that satisfies both criteria, the approach is as follows:

First, find the time-optimal trajectory using the cost function $J = t_f$.
In addition, it is enforced that $t_f \geq 0$.
It is well known that the time-optimal solution for such systems is a ``bang-bang'' controller~\cite{betts2020practical} -- a controller jumping between maximal and minimal control values.
However, it also provides a lower bound for the overall time required to follow the trajectory.

Afterward, to define a desired final time, the time-optimal final time is multiplied with a buffer factor $\alpha$: $t_{f,des} = \alpha \cdot t_f^*$, where the buffer factor $\alpha$ is chosen heuristically to provide slow, smooth movement.
The number of tunable heuristics is the main difference between this approach and simultaneously optimizing the final time and actuation costs.
Simultaneous optimization requires two separate weights for both cost functions, whereas the separation reduces this to one.

The goal is to find the trajectory that minimizes the propellant usage, finishing at the desired time.
The force exerted by the thrusters is approximately proportional to the propellant used; therefore, a reasonable proxy for minimal-propellant is minimal force.
The cost function is then
\begin{align}
	J = \sum_{k=1}^N\vec{u}_k\vec{R}\vec{u}_k^T\;\;,
\end{align}
where $\vec{R}$ is a diagonal matrix that contains the respective weights for each control value.
By choosing a large weight for all thrusters and a small weight for the \gls{rw} the actuation of the thrusters is minimized.

\subsubsection{Direct Collocation}
To find an optimal trajectory that minimizes the above cost functions, we use direct collocation~\cite{hargraves1987,kelly2017}.
Its key aspect is to discretize the trajectory at $N$ instances of time $t_k$, which are denoted as knot-points.
Each knot-point is subject to constraints that reflect the maximal and minimal state and control values and constraints concerning its neighbors.
In particular, the dynamic model (as derived in section~\ref{sec:SystemModel}) must be satisfied.
Since that model is continuous, we use  Hermite-Simpson collocation~\cite{hargraves1987} to integrate its dynamics.
Then it is ensured that the system dynamics are satisfied for any set of subsequent knot-points.
In other words, the state and the control applied at some knot-point must result in the state at the next knot-point according to the integrated dynamics.
From this it is possible to derive a minimization problem on all $N\times\left(\text{Dim}(\vec{x})+\text{Dim}(\vec{u})\right)$  variables.
For the time-optimal problem, the final time adds one more decision variable.
However, the optimization problem that incorporates the binary restriction on the actuators is of the class \gls{minlp}.
These problems are increasingly difficult to solve because they are NP-hard and combine challenges of handling non-linearities with a combinatorial explosion of integer variables~\cite{belotti_2013}.
By relaxing the binary condition on the respective control variables and assuming them to be continuous, the problem reduces to a problem of the class \gls{nlp}, which can be solved significantly faster.
The resulting optimization problem over all states $X$ and control values $U$ at all knot-points is:
\begin{align}
\begin{aligned}
	& \min_{X, U} \left\{J(X,U)\right\}\;\;\;\;\forall k \in [0, N-1]\text{ s.t. } \\
	&\vec{x}(0) = \vec{x}_{init}, \;\;\; \vec{x}(t_f) = \vec{x}_{final}\\
	&\vec{x}_{min} \leq \vec{x}_{k} \leq \vec{x}_{max}, \quad \vec{u}_{min} \leq \vec{u}_{k} \leq \vec{u}_{max}\\
	&\vec{x}_{k+1} - \vec{x}_{k} = \frac{\Delta t}{6}(\vec{f}_k + 4 \vec{f}_{k+1/2} + \vec{f}_{k+1})\\
	& \text{where }	\vec{x}_{k+1/2} = \frac{1}{2}(\vec{x}_{k} + \vec{x}_{k+1}) + \frac{\Delta t}{8}(\vec{f}_{k} - \vec{f}_{k+1})\\
	& \text{and } \vec{u}_{k+1/2} = \frac{1}{2}(\vec{u}_{k} + \vec{u}_{k+1})\\
\end{aligned}
\label{eq:cont_opt_prob}
\end{align}
Readily available, open-source solvers, such as IPOPT (Interior Point OPTimiser)~\cite{Wchter2006OnTI}, using the programming interface provided by Drake~\cite{drake}, find a solution for a zero initial-and final velocity trajectory within ten seconds.
However, this relaxation yields trajectories that demand continuous control input which the discrete or binary actuator cannot provide.
Therefore, any trajectory tracking controller needs to consider how to translate the desired control input into the discrete space.
This is further discussed in subsection~\ref{subsec:trajfollower}.

\subsection{Trajectory Follower}\label{subsec:trajfollower}

\subsubsection{Time Varying Feedback Controller}\label{subsec:trajtracker}

Once there is an optimal trajectory to be followed, the robot should find the controls that, given the current state, propels the robot along the trajectory.
We propose to use a full state feedback controller based on the \gls{tvlqr} formulation.
Solving the \gls{dre} by initializing the cost-to-go with its value at the final time and integrating it backward in time yields the respective cost-to-go matrices at different times $t$ and from this, one can compute the feedback gain matrices $\vec{K}(t)$~\cite{Underactuated}.
The resulting control law is:
\begin{align}
	\vec{u}(t) = \vec{u_0}(t) + \vec{K}(t)(\vec{x}(t) - \vec{x}_0(t)),
\end{align}
where $\vec{u}(t)$ is the desired control input, $\vec{u_0}(t)$ is the feed-forward control from the pre-computed trajectory, $\vec{x}(t)$ is the current state, and $\vec{x}_0(t)$ is the desired state according to the trajectory.
Note that solving the \gls{dre} backward in time implies the controller must pre-compute the gain matrices for a trajectory beforehand, resulting in a few additional seconds of computation time during the initialization.

\subsubsection{Sigma-Delta-Modulator}

Given that there are discrete actuators in the present system, one needs to answer how to modulate the continuous control signal derived in the previous section.
One approach introduced in~\cite{Zappulla2017ExperimentalEM} is using a $\Sigma\Delta$-Modulator, a technique commonly used in analog to digital modulation, to modulate the continuous force onto the binary actuators.
The basic concept of a $\Sigma\Delta$-Modulator is to trigger a pulse as soon as the integrated error between the desired and current output reaches some specific threshold.
The general concept of the $\Sigma\Delta$-Modulator is the following:
\begin{enumerate}
 	\item Sample the continuous signal $u(t)$ at some frequency $f_{smpl}$ using sample and hold.
 	\item Compute the error $e_{\Sigma\Delta}(t)$ by taking the difference of the current thruster output $y_{Thrust}(t)$ (which is already modulated) to the desired value.
 	\item Integrate the error by numeric integration where $\Delta t$ is the time difference between two samples:\\
 	$w_e(t) = \int_{t_{0}}^t e_{\Sigma\Delta}(\tau) d\tau \approx \Delta t\sum_{i = 0}^T e_{\Sigma\Delta}(i\cdot\Delta t)$ .
 	\item Once the integrator value surpasses some threshold, i.e. $w_e(t) > \epsilon$, trigger a pulse.
 	We guarantee equivalence of the integrals of the continuous and modulated signal by choosing the threshold such that a single pulse resets the error integrator to zero.
 	Thus the threshold must be the inverse of the control frequency times the nominal force, i.e., $\epsilon = \frac{f_{nom}}{f_{smpl}}$.
\end{enumerate}
Finally, the modulator feeds back the current output value, closing the loop.

\subsubsection{State-Estimation}

This work assumes that the entire state is available for feedback in the previous sections.
This assumption is not generally satisfied since the \gls{mocap} system only provides pose estimates $(x,y,\theta)$, and numerically differentiating those is not sufficient~\cite{Floris2020}.
Further, all available measurements are subject to noise and thus require some filtering process to improve their quality given some underlying system model.
The standard for this filter is the \gls{kf}~\cite{Kalman1960}.
By combining the knowledge of the underlying system and the measurements optimally, in the sense of a quadratic estimation error, the filter smoothes the data and rejects extreme outliers that fall significantly outside the distribution of the specified measurement error.
This work combines a classical \gls{kf} for the position, its derivative, and the \gls{rw} velocity with a \gls{kf} over the Lie Algebra $SO(2)\times\mathbb{R}$ for the orientation and the angular velocity as given in~\cite{Markovic2017} to achieve full state estimation.

\section{INTRODUCTION}

Space debris is widely recognized as a significant challenge to all future activities in space~\cite{Crowther1241, NEWMAN201830,Kessler1978}.
In the extreme case, it could entirely prohibit the possibility of safe spaceflight.
Becoming known as the ``Kessler-Syndrome'', the described effect gained traction in recent years for multiple reasons.
Firstly, today a significant portion of debris is caused by human activity.
Some of the most significant contributions stem from anti-satellite missile tests and satellite collisions~\cite{Neuneck2008, Kelso2009AnalysisOT}.
Despite stringent requirements on de-orbiting satellites, many community members argue that these are insufficient to avoid the Kessler-Syndrome mentioned above and campaign for \gls{asdr}~\cite{Chatterjee2015,MARK2019194}.

\begin{figure}
	\centering
	\includegraphics[width=0.49\textwidth]{images/anton-with-reacsa-annotated}
	\caption{The first author at the \gls{orl} at ESTEC. An epoxy flat-floor for floating air-bearing platforms, where slight unevenness induces disturbances.}
	\label{fig:orl}
\end{figure}

Given the proximity of the servicing/capturing device and the respective client, the missions carry above-average risk.
Hence, guaranteeing flawless operation as well as possible prior to launch is highly prioritized.
For this purpose, ground-test facilities that provide system-level evaluation are necessary.
The servicing/capturing system will eventually operate in a zero-g environment while all ground facilities are subject to Earth's gravity.
Hence, precisely replicating the entire operating domain proves to be very difficult.

