text:
\section{INTRODUCTION}
In recent work the scenario based approach is seen as one promising way to test automated vehicle functions \cite{ForschungsprojektPEGASUS.2017}. A kilometer based approach is not feasible for testing and validating functions for automated driving, which have to master all conditions within a given specification. That would take billions of kilometers to complete \cite{Shwartz2017, Zhao.2017, Maurer.2016b}. Functions, which are currently under development, show clearly the need for a relevance evaluation to limit the test expenditure \cite{Weitzel.2014}.
The test effort must be justified based on an analysis of the relevance of scenarios. Therefore, one must know which categories of scenarios appear on the road. Looking at scenarios microscopically, there is an infinite number of scenarios. A somewhat higher visual range shows that they nevertheless follow certain patterns and can be assigned to categories with a high degree of similarity. Testing representatives from each category ensures a broad scope, while minimizing the effort in the validation process.

The main contribution of this paper is to describe a process of how to learn categories/clusters of traffic scenarios in an unsupervised way, given only the data. The methods presented in this work are separated into three main parts.
The first element is a microscopic traffic simulation tool, which allows an accurate modeling of the vehicle motion and interaction between traffic participants.

The second part is the extended (Modified) Unsupervised Random Forest (xMURF) used to determine a data adaptive similarity measure. The xMURF is an extension of the MURF method presented in \cite{Kruber.2018}. As a part of the xMURF, a novel similarity measure, based on the Random Forest (RF) is introduced, called path proximity. The difference to the normal RF proximity is that, given a datapoint the whole path through each tree of the RF is considered instead of just the terminal leaf. The similarities between the scenarios achieved this way are visualized as a reordered proximity matrix. One defines clusters/categories based on this visualization.

As third and last part, the clusters are used to train a RF classifier. This way, new traffic scenarios can be assigned to a category. A special assignment rule is used, such that scenarios only get assigned to a cluster if they exceed a certain confidence threshold. The architecture is examined by using a data set of highway scenarios realized by the simulation tool.

In summary, the work presents a method which enables one to investigate relations between traffic scenarios. It also enables one to define groups of scenarios, such that categories are created, which are used to classify new scenarios. Moreover, also other research fields can benefit from this work, since the presented xMURF is not limited to traffic scenario data.

The paper is organized as follows. Section \ref{relatedwork_section} depicts related work. Section \ref{architecture_section} describes the architecture of the proposed method. The key components of the simulation are described in Section \ref{data_section}. Next, a definition of a scenario and a description of the extracted features is given in Section \ref{data_section}. Section \ref{clustering_section} explains the xMURF method. The enhancements to its predecessor version \cite{Kruber.2018} are discussed as well. The classification of new scenarios is explained in Section \ref{classification_section}. In Section \ref{results_section} some demonstrational results of the xMURF method based on the simulation data are presented. Finally, this work is concluded in Section \ref{conclusions_section}.
\section{RELATED WORK}
\label{relatedwork_section}
This section depicts a selection of related work for both adjacent topics, the validation of automated vehicles and the clustering method.
In \cite{Koopman.2016}, a summary of the challenges of autonomous vehicles and proposals to deal with them is given.
A method to accelerate the validation process is proposed in \cite{Zhao.2017}. The research initiative PEGASUS \cite{ForschungsprojektPEGASUS.2017} examines the validation for automated vehicles from various aspects and aims to provide widely accepted standards.
In \cite{Wachenfeld.2016b, Wagner.2018} two measures for risk assessment are proposed to capture relevant traffic scenarios. Both publications describe methods to find trigger points to recognize relevant scenarios, while this work is focused on finding categories within the set of recognized scenarios. Trigger points are used in this work to define the length of a scenario as described in\ Section \ref{data_section}.

The RF for classification and regression is presented in \cite{Breiman2001random}, while unsupervised usage is described in successing work \cite{Breiman02URF}.
In \cite{Cara.2015}, a classification for car-cyclist scenarios is presented. It is important to mention, that the classes are predefined in \cite{Cara.2015}.
An application of the unsupervised RF is presented in \cite{Shi2006}. In \cite{Liu2000}, a tree based clustering technique is shown, which was a starting point for the MURF algorithm \cite{Kruber.2018}. The related work on clustering differs by the techniques to generate noise data (see Section \ref{clustering_section}) and the way how the clusters are defined. Additionally, this paper proposes the path proximity to determine a similarity measure.
\section{ARCHITECTURE}
\label{architecture_section}
In this section an overview of the overall architecture is given. The main steps are depicted in Fig. \ref{fig:ToolChainComplete}.
\begin{figure}[h]
\centering
\begin{footnotesize}
	\input{ToolChainComplete.tex}
	\end{footnotesize}
	\vspace{-0.3cm}
	\caption{The overall architecture}
	\label{fig:ToolChainComplete}
	\vspace{-0.0cm}
\end{figure}
To begin with, a data set has to be collected. Therefore, a simulation tool has been developed which generates traffic flow. The road is modeled as a highway with two or three lanes. The number of vehicles, as well as their behavior, is varied over many simulation loops. One element in varying the traffic situations is the induction of randomness to the simulation parameters.

