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IIIT Hyderabad's Fine Analysis Of Traffic Violations
Home / Applied research / IIIT Hyderabad's Fine Analysis Of Traffic Violations
November 12, 2019 November 12, 2019 | Sarita Chebbi
Researchers from IIITH analyse Ahmedabad traffic e-challans data and discover interesting patterns in motorists' behaviour both in terms of repeat offenses as well as fine payment.
– Traffic offenders with more number of e-challans are less likely to pay fines
– Payment of smaller fines preferred over larger ones
– ML model trained on dataset predicts which vehicle is likely to commit a traffic offense in the near future
Last semester at IIITH, a novel elective course titled 'Big Data and Policing' drew over 60 odd students. Taught by Prof. Ponnurangam Kumaraguru (PK), an Associate Prof at Indraprastha Institute of Information Technology, Delhi and current Adjunct Faculty at IIITH (who was a full-time faculty at IIITH on sabbatical when the course was offered), it saw many interesting projects that culminated in an interactive poster presentation session. But one of the classroom projects undertaken by students Aanshul Sadaria, Kanay Gupta, Shashank Srikanth, Hiimanshu Bhatia, and Pratik Jain under Prof. PK's guidance, went on to bear fruit in a research paper titled 'Don't Cross That Stop Line: Characterizing Traffic Violations In Metropolitan Cities' that has now been submitted for review in a conference. For Prof. PK whose expertise lies in privacy and security in online social media, or "anything in society at large, where social computing can come in handy," he confesses that he gets excited about Data Science for social good. Or in this specific case, traffic data whose analysis can help rein in the number of road accidents due to violations.
Electronic Challans
With the Digital India initiative picking up steam and e-governance more of a reality than before, the Indian Police Department too is also making use of Information and Communication Technology (ICT) in monitoring the law and order situation. Big data is being used to note down trends and patterns in the behaviour of crimes with the intention of effectively reducing and preventing such crimes. But apart from serious crimes like murders and robberies, traffic violations too have come under the big data radar. In fact, one of the ways in making traffic police more efficient is in the manner in which traffic violations are recorded and dealt with. Thanks to the CCTV cameras installed at various traffic signals across many Indian states and cities, the Indian police is able to track traffic offenses via a non-contact method where traffic footage identifies the offending vehicle based on the license plate. And in lieu of a paper 'ticket' or receipt issued according to the type of traffic offense committed under the Motor Vehicles Act, 2019, offenders now receive electronic challans or e-challans where they are liable to pay an appropriate fee either online or offline.
Big Data and Policing
For the authors of the research paper, the goal of their project was to see how such digitized data on traffic violations could be analysed to provide useful feedback to improve the system. "With more and more cities moving to e-governance, we wanted to see how to provide useful insights to assist in governance and policing," says Aanshul Sadaria, one of the researchers.
An Ahmedabadi, Aanshul himself had been at the receiving end of traffic challans having recorded a few transgressions that he explained after some self-analysis. "There was a pattern to how the e-challans had been recorded for me. They were at 3pm and at a particular location, because that was when I used to go to my classes, through a particular route. Typically being late to class, I was prone to committing the offense of jumping a red light. That's how I thought we could use data available on the Ahmedabad e-challan website and find similar interesting patterns for the general public," he says.
"Not only did the Ahmedabad police have the most robust kind of a system, but it was also easier to access data online here versus other metropolitan cities where data was secured through captcha," explains Kanay Gupta, another student involved in the research. The researchers collected data on all kinds of traffic challans generated from September 2015 through August 2019. " While Gujarat has a prefix of GJ and Ahmedabad has city number registered as 01, we brute forced through all possible combinations of vehicle registration numbers from AA00 to ZZ99 to find information about challans generated, if any, against every single vehicle registered there," says Aanshul. In this manner, a dataset of over 3 million e-challans was generated. Every e-challan documented has information about location, time, date, type of traffic violation, amount of fine levied and whether it has been paid or not.
Traffic Transgression Trends
From the total number of e-challans found in the dataset, the research team segregated the number of paid versus unpaid challans. A whopping 59,24,30,400 cr is still outstanding to the government as on August 22, 2019. Challans were also characterised based on the type of offense committed – red light violation, riding without a helmet, improper parking, stop line violation, driving without a seatbelt and so on. It was found that jumping a red light accounted for the most number of challans recorded. By analyzing the date and time of challan issual, the researchers discovered a pattern of higher or lower incidences of violations corresponding to celebrations in the city such as festivals or other similar events. When e-challans issued were zero during events such as Rath Yatra, it meant that the police personnel were on security duty. However, during other festivals such as Ganesh Chaturthi and Navratri, there was a notable rise in the number of challans issued. A spatial analysis of the challans also revealed certain hotspots in the city where violations were more likely to occur.
Predicting Repeat Offenses
Apart from plotting trends, the team trained a machine learning model based on the history of registered vehicles getting challans. "Similar to how big data is being used in policing of big crimes, we have made an attempt to predict how likely a traffic offender is to commit an offense again. We achieved 95% accuracy in predicting violations," says Kanay. The researchers could narrow down on features that could predict a vehicle owner's tendency to repeat an offense – known as 'recidivism'. The features included unpaid number of challans: the higher the number of such challans, the greater the chances of repeat offenses, recency of the violation or number of days since last challan was issued and so on.
Insights from this study were handed over to the Ahmedabad police, who requested a similar analysis for the city of Rajkot. "With these kind of findings, the Police can get a sense of the violations that are taking place and the locations where they are happening. It will help in planning where they should dispatch their set of officers. In fact, I foresee that this kind of data can even be used for city planning. The answer to the question of how do I design my roads can actually come from this," says Prof. PK. With the new Motor Vehicles Act (Amendment) 2019, that came into effect from September 1, 2019 and its focus on enhancement of penalties for driving errors as well as violating other road regulations, such an analysis would be crucial. Similarly under the recent road-rationing scheme introduced by the New Delhi government where vehicles with odd-numbered license plates are allowed to ply on the roads on certain days and even-numbered license plates on others, patterning trends in traffic e-challans would be beneficial. "It would be nice to see the data before the implementation and after the implementation, just to show the effectiveness of the rules" says Prof. PK.
For more details on the research paper, see: Don't Cross That Stop Line: Characterizing Traffic Violations In Metropolitan Cities
Sarita Chebbi
Sarita Chebbi is a minimalist runner, practising yogi and baker of all things whole-wheat, and sugar-free. Currently re-learning her ABC's…the one that goes: A for algorithm, B for Bayesian, C for convolutional (neural network)….
Tagged #bigdata, iiith, iiithyderabad
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This is a collection of my favorite Vintage Christmas Greeting Cards that I collected over the years.
Derivatives done by Artsy Bee.
Truly Vintage Christmas Cards with Santa!
Truly Vintage Christmas Cards with stunning Children!


As I've mentioned in previous posts, our 7 year old son is a huge fan of trains. We are very lucky to be living so close to Walt Disney World, where he can ride on two different railways on a regular basis. The steam engines at the Magic Kingdom have always been his favorites. However, more recently, he has really enjoyed trips on the Wildlife Express at Animal Kingdom. Although this locomotive runs on diesel fuel, it is made to look like an old steam engine. It's primary purpose is to transport guests to Rafiki's Planet Watch, but we typically just opt for a round trip journey on the train.


MICHEL, Charles-Henri, 19. Jh. "Méditation de la mort"
Meditationsbild der Kartäuser, 19. Jh.
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New CW Shows Top TVGuide Watchlist
Filed Under:Drama, EMILY OWENS, Mamie Gummer, Skye, Smallville, Stephen Amell, The CW Television Network, TV Guide
Which new shows are TVGuide.com's users planning to watch?
The CW's Arrow currently leads the drama category on TVGuide.com's Watchlist! Arrow stars Stephen Amell as the DC superhero Green Arrow originally introduced on Smallville.
#7 on the drama list goes to The CW's Beauty and the Beast. This series follows Detective Catherine Chandler, who, many years ago, was saved by someone—or something—on the night of her parents' murder. Now, a case presents a clue to who her hero could be.
The CW's Cult tops of the drama category at #10. Investigative journalist, Jeff Sefton, attempts to save his brother from a television show following gone wrong, with the help of a suspicious research assistant for the show, Skye.
On the comedies list Emily Owens, M.D. comes in at #3. The series follows the life of Emily Owens (Mamie Gummer), an intern at Denver Memorial Hospital, as she discovers that atmosphere in the hospital is not that different (unfortunately) than the one she experienced in high school.
From TV Guide News
READ MORE: Brittany Adebumola And Joseph David-Jones Say 'The 4400' Is 'A Beautiful Companion To The Original'
Top New Dramas:
1. Arrow (The CW)
7. Beauty and the Beast (The CW)
10. Cult (The CW) (midseason)
Top New Comedies:
MORE NEWS: Batwoman Star Javicia Leslie Says 'I'm Really Excited For The Villains'
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redpajama_set_name: RedPajamaCommonCrawl


How to view the managed properties of a particular item?
I am able to view the managed properties in the search schema, but what I want to know is how to view the managed properties' values for a particular item?
I am a newbie here and I would really appreciate you people's help.
The easiest way to do this is via a REST call for search.
Not the answer you're looking for? Browse other questions tagged search managed-property or ask your own question.
Backup and restore the Managed properties(Metadata properties) of the search service application in SharePoint 2010?
What (exactly) makes managed properties returning values in Display Template?