Air-bearing-based platforms have become the most popular testing facility that simulates microgravity, with many examples in use~\cite{10.1007/3-540-45118-8_22,ABF,Papadopoulos2008,redah2019,Wehrmann2017,RYBUS2016239}.

Figure~\ref{fig:orl} depicts one of these facilities: the \gls{orl} at ESTEC, a \gls{esa} facility.
One of the testing platforms at the \gls{orl} provides a realistic actuator assembly, with several cold gas thrusters and a reaction wheel.
This system functions as a base platform for testing new technologies or as a dummy target for capturing tests.
Thus it is of interest to control the system along desired trajectories as a target or to enable the movement of the tested technology.
For all air-bearing-based floating platforms, the most limiting factor for the test duration is the amount of cold gas stored onboard, which provides the necessary pressure to keep the platform floating.
The compressed breathing air also functions as the propellant for the thrusters that control the position and orientation (pose) of the system.
Therefore, a controller aiming to prolong the test duration must use the thrusters in a propellant-optimal manner along any trajectory.
This objective is similarly vital for the control of satellites, as depletion of fuel limits the lifetime of a satellite.

The main contributions of this work are the open-source implementation and validation of a trajectory finding and following controller for free-floating systems, which are subjected to binary actuation constraints.
It proposes to find optimal trajectories between two points in state-space and then use optimal control methods combined with a modulation scheme for the thrusters to follow the desired trajectory.

The remainder of the document is structured as follows:
After introducing the system model in section~\ref{sec:SystemModel}, section~\ref{sec:controller} gives an overview of the control architecture.
Section~\ref{sec:results} carries out an evaluation in simulation and on the physical system before finally summarizing and discussing the results in section~\ref{sec:conclusion}.
\section{RESULTS}\label{sec:results}

\subsection{Simulation}

Before being evaluated on the physical system, this work evaluates the controller in a Gazebo~\cite{gazebo} simulation that incorporates sensor noise and the slight unevenness of the floor.
The simulated sensors are subjected to \gls{awgn} with variances that match the measured variances of the real system ($\sigma_x^2 = \sigma_y^2 = \SI{1e-5}{\meter^2}$, $\sigma_\theta^2=\SI{1e-5}{\radian^2}$ and $\sigma_{\omega_{RW}}^2 = \SI{1e-4}{(\radian\per\second)^2}$).

The simulation includes a heightmap representing the last openly available measurements from~\cite{ORL} to incorporate the unevenness of the flat-floor, which has a maximal deviation of \SI{1}{\milli\meter} over one meter.
For more details about the simulation, the interested reader is referred to~\cite{bredenbeck2022astra}.

\subsubsection{Stabilization}

The system is simulated while being subjected to the instantaneous disturbance consisting of a force and a torque $\vec{d}= \begin{bmatrix}\vec{f}_d & \vec{\tau}_d\end{bmatrix}$ and lasting for $\Delta t$, where:
\begin{align}
\resizebox{0.42\textwidth}{!}{$
\vec{f}_d = \begin{bmatrix} \SI{5000}{\newton} & \SI{5000}{\newton}\end{bmatrix}^T, \;\; \vec{\tau}_d = \SI{1000}{\newton\meter}, \;\; \Delta t = \SI{0.001}{\second}
$}.
\end{align}
The response is shown in Figure~\ref{fig:stab-with-response} and the actuation of the controller in Figure~\ref{fig:stab-with-actuation}.
Accompanying each plot of the controlled system response is a plot of the system response to the disturbance without being controlled to highlight the effect of the controller.

\begin{figure}
	\centering
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/with_controller/groundtrack.pdf}\hfill
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/without_controller/groundtrack.pdf}\\
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/with_controller/coordinates.pdf}\hfill
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/without_controller/coordinates.pdf}\\
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/with_controller/velocities.pdf}\hfill
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/without_controller/velocities.pdf}
	\caption{Ground-track, individual coordinates, and velocities of the system responding to a disturbance (at $T=\SI{0}{\second}$) on an uneven floor in simulation. Left: Controller stabilizing the system at the origin. Right: No controller running. An animation of the stabilization process is given at \href{https://youtu.be/KRYcq3VjQUo?t=4}{\url{https://youtu.be/KRYcq3VjQUo?t=4}}.}
	\label{fig:stab-with-response}
\end{figure}

\begin{figure}
	\centering
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/with_controller/torque.pdf}\hfill
	\includegraphics[width=0.24\textwidth]{images/sim_traj/stabilize/with_ground/with_controller/rw.pdf}\\
	\includegraphics[width=0.4\textwidth]{images/sim_traj/stabilize/with_ground/with_controller/forces.pdf}
	\caption{Actuation required to stabilize the system at the origin on an uneven floor in simulation while being subjected to a disturbance (cf. Figure~\ref{fig:stab-with-response}). Top Left: the torque exerted by the motor onto the RW. Top Right: the resulting RW velocity (raw and observed). Bottom: the thruster activity for all eight thrusters.}
	\label{fig:stab-with-actuation}
\end{figure}

As Figure~\ref{fig:stab-with-response} shows, the controller succeeds in bringing the system back to the origin after the initial disturbance.
It maintains the system within less than \SI{10}{\centi\meter} and \SI{6}{\degree} of the origin.
The unactuated system, on the other hand, drifts over \SI{1.5}{\meter} and performs more than a full rotation.
The offset from the origin of the controlled system is attributed to two factors: the thruster's binary nature and the unevenness of the floor.
The continuous actuation needs to accumulate in the modulator until a firing is triggered, propelling the system through the origin, and the process repeats in the opposite direction.
This well-known behavior for thruster-based systems is referred to as a limit cycle~\cite{Jeon2012}.
At the same time, the controller needs to compensate for the disturbances induced by the flat-floor, further adding to the oscillations about the origin.
In Figure~\ref{fig:stab-with-actuation} the torque clearly shows ``bang-bang'' behavior.
Since the inertia of the \gls{rw}s is two orders of magnitude smaller than the system's inertia, the controller demands high torques quickly alternating between maximal and minimal torque.
However, the \gls{rw} velocity remains within its allowable bounds.
Also, in Figure~\ref{fig:stab-with-actuation}, the thrusters 1, 2, 4, and 7 initially show high activity since they are the ones pointed in negative $x$ and $y$ direction, thus counteracting the disturbance.
Afterward, the thrusters show alternating behavior corresponding to the small oscillations about the origin.
Finally, the thrusters regularly fire to move the system towards the positive $y$ direction (Thrusters 0 and 5) and slightly less frequently towards the positive $x$ direction (Thrusters 3 and 6), which corresponds to the gradient of the floor at the origin.

\subsubsection{Monte Carlo}\label{subsec:monte-carlo}

To demonstrate the generalizability of the controller to different initial locations on the flat-floor the system also undergoes a Monte Carlo test simulation.
For a large ($n = 100$) number of episodes, the robot spawns at random initial poses, whereby $x, y$, and $\theta$ result from drawing from uniform random distributions that span the range $[-2, 2]$, $[-4, 4]$, and $[-\pi,\pi]$ respectively.
The controller computes the optimal trajectory to the origin and starts following it.
An episode is successful when the euclidean distance to the origin, the euclidean velocity as well as the angular error and velocity are smaller than the threshold $\vec{\epsilon}$:
\begin{align}
	&\begin{bmatrix}
		\epsilon_{lin}&\epsilon_{ang}&\epsilon_{lin, vel} &\epsilon_{ang, vel}
	\end{bmatrix} \nonumber\\
	&=\begin{bmatrix}
		\SI{0.05}{\meter}&\SI{0.05}{\meter\per\second}&\SI{0.05}{\radian}&\SI{0.05}{\radian\per\second}
	\end{bmatrix}
\end{align}
Figure~\ref{fig:monte-carlo} shows the results of the Monte Carlo test.
\begin{figure}
	\centering
	\vspace{0.15cm}
	\includegraphics[trim=12cm 0cm 2cm 0cm, clip=true, height=3.8cm]{images/monte_carlo/groundtrack.pdf}
	\includegraphics[height=3.8cm]{images/monte_carlo/velocities_small}\\
	\includegraphics[trim=0cm 1cm 0cm 0cm, clip=true, width=0.45\textwidth]{images/monte_carlo/coordinates.pdf}
	\caption{Monte Carlo simulation of following trajectories to the origin. Each optimal trajectory is computed using $N=100$ knot-points.}
	\label{fig:monte-carlo}
\end{figure}
During the Monte Carlo simulation, the controller commands the system to the origin from all 100 tested initial conditions.
As seen in Figure~\ref{fig:monte-carlo} the trajectories are mostly straight lines with some minor deviations caused by the uneven ground, combined with the noise of the system and the binary thrusters.
One particular trajectory (purple, bottom right of the ground-track) overshoots a desired state along the trajectory at approximately \SI{38}{\second}.
Since the controller only attempts to control the system to the desired state at some time (single planning approach), it returns to a previous location resulting in a loop.
This loop also corresponds to the spikes in velocities (purple).
All trajectories reach the desired region at the origin and slow down to the desired maximal velocity in less than \SI{140}{\second}.