After each loop, an algorithm checks for interesting scenarios. Within the time line of a scenario, relevant features are extracted. The features are aligned into a vector $\bm{x} \in \mathbb{R}^Q$ and used as the input for the xMURF. This intermediate step compresses the relevant information from the time series data. The feature vectors from all scenarios are then processed by the xMURF algorithm. The learning process is determined by the selected features and the given data set $\mathcal{D}$. The proposed method makes usage of the path a datapoint is following in each tree in the RF. Comparing the paths between two datapoints delivers the necessary similarity measure. The output of the xMURF is a similarity matrix with similarity values between all pairs of scenarios. This matrix is then rearranged by means of hierarchical clustering and represented as a graphic, where each pixel is colored according to its similarity value. As similar scenarios are located nearby and share a similar color, clusters get visible. Based on the visualization, clusters can be identified and labeled.

After assigning labels to each cluster, the class of each scenario can be stated. Taking again the input feature vectors with their new assigned label, one receives the data set $\mathcal{D}_\mathrm{c}$. The input data $\bm{x}$ is now assigned to a class $y$, so that
\begin{equation}
\mathcal{D}_\mathrm{c}=\left\lbrace (\bm{x}_1,y_{1}),\dots,(\bm{x}_{M_\mathrm{c}}, y_{M_\mathrm{c}})\right\rbrace,
\label{eq:Dclass}
\end{equation}
with ${M_\mathrm{c}}$ being the number of datapoints classified. Given $\mathcal{D}_\mathrm{c}$, now a supervised RF classifier is trained.

In the operational phase, a new datapoint is only assigned to a class, if a class adaptive threshold is exceeded. The threshold is computed based on the out-of-bag (OOB) method \cite{Breiman96b}.
If a datapoint gets not assigned nor clustered, that indicates, that not enough examples are collected to form a category of similar traffic scenarios for the given setup.
\section{DATA GENERATION}
\label{data_section}
This section describes the procedure of data generation to demonstrate the proposed method. It is divided into three parts: first the traffic simulation, followed by a definition for scenarios and finally a discussion about the chosen features.
\subsection{Traffic simulation}
\label{simulation_section}
In order to generate traffic flow data on a microscopic level, a simulation tool has been developed. In the previous work \cite{Kruber.2018}, SUMO \cite{SUMO_URL} was used and is replaced now for the following reasons. SUMO is optimized to simulate traffic flow for a large number of vehicles, while in this work the focus is put on more accurate vehicle models and controllers. Generally, SUMO generated traffic follows strictly accident free models, while for this work the vehicle properties are selected in such a fashion, that also highly critical constellations appear. This can rather be observed on roads than keeping guaranteed safe gaps.

Some main ideas of the simulation are described in the following. First, all participants react to the other vehicles if their safeness is affected. Every vehicle is in charge of the gap ahead on its own lane. The main goal is an accident free drive, while striving for the maximum allowed velocity. Vehicles are allowed to overtake from both, the left and right handed side. Overtaking from the right side is permitted in some countries on highways in dense traffic situations  with velocities lower than $\unit[60]{km/h}$. However, this can also be observed at higher velocities. In the simulation, the target velocity is changed over time and chosen from a normal distribution  $v \sim \mathcal{N}(\unit[18]{m/s},\,\unit[4]{m/s}$). The mean value is selected lower than permitted speed limits, which is supposed to emphasize a dense traffic situation to further increase the chance of capturing relevant scenarios.

The behavior setting includes the eagerness for higher accelerations and velocities, a risk profile which affects the accepted gaps and a politeness factor to cooperate with others during lane change maneuvers. The behavior setting changes during the simulation. As an example, a vehicle prevented from changing lanes caused by nearby vehicles on the target lane, might accept a smaller gap after some waiting time. Including such behavior models was inspired by \cite{SUMO_URL} and associated work. Depending on the vehicles settings, collisions might occur.