A new revelation today, under the things-I-started-and-comfortably-left-unfinished series! How I never completed home projects that I made detailed diagrams for – during exams! Yes! This is like a tradition. Every year, during my final exams in March-May, I get this scientific urge to try my hand at electronics. I do. I always liked electricity, you know, the light bulb..(hehe); I liked circuit diagrams too. I had a set when I was a kid with circuit diagrams given and I used to put those together. I remember, for certain ones, I had even taken the set to my favorite teacher's house to discuss and put them together! If Physics hadn't been ruined for me by those complex equations, I might not have done Pharmacy. Well, I wanted to do Arts, Psychology, and now I'm venturing into Economics. Undecided? No. Circumstantial.
So, this sudden urge would force me to leave my books and focus on coming up with methods for creating a good side-table lamp. I remember two projects. Sorry, two failed projects.
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2. The Big Bang Theory DNA fiasco: I like the show, I do. What I like more is the DNA structure in their living room. I love that. I decided, I shall make a side lamp in the shape of DNA and have tiny lights at every base pair, sugar and phosphate. I planned for tubes through which the wires could go, the type of bulbs or LED lights, the structure, the dimensions. It was a good plan, and I was inspired by Biochemistry, the exam for which I was studying, in my Second Year of College. I made the plan, folded the paper, kept it safely, enough to never be found by anyone, including me. If I didn't have an internship that summer which gave me exactly 8.5 hours at home everyday, I might have done it!
You know me too well! Who am I kidding, I still wouldn't have done it, like everything else!
It's always an adventure to start a new home project, but in time they will become easier and easier to complete with perfection. Keep up the hard work!


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Neodischistus är ett släkte av tvåvingar. Neodischistus ingår i familjen svävflugor.

Kladogram enligt Catalogue of Life:

Källor

Externa länkar

Svävflugor
Neodischistus

redpajama_set_name: RedPajamaWikipedia


text:
Matt was born in 1985 in Bournville, Birmingham, first taking up the guitar at the age of 15 at secondary school under the tuition of Bryan Lester. The following year Matt joined the Birmingham School's Guitar Ensemble (BSGE), working through an eclectic range of musical styles from classical and baroque to flamenco and gypsy jazz.
Matt attended the University of Birmingham from 2003-2007, graduating with a Masters in Physics. During this time, Matt took every opportunity to perform at various weddings and functions, often alongside fellow BSGE alumnus and Birmingham Consevatoire graduate Thomas Abela. Following graduation, Matt attended Oxford University for a year and a half as a research student in the field of the Multiple Sclerosis (MS), a topic close to his heart as his older brother has MS.
After leaving Oxford in 2009, Matt moved back to Birmingham and undertook various volunteering opportunities with the Birmingham branch of the MS Society, driving the branch minibus, helping to organise support groups for ethnic minorities with MS and young people affected my MS. After sitting on the committee for a few months Matt helped to fill a vacancy as Chairman of the branch, representing local MS Society members at regional level.
Since returning to Birmingham Matt has returned to performing at weddings, functions and recitals along with providing private tuition. Keen to build and refine his repertoire and add to his experience of playing at venues such as the Birmingham City Council House, the Adrian Boult Hall and Symphony Hall, Matt has also recently studied under the guidance of Mark Eden and Mark Ashford at the Birmingham Conservatoire.


text:
\section{Introduction}
Learning to control agents in simulated environments has been a challenge for decades in reinforcement learning (RL)~\cite{werbos1989neural,Robinson1989DynamicRD,schmidhuber1991learning} and has lately led to a lot of research efforts in this direction~\cite{silver_mastering_2016,ha2018recurrent,espeholt2018impala}, notably in policy gradient methods~\cite{silver2014deterministic,schulman2015high,haarnoja2018soft}. Despite progress, policy gradient algorithms still heavily suffer from sample inefficiency~\cite{kakade2003sample,wang2016sample,wu2017scalable}. In particular, many of those methods are subject to use as much experience as possible in the most efficient way. However, quantity is not quality: the quality of the sampling procedure also determines the learning curve of the agent and its final performance. Hence, we think that \textit{not all experiences are worth using} in the gradient update. Indeed, some transitions may add noise to the gradient update, diluting relevant signals, and hindering learning. The central idea of SAUNA is to reject transitions that are not informative.

Use of non-informative or misinformative transitions can only mislead the learning process and waste computational time. Amari's natural gradient~\cite{amari:natural} concept concerns the geometry of the search space related to the ``value of information'': this has been studied for long in RL since~\cite{kakade2002natural}. Our work focuses on a different notion of value of information, and treats it differently: we evaluate whether a transition conveys useful information and use it only if it is considered beneficial to learning. For this purpose, we use a measure of the discrepancy between the estimated state value and the observed returns. This discrepancy is formalized with the notion of the fraction of variance explained $\mathcal{V}^{ex}$~\cite{10.2307/2683704}. Transitions for which $\mathcal{V}^{ex}$ is close to zero are those for which the correlation between the value function $V$ and the observed returns is also close to zero. SAUNA keeps transitions where there is either a strong correlation or a lack of fit between $V$ and the returns while avoiding the dilution of useful information by removing useless samples. We consider on-policy methods for their unbiasedness and stability compared to off-policy algorithms~\cite{nachum2017bridging}. However, our method can be applied to off-policy methods as well, and we leave this investigation open for future work.

In summary, in this paper:
\begin{enumerate}
\item We propose to move from a traditional policy-based sampling procedure to a refined sample selection driven by $\mathcal{V}^{ex}$. We explore how transition filtering simplifies the underlying state space and affects performance.

\item We hypothesize that not all samples are useful for learning and that disturbing samples should be rejected to avoid performance loss. We provide experimental evidence corroborating this claim.

\item By combining (1) and (2), we obtain a learning algorithm that is empirically effective in learning neural network policies for challenging control tasks. Our results significantly improve the state of the art in using RL for high-dimensional continuous control.
\end{enumerate}
Section \ref{sec:preliminaries} recalls basic notions of policy gradient methods in RL and the notion of ``fraction of variance explained'' drawn from the statistics literature. Section \ref{sec:relatedWork} sets our contribution within the RL domain. Section \ref{sec:method} introduces SAUNA. Section \ref{sec:exp} provides experimental evidence of the benefit of using our method, and also investigates various experimental aspects of SAUNA. Section \ref{sec:disc} further discusses the method. Finally, Section \ref{sec:conclusion} concludes and draws some lines of future research.

\section{Preliminaries}
\label{sec:preliminaries}
\subsection{Notations}
We consider a Markov Decision Process (MDP) with states $s \in \mathcal{S}$, actions $a \in \mathcal{A}$, transition distribution $s_{t+1} \sim {\cal P} (s_{t},a_{t})$ and reward function $r_t \sim {\cal R} (s_t, a_t)$. Let $\pi(a | s)$ denote a stochastic policy and let the objective function be the expected sum of discounted rewards:
\begin{equation}
J(\pi) \triangleq \underset{\tau \sim \pi}{\mathbb{E}}\left[\sum_{t=0}^{\infty} \gamma^{t} r\left(s_{t}, a_{t}\right)\right],
\end{equation}
where $\gamma \in [0,1)$ is a discount factor~\cite{puterman1994markov} and $\tau=\left(s_0, a_0, r_0, s_1, a_1, r_1, \dots\right)$ is a trajectory sampled from the environment while the agent is following a given policy $\pi$. Let us remind the notions of the value of a state in the MDP framework. The value $V^\pi(s)$ of a state $s$ while following a policy $\pi$ starting in state $s$ is defined by: $V^\pi(s) \triangleq \underset{\tau \sim \pi}{\mathbb{E}}\left[\sum_{t=0}^{\infty} \gamma^{t} r\left(s_{t}, a_{t}\right) | s_0 = s\right]$.

Closely related is the value (or quality) of a state-action pair: the quality $Q^\pi (s,a)$ of performing action $a$ in state $s$ and then following policy $\pi$ is defined by: $Q^\pi (s,a) \triangleq \underset{\tau \sim \pi}{\mathbb{E}}\left[\sum_{t=0}^{\infty} \gamma^{t} r\left(s_{t}, a_{t}\right) | s_0 = s, a_0 = a\right]$. Finally, the advantage function quantifies how an action $a$ is better than the average action in state $s$ (following policy $\pi$): $A^\pi (s,a) \triangleq Q^\pi (s,a) - V^\pi (s)$. MDP theory asserts that there exists an optimal policy $\pi^*$ that maximizes $J$: we denote its value function $V^*$. In practice, value functions are unknown; we denote $V$, $Q$, and $A$ their current estimates.

\subsection{Policy Gradient Methods}
Policy gradient methods aim at optimizing the policy directly~\cite{williams1992simple}.
The policy $\pi$ is often implemented with a function parameterized by $\theta$: learning a policy boils down to finding the best parameters. In the sequel, we use $\theta$ to denote the parameters as well as the policy. In deep RL, the policy is represented by a neural network (the policy network) and is assumed to be continuously differentiable with respect to its parameters $\theta$. When the policy is represented by such a parameterized function, hence by an approximation of a policy, the MDP theory basically breaks down.

In this paper, we consider Proximal Policy Optimization (PPO)~\cite{schulman2017proximal}, an on-policy policy gradient method achieving state of the art performance on a suite of benchmark tasks despite a relatively simple implementation. Very interestingly, PPO is an evolution of TRPO that builds on the notion of natural gradient, hence Amari's notion of ``value of information'' mentioned above. PPO has been shown to outperform TRPO experimentally. By building on PPO, this paper combines two different ideas related to the notion of the value of information. At each episode, PPO collects $(s_t, a_t, r_t)$ samples using its current policy $\theta_k$. After some episodes, using these collected transitions, PPO updates its policy and gets a new one $\theta_{k+1}$:

\begin{equation}
  \theta_{k+1} \gets \underset{\theta}{\mathrm{argmax}} \underset{s_{t}, a_{t} \sim \pi_{\theta_k}}{\mathbb{E}}\left[\mathcal{L}_\text{PPO}\left(s_{t}, a_{t}, \theta_k, \theta\right)\right].
\end{equation}
We use the clipped version of PPO:
\begin{equation}
  \mathcal{L}_\text{PPO}(s_t,a_t,\theta_k,\theta) =
   \mbox{Clip} (A^{\pi_{\theta_k}}(s_t,a_t),
                 \frac{\pi_{\theta}(a_t|s_t)}{\pi_{\theta_k}(a_t|s_t)},
                 \delta),
  \label{eq:min}
\end{equation}
where $
 \mbox{Clip} (A, \alpha, \delta) = \left\{
  \begin{array}{ll}
    \min{(\alpha A, (1+\delta) A)}, A \geq 0 \\
    \min{(\alpha A, (1-\delta) A)}, A < 0.
  \end{array}\right.
$
$A$ is the advantage function introduced above. Clipping makes the training updates more stable: it ensures that the gradient steps do not lead the policy outside of the region of parameter space where the samples collected are informative.