\subsection{Physical System}

\subsubsection{Experimental Setup}

The \gls{rw} experiences stiction at low revolutions per minute.
Thus, to avoid issues, the \gls{rw} is spun up to half its rated velocity before each trajectory.
From this state, the experimenter places the system manually at the origin of the coordinate system before starting the trajectory follower.

\subsubsection{Results}

\paragraph{Stabilization}

This first section also evaluates the system's stabilization capabilities for the physical system.
The disturbance is added by manually pushing the system.
The results are shown in Figures~\ref{fig:real-stabilize-gt} and~\ref{fig:real-stabilize}.

\begin{figure}
	\centering
	\includegraphics[height=3.5cm]{images/real_traj/stabilize/groundtrack.pdf}\hfill
	\includegraphics[height=3.5cm]{images/real_traj/stabilize/coordinates.pdf}
	\caption{Ground-track and individual coordinates of the controller stabilizing the physical system at the origin.
	On the right the desired value is indicated as a dashed line.
	A video is given at \href{https://youtu.be/KRYcq3VjQUo?t=168}{\url{https://youtu.be/KRYcq3VjQUo?t=168}}.}
	\label{fig:real-stabilize-gt}
\end{figure}
\begin{figure}
	\centering
	\vspace{0.15cm}
	\includegraphics[width=0.24\textwidth]{images/real_traj/stabilize/torque.pdf}\hfill
	\includegraphics[width=0.24\textwidth]{images/real_traj/stabilize/rw.pdf}\\
	\includegraphics[width=0.3\textwidth]{images/real_traj/stabilize/forces.pdf}
	\caption{Actuation of stabilizing the physical system (cf. Figure~\ref{fig:real-stabilize-gt}).}
	\label{fig:real-stabilize}
\end{figure}

The system generally exhibits the tendency to drift in negative $x$ and $y$ directions in all experiments.
This tendency implies a slope pointing in this direction, which the heightmap from~\cite{ORL} further supports.
During the stabilization process, the system initially stabilizes within \SI{15}{\centi\meter} and \SI{15}{\degree} of the origin before the disturbance.
The disturbance moves the system about \SI{35}{\centi\meter}, and within \SI{30}{\second} the system stabilizes in the initial region again.
Figure~\ref{fig:real-stabilize} shows that very little thrusting is required to achieve this result, firing no thruster more than once every two seconds during the entire process.
The \gls{rw}, on the other hand, saturates rather quickly after the disturbance.
It quickly reaches its maximum rotational velocity as it attempts to absorb the entire angular momentum put into the system by the disturbance.
Afterward, the thrusters perform the attitude control themselves; thus, the pointing accuracy degrades as larger errors are required to trigger a pulse since thruster usage is penalized more than \gls{rw} acceleration.

\paragraph{Straight-Line Trajectory}

Further, this section evaluates the physical system's performance following a straight-line trajectory (similar to the ones from section~\ref{subsec:monte-carlo}).
The results are shown in Figures~\ref{fig:real-straight_line-gt} and~\ref{fig:real-straight_line}.

\begin{figure}
	\centering
	\vspace{0.1cm}
	\includegraphics[height=4.025cm]{images/real_traj/straight_line/groundtrack.pdf}\hfill
	\includegraphics[height=4.025cm]{images/real_traj/straight_line/coordinates.pdf}
	\caption{Ground-track and individual coordinates of the controller following a straight-line trajectory on the physical system.
	After reaching the final pose of the trajectory the desired value is indicated as a dashed line.
	A video is given at \href{https://youtu.be/KRYcq3VjQUo?t=193}{\url{https://youtu.be/KRYcq3VjQUo?t=193}}.}
	\label{fig:real-straight_line-gt}
\end{figure}

\begin{figure}
	\centering
	\vspace{0.1cm}
	\includegraphics[width=0.24\textwidth]{images/real_traj/straight_line/torque.pdf}\hfill
	\includegraphics[width=0.24\textwidth]{images/real_traj/straight_line/rw.pdf}\\
	\includegraphics[width=0.3\textwidth]{images/real_traj/straight_line/forces.pdf}
	\caption{Actuation of following the straight-line trajectory (cf. Figure~\ref{fig:real-straight_line-gt}) on the physical system.}
	\label{fig:real-straight_line}
\end{figure}

The average Euclidean and angular error of the physical system to the desired trajectory are \SI{0.325}{\meter} and \SI{23.8}{\degree} respectively, in a trajectory covering \SI{2.2}{\meter} and \SI{180}{\degree}.
In particular, the error in the $x$-axis is significant.
This error is due to the slope in that region of the flat-floor, with a gradient in the negative $x$-direction.
As in the stabilization case, the heightmap shows a local minimum adjacent to the trajectory.

Further, the \gls{rw} saturates at both ends of the allowable range throughout the trajectory.
At each instance, the orientation deviates more significantly from the desired orientation, implying that large desired changes in angular momentum of the entire system quickly lead to \gls{rw} saturation.
The controller then performs orientation control using only thrusters, thus, losing precision.
However, at the end of the trajectory, the \gls{rw} recovers from saturation, and the pointing accuracy at the final state is within \SI{10}{\degree}.
The thrusters were firing appropriately, never exceeding one fire per second for an individual thruster.
Moreover, when considering the thruster on-times, as depicted in Table~\ref{tab:thruster-on-time}, it shows an increase of less than one order of magnitude for the overall thruster on-times compared to the optimal value.
Some individual thrusters (0, 5) even decrease on-time, whereas others increase by one or multiple orders of magnitude while compensating for uneven ground.
Note that the long on-times for thrusters 1 and 4 stem from compensating the previously mentioned error in $x$-direction since these thrusters are enacting a force in positive $x$-direction throughout the middle section of the trajectory.

\begin{table}
 	\centering
	\vspace{0.0cm}
 	\caption{Optimal and real thruster on-time (cf. Figure~\ref{fig:real-straight_line-gt}).}
 	\resizebox{0.48\textwidth}{!}{
 	\begin{tabular}{@{}c|cccccccc|l@{}}\hline
 	Thruster & 0 & 1 & 2 & 3 & 4 & 5 & 6 & 7 & $\Sigma$\\\hline\hline
 	Optimal & \SI{0.499}{\second} & \SI{0.004}{\second} & \SI{0.061}{\second} & \SI{0.296}{\second} & \SI{0.004}{\second} & \SI{0.499}{\second} & \SI{0.296}{\second} & \SI{0.061}{\second} & \SI{1.72}{\second}\\
 	Real & \SI{0.30}{\second} & \SI{3.40}{\second} & \SI{0.70}{\second} & \SI{1.30}{\second} & \SI{3.40}{\second} & \SI{0.30}{\second} & \SI{1.30}{\second} & \SI{0.70}{\second} & \SI{11.40}{\second}\\\hline
 	\end{tabular}
 	}
 	\label{tab:thruster-on-time}
\end{table}

\paragraph{Discussion}

The experiments demonstrate that the general behavior of the simulation and the physical system is similar, indicating that the simulation is a realistic representation of the scenario.
The controller manages to stabilize the system and follow a pre-computed trajectory.
However, the deviations from the set values are more significant in the physical system.
Besides shortcomings in the simulation, such as the idealized thrusters, the limited heightmap resolution, and a single ground-contact point, other factors that influence this difference stem from the hardware.
The most significant factors that influence the overall system performance are the lack of precise system identification and limited control authority.
The former is outside the scope of this work; thus, it relies on previous inertial measurements of the system.
An offset here contributes to the size of the limit-cycle the system exhibits around the desired orientation.
This effect is particularly powerful since the control architecture combines the controller with a \gls{kf}, such that the model errors accumulate and deteriorate performance~\cite{doyle1978}.
Improving this model regarding inertial parameters, thrust, and thrust vectors for individual thrusters will significantly improve the system performance.

The latter is a consequence of the initial design of the floating platform.
The system's high mass means that the thrusters can hardly compensate for the effects of any unevenness of the floor.
For example, on a slope of \SI[per-mode=fraction]{1}{\milli\meter\per\meter} the system experiences a constant disturbance force of approximately \SI{2.2}{\newton}.
In an ideal scenario aligning two thrusters exactly with this disturbance force, they can provide approximately \SI{20}{\newton} in the opposing direction.
Thus to compensate for the disturbance force, the thrusters would have to have an on-time of at least 10\%.
This firing rate is already larger than the firing rate observed for the followed straight-line trajectory.