One possibility to increase the variety of traffic scenarios generated, is the induction of randomness. Therefore, variables describing the vehicles abilities and its behavior, are shuffled on a random basis within defined boundaries. As an example, the maximum acceleration and jerk are limited based on real vehicle measurements. Next, a highway with $n_\mathrm{l}\in\{2,3\}$ number of lanes is generated. A random number of vehicles ($n_\mathrm{v}$) within the range of
\begin{equation}
n_\mathrm{l} +1 \leq n_\mathrm{v} \leq n_\mathrm{l} \, n_\mathrm{vpl},
\end{equation}
where $n_\mathrm{vpl}$ is the maximum number of vehicles per lane, are placed on the road.
As vehicles perform lane changes and overtake others, the unique index of each vehicle must be tracked for each time step $\mathrm{ts}$. These indices are stored in a three dimensional array $\bm{A} \in \mathbb{N}^{n_\mathrm{l} \times n_\mathrm{vpl} \times n_\mathrm{ts}}$. For modeling the lane change behavior several models are available, e.\,g. \cite{Treiber.2006}. The four motivations for lane-changing are described in \cite{Erdmann.2014}. Nevertheless, the motivation for a lane change in this simulation is mainly determined on a random basis. The purpose is not to model an ideal vehicle and traffic flow behavior. Lane changes are not always based on rational effectiveness. Additionally, wrong decisions can be made due to incomplete perception regarding both, humans and autonomous vehicles. As all vehicles aim towards an accident free travel, the lane changing vehicle checks for some empty space, while the accepted gap is set according to its risk and patience level. If the gap decreases below a threshold during the lane change, the vehicle aborts its maneuver.

The longitudinal goals, which cause the acceleration at a certain time step, are determined by a leader vehicle. This behavior model is called the car-following model. Contrary to accident-free implementations, the distances in this simulation fall below an optimal safe gap to achieve a more natural approaching behavior and in order to generate critical scenarios. The maximum deceleration for a following vehicle, given optimal conditions with $a_{x} \approx \unit[-1]{g}$, is reached to eliminate the relative velocity at a distance close to zero. The leader vehicle acceleration is determined by the target velocity $v_{x,\mathrm{l}}$. Additionally, the inter-leader gap $d_\mathrm{il}$ in driving direction is bounded to $d_\mathrm{il,max}$ and overrules the target velocity, in order to keep all vehicles within a certain region and ensure dense traffic with a limited number of vehicles. The acceleration profiles are specified according to the Gompertz function
\begin{align}
a_{x,\mathrm{f}}(d_\mathrm{fl}) &= a_\mathrm{m}e^{{-be}^{(-cd_\mathrm{fl})}},\\
a_{x,\mathrm{l}}(v_{x,\mathrm{l}}, d_\mathrm{il}) &= \left\lbrace \begin{array}{l l}
a_\mathrm{m}e^{{-be}^{(-c d_\mathrm{il})}} & d_\mathrm{il} > d_\mathrm{il,max} \\
a_\mathrm{m}e^{{-be}^{(-c v_{x,\mathrm{l}})}} &\text{else}\\
\end{array}\right.,
\end{align}
where the variable $a_{x}$ applies to the actual longitudinal acceleration. The three Gompertz function variables are $a_\mathrm{m}$, $b$ and $c$, where $a_\mathrm{m}$ applies to the maximum acceleration ability and $b$ and $c$ are shuffled. The index f indicates the following vehicle, l the leader vehicle, il the inter-leader vehicle relation and fl the follower leader vehicle relationship.
The Gompertz function implies a simplified model for the mass inertia at the beginning of the acceleration, followed by a linear increase and the limited torque or braking capacity towards the maximum acceleration or deceleration, respectively. Furthermore, a reaction time is added for each vehicle.

The lateral dynamics are governed by the combination of a one-track model (OT) and a controller that steers the vehicle to the middle of its current lane, or towards the middle of the neighboring lane in case of a lane change. First, the future pose of the vehicle is predicted for a velocity dependent look-ahead time using the current velocity and steering angle during the prediction horizon. An orientation error and distance error are computed by comparing the predicted pose with the desired one. These two quantities and a velocity dependent weight are used by a P-controller
to output the steering angle. Larger distance errors favour steering the vehicle towards the desired lane, and smaller distance errors favour correcting the vehicle orientation. Finally, the OT calculates the updated state variables, which allows modeling the driving dynamics approriatly up to a lateral acceleration of $a_{y} \approx \unit[0.4]{g}$ \cite{Ammon.1997}. This is sufficient for the simulated lateral maneuvers.
\subsection{Scenario Definition}
\label{scenario_subsection}
A traffic scenario can be defined in different ways. A literature review and a proposal of a scenario definition in the sense of context modeling is given in \cite{Ulbrich.2015}. Still, up to now there is no widely accepted, unified definition available. For this work, the general understanding of a scenario is a sequence of connected events. It implies the entities and their state transitions over time.
The entities with dynamically changing states are the ego-vehicle $ego$ and the surrounding vehicles $tg$ in this work. The $tg$ are evaluated based on the relevance for the $ego$. All vehicles have their own dynamic model, the state is updated each time step. The scenery, i.\,e. the static objects, is limited to the highway road with its number of lanes and its meta data, which is here the permitted velocity. Hence, the environment model of the scenario is described in an object-based form. All relevant objects in the vicinity of the $ego$ are tracked and evaluated over time. An alternative form would be the grid-based form, which discretizes the static environment into cells of equal size. The existence of objects is indicated by the occupancy of the cells in the stationary raster map \cite{Maurer.2016b}.