\subsection{$\mathcal{V}^{ex}$: Fraction of Variance Explained}
Now we introduce the key notion of this paper, namely the fraction of variance explained, denoted by $\mathcal{V}^{ex}$. As shown in this paper, a yet elementary use of this concept strikingly improves the performance of policy gradient algorithms. In general terms, $\mathcal{V}^{ex}$ gives some information about the goodness of fit of a model. In statistics, it is also denoted $R^2$, which is a poor notation since this quantity can be negative for non-linear models~\cite{10.2307/2683704} (also, in the context of RL, $R$ usually refers to the return). This quantity is also known as the coefficient of determination. In a regression setting, assume a model $\hat{y}$ aims at predicting $y$ from $x$, given a set of $N$ couples $(x_i, y_i)$, $\mathcal{V}^{ex}$ is defined by:
  \begin{equation}
    \mathcal{V}^{ex} \triangleq 1 - \frac{\mathrm{MSE}}{\mathrm{VAR}}
  \end{equation}
where $\mathrm{MSE}$ is the mean squared error of the model measured on these $N$ couples ($\mathrm{MSE} = \frac{1}{N}\sum_i \left(y_i - \hat{y} (x_i)\right)^2$), and $\mathrm{VAR}$ is the variance of the observed targets $y_i$. $\mathcal{V}^{ex} \le 1$ and:
\begin{itemize}
\item $\mathcal{V}^{ex} = 1$ means that the model perfectly predicts the data ($\mathrm{MSE} = 0$).
\item $\mathcal{V}^{ex} = 0$ means that the model performs as always predicting the average ($\mathrm{MSE} = \mathrm{VAR}$).
\item $\mathcal{V}^{ex} < 0$ means that the model performs worse than merely predicting the mean value ($\mathrm{MSE} > \mathrm{VAR}$).
\end{itemize}

\section{Related Work}
\label{sec:relatedWork}
Our method integrates three key ideas: (a) function approximation with a neural network combining or separating the actor and the critic with an on-policy setting, (b) transition filtering reducing information/signal dilution in the gradient update while simplifying the underlying MDP, and (c) using $\mathcal{V}^{ex}$ as a measure of correlation between the value function and the returns to allow better sampling and more efficient learning. Below, we consider previous work building on some of these approaches.

Actor-critic algorithms essentially use the value function to alternate between policy evaluation and policy improvement~\cite{barto1983neuronlike,sutton2018reinforcement}. In order to update the actor, many methods adopt the on-policy formulation~\cite{peters2008reinforcement,mnih2016asynchronous,schulman2017proximal}. However, despite their important successes, these methods suffer from sample complexity.

In the literature, research has also been conducted in prioritization sampling. While \cite{schaul2015prioritized} makes the learning from experience replay more efficient by using the TD error as a measure of these priorities in an off-policy setting, our method directly selects the samples on-policy. \cite{schmidhuber1991curious} is related to our method in that it calculates the expected improvement in prediction error, but with the objective to maximize the intrinsic reward through artificial curiosity. Instead, our method estimates the expected fraction of variance explained and filters out some of the samples to improve the learning efficiency.

$\mathcal{V}^{ex}$ has already been used in~\cite{merl} as one of the auxiliary tasks for self-assessment of performance. Finally, motion control in physics-based environments is a long-standing and active research field. In particular, there are many prior work on continuous action spaces~\cite{levine2014learning,heess2015learning,lillicrap2015continuous,schulman2015high} that demonstrate how locomotion behavior and other skilled movements can emerge as the outcome of optimization problems.

\section{SAUNA: Dynamic Transition Filtering}
\label{sec:method}
We introduce a general method to filter transitions that contain useful information for policy gradient updates. In this paper, we detail how to couple SAUNA with PPO, an on-policy gradient algorithm achieving state of the art performance. We refer to this combination as PPO+SAUNA. SAUNA can be coupled with other algorithms, especially with non-policy methods such as DQN: we leave this for future work. Below we detail how to adapt the notion of $\mathcal{V}^{ex}$ to RL.

\subsection{$\mathcal{V}^{ex}$ applied to RL}
The fraction of variance that the current estimate of the value function explains about the observed returns corresponds to the proportion of the variance in the dependent variable $V$ that is predictable from $s_{t}$. We define $\mathcal{V}^{ex}_{\tau}$ as the fraction of variance explained for a trajectory $\tau$:

\begin{equation}
  \mathcal{V}^{ex}_{\tau} \triangleq 1 - \frac{\sum_{t\in\tau}\left(R_t-V(s_{t})\right)^{2}}{\sum_{t\in\tau}\left(R_t- \langle R \rangle_\tau \right)^{2}},
  \label{eq:vex}
\end{equation}
where $R_t = \sum_{k\ge{}0} \gamma^k r_{t+k}$, $r_t$ is the immediate reward collected at timestep $t$, $V(s_{t})$ is the current estimate of the value of state $s_t$, and $\langle R \rangle_\tau$ is the average of the $R_t$ in trajectory $\tau$. This definition can be extended from a trajectory $\tau$ to a batch ${\cal B}$ of sampled transitions $\mathcal{V}^{ex}_{{\cal B}}$. In the RL context, the interpretation of $\mathcal{V}^{ex}_{{\cal B}}$ is:

\begin{itemize}
\item $\mathcal{V}^{ex}_{{\cal B}} = 1$: $V$ perfectly explains the observed returns.
\item $\mathcal{V}^{ex}_{{\cal B}} = 0$: $V$ corresponds to a simple average prediction.
\item $\mathcal{V}^{ex}_{{\cal B}} < 0$: $V$ provides a worse prediction than the average of the returns.
\end{itemize}

The intuition is that $\mathcal{V}^{ex}_{{\cal B}}$ close to 1 corresponds to well-predicted returns. $\mathcal{V}^{ex}_{{\cal B}} < 0$ corresponds to a rather large prediction error of the value function, meaning that these samples are useful because the agent has something to learn from. On the other hand, $\mathcal{V}^{ex}_{{\cal B}}$ close to 0 means that the samples do not provide any valuable information to improve the value estimates. We will demonstrate that $\mathcal{V}^{ex}$ is indeed a relevant indicator for assessing self-performance in RL.

\subsection{Estimating $\mathcal{V}^{ex}$}
While sampling the environment, SAUNA rejects transitions for which $V(s_{t})$ is not correlated with returns that have followed $s_{t}$. Therefore, $\mathcal{V}^{ex}_{{\cal B}}$ should be estimated at each timestep and we define $\mathcal{V}^{ex}_{\theta}(s_{t})$ as the prediction of $\mathcal{V}^{ex}_{{\cal B}}$ with parameters $\theta$ at state $s_{t} \in {\cal B}$. In addition, for shared parameters configurations, an error term on the value estimation is added to the objective. The final objective function becomes:
\begin{align}
  \mathcal{L}_{\mathrm{SAUNA}}(s_{t},a_{t},\theta_{old},\theta)=&\;\mathcal{L}_\text{PPO}(s_{t},a_{t},\theta_{old},\theta)-\label{eq:PPO1}\\
    &\;c_{1}\left(V_{\theta}(s_{t})-R_{t}\right)^{2}-\label{eq:PPO2}\\
    &\;c_{2}\left(\mathcal{V}^{ex}_{\theta}(s_{t})-\mathcal{V}^{ex}_{{\cal B}}\right)^{2}
    \label{eq:objVex},
\end{align}
where $c_{1}$ and $c_{2}$ are the coefficients for the squared-error losses of respectively the value function and the fraction of variance explained function. Note that only the term (\ref{eq:objVex}) is specific to SAUNA. (\ref{eq:PPO1}) and (\ref{eq:PPO2}) come from PPO. When the network is not shared between the policy and the value function, SAUNA embeds $\mathcal{V}^{ex}_{{\cal B}}$ to the value function network using a single hidden layer. The rest of the network is unchanged, making our method very easy to use without significantly increasing the complexity of the underlying algorithm.

\subsection{SAUNA Algorithm}
\cref{alg:learning} shows the pseudocode of SAUNA when coupled with PPO. Overall, the resulting algorithm visits a set of trajectories along which it collects useful samples in the sense explained above, assessed with regards to $\mathcal{V}^{ex}$. The mechanism may be viewed as analogous to the method of dropout in deep learning~\cite{srivastava2014dropout,learningtopredict2019} although here dropout happens in the state space of the underlying MDP and is directed by $\mathcal{V}^{ex}$. Once a batch ${\cal B}$ of $T$ such useful samples is collected, SAUNA performs the usual gradient update following the PPO template.

The gradient update concerns the three quantities estimated by SAUNA: the policy parameters $\theta$, line \ref{eq:updatethetaInAlgo}, the value estimation parameters $\phi$, line \ref{eq:updatephiInAlgo}, and the $\mathcal{V}^{ex}$ estimation parameters $\psi$, line \ref{eq:updatepsiInAlgo}. The \textit{if} statement filters the useful samples: $\widetilde{\mathcal{V}^{ex}_{\psi_{k}}}(s_{0:t-1})$ denotes the median of $\mathcal{V}^{ex}_{\psi_{k}}$ between timesteps $0$ and $t-1$, $\epsilon_{0}$ is a Laplace estimator (set to $10^{-8}$), and $\rho$ is the filtering threshold. One may legitimately ask why not use directly $|\mathcal{V}^{ex}_{\psi_{k}}(s_{t})|$ in the predicate. The rationale is practical: the ratio is a standardized measure as the agent learns, stabilized by the median, more robust to outliers than the mean. For better legibility, \cref{alg:learning} does not share parameters between the $\pi$, $V$ and $\mathcal{V}^{ex}$ networks. A version where these parameters would be partially shared is straightforward.