Additionally the \gls{rw} saturates very fast.
Given the inertias of the entire system and the \gls{rw} it can compensate only for a slight change in angular velocity of approximately \SI{6}{\degree\per\second}.
Despite the trajectory planner incorporating this limitation, any disturbance that imposes an equivalent torque on the system quickly saturates the \gls{rw} and thus degrades the control authority of the system.
One source of such disturbance is the uneven floor.
Another is an unequal nominal force of individual thrusters.
When firing two thrusters that point the same way (e.g., thrusters 0 and 5), the exerted wrench should only contain a force pointing in one direction.
However, assuming a difference between the two thrusters, it also contains a disturbance torque $\tau_d$.
If this difference is only 10\% and one assumes the 10\% thruster on-time to compensate for the floor unevenness, this will saturate the \gls{rw} within \SI{34}{\second} of operation.

All in all, the evaluation shows that this control architecture, while limited by immaturity aspects, is effective for a free-floating system with binary actuation constraints.

\section{SYSTEM MODEL}\label{sec:SystemModel}

The used platform is the combination of three previously existing, modular platforms: \gls{acrobat}, \gls{satsim}, and \gls{recap}~\cite{orgl}.
The platforms are stacked to form the overall system, and each provides a different functionality:
\begin{itemize}
  \item \gls{acrobat} provides the base of the platform.
  Using three New Way \SI{200}{\milli\meter} air-bearings which are supplied with compressed air at \SI{4.8}{\bar} it enables the micro-gravity behavior on the flat ground.
  \item \gls{satsim} provides air tanks that supply the \gls{acrobat} air bearing as well as the thrusters that \gls{satsim} uses to provide thrust to the stack.
  \gls{satsim} combines eight thrusters that are arranged pairwise on each side of the platform to induce forces parallel to the coordinate axes of the local robot coordinate system as indicated in Figure~\ref{fig:reacsa}
  \item \gls{recap} provides the \gls{rw} used for yaw control.
\end{itemize}
Their mass, \gls{moi}, and size properties are shown in Table~\ref{tab:mass_and_size_properties}.
\begin{table}
  \centering
  \vspace{0.15cm}
  \caption{Physical properties of the system.}
  \begin{tabular}{@{}lllll@{}}\hline
  Subsystem & Mass &\gls{moi}& Height & Radius\\\hline\hline
  ACROBAT & \SI{154}{\kilo\gram}& \SI{10.090}{\kilo\gram\meter^2} &\SI{62.5}{\centi\meter}&\SI{35}{\centi\meter}\\\hline
  SATSIM & \SI{50}{\kilo\gram}& \SI{1.416}{\kilo\gram\meter^2} &\SI{20}{\centi\meter}&\SI{35}{\centi\meter}\\\hline
  RECAP & \SI{13.66}{\kilo\gram}& \SI{0.67}{\kilo\gram\meter^2} &\SI{20}{\centi\meter}&\SI{35}{\centi\meter}\\\hline
  RW & \SI{4.01}{\kilo\gram}& \SI{0.047}{\kilo\gram\meter^2}& -- & -- \\\hline\hline
  $\Sigma$ & \SI{221.67}{\kilo\gram}&\SI{12.223}{\kilo\gram\meter^2} & \SI{102.5}{\centi\meter}& -- \\\hline
  \end{tabular}
  \label{tab:mass_and_size_properties}
\end{table}

This section characterizes the overall system.
In particular, this section identifies the thrust by an individual thruster and the motion model.

\vspace{-0.1cm}
\subsection{Thruster Characterization}

The thrusters built into this system are a combination of a tank holding pressurized gas, an intermediate pressure regulator to achieve a lower operating pressure, a regulating solenoid valve, and a Laval nozzle through which the gas escapes.
Solenoid valves only allow for the states on and off.
Thus, their nominal force, when opened, is of interest.
At a regulated operating pressure of $\SI{5.0(2)}{\bar}$ the force is measured to be $\SI{10.0(7)}{\newton}$.
The thrusters can hold this peak force for pulses of \SI{100}{\milli\second} but experience a significant drop for longer pulses in the order of seconds.
In the following, this work assumes that the force is constant for the opening duration, and no pulses long enough to induce significant deviation from this model are considered.

\subsection{Dynamic Model}

The following derives the overall motion model using the thrust identified above and a torque-based model for the \gls{rw}.
First, we define all actuators as in Figure~\ref{fig:reacsa}.
The position $(x,y)$ of the system is defined relative to some world coordinate system, and the orientation $\theta$ is defined relative to that $x$ axis.

\begin{figure}
  \centering
  \vspace{0.15cm}
  \includegraphics[width=0.49\textwidth, trim={0cm 10.5cm 1cm 1cm}, clip]{images/drawIO/reacsa.pdf}
  \caption{Definitions of coordinate system and wrenches imposed by the actuators.}
  \label{fig:reacsa}
\end{figure}

\noindent Using the state and control vectors:
\begin{align}
  \vec{x} &= \begin{bmatrix}x & y & \theta & \dot{x} & \dot{y} & \dot{\theta} & \omega_{RW}\end{bmatrix}^T\\
    \vec{u} &= \begin{bmatrix}\tau & f_0& f_1& f_2& f_3& f_4& f_5& f_6& f_7\end{bmatrix}^T
\end{align}
with the forces of the thrusters $f_0$ to $f_7$, the velocity of the reaction wheel $\omega_{RW}$ and the torque $\tau$ on the \gls{rw}, the resulting continuous state equation is:
\begin{align}
  \begin{aligned}
    &\dot{\vec{x}} = \vec{f}\left(\vec{x},\vec{u}\right) = \begin{bmatrix}
    \vec{0}^{3\times3} & \vec{I}^{3\times3} & 0\\
    & \vec{0}^{4\times7}
    \end{bmatrix} \vec{x}
    \\&+\resizebox{0.4\textwidth}{!}{
    $\begin{bmatrix}&&&& \vec{0}^{3\times7}&&&\\
    0 & \frac{-s_\theta}{m} & \frac{s_\theta}{m} & \frac{-c_\theta}{m} & \frac{c_\theta}{m} & \frac{s_\theta}{m} & \frac{-s_\theta}{m} & \frac{c_\theta}{m} & \frac{-c_\theta}{m}\\
    0 & \frac{c_\theta}{m} & \frac{-c_\theta}{m} & \frac{-s_\theta}{m} & \frac{s_\theta}{m} & \frac{-c_\theta}{m} & \frac{c_\theta}{m} & \frac{s_\theta}{m} & \frac{-s_\theta}{m}\\
    \frac{-1}{I_b} & \frac{r}{I_b} & \frac{-r}{I_b}& \frac{r}{I_b} & \frac{-r}{I_b} & \frac{r}{I_b} & \frac{-r}{I_b} & \frac{r}{I_b} & \frac{-r}{I_b}\\
    \frac{1}{I_w} &&&& \vec{0}^{1\times6}&&\end{bmatrix}\vec{u}$}\;\;,
  \end{aligned}\label{eq:continuousDynamics}
\end{align}
where $s_\theta$ and $c_\theta$ denote the sine and cosine of the respective angle, $m$ is the system mass, $r$ the radius of the cylindrical body, $I_w$ and $I_b$ are the \gls{moi} of the \gls{rw} and the overall system respectively.

\subsection*{Weight Matrices}\label{appendix:weightmatrices}

\begin{table}[ht]
	\centering
	\resizebox{0.5\textwidth}{!}{
	\begin{tabular}{@{}ll@{}}\hline
	& Simulation \\\hline\hline
	$Q_{kf}$ & Diag$\left(\begin{bmatrix}
	                0.1 & 0.1 & & 0.1 & 0.1 & 0.1 & 0.1 & 1
	             \end{bmatrix}\right)$\\
	$R_{kf}$ & Diag$\left(\begin{bmatrix}
	                \num{1e-3} & \num{1e-3} & \num{1e-3} & \num{5e3} & \num{5e3} & \num{5e3} & 1
				  \end{bmatrix}\right)$\\
	$Q_{TVLQR}$ & Diag$\left(\begin{bmatrix}
	                \num{1e4} & \num{1e4} & \num{1e4} & 100 & 100 & 100 & \num{1e-3}
				  \end{bmatrix}\right)$\\
	$Q_{final}$ & Diag$\left(\begin{bmatrix}
	                \num{1e5} & \num{1e5} & \num{1e5} & \num{1e6} & \num{1e6} & \num{1e6} & \num{1e-7}
				  \end{bmatrix}\right)$\\
	$R_{TVLQR}$ & Diag$\left(\begin{bmatrix}
	                \num{1e1} & \num{1e1} & \num{1e1} & \num{1e1} & \num{1e1} & \num{1e1} & \num{1e1} & \num{1e1} & \num{1e1}\\
				  \end{bmatrix}\right)$\\
	$R_{final}$ & Diag$\left(\begin{bmatrix}
	                \num{1} & \num{1} & \num{1} & \num{1} & \num{1} & \num{1} & \num{1} & \num{1} & \num{1}\\
				  \end{bmatrix}\right)$\\\hline
	 & Real System \\\hline\hline
	 $Q_{kf}$ & Diag$\left(\begin{bmatrix}
	                0.1 & 0.1 & & 0.1 & 0.1 & 0.1 & 0.1 & 1
	             \end{bmatrix}\right)$\\
	$R_{kf}$ & Diag$\left(\begin{bmatrix}
	                \num{1e-3} & \num{1e-3} & \num{1e-3} & \num{5e3} & \num{5e3} & \num{5e3} & 1
				  \end{bmatrix}\right)$\\
	$Q_{TVLQR}$ & Diag$\left(\begin{bmatrix}
	                \num{5e3} & \num{5e3} & \num{5e2} & \num{5e2} & \num{5e2} & \num{2e3} & \num{1e-3}
				  \end{bmatrix}\right)$  \\
	$Q_{final}$ & Diag$\left(\begin{bmatrix}
	                \num{5e3} & \num{5e3} & \num{5e2} & \num{5e2} & \num{5e2} & \num{2e3} & \num{1e-3}
				  \end{bmatrix}\right)$  \\
	$R_{TVLQR}$ & Diag$\left(\begin{bmatrix}
	                \num{1} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200}\\
				  \end{bmatrix}\right)$\\
	$R_{final}$ & Diag$\left(\begin{bmatrix}
	                \num{1} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200} & \num{200}\\
				  \end{bmatrix}\right)$\\\hline
	\end{tabular}
	}
	\caption{Weight Matrices used for the observer and controller for the simulation and the real-system}
	\label{tab:weight-Matrices}
\end{table}