The starting point of a scenario for this work is set if a criticality measure is exceeded and ends whenever the value falls below the threshold again. Hence, the scenario contains an arbitrary number of entities and maneuvers in an arbitrary period of time.

Plenty of options to choose a criticality measure can be utilized, for example \cite{Wachenfeld.2016b, Wagner.2018}. In \cite{Kitajima.2009} several measures are compared, including the common Time-To-Collision (TTC) and Time-Headway (THW). The THW is calculated by the relative distance over the $ego$ velocity. The TTC is introduced as the relative distance divided by the relative velocity, which is difficult to estimate for humans. The paper \cite{Kondoh.2008} analyzes THW and TTC more detailed: The THW determines the car-following strategies of drivers and the magnitude of the THW influences their stress level.
Because of its intuitiveness and its reflection of the stress level for drivers or passengers in automated vehicles, the THW is chosen here.

In this work, the recording of a scenario begins far beyond criticality. It is rather an undercutting a comfort zone, which is set to $\mathrm{THW} \leq \unit[1.0]{s}$. As a constraint, the scenario is withdrawn if $\mathrm{THW_{min}} > \unit[0.8]{s}$ to retrieve scenarios with some inter-vehicle dynamics, where $\mathrm{THW_{min}}$ corresponds to the minimum THW in the scenario. The goal is to record the evolving situation from a normal state to its maximum criticality and the recording is continued until the scenario resolves and reaches either a comfortable state again or ends in a collision. In order to be able to better judge the numbers, following the administrative rule of thumb for German highways would yield a $\mathrm{THW} \approx \unit[1.8]{s}$. Approaching the leader vehicle closer than $\mathrm{THW} \leq \unit[0.9]{s}$ is punishable because of violating a safe distance \cite{Filzek.2002}.
\subsection{Feature generation}
The features are derived from both, time and space considerations of the scenario. They all share some relevance to the $ego$ and can be recorded by state of the art vehicles. It is assumed, that the data source is exclusively the $ego$ sensors and no presence of V2X communication. The goal is to find a set of features, which gives an appropriate balance to capture the environment in 360 degrees over time, while still being compact for fast computation. Some features are discussed in this section, the complete set is available under \cite{KruberGithub.2019}.

As mentioned before, the existence of a scenario is defined by its criticality magnitude, which results in arbitrary time spans. Therefore, the features which are related to the time dimension, are set up on three time instances: At the beginning and the end of a scenario and at the critical changepoint, which is here defined by $\mathrm{THW_{min}}$. Other features observe changes over time. As an example, the actual distance to the leader vehicle is compared to the desired distance over time by utilizing the dynamic time warping function, which compares the shapes of two curves. A high discrepancy between both curves indicates high dynamics between both vehicles and thus criticality.

The area around the $ego$ is divided into six zones. It is assumed, that the maximum number of vehicles, which influence the $ego$ directly and vice versa, is limited to six. This proposition is depicted in Fig. \ref{fig:vehicles}, where the red vehicle represents the $ego$. The six surrounding vehicles determine its moving options in longitudinal and lateral direction. As a consequence, the relative distance to all of those vehicles is important and added to the feature set. The desired relative distances act as simplified forms of safety zones, which are schemed by the green boxes in Fig. \ref{fig:vehicles}. The safety zones determine the $ego$s options to plan its trajectory and prevents the vehicles from contact. The main attention while defining features, however, is focused on the interaction with the leader vehicle.
\begin{figure}
\par\smallskip
\centering

  \input{streetOverview.tex}
	\caption{The movement of the ego vehicle (red) is determined by the six surrounding vehicles. Therefore the surrounding space is divided into six regions. The size of the regions is adapted to the velocity.}
	\vspace{-0.2cm}
	 \label{fig:vehicles}
	 \vspace{-0.0cm}
\end{figure}

Other features are defined according to the semantics of the road, which are in a simplified highway case the number of lanes. Features indicating a lane change of the $ego$, as well as changes of a $tg$, which result in a cut-in maneuver from the $ego$ perspective are captured. Also the lane index of the $ego$ is taken into account: it emphasizes, if the $ego$ had the chance to escape the threatening situation by performing a lane change onto the left or right side.
In total a set of 47 features are selected to be fed in the clustering process. The description of all features, along with the recorded features for all generated scenarios, are given in \cite{KruberGithub.2019}.
\section{CLUSTERING}
\label{clustering_section}
The aim of this work is to find scenario categories in an unlabeled data set. For this purpose, the clusters are defined manually by examining a sorted proximity matrix $\bm{P}_\mathrm{o}$ visually. The unsorted proximity matrix  $\bm{P}$ itself is generated based on the xMURF algorithm, which is presented in this section.
\subsection{The Extended Unsupervised Random Forest}
In the previous work \cite{Kruber.2018}, a modification of the RF algorithm \cite{Breiman2001random} for unsupervised usage is shown, called MURF. The MURF algorithm is based on the Unsupervised RF (URF) \cite{Breiman02URF,Shi2006}. The aim of the URF is to provide a data adaptive similarity measure in terms of the RF proximity. In \cite{Kruber.2018} also the graphical interpretation of the resorted proximity matrix is explained, where the resorting is realized through hierarchical clustering. In this paper, some extensions to this technique are shown.