\def\hspace{\fontdimen2\font}{\hspace{\fontdimen2\font}}
\begin{algorithm}
  \caption{SAUNA coupled with PPO.}\label{alg:learning}
\begin{algorithmic}[1]
\State \textbf{Initialize} policy parameters $\theta_{0}$, value function parameters $\phi_{0}$ and $\mathcal{V}^{ex}$ function parameters $\psi_{0}$
\For {$k = 0,1,2,\ldots$}
\State $s_0 \gets$ initial state
\State batch ${\cal B} \gets \emptyset$
\While {size$({\cal B})\leq{}T$}
\State $a_{t} \sim \pi_{\theta_{k}}(s_{t})$
\State \textbf{execute} action $a_{t}$ and observe $r_{t+1}$ and $s_{t+1}$
\If {$\frac{|\mathcal{V}^{ex}_{\psi_{k}}(s_{t})|}{|\widetilde{\mathcal{V}^{ex}_{\psi_{k}}}(s_{0:t-1})|+\epsilon_{0}} \geq \rho$}\label{line:if}
\State \textbf{add} $\left(s_{t}, a_{t}, r_{t}, V_{\phi_{k}}(s_{t}), s_{t+1}, \mathcal{V}^{ex}_{\psi_{k}}(s_{t})\right)$ to ${\cal B}$
\EndIf
\If {$s_{t+1}$ is a final state}
\State $s_{t+1} \gets$ initial state
\EndIf
\EndWhile
\State $\theta_{k+1} \gets\hspace{\fontdimen2\font}\HS\hspace{\fontdimen2\font} \underset{\theta}{\mathrm{argmax}} \sum_{t\in{\cal B}} \mathcal{L}_\text{PPO}\left(s_{t}, a_{t},\theta_k, \theta\right)$\label{eq:updatethetaInAlgo}
\State $\hphantom{\theta_{k+1}}\mathllap{\phi_{k+1}} \gets\hspace{\fontdimen2\font}\HS\hspace{\fontdimen2\font} \underset{\phi}{\mathrm{argmin}} \sum_{t\in{\cal B}}\left(V_{\phi}\left(s_{t}\right)-R_{t}\right)^{2}$\label{eq:updatephiInAlgo}
\State $\hphantom{\theta_{k+1}}\mathllap{\psi_{k+1}} \gets\hspace{\fontdimen2\font}\HS\hspace{\fontdimen2\font} \underset{\psi}{\mathrm{argmin}} \sum_{t\in{\cal B}}\left(\mathcal{V}^{ex}_{\psi}\left(s_{t}\right)-\mathcal{V}^{ex}_{{\cal B}}\right)^{2}$\label{eq:updatepsiInAlgo}
\EndFor
\end{algorithmic}
\end{algorithm}

\section{Experiments}
\label{sec:exp}
We have forked the \textit{stable-baselines} repository~\cite{stable-baselines} and minimally modified the code to incorporate our method. Unless otherwise stated, the policy network used for all tasks is a fully-connected multi-layer perceptron with 2 hidden layers of 64 units. Moreover, the architecture for the $\mathcal{V}^{ex}$ function head is the same as for the value function head.

\subsection{SAUNA in the Continuous Domain}
To assess SAUNA, we compare PPO+SAUNA against its natural baseline PPO. We use six simulated robotic deterministic tasks from OpenAI Gym~\cite{brockman2016openai} using~\textit{MuJoCo}~\cite{todorov2012mujoco}.
\begin{figure}[h]
    \centering
    \subfloat{{\includegraphics[width=.47\linewidth]{Gym/HalfCheetah.pdf}}{\includegraphics[width=.47\linewidth]{Gym/Hopper.pdf}}}
    \qquad
    \subfloat{{\includegraphics[width=.47\linewidth]{Gym/InvertedDoublePendulum.pdf}}{\includegraphics[width=.47\linewidth]{Gym/InvertedPendulum.pdf}}}
    \qquad
    \subfloat{{\includegraphics[width=.47\linewidth]{Gym/Reacher.pdf}}{\includegraphics[width=.47\linewidth]{Gym/Swimmer.pdf}}}
    \caption{Performance of PPO+SAUNA (red) relative to PPO (blue) on 6 \textit{MuJoCo} environments averaged across 6 seeds. X-axis: number of environment steps. Y-axis: total undiscounted return. Shaded areas: standard deviation.}
    \label{fig:mujoco}
\end{figure}The two hyperparameters required by our method ($\rho=0.3$ from Eq.~\ref{eq:vex} and $c_{2}=0.5$ from Eq.~\ref{eq:objVex}) and all the others (identical to those in~\cite{schulman2017proximal}) are exactly the same for all tasks.

We made the choice of not tuning the hyperparameters for each algorithm and for each task to have a tougher assessment of SAUNA: only SAUNA-specific hyperparameters $\rho$ and $c_2$ have been tuned by grid-search. Hence, the performance we report for SAUNA is not necessarily the best that could be obtained with parameter tuning. The graphs reported in~\cref{fig:mujoco} show that our method outperforms PPO on all considered continuous control tasks.

We then experiment with the more difficult, high-dimensional continuous domain environment of \textit{Roboschool}~\cite{klimov2017roboschool} with various neural network sizes. In~\cref{fig:roboschool-a}, the same fully-connected network as for the previous \textit{MuJoCo} experiments (2 hidden layers each with 64 neurons) is used. In~\cref{fig:roboschool-b}, the network is composed of a deeper and wider 3 hidden layers with 512, 256 and 128 neurons. We trained those agents with 32 parallel actors. In both experiments, PPO+SAUNA performs better and learns faster at the beginning. The gap closes with a larger network and our method does as well as PPO. As resources are limited in terms of the number of parameters and models become less complex, it seems natural that filtering samples according to their expected informational value helps to reduce noise in the gradient update and to speed up learning.

\begin{figure}[h]
  \centering
  \subfloat[]{\includegraphics[width=.47\linewidth]{Roboschool/RoboschoolHumanoidFlagrunHarder-v1-64-64.pdf}\label{fig:roboschool-a}}\hspace{-0.7cm}
  \qquad
  \subfloat[]{\includegraphics[width=.47\linewidth]{Roboschool/RoboschoolHumanoidFlagrunHarder-v1-512-256-128.pdf}\label{fig:roboschool-b}}\\[-1ex]
  \caption{Performance of PPO+SAUNA (red) relative to PPO (blue) on the \textit{Roboschool} environment averaged across 6 seeds. X-axis: number of environment steps. Y-axis: total undiscounted return. Shaded areas: standard deviation.}
  \label{fig:roboschool}
\end{figure}

\subsection{Learning with SAUNA}
\subsubsection{The Advantages of Filtering}
\label{sec:exp_filter}
We further study the impact of filtering out noisy samples by conducting additional experiments in predicting $\mathcal{V}^{ex}$ while omitting the filtering step: the \textit{if} statement (\cref{line:if} of~\cref{alg:learning}) is removed and all transitions are kept in the batch ${\cal B}$. Indeed, SAUNA may improve the agent's performance by simply training the shared network to optimize the $\mathcal{V}^{ex}$ head as an auxiliary task.~\cref{fig:mujoco-nofilter-1} demonstrates the positive effects of filtering out the samples. In addition, we studied the number of filtered out samples per task and its evolution along the training. On average, SAUNA rejects 5-10\% of samples at the beginning of training, 2-6\% near the end.

\begin{figure*}[h]
  \centering
  \subfloat{{\includegraphics[width=.33\linewidth]{Gym/InvertedDoublePendulum-nofilter.pdf}}{\includegraphics[width=.33\linewidth]{Gym/InvertedPendulum-nofilter.pdf}}{\includegraphics[width=.33\linewidth]{Gym/Reacher-nofilter.pdf}}}
  \caption{Performance of PPO+SAUNA (red) relative to PPO (blue) and PPO with the prediction of $\mathcal{V}^{ex}$ but without the filtering out of noisy samples (green) on 3 \textit{MuJoCo} environments averaged across 6 seeds. X-axis: number of environment steps. Y-axis: total undiscounted return. Shaded areas: standard deviation.}
  \label{fig:mujoco-nofilter-1}
\end{figure*}

\subsubsection{The Impact of SAUNA on the Gradients}
\label{sec:grad}
Prior to the gradient update, SAUNA removes the useless transitions. By so doing, we hypothesized that information signals from samples with large $\mathcal{V}^{ex}$ would be less diluted by filtering out samples.
\begin{figure}[h]
  \centering
  \subfloat[]{\includegraphics[width=.5\linewidth]{figures/grad-first.png}\label{fig:grad-first}}\hspace{-0.8cm}
  \qquad
  \subfloat[]{\includegraphics[width=.5\linewidth]{figures/grad-last.png}\label{fig:grad-last}}\\[-1ex]
  \caption{Gradients L1-norm from the (a) first layer and (b) last layer of the shared parameters network for PPO and PPO coupled with SAUNA. Task: \textit{HalfCheetah-v2}.}
  \label{fig:grad}
\end{figure}Fig.\@~\ref{fig:grad} shows that SAUNA filtering leads to larger gradients. As a result, policy updates make bigger steps, which ultimately translates into better performance. It is questionable why performance is not negatively affected, since larger gradients could hinder learning. Experience shows that gradients contain more useful information: as the relevant signals are less diluted, the gradients are more qualitative and have been partially denoised.

\subsubsection{\textit{HalfCheetah}: Qualitative Study}
\label{sec:case}
In \textit{HalfCheetah}, a well-known behavior~\cite{lapan_deep_2018} is that, for multiple seeds, a PPO agent gets stuck in a local minimum in which the agent moves on its back. However, we observed that SAUNA made it possible to leave from, or at least to avoid these local minima.
\begin{figure}[h]
  \centering
  \subfloat[]{\includegraphics[width=1.0\linewidth]{Gym/frames.png}\label{fig:mujocoenv}}
  \qquad
  \subfloat[]{\includegraphics[width=1.0\linewidth]{figures/graph-vex.png}\label{fig:evresults}}\\[-1ex]
  \caption{(a) Example of PPO getting trapped in a local minimum (top row) while PPO+SAUNA reaches a better optimum (bottom row). (b) $\mathcal{V}^{ex}$ score for PPO (blue) and PPO+SAUNA (orange).}
\end{figure}This is illustrated in~\cref{fig:mujocoenv} where we see still frames of two agents trained with PPO+SAUNA for $10^{6}$ timesteps on identically seeded environments. Their behavior is entirely different. Looking at $\mathcal{V}^{ex}$ in~\cref{fig:evresults}, we can see that the graphs differ quite interestingly. The PPO agent seems to find very quickly a local minimum on its back while the blue agent's $\mathcal{V}^{ex}$ varies much more. This seems to allow the latter to explore more states than the former and finally to find a better optimum. Supported by the previous study, we can infer that agents trained with SAUNA are better able to explore interesting states while exploiting with confidence the value given to the states observed so far.