\section*{APPENDIX}

\bibliographystyle{ieeetr}

redpajama_set_name: RedPajamaArXiv


50+ years of playing pool. Author of five pool books, PBIA & ACS instructor, MVP winner.
Hobbies: Pool, more pool, and more more pool.
Favorite Quotes: "Let that be a lesson to you." -from my father EVERY time I screwed up.


text:
Last edited by Bakinos
4 edition of Utility demand-side management programs for elders found in the catalog.
changes in the last five years
Published 1993 by National Consumer Law Center in [Boston, Mass.?] .
Older people -- Energy assistance -- United States,
Public utilities -- United States,
Energy conservation -- United States
Other titles Utility demand side management programs for elders.
Statement by Nancy Brockway ... [et al.].
Contributions Brockway, Nancy., National Consumer Law Center.
Demand Side Management The Dubai Supreme Council of Energy strives at rationalization of energy use while ensuring environmental sustainability in the Emirate of Dubai. Therefore a governance framework is set to streamline existing energy practices across the DSCE entities to . Demand-side management (DSM) programs run by electric utility companies to promote energy efficiency attempt to counteract market failures in the electricity markets in order to increase investment in energy efficient technology. However, the effectiveness of these programs is inhibited by the disincentives facing utility Size: KB.
Demand Side Management: Overview of Key Issues (Power of Choice Bookshelf Series, Vol 1) ISBN ISBN Why is ISBN important? ISBN. This bar-code number lets you verify that you're getting exactly the right version or edition of a book. Demand-side management grows up Kathleen Wolf Davis In the old days, demand-side management (DSM) was almost exclusively about turning things off—pool pumps, air conditioners—in order for the local utility to survive those peak electricity use moments with a bit more breathing room (and no breath-holding).
Editor Note: Demand-Side Management (DSM) is an electric-utility program where all ratepayers subsidize the energy conservation investments of those ratepayers who participate in the program. Dan Simmons, director of state affairs for the American Energy Alliance and for the Institute for Energy Research in Washington, D.C., submitted the following testimony in opposition to Georgia . ment Curves built up from specific projects and programs to reduce GHGs. Energy Efficiency and Demand Side Management Programs are the first steps towards implementing the low carbon strategy. Recognizing the global challenge from climate change impacts, the Govern-ment prepared five scenarios designed to decrease GHG emissions (see Figure 2).File Size: KB.
Before the Federal Energy Regulatory Commission
Existence of a control satisfying Mangasarians sufficiency conditions for optimality makes these conditions necessary
Lets Go Fishing!
Mexican cooking
SuperCalc users guide and reference manual.
Quartet no. 1, op. 49
Using literature in the middle school curriculum
Old Town Clock Church
Semantic-enabled advancements on the Web
Cancer Journey: Issues For Survivors, A Training Program For Health Professionals, July 1998.
Perceived peace-mindedness of the superpowers
Eulogies.
Psychology of sex
Utility demand-side management programs for elders Download PDF EPUB FB2
Demand side management (DSM) activities in the electric power industry. The report presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year.
Also present are discussions and more detailed data on energy savings, peak load reductions and costs attributable to. Get this from a library. Utility demand-side management programs for elders: changes in the last five years. [Nancy Brockway; National Consumer Law Center.; United States.
Administration on Aging.;]. Primer on Demand-Side Management With an emphasis on price-responsive programs PREPARED FOR The World Bank H Street N.W. Washington, DC PREPARED BY Charles River Associates College Avenue, Suite 26 Oakland, California February CRA No.
DFile Size: KB. Chapter 3 Demand-Side Resources Current Situation Utilities in many states have been implementing energy efficiency and load management programs (collectively called demand-side resources), some for more than two decades.
According to one source, U.S. electric utilities spent $ billion on. Energy demand management, also known as demand-side management (DSM) or demand-side response (DSR), is the modification of consumer demand for energy through various methods such as financial incentives and behavioral change through education.
Usually, the goal of demand-side management is to encourage the consumer to use less energy during peak hours, or to move the time. Electric Utility Demand-Side Management Executive Summary Background Demand-side management (DSM) programs consist of the planning, implementing, and monitoring activities of electric utilities that are designed to encourage consumers to modify their level and pattern of electricity Size: KB.
Utility Demand-Side Management Programs Joseph Eto Environmental Energy Technologies Division Ernest Orlando Lawrence Berkeley National Laboratory University of California Berkeley, California December The work describe d in this study was funded by the Assistant Secretary of Energy Efficiency and Renewable Energy.
Electric utility demand side management (DSM) programs were con- ceived following the dramatic energy price increases of the s and early s. Increases in fuel prices during this period were. Define the water utility's conservation goals and objectives.
Create technical service contract with utility. Review customer base to identify and screen customers for demand-side management assistance. Confirm that customers management is committed to implement water efficiency measures.
of Utility. Demand Side Management Programs. M a y 2 0 1 3. B Y A U T H O R I T Y O F. The Florida Public Service Commission. Office of Auditing and Performance Analysis.
Review of. Administrative Efficiency of. Investor-Owned Utility. DSM Programs. Jerry Hallenstein. Senior Analyst. Utility Demand Side Management Programs. Utility Public Benefits Programs MassSave. Home - Log in - Register. Energy Efficiency and Utility Demand‐Side Management Programs Ahmad Faruqui, Ph.D.
Peter Fox‐Penner, Ph.D. The World Bank J The views expressed in this letter are strictly those of the authors and do not necessarily state or reflect the views of The Brattle Group, Size: KB.
Demand-Side Management Programs Annual Summary May SECTION 1 EXECUTIVE SUMMARY SoCalGas's Demand-Side Management (DSM) activities in were limited to carryover commitments from program years through This year, the DSM Annual Summary and Technical Appendix encompasses primarily the.
Electric Power Systems Research, 8 (/85) - Demand-Side Management: Research Opportunities for Electric Utilities LAWRENCE J. HILL and ERIC HIRST Energy Division, Oak Ridge National Laboratory, Oak Ridge, TN (U.S.A.) (Received August 4, ) SUMMARY Because of dramatic changes in electricity costs, prices, and consumption during the past decade, electric utilities Cited by: 2.
DEMAND-SIDE Management (DSM) commonly refers to programs implemented by utility companies to control the energy consumption at the customer side of the meter. Why These programs are employed to use the available energy more efficiently without installing new generation andFile Size: 1MB.
Demand Side Management How Do DSM Programs Work: • Energy Efficiency (EE) programs accumulate savings year-over-year that can, in aggregate, offset future load growth and reduce peak system demand.
–Requires a volume of scale, many measures –Measures have varying lifetimes or persistence, tracking is requiredFile Size: KB. A recent study from Lawrence Berkeley National Laboratory pegs the overall cost of public power energy savings at $/kWh — but for residential customers, costs.
The smart grid and the promise of demand-side management 43 •Two-way networks. Smart grid networks allow utilities to collect usage data and verify reduced demand (load shed), as well as send time-of-use rates and other information to the customer.
Network costs are low enough to justify near-ubiquitous deployment, allowing utilities toFile Size: KB. Electric utility demand side management (DSM) programs seek to reduce electric loads from the end-user or consumer through energy efficiency (EE) and load-shaping measures.
Successful demand side management programs, stimulated by state incentives, requirements, and financial structures, can reduce the amount of electricity a utility must. (ce) As used in this rule, "demand-side management" or "DSM" means the planning, implementation, and monitoring of a utility activity designed to achieve energy efficiency or demand response.
influence customer use of electricity that produces a desired change in a. The Leading Cost Effectiveness Tool for Energy Efficiency, Demand Side Management and Demand Response Programs.
• AESP Innovative Product Award Winner • Most accurate cost effectiveness testing DSMore • Integrates with IRP Planning DSMore is the only modeling tool for Energy Efficiency, DSM and Demand Response that.Module Demand-side management SUSTAINABLE ENERGY REGULATION AND POLICY-MAKING TRAINING MANUAL page iv.
MODULEDEMAND-SIDEMANAGEMENT page 1. MODULEOBJECTIVES Moduleoverview an individual utility, industry or commercial company, at the national level,File Size: KB. The Year of the Customer: 5 demand management trends to watch in Industry insiders see technology allowing customers and utilities more control over power consumption in .
travelingartsfiesta.com - Utility demand-side management programs for elders book © 2020

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: HTML/CSS table-layout fixed but want one td to be a smaller width I have a table with 4 columns. I want the first one to be a fixed 5% and the next 3 to be a fixed 20%. So in order to make sure the last 3 are always the same width I am using table-layout:fixed. However, this is causing the first td to be the same width as the last 3 columns.
Here's my HTML:

<input type="checkbox"/>
{{COMPONENT_NAME}}
{{CO}}
{{PANEL_OPTIONS}}

And my CSS:
.creatorOptionsTable {border-collapse: collapse; width: 80%; table-layout: fixed;}
.creatorOptionsTable tr {border-bottom: 1px solid black;}
.creatorOptionsTable td {padding: 5px 3%; width: 20%; border-left: 1px solid black;    word-wrap: break-word}
 .creatorOptionsTable td.groupsOptionsCheckboxCell, .creatorOptionsTable th.groupsOptionsCheckboxCell {width: 5% !important;  text-align: center; border-left: none;}

Note, I'm aware that I haven't included the
 tag in this. But it is there.
Seems like this should be easy, but won't work.