The URF is used to generate a data adaptive similarity measure. In order to perform unsupervised learning with a RF, a noise data set $\mathcal{S}$ is generated based upon the given data set $\mathcal{D}$. The RF is trained to solve the classification task, where it has to be distinguished between the given data set $\mathcal{D}$, labeled as one class, and the generated noise data set $\mathcal{S}$, labeled as a different class. This way, the trees have to fit their leaves to the given data set $\mathcal{D}$. Extracting the RF proximity for the given data set leads to a data adaptive similarity measure. In the MURF algorithm proposed in \cite{Kruber.2018}, the noise data is not generated, instead it is assumed in each split. The used distribution to calculate the necessary number of noise datapoints is based on an uniform distribution.

On the one hand side, the MURF algorithm enables one to adjust the granularity of the proximity measure by adjusting the impurity level, which is used as the pruning criterion. On the other hand side, the results are very sensitive to the choice of this hyperparameter, leading to a tedious tuning process. Since the RF proximity just examines the terminal leaves, the pruning has a large influence on the resulting similarity measure.

In this paper two important extensions of the MURF algorithm are introduced. Both are summarized in the algorithm called xMURF. First, the pruning impurity parameter is removed by extracting the similarity out of the datapoints' paths through the trees instead of only taking the terminal leaves into account. Therefore, the path proximity is introduced in this paper. In xMURF the complete information regarding the similarity provided by the RF is captured, which makes the process robust. Second, the dependency on the uniform distribution in MURF, used to calculate the splits, is optimized. In the xMURF algorithm the used distribution at each split is randomly chosen from a set of predefined probability density functions.

The proximity matrix $\bm{P}$ generated by the xMURF algorithm is reordered by hierarchical clustering, following the explanations in \cite{Kruber.2018, Behrisch2016}. For this purpose, one has to extract the leaf order of the dendrogram, which represents the hierarchical clustering. Then, the matrix $\bm{P}$ is resorted corresponding to the leaf order of the dendrogram, such that the similarity between the neighbors gets higher. If necessary, an optimal leaf ordering algorithm can be applied to refine the sorting further.

The reordered matrix $\bm{P}_\mathrm{o}$ is then examined graphically, in order to identify clusters as well as inter-cluster relationships. Some general rules for the interpretation are also explained in \cite{Kruber.2018} and more detailed in \cite{Behrisch2016}. Clusters will appear as bright squares (high similarity) along the diagonal of the proximity matrix. An example is depicted in Fig. \ref{fig:prox_Matrix}.
\subsection{Path Proximity}
This work introduces a novel proximity measure for the RF algorithm. The proximity measure takes into account the full paths of the datapoints through the trees instead of just using the terminal leaves. In \cite{Englund.2012} an alternative proximity measure for the RF was introduced, where the distance between two terminal leaves is examined.

Let a RF consist of $B$ trees $T$, where the $b$th tree $T_b$ is constructed based on the bagged data set $\mathcal{D}_b$. Then a tree $T_b$ consists of $N_b$ nodes $t_{n,b}$. A path of a datapoint through a tree can be defined by a set including all nodes the datapoint passed. This leads to the path formulation as
\begin{equation}
\mathcal{T}_{i,b} = \left\lbrace t_{1,b},t_{n_{i_2},b},\dots,t_{N_i,b}\right\rbrace,
\end{equation}
where $i$ is an index, representing the $i$th data point $\bm{x}_i$. The node $t_{1,b}$ is the root node of the $b$th tree $T_b$ and hence the first node on the path of the $i$th datapoint. The node $t_{n_{i_2},b}$ is the second node on the path, where $n_{i_2}$ represents the node number $n$ the datapoint has passed. The last node on the path of the $i$th data point in the $b$th tree is $t_{N_i,b}$.