\section{Discussion}
\label{sec:disc}
Intuitively, for the policy update, our method will only use qualitative samples that provide the agent with (a) reliable and exercised behavior (high $\mathcal{V}^{ex}$) and (b) challenging states from the point of view of correctly predicting their value (low $\mathcal{V}^{ex}$). SAUNA algorithm keeps samples with high learning impact, rejecting other noisy samples from the gradient update.

\subsection{Filtering Policy Gradient Updates and the Policy Gradient Theorem}
Policy gradient algorithms are backed by the policy gradient theorem~\cite{sutton2000policy}. As long as the asymptotic stationary regime is not reached, it is not reasonable to assume the sampled states to be independent and identically distributed (i.i.d.). Therefore, it seems intuitively better to ignore some of the samples for a certain period, to allow the most efficient use of information. One can understand SAUNA as making gradient updates more robust through filtering, especially when the update is low and the noise can be dominant. Besides, filtering out disturbing samples reduces the bias in the state distribution.

\subsection{Learning $\mathcal{V}^{ex}$ and the Shared Network Parameters}
SAUNA network predicts $\mathcal{V}^{ex}$ in conjunction with the value function and the policy. Therefore, as its parameters are updated through gradient ascent, they converge to one of the objective function minima (hopefully, a global minimum). This parameter configuration integrates $\mathcal{V}^{ex}$, predicting how much the value function has fitted the observed samples, or informally speaking how well the value function is doing for state $s_{t}$. This new objective tends to lead the network to adjust predicting a quantity relevant for the task. Instead of using domain knowledge for the task, the method rather introduces problem knowledge by constraining the parameters directly.

\subsection{Additional Experimental Results}
We also compare SAUNA to A2C, a synchronous variant of~\cite{mnih2016asynchronous} and a weaker version of PPO. As expected, we observe a $15\%$ increase in performance. We do not present the complete results in this version of the article due to space limitations. Below is a discussion about additional experimental results, which we think contribute interestingly to the study.
\begin{description}[leftmargin=0pt]
  \item[Mean of $\mathcal{V}^{ex}$.] Although $\widetilde{\mathcal{V}^{ex}}$, the median of $\mathcal{V}^{ex}$, is more expensive to calculate, we observe that it gives better results than if we use its mean in the \textit{if} statement of~\cref{alg:learning}. Using the median helps~\cite{10.2307/2683704} because the distribution of $\mathcal{V}^{ex}$ is not normal and includes outliers that will potentially produce misleading results.
\end{description}
\begin{description}[leftmargin=0pt]
  \item[Non-empirical $\mathcal{V}^{ex}$.] We also experimented with using the empirical values of $\mathcal{V}^{ex}$ in \cref{line:if} of~\cref{alg:learning} when calculating $\widetilde{\mathcal{V}^{ex}}$, instead of the predicted ones. This has yielded less positive results, and it is likely that this is due to the difference between the predicted and actual values at the beginning of learning, which has the effect of distorting the ratio in the \textit{if} statement.
\end{description}
\begin{description}[leftmargin=0pt]
  \item[Adjusting state count.] In order to stay in line with the policy gradient theorem~\cite{sutton2000policy}, we have worked to adjust the distribution of states $d^{\pi}$ to what it truly is, since some states visited by the agent are not included in the batch. We adjusted it using the ratio between the number of states visited and the actual number of transitions used in the gradient update, but this did not improve the learning, and instead, we observed a decrease in performance.
\end{description}
\begin{description}[leftmargin=0pt]
\item[Adjusted $\mathcal{V}^{ex}$.] The definition of $\mathcal{V}^{ex}$ is biased. An unbiased estimator does exist (known in statistics as the adjusted $R^2$). We performed the same set of experiments using such an adjusted $\mathcal{V}^{ex}$: it did not change the experimental performance significantly.
\end{description}
\begin{description}[leftmargin=0pt]
  \item[Random filtering.] We experimented with dropping out at random, and before each gradient update, a number of samples corresponding to the same average number of samples that SAUNA drops. This resulted in a decrease in performance compared to PPO, as one can expect.
\end{description}
\begin{description}[leftmargin=0pt]
  \item[Atari domain.] We tested our method on the \textit{Atari 2600} domain~\cite{bellemare2013arcade} without observing any improvement in learning: some of the tasks were best performed by one method and others by the other.
\end{description}

\section{Conclusion}
\label{sec:conclusion}
Policy gradient methods optimize the policy directly through gradient ascent. We have introduced a new, lightweight and agnostic method applicable to any policy gradient algorithm. The central idea of this paper is that $\mathcal{V}^{ex}$ is a useful measure to filter out samples that are perturbing the policy update.
Those non-informative or misinformative samples are ignored by SAUNA with a mechanism controlled by the estimated fraction of variance explained by the value function at each state. The relevant signals being less diluted, this improved sampling results in a denoising effect on the gradients, improving the learning curve, ultimately leading to improved performance.

We demonstrated the effectiveness of our method when applied to PPO, a commonly used state of the art policy gradient method, on a set of benchmark high-dimensional environments. We also established that samples can be removed from the gradient update without hindering learning but, on the opposite, can improve it. We further studied the positive impacts that such a modification in the sampling procedure has on learning. Several open topics warrant future study. Our results suggest that the influence of SAUNA on the distribution of states has beneficial effects: in order to gauge the theoretical implications of transition dropout in the MDP, our method might be formulated using the options framework~\cite{sutton1999between,precup2000temporal} where holes in a trajectory result in the appearance of options. Moreover, we are studying other ways to use $\mathcal{V}^{ex}$ in the context of RL.