Well here is my entire code:

    Component
    Description
    Panel

<input type="checkbox"/>
{{COMPONENT_NAME}}
{{COMPONET_DESCRIPTION}}
{{PANEL_OPTIONS}}

A: That should work just fine.  That's not all your HTML though right?  Make sure you declare the table class as well.  I have edited the code to take your entire HTML sample into account.  The problem was that you had no CSS rules for your ths declared, so they were impacting the width of your tds.  Let me know if this still doesn't work, although it works fine in jsfiddle (http://jsfiddle.net/QWsZT/2/).
HTML:

    Component
    Description
    Panel

<input type="checkbox"/>
{{COMPONENT_NAME}}
{{COMPONET_DESCRIPTION}}
{{PANEL_OPTIONS}}

CSS:
.creatorOptionsTable {border-collapse: collapse; width: 80%; table-layout: fixed;}
.creatorOptionsTable tr {border-top: 1px solid black;}
.creatorOptionsTable tr.firstRow {border-top: none;}
.creatorOptionsTable td {padding: 5px 3%; width: 20%; border-left: 1px solid black; word-wrap: break-word}
.creatorOptionsTable td.groupsOptionsCheckboxCell, .creatorOptionsTable th.groupsOptionsCheckboxCell {width: 5% !important;  text-align: center; border-left: none;}
.creatorOptionsTable th {padding: 5px 3%; width: 20%; border-left: 1px solid black; word-wrap: break-word}
.creatorOptionsTable th.groupsOptionsCheckboxCell, .creatorOptionsTable th.groupsOptionsCheckboxCell {width: 5% !important;  text-align: center; border-left: none;}

A: Ah! I found it. I had this here before I decided to use table-layout: fixed:
.creatorOptionsTable {width: 80%;}

Take that out, and it's fixed. Thanks for help anyway guys!

A: ahhh so you are doing a silly mistake check in your th tag what you have written

do you think its right.

A: First, you are misunderstanding what this means:
.creatorOptionsTable { width: 80%; }

This sets the table element to 80% of the parent element.  So if your parent is 1000px -- this would be telling the browser, "make this table 800px".  THEN, it orders the width of the columns.
Second, if you are going to set the width of each column, it must equal 100%.  The browser can't account for all columns totalling less the 100%.  It would be like saying: there are 8 slices of pizza: Joe ate 1, John ate 2, Sam ate 2, Steve ate 2 -- we ate the whole pizza -- FALSE.
Understanding that, if you want one column to be 1/4th of the other three columns.  Should be about 8%, and 30%, 31%, 31% (or just do 10, 30, 30, 30).  Or you can just set the width of the 3 the same, and the narrow will fill the remaining space.

A: Set the general width of td to like 30px and fix it with max-width, then set the width of the other 3 to 20% with recurring +td (td+td means second td and on, td+td+td means third td and on, etc...)
/*Set first (general) width fixed*/
.creatorOptionsTable td {
    width: 30px;
    max-width: 30px;
}
/*Set recurring cells' width 20%*/
.creatorOptionsTable td+td {
    width: 20%;
}

Also put the table inside a div with a width of 80% and set the width of the table to 100%:
div.container {
    max-width: 80%;
}
.creatorOptionsTable {
    width: 100%;
    word-wrap: break-word;
}

redpajama_set_name: RedPajamaStackExchange


text:
Cerraty - Chagi
Ceruozzi - Cervellini
Elena - Emil
Elizabeth Cervantes
Elizabeth R Cervantes
Elizabeth R Cervantes (1950 - 2003)
Woodburn, Marion County, Oregon 97071
Elizabeth R Cervantes of Woodburn, Marion County, Oregon was born on September 30, 1950, and died at age 52 years old on February 20, 2003.
Elizabeth R Cervantes Elizabeth Cervantes (1950 - 2003)
Elizabeth Cervantes' Biography
Family, friend, or fan this Collaborative Biography is for you to show & tell Elizabeth's life so that she is always remembered.
This section is to introduce Elizabeth Cervantes with highlights of her life and how she is remembered. Select the pencil to add details.
Looking for another Elizabeth Cervantes?
What is Elizabeth's ethnicity and where did her parents, grandparents & great-grandparents come from?
Where was Elizabeth born and where did she live?
Did Elizabeth finish grade school, get a GED, go to high school, get a college degree or masters? What schools or universities did Elizabeth attend?
Was Elizabeth a religious woman?
Share what Elizabeth did for a living or if she had a career or profession.
Share highlights of Elizabeth's life. Experiences, organizations, & how she spent her time.
Did Elizabeth serve in the military or did a war or conflict interfere with her life?
The below was generated. Please share Elizabeth's obituary if available, or write one in your own words to preserve her memory.
Elizabeth Cervantes passed away at age 52 years old on February 20, 2003. Elizabeth R Cervantes of Woodburn, Marion County, Oregon was born on September 30, 1950.
Elizabeth R Cervantes lived 12 years shorter than the average Cervantes family member when she died at the age of 52.
The average age of a Cervantes family member is 64.
Who is Elizabeth Cervantes to you? Share memories and family stories, photos, or ask questions.
Find records of Elizabeth Cervantes
Find records of Elizabeth
Elizabeth's immediate relatives including parents, siblings, partnerships and children in the Cervantes family tree.
Elizabeth's Family Tree
Friends can be as close as family. Add Elizabeth's family friends, and her friends from childhood through adulthood.
Refresh this page to see various historical events that occurred during Elizabeth's lifetime.
In 1950, in the year that Elizabeth R Cervantes was born, on October 2, Charlie Brown appeared in the first Peanuts comic strip - created by Charles Schultz - and he was the only character in that strip. That year, Schultz said that Charlie was 4 years old, but Charlie aged a bit through the years.
In 1963, when she was only 13 years old, the British Secretary of War, 46 year old John Profumo ,was forced to resign when he lied about an affair with 19 year old Christine Keeler. Keeler was also involved with the Soviet naval attaché and charges of espionage were feared. No proof of spying was ever found.
In 1972, when she was 22 years old, on June 17th, 5 men were arrested by police in an attempt to bug the Democratic National Committee headquarters in Washington D.C.'s Watergate hotel. The burglars were found to be paid by cash from a slush fund used by the Committee for the Re-Election of the President - the official organization of President Nixon's campaign.
In 1983, when she was 33 years old, "crack" cocaine was developed in the Bahamas and spread to the United States. Previously, cocaine had been cut with other substances, diluting it. Crack was 80% pure and therefore was more addictive. It was also cheaper, making it more easily available to low income neighborhoods.
In 1995, by the time she was 45 years old, on May 19th, the deadliest terrorist attack on American soil - before 9/11 - took place in Oklahoma City. A truck bomb went off outside the Alfred P. Murrah Federal Building in downtown - killing 68 people, injuring more than 680 others, and destroying one-third of the building. The most disturbing images were of children - a daycare center was hit by the bomb. The deadliest incident of domestic terrorism ever, Timothy McVeigh, Terry Nichols, and Michael Fortier were convicted of the bombing.
Other Elizabeth Cervantes Biographies
Elizabeth R. (Salas) Cervantes
Born c. 1980
Elizabeth (Estrada) Cervantes
Elizabeth (Reyes) Cervantes
Elizabeth R. (Hernandez) Cervantes
Elizabeth A. (Bradley) Cervantes
Elizabeth G. (Briones) Cervantes
Elizabeth A. (Tuttlebee) Cervantes
Elizabeth D. (Flagg) Cervantes
Elizabeth (Gutierrez) Cervantes
Elizabeth S. (Farner) Cervantes
Elizabeth A. (Sanchez) Cervantes
Elizabeth G. (Tamayo) Cervantes
Elizabeth (Cordova) Cervantes
Elizabeth (Ramirez) Cervantes
Elizabeth M. (Samudio) Cervantes
Elizabeth (Gaxiola) Cervantes
Elizabeth (Rodriguez-Medina) Cervantes
Elizabeth (Alvarez) Cervantes
Elizabeth R. (Rivera) Cervantes
Elizabeth (Dominguez) Cervantes
Other Cervantes Family Biographies
Jeffery L Cervantes
Jan 6, 1966 - Sep 20, 2010
Carol M Cervantes
Dec 17, 1945 - Jul 15, 2004
Vincente Cervantes
Aug 25, 1921 - Dec 1988
George Cervantes
Aug 22, 1913 - Aug 1984
Carolyn (Rice) Cervantes
Jun 19, 1940 - Apr 15, 2005
Raymond Cervantes
Sep 27, 1912 - May 1980
Maria Cervantes
Mar 27, 1932 - Jul 13, 2003
Soledad D Cervantes
May 9, 1934 - Dec 20, 2010
Jack Cervantes
Jun 23, 1930 - Oct 1971
Edwin Cervantes
Sep 5, 1939 - Jan 5, 2011
Hermitania Cervantes
Jun 25, 1921 - Mar 5, 2004
Julia E Cervantes
Aug 1, 1932 - Sep 7, 2000
Carlos Cervantes
Nov 4, 1913 - Jan 4, 1993
Joseph F Jr Cervantes
Olga Cervantes
Jun 3, 1932 - Jan 31, 2008
Diana Cervantes
Jul 26, 1952 - Jul 1976
Sofia Cervantes
Jan 3, 1904 - Mar 1987
Santiago A Cervantes
Jul 19, 1955 - Jun 29, 2008
Adeline Cervantes
Feb 27, 1910 - Aug 6, 2009
Isabel Cervantes
Jan 18, 1907 - Nov 9, 2003
Help paint a picture of Elizabeth so that she is always remembered.
Who were the people in Elizabeth's life? Link to family and friends whose lives she impacted.