In order to compare the paths of two datapoints $i$ and $j$ through the $b$th tree, the corresponding sets $\mathcal{T}_{i,b}$ and $\mathcal{T}_{j,b}$ need to be compared. In this work, the Jaccard Index \cite{Jaccard.1912}
\begin{align}
P_{ij}\left(b\right) &= \frac{\vert\mathcal{T}_{i,b}\cap\mathcal{T}_{j,b}\vert}{\vert\mathcal{T}_{i,b}\cup\mathcal{T}_{j,b}\vert}\\
&=\frac{\vert\mathcal{T}_{i,b}\cap\mathcal{T}_{j,b}\vert}{\vert\mathcal{T}_{i,b}\vert+\vert\mathcal{T}_{j,b}\vert-\vert\mathcal{T}_{i,b}\cap\mathcal{T}_{j,b}\vert}\label{eq:pathProxSingleTree}
\end{align}
is used for this purpose. It holds that $P_{ij}(b)\in(0,1]$, since at least the root node is present in both sets. This way, a similarity measure, given the two datapoints $i$ and $j$, based on the $b$th tree is defined. In Fig. \ref{fig:pathProximity} an example tree with two arbitrary paths is shown. The mutual path of both datapoints is marked in ocher, where the single paths are shown in green and red. Interpreting Eq. (\ref{eq:pathProxSingleTree}) based on Fig. \ref{fig:pathProximity} leads to $\vert\mathcal{T}_{i,b}\cap\mathcal{T}_{j,b}\vert$ being the length of the mutual path and $\vert\mathcal{T}_{i,b}\vert$ being the length of the $i$th path ($i$th datapoint) starting from the root node, $\vert\mathcal{T}_{j,b}\vert$ respectively. For the given example, the corresponding Jaccard index would be $\nicefrac{2}{5}$. Or in other words, the $i$th and $j$th datapoints have a similarity of $0.4$. A value of $1$ indicates, that both datapoints are identical or very similar according to the given tree.
\begin{figure}
\par\medskip
\centering
	\input{baseTree_doublePath1.tex}
	\caption{Path proximity example}
	\vspace{-0.3cm}
	\label{fig:pathProximity}
	\vspace{-0.0cm}
\end{figure}

By averaging over all $B$ values $P_{ij}\left(b\right)$ in a forest, one achieves the RF path proximity
\begin{equation}
P_{ij}=\frac{1}{B}\sum\limits_{b=1}^B \frac{\vert\mathcal{T}_{i,b}\cap\mathcal{T}_{j,b}\vert}{\vert\mathcal{T}_{i,b}\vert+\vert\mathcal{T}_{j,b}\vert-\vert\mathcal{T}_{i,b}\cap\mathcal{T}_{j,b}\vert}.
\end{equation}
If two datapoints have the same paths in all trees the proximity will be one. Contrary, if they only share the root nodes, the proximity will be very small tending towards zero, the longer both paths are. The RF path proximity enables one to cover more than just the leaf information of the forest within one scalar value.

As already mentioned, the path proximity removes the highly sensible impurity pruning parameter from the MURF algorithm. Fully grown, instead of pruned trees can be used, since they lead to a more meaningful similarity measure.
\subsection{Ensemble Noise}
In this work, a random selection of noise distribution at each split is performed, called ensemble noise. During the construction of the xMURF, the used distributions are chosen randomly from a collection of predefined distributions.