\bibliographystyle{named}

redpajama_set_name: RedPajamaArXiv


text:
Japan and Australia: What the Reciprocal Access Agreement is all about
Oleg Paramonov
Image source: interaffairs.ru
During his brief visit to Japan in mid-November, Australian Prime Minister Scott Morrison and his Japanese counterpart Yoshihide Suga announced a plan to strengthen defense cooperation between their two countries.
In keeping with the Reciprocal Access Agreement (RAA), Australia and Japan will provide their territories for joint measures of a defense nature and operations to eliminate the consequences of natural calamities and humanitarian disasters. It does not envisage any permanent troop deployments, like in the case of US military bases in Japan, however, and will only apply to joint or multilateral exercises, including naval ones. Earlier, in 2017, the two countries inked an agreement on logistical support, and their military-political dialogue has been ongoing since the adoption in 2007 of the joint Declaration on Security Cooperation.
The RAA is scheduled to be signed in Australia, but it will still require parliamentary approval in Japan.
Once the agreement is implemented, Japan will for the second time ever authorize the presence of foreign military personnel on its soil. However, while the presence of US troops is an unpleasant reminder of Japan's defeat in WW2, the new accord is seen as a major diplomatic success for Tokyo. The Japanese-Australian tandem is already beginning to look like a "semi-alliance." However Americans are not the only foreign military personnel that have set foot in Japan. In 2018, 50 British troops joined their Japanese counterparts in a drill held in three Japanese prefectures practicing rescue and reconnaissance operations as well as parachuting from helicopters, but strictly without the use of firearms. Holding such joint exercises on a regular basis requires a pertinent agreement on the application of criminal, tax, and other types of legislation to foreign military personnel as well as customs clearance of weapons and military equipment.
Unlike the 1960 agreement with the United States, the one that Tokyo is going to sign with Canberra will be between equal partners. It also differs from the 1960 accord in that Tokyo made sure that Australian servicemen who happen to commit crimes on Japanese territory will be punished in keeping with Japanese laws. The situation is greatly complicated by the existence in Japan of the death penalty (in Australia it was abolished in 1985). However, even in the case of less serious crimes, conditions of detention in Japanese prisons are no match for what they have in the West. For example, the former Nissan CEO, Carlos Ghosn, was sleeping in a Tokyo prison on a straw mattress.
Although the Reciprocal Access Agreement will also contribute to Australia's growing role in regional security issues, Japan's participation in it will be perceived as another big step towards changing the region's fragile status quo. According to experts, this ushers in a new period in Japan's foreign policy, demonstrating to the "middle powers" its readiness to cooperate on security issues. Tokyo apparently believes that while becoming a serious addition to the Japanese-US alliance, the agreement may simultaneously serve as an alternative for it to lean on if it has reasons to doubt Washington's security guarantees. Donald Trump's departure from the White House does not mean that the ideas of neo-isolationism and neo-mercantilism are all gone now. It is with this understanding in mind that Japan is now building a new institutional framework for relations with the "middle powers" as it promotes its own concept of a "Free and Open Indo-Pacific."
Even though such trends in Japan's security policy are now being associated by many with Yoshihide Suga, this is essentially the result of the hard and persistent work done by his predecessor, Shinzo Abe. For example, the whole idea to begin negotiations with Australia on the RAA was pitched back in 2014. The Japanese government has been doing a pretty hard job of settling issues that are of great concern to Japanese politicians and their voters alike. These are not only about the numerous scandals with US Marines. The Japanese have traditionally been against allowing "outsiders" to enter their country.
The news about the preparatory work on the agreement now over, came already in June 2020, and there were already good reasons for not only to announce this, but also to sign the document. For example, this could have been done during the October 6 meeting by the foreign ministers of the United States, Japan, Australia, and India, (the so-called "Security QUAD"). The question is why didn't this happen earlier, and why not just wait for the document to be signed? And although there may be several reasons for this, the main one was the Japanese and Australian Prime Ministers' intention to wait for the outcome of the US presidential elections. Suga and Morrison are thus sending a signal to the new US administration that they have something to please their common ally in the event of a return to "pre-Trump" relations.
So the agreement has not been signed yet, and here we should recall the events of 2014-2015, namely the planned supply of Japanese-made Soryu-class submarines to the Royal Australian Navy. Despite a preliminary agreement between the then Prime Ministers Shinzo Abe and Tony Abbott on the purchase of submarines without a tender, the Australian government took flak from the opposition for the uncontested choice of the Japanese proposal and was eventually forced to announce a tender, where the Japanese lost out to the French. Today, the Australian government may likewise be criticized for being overly compliant with Tokyo about the prospect of Australian military personnel to be tried in Japan. There is still no clarity here, and the sides are reportedly prepared to hold more consultations on this particular issue.
For Canberra, the process of the accord's ratification by the Japanese parliament may become a source of unpleasant surprises. Although there is a high degree of probability that the document will be ratified, the officials' failure to provide convincing answers to lawmakers' questions could make important provisions of the agreement wide open to all sorts of interpretation by politicians. Fully aware of this possibility, the government has made every effort to prevent this happening. Meanwhile, significant delays in the consultations between Tokyo and Canberra on agreeing the final text of the document were already construed as signs of fundamental disagreements between the parties on other issues as well. However, the delay was due to Tokyo's desire to work out the future agreement as carefully as possible for the sake of its further use as a basis for similar initiatives with other regional neighbors and also those further afield. Presently, Tokyo can also count on the participation of new external players in the regional agenda, primarily from among NATO countries. For example, Britain is currently negotiating its participation in the Comprehensive and Progressive Trans-Pacific Partnership, which is actually moderated by Tokyo. Moreover, there is more to London's interest in the Indo-Pacific region than just a desire to partially recoup the costs associated with Brexit. The interest is also political, particularly related to the situation around Hong Kong, which the British are watching very closely. London and Tokyo have been conducting joint military exercises since 2016, and work on an agreement similar to the Japanese-Australian one is reportedly underway now.
France, which has overseas territories in the Pacific Ocean, is also a potential partner of Tokyo on the Indo-Pacific track. In Japan, they can also count on Canada's interest in defense-related cooperation. Needless to say, Tokyo realizes full well that new potential "semi-allies" will be closely watching the outcomes of the agreement with Australia, as this may serve a precedent for similar and wider-scale projects with other countries.
In conclusion, getting back to the issue of foreign military personnel in Japan, it is worth recalling the tragic events that happened there on March 11, 2011 when a Russian Emergencies Ministry helicopter brought a group of our rescuers to Fukushima, and another team of Emergencies Ministry employees and nuclear workers arrived by plane in Tokyo. They marched 500 kilometers to the city of Sendai (Miyagi Prefecture). At the same time, it was noted that bureaucratic hassles hampered foreign rescuers' work in Japan. Perhaps one should consider the possibility of an appropriate agreement to be signed by Russia and Japan. Tokyo will not agree to a full-fledged Reciprocal Access Agreement with Russia of course, since the do-what-I-tell-you relationship still existing between Washington and Tokyo hasn't gone anywhere. It is still possible, however, to narrow the scope of such a document to dealing with the consequences of natural and man-made disasters, rescue operations and countering sea piracy.
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The latest turmoil in the Covid-ridden strata of mainland China is not servile to any pandemic, however, the issue has been one of the most queer and rare kinds, enough to be classified as one of the endemic issues in the global affairs. The tension at helm is the chaos following the announcement of a "New Security Law" by the Chinese regime which is being eyed as one of the monumental events of this decade; slicing off a sliver of attention from the deadly Corona virus that continues to exponentiate around the world in its second wave and sporadic variants.
The law that set out by the Chinese lawmakers back on 22nd May 2020, threatens the liberties of subversion and sedition enjoyed by the citizens of Hong Kong under a constitution. Simplistically named "Basic Law", it aims to tame the country scaffolded by the "One country, Two systems" framework since the power handover by the former colony to China back in 1997. This act came around amidst strained economic relations between the two superpowers of the world; China and USA, each passing the baton in the blame game of who sustains the blood-crown of the catastrophe impending on the world courtesy of the lethal virus that engulfs every periphery in each continent on the globe. The matters seem complex at sight and a glimpse to the historical timeline of how riddled the relations were could hint at how strained they could reach.
The colony, known as 'Hong Kong' today, had been the battle ground, figuratively, to the major competitors of the 20th century: The Great Britain and China. The British dominated the colony for more than 150 years, tracing back to the late 19th century; leasing the territory for the span to morph it into the modernised metropolis marking it as the hub we know today. In 1997, an agreement was reached via an accord, 'The Sino-British Joint Declaration' between the two sides. The treaty allowed Hong Kong a semi-autonomous status, that is, relaying self-sufficiency in all the national domains except in defence and foreign affairs. The allotted autonomy arches under the sovereignty of China until year 2047, henceforward melding into the mainland China as harkened by the Chinese hegemony over decades.
Despite of the granted protection of Hong Kong's own legislation, borders and freedom of speech, the liberties have been trampled on by the Chinese government over the last couple of decades. A similar law abolishing the right to sedition was initiated in 2003 yet mass protests calling out up and about 50,000 citizens impeded the efforts that went futile and drastically ended up being shunned for good. The Communist party under the wings of Chinese president Xi Jinping have expounded further in tightening their talons on the city since 2012 as efforts were made to corrode the educational system of the country via meddling with the curriculum, biasing the foundation to hail Chinese communism. These acts were proactive reactions to the advances of the United States forging relations with the city. China even tried to manipulate the elections in 2014, tampering with the selection their Chief Executive leading to a 3-month long protest known as the 'Umbrella movement' and ultimate downfall of Hong Kong's autonomous political system.
The security law falls in tandem to the events of 2019; the legislation allowing the convicts from Hong Kong to be extradited in China causing a rave of fear of a massive tactical crackdown of the Anti-communist activists of Hong Kong, sighting it just as ruse to underwhelm the right of sedition of the people of Hong Kong. The Law passed by the parliament notions to only one thing; The ultimate end to Hong Kong. The lawmakers in China, hailing from the National People's Congress (NPC), sight this move as extricating a threat to the national security and stability of the country while many of the pro-activists in Hong Kong deem the law as betrayal, accusing China of walking back on its promise of high-degree autonomy and freedom of speech, marking it as the final straw, the last struggle before the country could override the laws in the city and indirectly, transition from the entity holding the right to veto the laws to now gripping the law altogether.
Despite of the speculated protests to spark like the history dictates, many of the sage minds predict either a relatively dormant demonstrations or none at all, having a tint of finality in the statement shote the protests are "high stake in risk and repression". The recent arrest of the leading activists of Hong Kong standing up to voice their disdain to the separatist efforts of China further solidify the notion. Despite of a global condemnation to the new law, the efforts of China resume to subdue any opposition in Honk Kong no matter how sparse. Foreseeing no way out for Hong Kong this time; the Covid-19 paralysis the United States in its own crisis and the legislature inclining towards the Chinese pressure, a complete erasure of Hong Kong is sighted and could not be restrained- for better or for worse.
Rajesh Kumar Sinha
The Chinese media has recently reported of Xi Jinping writing a letter to George Schultz the former chairman of Starbucks, the US coffee giant. In the letter, he has requested Schultz to play a positive role in advancing the US-China relations. While head of a major state writing letter to big corporate heads is not a common but not an unusual development either, this letter from Jinping should be seen in a relevant context. It indicates a certain amount of desperation and difficulty of China in its dealings with the US.
It suggests that after months of aggressive posturing and verbal duels against Trump, the State Department and Pentagon, China is now cosying up to the new Joe Biden administration. Further, it also means the recent Chinese aggressive posturing, wolf diplomacy has failed to bring in the desired results and that the Xi Jinping-led CCP is under more pressure now to soft-pedal the recent acrimonious ties between the two.