Bruno Hoeft is preparing an IPv6 Talk for the Amsterdam meeting. Networks that are implementing IPv6 in LHCONE can expect to receive requests for input from Bruno.
If your network is planning on providing traffic and flow data at the Amsterdam meeting please respond to this email thread. If enough networks are willing to provide data then we may bring the data together into an additional agenda item. Don't let your network be left out.
Dale indicated that Internet2 is reviewing transit policies in a general sense and that this topic is being discussed in several contexts in addition to LHC networking. Internet 2 will be in attendance at the Amsterdam meeting as an active participate in the LHCONE VRF transit discourse.


Taylor Elementary School is located in Abilene, Texas. The school belongs to Abilene ISD District, and its zip code is 79601-3635. The contact phone number of Taylor Elementary School is (325) 671-4970.
Taylor Elementary School is located at 916 E N 13Th St, Abilene, TX, 79601-3635.


Bookkeeping! For most people, the word alone can be stressful. Many business owners take two common approaches to tackling the issue of bookkeeping.
Yes – it definitely makes sense to outsource your bookkeeping work to a professional bookkeeper with the skills and experience to do the job right.
Outsourcing itself is not a new business concept and companies have been doing it for years. However, many companies are not familiar with the growing area of outsourcing their bookkeeping work. As companies look for ways to survive tough economic times, outsourcing looks to be the most practical way to help streamline cost and effectively allocate money where it is needed.
Start by gathering all the documents that are needed such as invoices, receipts, deposit slips, bills, etc. Then once a week or so send them off to your bookkeeper via fax, email, UPS or regular mail.
Through an online system which you can access from your computer, your professional bookkeeper is able to enter your transactions, reconcile your accounts, set your bills up for easy payment and generate regular, easy to read reports. In a properly designed system, a bookkeeper only takes over the process of tracking transactions such as sales, accounts payable and balancing the books. Only the business owner makes management decisions. With online bill pay, the owner has the final word on who gets paid and when.
Suddenly your bookkeeping gets done faster, more efficiently and with less expense than ever before and you now have complete and up to date books with reports of sales, profits and cash on hand right at your fingertips. But best of all, this can all be done for about half of what a bookkeeper costs as a full-time employee.
Now you can focus on your business and not on work you shouldn't be doing.
Save Money – The number one benefit is the cost savings involved with outsourcing. During times of economic stress, everyone is looking for ways to save money. Did you know that outsourcing your bookkeeping can save you over 50% of the cost of hiring and training a full-time employee? When you outsource your finance needs you work with trained professionals for a lower cost while not worrying about increased costs involved with employee benefits and insurance. Small business owners and professionals are discovering that outsourcing bookkeeping saves payroll and overhead costs and it's a giant step in freeing up valuable time.
Save Time – Bookkeeping is a time consuming and tedious job and it's not for everyone. As a business person, your time is better spent on important matters that will save your company money and bring in profits. Outsourcing this side of work will provide the most efficient use of your company's time. For many business owners just the effort of hiring, training and managing a bookkeeper can take many hours – and if you're doing the books yourself the number of hours is even greater. As a business owner, your time is best spent doing what you do well – working with customers.
More Marketing – The amount that you save with outsourcing your bookkeeping work can be put into marketing your business to gain more customers and more visibility in your market. Getting exposure is the most important and sometimes the most costly part of any business. So why spend money where you don't have to?
Best Tools – Best Talent – Bookkeeping outsourcing companies already have technology and tools in place that can be costly to a business owner. Outsourcing gives you the advantage of having these premium tools for your business while paying a lot less. You also have access to a higher caliber skill level and knowledge base than you might be able to afford in an employee – not to mention the cost of training.
Extra Help When Needed – During peak times of tax and company financial reporting things can get very busy. When you feel like you need more people, having a bookkeeping partner is a great resource. Outsourcing firms can add employees to your account without any operational costs to you.
Books that are inaccurate or do not reflect the true health of your business provide no real clue to managing your business. Being clueless at any level about where you are making money or who is a good customer is not being in control.
Making the decision to outsource is an easy one. If an individual or company can do the work better, faster, and with less cost to you then that work should not remain in-house. Outsourcing has become a universally accepted business tool.
By turning this side of your business over to a company that considers this its core competency, you now have the ability to become more profitable, more efficient and far more competitive by focusing on more important tasks.


text:
Home » Lifestyle » Putting South-East Clare's past in the frame
At the RIC Barracks at Sixmilebridge in 1912 were District Inspector George D'Urban Rodwell, with the Head Constable Michael Tobin in the side car. Behind Tobin is Sergeant O'Sullivan. The RIC man holding the carbine alongside Rodwell is Constable McLoughlin. Constable Gleeson stands with the bicycle. The constable on the right facing the camera is unidentified. With the permission of Patricia Haselbeck Flynn, copyright the Haselbeck Collection
Putting South-East Clare's past in the frame
January 19, 2014	1,605 Views
DIFFERENT facets of life in South-East Clare over a 60-year period have literally been put into the frame in a major photographic exhibition at Limerick City Hall.
At the RIC Barracks at Sixmilebridge in 1912 were District Inspector George D'Urban Rodwell, with the Head Constable Michael Tobin in the side car. Behind Tobin is Sergeant O'Sullivan.
The RIC man holding the carbine alongside Rodwell is Constable McLoughlin. Constable
Gleeson stands with the bicycle. The constable on the right facing the camera is unidentified. With the permission of Patricia Haselbeck Flynn, copyright the Haselbeck Collection
The Street, comprising photographs from The Haselbeck Collection, was officially launched by Heritage Minister Jimmy Deenihan, TD and Mayor of Limerick Kathleen Leddin recently.
In addition, the museum at City Hall hosts a display of his camera equipment, as well as some archival documents illustrating the professional and personal life of professional photographer Franz S Haselbeck.
It will remain open to the public at Limerick City Hall from Monday to Friday from 9am to 5pm until the end of February. Admission is free.
The exhibition follows the publication of a book, Franz S Haselbeck's Ireland, which was compiled by his granddaughter, Patricia Haselbeck Flynn, with 200 selected images from the Haselbeck Collection.
The book followed his career from Dublin to Kerry and concentrates on his work throughout the Mid-West, where he spent most of his career.
Mr Haselbeck worked as head storekeeper and German interpreter in the Shannon Scheme, thanks to his parents, who came to settle in Limerick in the early part of the 20th century.
He photographed the first arrival of equipment for the Shannon Scheme up until the very last, when the German workers left in 1929.
Having taken more than 5,000 shots during his career, Ms Haselbeck Flynn said it was an extremely difficult and time-consuming task to whittle this down to a limited selection for the book and exhibition.
Mr Haselbeck worked as a professional photographer in the Mid-West from 1912 until his death in 1973.
He cycled all over Limerick City and throughout South-East Clare to photograph the important events of his time, including the War of Independence and major construction projects, as well as everyday events around the city.
Today, The Haselbeck Collection is regarded as one of the most important collections of 20th century Ireland, as it chronicles the social, political, military and industrial change through the decades.
Mr Haselbeck's family moved from Germany, via England, to Wolfe Tone Street in the early 1900s before establishing a sausage and pudding craft business in St John's Square.
Franz's artistic temperament saw him pursue a career as a photographer. He served his apprenticeship in Dublin and Paris and settled in Limerick in 1912, where he set up his own studio.
Mr Haselbeck started working initially with wet and dry glass plate negatives and took photographs with a brass mahogany camera. In spite of moving on to cellulose roll film, he kept a back-up copy of all his work, often re-photographying subjects he had taken with new technology.
The exhibition features photographs such as the Shannon Scheme at Ardnacrusha, the RIC at Sixmilebridge on November 30, 1912; RIC Constable Francis Hamill with his sons, Thomas, Michael and Francis, at O'Briensbridge in February 1913 and the Bourke family outside their home at Yardfield, Clonlara in May 1916.
A group of German workers on the Shannon Scheme celebrate their imminent departure from Ireland with a session in the company of their Irish friends. The sign held by the man lying on the grass in the front, reads, Last Sunday in Ireland. Whit Sunday 1929. With the permission of Patricia Haselbeck Flynn, copyright the Haselbeck Collection
Ms Haselbeck Flynn inherited the collection in 1990 and has offered the use of the collection to her native city. She worked in close partnership with Limerick City Museum and Archives (LCMA) in presenting a selection of her grandfather's work.
Having successfully ensured its survival, and through meticulous research, the author of Franz S Haselbeck's Ireland has brought his photographs back for relatives of people he photographed to savour.
She explained, "It was almost as if my grandfather knew that it would be important to the city to record these events, as if he felt I that it was his civic duty. In turn, I felt it to be my own civic duty to try to preserve it for all and have spent the intervening years in that quest.
"This collection of images of early 20th century Limerick and South-East Clare, right though to the 1960s, is both beautiful and fascinating with something of interest for all.
"I am sure my grandfather would be very proud of their use in this wonderful exhibition, especially during City of Culture 2014," she added.
Ms Haselbeck Flynn said photographs were chosen that represented key moments in social history and from a technical and aesthetic perspective.
"We thought the Bourke family from Clonlara, who were beautifully dressed, looked very well outside their house. They were typical of a family of that time, were very appealing and charming. I have been contacted by relatives of that family who have that photograph hanging on their wall once they saw it in the book.
"A lot of people have found their relatives in photographs and have come back to me to express their appreciation, which is very heart-warming," she added.
In addition to working for Shannon Development, she conducted sales and public relations work for Fitzpatrick's Hotel in Bunratty and Killiney. She now works part-time at the University of Limerick as tutor on the Access Transition to University course.
According to Jacqui Hayes, archivist with the LCMA, "Franz Haselbeck enjoyed capturing the major events of his time and through his lens, the people and places come to life. He was very interested in technology, architecture and engineering and his photographs of the great construction projects reflect this passion.
"The Street exhibition is one of the first events on the Limerick City of Culture 2014 calendar and is one of many showcasing the history of the city.
"Patricia Haselbeck Flynn, who holds responsibility for the preservation of her grandfather's collection, has played a central role in curating this exhibition and without her assistance, we would not have been able to bring this project to fruition," he said.
Tags photographic South-East Clare War of Independence
About Dan Danaher
Previous Lectures examine changing landscape
Next Bobby Duggan makes impressive debut
Vast research behind The Time of The Tans
ESB swim warning for Ardnacrusha
Commemoration for Volunteer John Ryan
'Shock and Disbelief' at Sixmilebridge Shooting
THE shooting of two men last outside a pub in Sixmilebridge last night has brought …