The estimated Gini impurity for the node $t$ in an arbitrary tree is defined as
\begin{equation}
r(t) = \sum\limits_{c=1}^C \frac{M_c(t)}{M(t)}\left(1-\frac{M_c(t)}{M(t)}\right),
\end{equation}
where $C$ is the number of classes (2 for the xMURF) and $M_c(t)$ the number of datapoints in node $t$, which belong to class $c$. Based on the Gini impurity, the Gini gain $\Delta R$ resulting by splitting $t$ into the child nodes $t_\mathrm{L}$ (left) and $t_\mathrm{R}$ (right) is defined by
\begin{equation}
\Delta R(t,t_\mathrm{L},t_\mathrm{R}) = r(t)-\frac{M(t_\mathrm{L})}{M(t)}r(t_\mathrm{L})-\frac{M(t_\mathrm{R})}{M(t)}r(t_\mathrm{R}).
\end{equation}
The optimal split is given if $\Delta R(t,t_\mathrm{L},t_\mathrm{R})$ is maximal. Hence, the number of datapoints of each class in each node ($t$, $t_\mathrm{L}$ and $t_\mathrm{R}$) is required. The number of original datapoints $M_{\mathcal{D}_b}\left(t_{n,b}\right)$ of the bagged data set $\mathcal{D}_b$ belonging to the $b$th tree in the $n$th node $t_{n,b}$ of this tree, as well as in the possible child nodes can simply be counted. The number of noise datapoints in the same node needs to be estimated for a given split value $\tau_{\tilde{q}}$. Let $z_{\tilde{q}}$ be the standardized value of $\tau_{\tilde{q}}$ (see Eq. (\ref{eq:tauz})). Then, the number of noise datapoints for the left and right child nodes of a given node $t_{n,b}$ is calculated as
\begin{align}
M_{\mathcal{S},\mathrm{l}_{n,b}}\left(z_{\tilde{q}}\right) &= M_{\mathcal{D}_b}\left(t_{n,b}\right) \mathrm{P}\left(\randScal{z}_{\tilde{q}}\leq z_{\tilde{q}}\right)\text{ and}\\
M_{\mathcal{S},\mathrm{r}_{n,b}}\left(z_{\tilde{q}}\right) &= M_{\mathcal{D}_b}\left(t_{n,b}\right)-M_{\mathcal{S},\mathrm{l}_{n,b}}\left(z_{\tilde{q}}\right),
\end{align}
where $\tilde{q}$ stands for the $\tilde{q}$th dimension of the vector whose features are chosen randomly in each node when constructing the trees in a RF. The number of features that are used at each split of each tree in the RF is $\tilde{Q}\in\mathbb{N}$, with $\tilde{Q}=\lfloor\sqrt{Q}\rfloor$. The values $M_{\mathcal{S},\mathrm{l}_{n,b}}$ and $M_{\mathcal{S},\mathrm{r}_{n,b}}$ denote the number of corresponding noise points in the left and right child note of $t_{n,b}$, given that the split $\tau_{\tilde{q}}$ is chosen, since $z_{\tilde{q}}$ is the standardized value of $\tau_{\tilde{q}}$. $ \mathrm{P}\left(\randScal{z}_{\tilde{q}}\leq z_{\tilde{q}}\right)$ is the value of the cumulative density function at the standardized threshold $ z_{\tilde{q}}$. The standardized threshold $ z_{\tilde{q}}$ in the $\tilde{q}$th RF dimension is determined with
\begin{align}
z_{\tilde{q}} &=\frac{\tau_{\tilde{q}}-\mu_{\tilde{q}}}{\sigma_{\tilde{q}}},\label{eq:tauz}\\
\mu_{\tilde{q}} &=\frac{\mathrm{max}\left\lbrace \mathcal{X}_{t_{n,b}}\right\rbrace_{\tilde{q}}+\mathrm{min}\left\lbrace \mathcal{X}_{t_{n,b}}\right\rbrace_{\tilde{q}}}{2},\\
\sigma_{\tilde{q}} &=\frac{\mathrm{max}\left\lbrace \mathcal{X}_{t_{n,b}}\right\rbrace_{\tilde{q}}-\mathrm{min}\left\lbrace\mathcal{X}_{t_{n,b}}\right\rbrace_{\tilde{q}}}{6},
\end{align}
where $\mathrm{max}\left\lbrace \mathcal{X}_{t_{n,b}}\right\rbrace_{\tilde{q}}$ and $\mathrm{min}\left\lbrace \mathcal{X}_{t_{n,b}}\right\rbrace_{\tilde{q}}$ yield the maximum or minimum value of the subspace $\mathcal{X}_{t_{n,b}}$ in the dimension specified by $\tilde{q}$. The interval of a node covers $\pm 3\,\sigma_{\tilde{q}}$.

The first distribution used is the uniform distribution, where its cdf is given by
\begin{equation}
\mathrm{P}_\mathrm{u}\left(\randScal{z}_{\tilde{q}}\leq z_{\tilde{q}}\right)=\frac{1}{6}z_{\tilde{q}}+\frac{1}{2}.
\end{equation}
The standard normal distribution is the second used distribution and is approximated through \cite{Waissi.1996}
\begin{equation}
\mathrm{P}_\mathrm{n}\left(\randScal{z}_{\tilde{q}}\leq z_{\tilde{q}}\right)=\frac{1}{1+e^{-\sqrt{\pi}\left(\beta_1 z_{\tilde{q}}^5+\beta_2 z_{\tilde{q}}^3+ \beta_3 z_{\tilde{q}}\right)}},
\end{equation}
where $\beta_1=-0.0004406$, $\beta_2=0.04181198$ and $\beta_3=0.9$ holds.
Third, a bimodal distribution is used, which is build as the sum of two shifted standard normal distributions $\mathrm{P}_\mathrm{n}$ with
\begin{equation}
\mathrm{P}_\mathrm{b}\left(\randScal{z}_{\tilde{q}}\leq z_{\tilde{q}}\right)=\mathrm{P}_\mathrm{n}\left(\randScal{z}_{\tilde{q}}\!-\!3\leq z_{\tilde{q}}\!-\!3\right)+\mathrm{P}_\mathrm{n}\left(\randScal{z}_{\tilde{q}}\!+\!3\leq z_{\tilde{q}}\!+\!3\right).
\end{equation}

The randomly selected noise distributions at each split relax the dependency of the proximity measure to one specific distribution. Clearly, it is also possible to add other distributions to the assortment.
\section{CLASSIFICATION}
\label{classification_section}
This section describes, how the clustering results can be used for the operational phase, where new datapoints are compared to the known clusters.
Once the xMURF is trained with a data set $\mathcal{D}$ and the clusters are selected, they get assigned with a label resulting in a data set $\mathcal{D}_\mathrm{c}$ from Eq. (\ref{eq:Dclass}).
Then a RF classifier is trained with $\mathcal{D}_\mathrm{c}$.

A class adaptive threshold is calculated as follows. The OOB method is used to determine $\kappa_i$, which is the proportion of the votes for the correct class for the $i$th datapoint. The class adaptive threshold $\bar{\kappa}_c$ is computed as the average value of all $\kappa_i$ belonging to the class $c$.