The year 2020 had been a very disappointing and calamitous year for the world. And Corona pandemic could well be cited as the most important reason. While the world as a whole has struggled to fight this unknown enemy individually as well as collectively, one country that has been in the limelight, for all the wrong reasons, been China.
Foreign policy and diplomacy is all about protecting and promoting the perceived national interests of a country. While achieving its objectives, the country tries to create and maintain a favourable image in the international community. The Chinese diplomatic endeavour since the ascension of Xi Jinping has been starkly opposite. From the most likely origin of Corona virus, to rebuking leaders, diplomats and media of other countries, China has been trying to create a new diplomatic norm, a new normal where none of the countries would dare criticising China, through political discourse, media or any other way while silently acceding to its territorial expansionary designs.
There have been unusually vitriolic reactions by Chinese diplomats against seemingly innocuous comments or actions by governments, politicians, diplomats or media in various countries. A very rational request by the Australian government to initiate investigations by the international community into the genesis of Corona virus, made China so furious that apart from making crude undiplomatic comments, it even created a virtual political, diplomatic and trade war against the country. Critical comment by certain politicians in Brazil and Japan, led Chinese diplomats to publicly issue personalised attacks against them.
The Chinese ambassador to Sweden has went on to lambast the country's media in most rustic manner. No wonder, in the last two years, he has been summoned to the Swedish foreign ministry an unprecedented 40 times and there have been demands from native politicians for his expulsion. In India, a country that is being seen as the closest political and military rival by China but is scared of admitting it publicly, the diplomats have kept on reminding the government and media not to play the so-called Tibet card or must adhere to One-China policy by not getting close to Taiwan, have repeatedly been ignored by the government as well as the media.
No wonder, a recent Pew Research study has revealed that globally China has lost a huge amount of goodwill. A significantly very high majority of natives in nine of the advanced economies like the US, UK, Germany, Australia, South Korea, Sweden, Netherlands think negatively of China. Australia (81%), UK (74%), Sweden (85%), Netherlands (73%) show a very high increase in the negative perception against China, very recently and that has affected their politico-commercial relations too.
With the US, the Trump administration acting aggressively in the backdrop of the November Presidential elections, the Chinese actions of challenging the lone superpower has not helped the country anyway. On the contrary, US has become more supportive of Taiwan, politically as well as militarily, making it even more difficult or virtually impossible to China to even think of occupying the territory forcibly in near future. India that had maintained a cautious approach towards Taiwan till recently, have started enhancing political and commercial relations with the country.
In Asia, its aggressive military designs against India's northern borders has had a very rude awakening for China. Used to a timid Indian approach since 1950s under Nehru, it never expected the aggressive Indian response that even put its own military positions in Moldo and other strategic positions vulnerable. To further undermine political and military calculations, its adversaries in South China seas like Vietnam, Indonesia and Philippines today are in advance negotiations with India to secure sophisticated missiles and armaments.
A very significant strategic development in the form of QUAD has taken the preliminary shape and that whenever gets in a concrete form, could well portend an ominous future for China, politically and militarily. The belligerent Chinese behaviour, especially since the onset of Corona virus has brought India, Australia, the US and Japan very close. With talks of Vietnam, Philippines and others in south-east Asia joining it later, the future of a QUAD could well be a security nightmare for China.
In the economic realm, India has reacted sharply too. Being a huge market for Chinese cheap goods and scores of apps till recently, India has not only banished hundreds of apps but has also been working on a mechanism to regulate, control and even stop imports in a number of segments from China. A big share of enormous infrastructural contracts in telecommunications, roads, ports, airports and railways in India too, have become difficult for Chinese companies. And taking a leaf out of India, the US and other countries too, are making it difficult for Chinese organisations to secure big contracts in their respective countries.
Over the next few years, China is going to lose a huge chunk of its popular and big market in India while territorially too, it has failed to make any significant gains. Strategically what China wished to see was countries like Japan, India, Australia, Vietnam, US all having disputes with it dealing individually rather than getting together and forming a coordinated and collective political, economic and strategic response against it. And the very opposite has happened. There have been greater and collective political, military and economic coordination amongst all these countries today and most of the strategies are aimed against one country, China.
All these developments including Xi's letter to Schultz, indicate one point very certainly that Chinese belligerence has backfired hugely. It needs to reorient its diplomacy and political behaviour significantly and if it fails to do so, its position in the emerging post-Covid geopolitical order could be anything but that of an emerging superpower.
Chan Kung
Authors: Chan Kung and Yu(Tony) Pan*
Throughout the modern history of the world, Japan is undoubtedly an interesting country: it went from the edge of becoming a colony to one of few independent countries in Asia before World War II, and after the Great War, Japan even became a great power. From a broader level, Japan's success at that time showed that Asians were not inherently inferior to Westerners. Unfortunately, Japan which was supposed to be the leader of Asia to a bright future, chose the path fascism and imperialism. Eventually, Japan became the source of the Pacific War.
It is undeniable that from the Meiji Restoration until the early Showa period (the end of World War II), Japan adapted an expansionary policy, which brought deep suffering to its neighboring countries and ultimately dragged itself into the abyss of destruction. When World War II ended, nearly 70 years of development achievements were utterly wiped out by the war.
In this context, an important question we need to ponder is: What led Japan to embark on an expansionary and self-destructive path? At what point in time did Japan's policymakers start to lose its mind? What can future generations of nations learn from Japan's tragic experience to prevent the same fate from happening again? As a country that has been entangled with Japan for generations and has a complicated relationship with Japan, these issues are of even greater relevance to Chinese researchers today.
Fortunately, there is actually a fair amount of scholarly research on the subject, and there exist four main explanations. The first is the "international structure theory" most commonly used by IR scholars (especially the realists), and the second, more common among Western scholars, is the "weak democratic government theory. The third is the "Pan-Asianism," which focuses on the constructivist perspective. Finally, there is the political economy explanation of expansionary policies.
At the first glance, it seems that each of these explanations has its own rationale. Of the four, the view that the navy and the military were increasingly extreme in their struggle for policy dominance is the most possible explanation. However, it seems that each of the four existing explanations can, in fact, be incorporated into a new one, namely, that Japan's self-destructive expansionary policies prior to World War II were the material manifestation of an uncontrolled nationalism. More specifically, these four explanations answer why the Showa government was unable to control the nationalist forces in the country. On the other hand, however, the question of whether nationalism would necessarily expand without outside interference and lead to expansionist policies was left unexplained.
Because of the natural characteristics of nationalism, it seems to us that there is a natural tendency for nationalism to expand in the course of its development. The main reasons for this phenomenon are not complicated. First of all, nationalism is a group ideology, which means that nationalists have a common goal at the macro level, but the boundaries of national interest are not consistently defined by different individuals. On this basis, because of the unreliability of group rationality, nationalism as a groupthink is prone to overstretch in the course of its development. Moreover, when such currents are not rationally controlled and end up holding state policy hostage, the state tends to follow a self-destructive path of expansionism. Pre-World War II Japan is a classic case in point.
It should be noted that the positive effects of nationalism is not being denied here, but it is crucial that a country's policymaking process should not be ultimately being a hostage to nationalist forces. The question then, is how to prevent nationalism from spiraling out of control. From an empirical point of view, there are two different directions to prevent nationalism from getting out of control at the macro level: first, to eliminate "group irrationality" in nationalism; Second, to establish a corresponding gatekeeper between nationalism and state policymaking.
The first direction is essential to improve the thinking capacity and cultural literacy of society as a whole. This is a radical way to solve the above problems, and the improvement of the education system is the most crucial part of it. However, for reasons that are easy to understand, this approach often takes too long to implement, and the process is not really controllable. As a result, this approach, while very important, is often insufficient for policymakers.
The second approach, on the other hand, is a short-term solution (relatively speaking). To use the common metaphor of treating a bodily disease, a gatekeeper-kind-of-approach is not to eradicate the disease but rather to prevent it from damaging health amid acceptance of its existence. There are two other ways to establish gatekeepers: one is to establish a mature political system that uses institutional factors to insulate people from the negative effects of nationalism. This is also the more popular approach in developed Western countries. It should be noted that this approach has proven itself to be effective, most notably in the case of the United States, which also has two populist leaders, as opposed to Brazil, where institutional constraints and the resulting establishment have been significantly more effective in containing the negative effects of nationalism on the policy.
The alternative is to rely on a small number of political authorities within society to isolate the scourge of nationalism through the elite's prestige and quality. Again, this is also an approach that has worked before. The best example is the significant role played by Chinese leader Deng Xiaoping in the "reform and opening-up" process.
So, which is more effective, institutions or authority? This is not a question that can be easily answered. There are advantages and disadvantages to both approaches, and because every country and society is different, and there is no one-size-fits-all solution.
First of all, the main advantage of institutional gatekeepers is that once established, the containment is apparent and fairly solid; however, the disadvantage is that institutions may take a long time to develop and may come at a cost (e.g., the French Revolution). An authoritative gatekeeper's advantage is its high degree of operability, while the disadvantage is the unsustainability and instability of the individual factor. On this basis, the realization of either approach needs to be linked to local realities; in other words, neither is necessarily successful. However, despite the different possibilities of approaches and paths, one issue is certain: in this day and age, uncontrolled nationalism is still a problem that threatens national interests, and this issue must be given sufficient attention and focus by policymakers.
Lastly, for contemporary China, the case of Showa Japan has another area of critical research value: how to deal with the current international order? History has shown that almost every attempt to challenge the existing international order independently has often ended in self-destruction. Successful transformations of the international structure tend to be incremental. In the case of pre-World War II Japan, the immediate effect of nationalism was to push the Japanese government to place itself on the opposite side of the prevailing international order. Today's China has certainly not come that far. In fact, as Professor Wang Jisi says: "In those days, Japan was an 'institution' in the international order, while China was rejected and discriminated against by the West as an 'other.' Today, Japan is still 'within the system' of the international order, while China has risen to become the world's second-largest economy and its military power is not what it used to be, but there is still the question of how China views the existing international order and how to deal with its relationship with the existing international order. " In dealing with this problem, preventing the negative effects of nationalism on state policy is undoubtedly an important aspect.
*Mr. Yu(Tony) Pan serves as the associate research fellow and the research assistant of Mr. Chan Kung, Founder, Chairman, and the Chief Researcher of ANBOUND. He obtained his master's degree at George Washington University, the Elliott School of International Affairs; and his bachelor's degree in University of International Business and Economics in Beijing. Mr. Pan has published pieces in various platform domestically and internationally. He currently focuses on Asian Security, geopolitics in Indo-Pacific region and the U.S.-Sino Relations.