As a healthcare professional, you certainly understand the importance of annual and semi–annual physicals and doctor visits. By scheduling these regular visits and check ups, you are likely to stay ahead of any issues by being proactive in your personal health. When you visit your doctor, he or she asks a series of questions, takes your vitals, and looks for any warning signs or potential health risks. Your doctor knows your personal and family health history, so by staying on top of the visits, can ensure that even if a problem does arise, that you are able to get the prescription or make changes to your lifestyle in a proactive manner – not a reactive one.
How does going to the doctor for an annual or semi–annual check up relate to your laboratory? Just like you need to stay on top of your personal health by scheduling regular doctor visits, your lab needs to stay on top of its health, too. Conducting an annual or semi–annual check up can help your lab stay competitive, ensure the vital signs are all in order, and make sure processes are operating smoothly and efficiently.
How Should Your Lab Conduct a Semi–Annual Check Up?
Conducting a semi–annual check up doesn't need to be a long or arduous process – especially if your lab conducts the check up every 6 months. The more often you conduct a check up, the smoother the process and the more your lab staff will understand what's expected of them, and what metrics and vital signs are most important to your lab's success.
Efficient turnaround times (TaTs) are imperative to the success of your lab. Taking a pulse on how your team and your equipment and lab tech is doing in the area of TaT is one of the most important vitals to monitor. While you likely calculate turnaround time each day – and maybe even more than that – the mid year check up is a prime opportunity to evaluate the last half of the year's trending TaTs to ensure that your lab is on target, or above target.
Many innovative labs leverage new technology to help their teams work smarter, faster, and communicate better – both for the benefit of the lab, as well as the patient experience. These labs need complete visibility and improved communication across their workflows and processes, which inevitably improve turnaround time.
Does your lab staff waste time or resources putting together manual and time consuming reports for referring physicians or groups? What is your current reporting process, and are there manual steps that you can work to eliminate? How do you know if your referring physicians or groups are getting the information from the reports that they need? Taking the vitals of the reporting process for your lab can be a daunting process, but a necessary one to evaluate during the mid year check up.
Lab data can be integrated into many electronic medical records that provide "summary reports" and "trends" to visualize patient data. During your mid year check up, review your reports to see how they are generated. Generic reports are not sufficient to manage complex tests or reporting that advanced labs increasingly require, so ensuring your reporting structure is up to par is important for your lab's continued competitive advantage.
While there are many ways to improve output for physicians and increase the value a lab can provide, one way to immediately impact value while improving efficiency is to streamline reporting and increase the number of tests and case types that your lab's reporting software can handle. Advanced labs need the ability to adapt to changing technology and provide interpretive reporting across existing and emerging tests. Platforms like Pathagility – which can serve as a lab's LIMS or Interpretive Reporting Software – or both, can dramatically increase the output while simplifying reporting.
Labs need to deliver reports and lab tests electronically, reliably, and efficiently to referring physicians or clients, all in a timely and affordable manner. Is your lab operating in a connected environment that reduces errors and simplifies processes for everyone involved? Delivering in a competitive market is essential – especially when the patient's well being is at stake. The mid year check up is a great time to evaluate all of your lab technologies and ensure they are working as one cohesive unit, rather than in silos.
Is your technology keeping up with the changes that are happening each and every day in the healthcare and technology world? It's imperative that your lab stop and evaluate your current vitals every few months, but at least twice a year. The mid year check up is a prime opportunity to review the top 3 ways your lab can reduce error, improve efficiency, and save money and resources across your staff. And not only that, labs should use the mid year check up to ensure they have a plan in place for the remainder of the year.
What are other vital signs your lab checks during the year? How do you determine when to make changes?
To learn more about how Pathagility can help your lab establish best practices, request a 30–minute demo.


text:
Q: Psexec does not open the application When I run psexec from my machine to open notepad in the remote machine, I see notepad is running as a process, but nothing is there in the Application list and notepad window has not opened in the remote window.
c:\Users\Ask\Downloads\PSTools>psexec -h -u administrator -p force   \\135.20.230.167 notepad.e

xe
What might be the reason?
Thank you for your help.


text:
Q: Modifing comment into Spark table on Databricks How to modify the comment associated to a table Spark,something like:
ALTER TABLE table CHANGE column1 column1 VARCHAR COMMENT "some comment"

But for the comment table description.
Thanks!

A: There is no option to update an existing comment for a column unless updating it in the COLUMNS_V2 table in metastore. The hack for this is to do
ALTER TABLE table CHANGE column1 column1 VARCHAR COMMENT "temp comment"

then
ALTER TABLE table CHANGE column1 column1 VARCHAR COMMENT "final intended comment"


While working at the Citizen's Climate Lobby table during a recent event, I was approached by a young biologist and student of science who reminded me that science is fluid and that new discoveries often invalidate previously held beliefs. Therefore, he believed that the science on human caused climate change was still being determined. I agree. However, if as a parent you are told by the best pediatricians available that they are 97 percent certain that second-hand smoke will do irreparable damage to your children, what would you do?
Well, today, greater than 97 percent of the world's best climate scientists are warning us that our use of fossil fuels and continued greenhouse gas emissions will significantly change weather patterns, damage ocean life, cause sea level rise and may create other unforeseen catastrophes. We have witnessed the loss of glaciers and sea ice, increased storm intensities, increased flooding, the disappearance of numerous species and severe declines in other species populations that seemingly corroborate the climate scientists' warnings.
So, the choice is ours, do we act on the best know science of today, or do we wait until the science is settled. What do you think we should do?


Cannondale designed the Topstone to help you explore further than your standard road bike will allow. This bike is capable of utilising roads less travelled such as gravel and solid off-road routes. It has been designed with flare handlebars that help to enhance your control when bumps make it tricky. 40c tyres promote brilliant traction that also doesn't slow you down so that you can enjoy riding at speed on your favourite routes. In the top-spec model of the Topstone range, this bike features SRAM's Apex 1 groupset which showcases a 1x11 42t groupset that improves performance in mucky conditions that would usually make front derailleur shifting difficult as well as hydraulic disc brakes that ensure reliable smooth braking on all surfaces and in all weathers. Finally, this model spec's an improved WTB wheelset that is built tubeless ready, preventing silly and annoying punctures which means you can spend more time focusing on having fun and going fast!
Pure gravel goodness. With its high-volume tyres, confident rider position and sporty handling, Topstone is ready to smash out big miles on the backroads, explore routes less travelled, or smooth out the chop on your morning commute.