Imagination and information meet in the education programs at the Wendell Gilley Museum. You can stop in for help identifying a bird, research a paper or prepare an art project in the library. If you are interested in learning to carve, you can sign up for a lesson or a lifetime; short and long workshops are offered. Teachers and youth group leaders are welcome to schedule art and natural history programs year-round.


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Has this prankster dad gone too far?
The prank named 'killing my own kid' is going viral but is it actually funny?
When it comes to pranks, we think there's a very thin line between funny and cruel – particularly when kids are involved. So this shocking video named " Killing My Own Kid" is certainly not for the faint hearted!
It all starts when the notorious YouTube prankster Roman is playing with his 2 children. His youngest son is dressed in a Spiderman costume – including mask.
When his partner Brittney arrives home, he asks her to fetch them some water, and quickly switches out his real son for a mannequin dressed in the same costume. He then pretends to accidentally throw his son off a balcony in front of her.
Of course, the mum shrieks and runs to her toddler's side – panicking while he seems to lie unmoving on the floor. But once she removes his mask she sees it's just a mannequin. Well, of course she's relieved her son is unharmed, but lets just say she is NOT happy about being scared to death by her partner.


MIN-AD is a naturally occurring calcium magnesium carbonate product (Ca,Mg)(CO3)2 that serves as an effective and economical buffer and rumen microbial growth enhancer. Research conducted by Cornell University confirms using MIN-AD as source of digestible Ca and Mg in transition cow rations increases feed efficiency and energy balance during this period.
MIN-AD provides 61-75% more acid-consuming capacity than sodium based buffers, ensuring rapid buffering and longer term pH balance in the rumen and lower gastrointestinal tract. As a bioavailable source of Ca and Mg, MIN-AD can replace supplemental magnesium oxide (MgO) and limestone in the diet. When used in conjunction with sodium bicarbonate, MIN-AD increases microbial efficiency by 10% compared to typical MgO and sodium bicarbonate buffer packs, making MIN-AD a perfect fit for both dry and lactating dairy cow rations.


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Euro Games Technology (EGT) was founded in 2002 in Bulgaria. After their initial expansion in 2008, EGT moved to a sprawling new administration and manufacturing facility. The modern design and enhanced functionality of the site mirrored the company's cutting edge ambitions.
Today, the company employs over 1400 people. with EGT products available in over 80 countries. Aggressive marketing and a wide variety of gaming products have always been the hallmarks of EGT.
EGT products include gaming machines, jackpot systems, semi-electronic Blackjack tables, mobile play stations and gaming accessories. With such ambition, it's not surprising EGT was quick to realise the enormous potential of Blockchain technology and the ensuing cryptocurrency revolution. Soon, online Bitcoin casinos were among their many clients.
Brave Cat: It's tough to resist this classic rendition of Puss in Boots.
Aloha Party: Hawaii comes to life with beautiful background visuals.
Genius Leonardo: Perhaps EGT's most inventive game. Da Vinci's classic artwork, inventions and theories are on display.
Penguin Style: A rare EGT game with humour, Penguin style is a whacky adventure with some lovable tuxedo'd birds.
EGT games are generally lacking in laughs and originality. Some of the sound effects are recycled from game to game. Furthermore, the controls are not intuitively designed. The RTP information is also not readily available on all slots.
On the plus side, graphics in EGT slots are decent and in some cases excellent. Many of them also offer progressive jackpots which will appeal to a lot of players.
For lovers of Progressive Jackpots, EGT might well be a breath of fresh air. For the rest of us though, the offerings are fairly stale in concept and design. This, coupled with the fact that EGT online slots are somewhat difficult to locate, make this providers offerings unappealing. Hopefully, the quality and accessibility will increase over time.


ACCIDENT WAIVER AND RELEASE OF LIABILITY: I wish to participate in the Trailwood T-Bird Trot. I hereby assume all the risk of participating in this event. I know that although police protection will be provided there will be traffic on the course. I assume the risk of walking in traffic. I also assume any and all other risks associated with walking this event, including but not limited to falls, contact with other participants, the effects of the weather and condition on the roads. I acknowledge that this Accident and Release of Liability form will be used by the event holders, sponsors and organizers of the event in which I may participate, and that it will govern my actions and responsibilities at said event. In consideration of my application and permitting me to participate in this event, I hereby for myself, my executors, administrators or anyone else who might claim on my behalf, waive, release and discharge Trailwood Elementary PTA, Trailwood Elementary School, the Shawnee Mission School District, all volunteers, workers and sponsors, including but not limited to the City of Overland Park and all of their agents, employees assigns or anyone acting for or on their behalf, from claims or liability for death, personal injury, or property damage of any kind or nature whatsoever arising out of or in the course of my participation in this event. I hereby consent to medical treatment, which may be deemed advisable in the event of injury, accident and/or illness during this event. The Accident Waiver and Release of Liability shall be construed broadly to provide a release and waiver to the maximum extent permissible under applicable law. No headsets, roller skates, in-line skates, skateboards, dogs or motorized vehicles allowed on the route. The Walk Committee reserves the right to cancel the event due to inclement weather. There will be no refunds if the race is cancelled. PARENT/GUARDIAN WAIVER FOR MINORS (UNDER 18 YEARS OLD): The undersigned parent and natural guardian does hereby state that he/she is, in fact, acting in such capacity and agrees to indemnify, save and hold harmless each and all of the parties referred to above from liability, loss, cost, claim or damage whatsoever which may be imposed upon said parties because of any defect in or lack of such capacity to so act and further releases said parties on behalf of the above registered minor(s) and parents or legal guardian of said minor(s).


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Militants Attack Saudi Patrol on Iraq Border, Killing Two Guards: Ministry
© CC BY 2.0 / Jon Rawlinson / ministry of the interior, riyadh, saudi arabia
https://sputniknews.com/middleeast/201501051016520334/
According to the Saudi Interior Ministry, a militant detonated himself and two Saudi border guards with a suicide belt on the country's northern border with Iraq.
© REUTERS / Khalil Ashawi
Syrian Army Kills 70 IS Militants in Two Days Near Syria-Turkey Border: Reports
BEIRUT, January 5 (Sputnik) — Two Saudi border guards were killed and one wounded in a suicide attack at Saudi Arabia's northern border with Iraq, the Ministry of Interior of the Kingdom of Saudi Arabia said on Monday.
"A border patrol at Suwaif center of Judaydit Arar (village — ed.) was fired [on] from terrorist elements, and the situation was dealt with as required […]," a ministry spokesperson said in a statement on the ministry's website.
According to the statement, border guards returned fire, killing one of the insurgents. However, another militant detonated himself and two Saudi border guards with a suicide belt.
Saudi Arabia shares an 800-kilometer (500 mile) border with Iraq and is one of six Arab states involved in multinational coalition airstrikes aimed at countering the Islamic State (IS) jihadist group operating in Northern Syria and Iraq.
Iraq Holds Talks With Bahrain on Release of Opposition: Parliamentarian
US-Led Airstrikes Hit Multiple IS Positions in Syria, Iraq: Central Command
Violence in Iraq Claims Over 15,000 Lives in 2014: Officials
border, violence, terrorist attack, Iraq, Saudi Arabia


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Q: Query time in id lookup Vs index searching i`m developing a social network with php and neo4j
entities like people, company, university have unique addresses like facebook exp: www.network.com/foo-bar
i use foo-bar for index searching and showing the entity
my question is "in 1-3 million nodes on target label how much time and resource will save if i use id lookup in internal links"
to be more clear i can use www.network.com/foo-bar/nodeId when user see foo-bar in recommendation and lookup with id and use index searching only in cases someone want access it via entering address in browser.
but its a little ugly

A: In general you're right, selecting the node by ID directly is faster than searching the index. But index search is made for the case you described! Make sure you have enough memory and your search should be fast enough to make your URL s look beautiful without speed problems!

redpajama_set_name: RedPajamaStackExchange


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Home / Company / About Us / Transmission
Connecting power sources and end users
FERC Standards of Conduct | Regulatory Matters
Minnesota Power has 8,742 miles of electric transmission and distribution lines with 164 substations. In 2009, Minnesota Power purchased a 465-mile direct current transmission line between Duluth, Minn., and Center, N.D., to transport renewable wind energy from its Bison Wind Energy Center in North Dakota.
For Minnesota Power and ALLETE, Minnesota Power's parent company, investing in transmission is a cornerstone of their growth strategy. Those investments include:
In April 2014, Minnesota Power applied to state and federal regulators for permits to build the 500-kilovolt Great Northern Transmission Line from the Minnesota-Manitoba border to an electric substation on the Mesabi Iron Range. The Minnesota Public Utilities Commission approved a route permit for the transmission line in April 2016, and the U.S. Department of Energy approved a Presidential Permit for the international connection at the U.S.-Canadian border in November 2016.
Construction of the transmission line, an essential component of a long-term power purchase agreement between Minnesota Power and Manitoba Hydro, began in January 2017. The line is expected to be in service in 2020.
American Transmission Co.
ALLETE began investing in ATC in 2006 and the company's investment in the Wisconsin-based public utility now represents an 8 percent ownership interest. ATC is the first multistate, transmission-only utility in the United States. It owns and operates transmission systems in portions of Minnesota, Wisconsin, Michigan and Illinois.
CapX2020
Minnesota Power is a participant in the CapX2020 initiative, a collaboration consisting of Minnesota's largest transmission owners as well as electric cooperatives, municipals and investor-owned utilities.
Minnesota Power participated in two CapX2020 transmission line construction projects: the new 345-kilovolt Monticello-Fargo line, and a new 230-kilovolt line between Bemidji and the Boswell Energy Center near Grand Rapids, Minn. Our participation with CapX continues with operation and maintenance of the lines.
The Bemidji-Grand Rapids line was completed in September 2012, and the last segment of the Monticello-Fargo line was energized in April 2015.


Police arrested a 22-year-old man suspected of stealing a car in Paphos on Friday night, authorities said on Saturday.
According to police, the car was reported stolen by a 54-year-old woman on February 10. The car was determined to have been stolen some time from December 2018 to January 22, 2019, from where it was parked in Paphos.
Police eventually found the car parked in a field during rounds last Wednesday morning.
During their investigations police obtained a witness statement identifying the 22-year-old, who was arrested by police on a court order Friday night.
Paphos police are continuing their investigation.


Raspberry and chocolate - you can't go wrong with that combination.
14-1/2 oz. Yields one 9" x 9" pan of brownies.
Ingredients: Wheat Flour, Sugar, Unsweetened Cocoa Powder, Raspberry Powder, Baking Powder, Vanilla Powder, Salt.


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Richard Carpenter: 'The cultural impact of the Carpenters would make a great doctoral thesis'
The musician Richard Carpenter talks about the death of his sister, Karen, at the age of 32 and keeping her legacy alive with a new recording
Ben Hoyle
December 6 2018, 12:01am, The Times
Richard Carpenter and Karen Carpenter in 1978GETTY IMAGES
The Carpenters were at the peak of their huge success and chafing against their clean-cut image when they received perhaps the least cool endorsement in the history of popular music. It came from President Nixon in the White House in May 1973, shortly after he withdrew US combat troops from Vietnam and just as the Watergate scandal was getting into full swing. Richard Carpenter smiles ruefully as he repeats, 45 years later, what the soon to be disgraced leader called him and his sister, Karen: "Young America at its very best."
Nixon's verdict for ever crystallised the way that the grinning duo from the Californian suburbs were seen: as a wholesome, unthreatening counterpoint to the social, cultural and political tremors shaking America at the time.…