Next, the trained RF is used to predict the class assignment for a datapoint $\bm{x}_{i,\mathrm{new}}$ from a new data set $\mathcal{D}_\mathrm{new}$. The proportion of the votes of all trees for the winning class $c$ is compared to the class adaptive threshold $\bar{\kappa}_{c}$. If the value is below the threshold $\bar{\kappa}_{c}$, the assignment is withdrawn.

The threshold $\bar{\kappa}_{c}$ is dependent to the choice of clusters. Using an adjustable ratio of $\bar{\kappa}_c$, enables one to select an appropriate class assignment threshold, such that it fits to the given requirements. The ratio can be used to loosen or increase the strictness for the decision of assigning or withdrawing new datapoints to a class.

Setting the threshold equally for all clusters, the assignment rate would be favored towards clearly separable clusters.
\section{RESULTS}
\label{results_section}
This section discusses results of the proposed architecture using an example data set $\mathcal{D}_{1}$ with $ M = 5131$ generated scenarios. The scenarios can be divided into three main types: The $ego$ approaching its leader vehicle while following its lane (type $\mathrm{A}$), the $ego$ performing a lane change and violating the safety zone after the lane change (type $\mathrm{L}$) and a cut-in maneuver performed by a $tg$ causing the violation (type $\mathrm{C}$). A combination of type B and C also appears in some clusters.
The xMURF was trained with $B = 300$ trees. The symmetric proximity matrix $\bm{P}_\mathrm{o}$ of number $M \times M$ is depicted in Fig. \ref{fig:prox_Matrix}, where yellow pixels indicate a high similarity, dark blue pixels a low similarity. Each pixel contains the value of the similarity measure of two compared scenarios.
\begin{figure}
\par\medskip
\centering
\input{proxRect.tex}

	\caption{The resulting proximity matrix of data set $\mathcal{D}_{1}$, where yellow pixels indicate a high similarity. Clusters are represented as bright squares along the diagonal. Inter-cluster similarities are depicted as bright areas outside the clusters.}
	\vspace{-0.3cm}
	\label{fig:prox_Matrix}
	\vspace{-0.0cm}
\end{figure}
A zoom-in view on the graphic reveals, that bigger dominant cluster contain smaller clusters. For demonstration purposes in total 100 clusters were manually chosen. The clustered scenarios can be downloaded and plotted in Matlab \cite{KruberGithub.2019}. The question how many clusters to choose is a problem specific one and therefore has to be adjusted to the requirements. The clusters can be selected by the following criteria: the minimum number of datapoints within a cluster, the minimum similarity value within that cluster, the homogeneity within that cluster and the deviation of the inter-cluster similarity in the local region around that cluster. The inter-cluster similarity is indicated by the brightness of the pixels outside the clusters. The next sub-section will give examples on some clusters.
\subsection{Scenario cluster examples}
This section discusses examples of clusters, that result by applying the presented method. The example scenarios are depicted in Fig. \ref{fig:ScenarioExamples}. The figure depicts in total 6 scenarios, each one is a representative of its cluster.
\begin{figure}
\par\medskip
\captionsetup[subfigure]{labelformat=empty}
	\center
	\vspace{-0.24\carLength}
	\begin{subfigure}[c]{0.48\columnwidth}
 		\resizebox{\columnwidth}{!}{\input{Approach1.tex}}
 		\vspace{-0.9cm}
 		\caption{$\mathrm{A_{1}}$}
	\end{subfigure}
	\begin{subfigure}[c]{0.48\columnwidth}
 		\resizebox{\columnwidth}{!}{\input{Approach2.tex}}
 		\vspace{-0.9cm}
 		\caption{$\mathrm{A_{2}}$}
	\end{subfigure}
	\begin{subfigure}[c]{0.48\columnwidth}
		\resizebox{\columnwidth}{!}{\input{LaneChange2.tex}}
		\vspace{-0.9cm}
		\caption{$\mathrm{L_{1}}$}
	\end{subfigure}
	\begin{subfigure}[c]{0.48\columnwidth}
 		\resizebox{\columnwidth}{!}{\input{LaneChange1.tex}}
 		\vspace{-0.9cm}
 		\caption{$\mathrm{L_{2}}$}
	\end{subfigure}
	\begin{subfigure}[c]{0.48\columnwidth}
		\resizebox{\columnwidth}{!}{\input{CutIn2.tex}}
		\vspace{-0.9cm}
		\caption{$\mathrm{C_{1}}$}
	\end{subfigure}
	\begin{subfigure}[c]{0.48\columnwidth}
 		\resizebox{\columnwidth}{!}{\input{CutIn1.tex}}
 		\vspace{-0.9cm}
 		\caption{$\mathrm{C_{2}}$}
	\end{subfigure}
		\caption{Each row depicts two examples for each scenario type ($\mathrm{A}$, $\mathrm{L}$, $\mathrm{C}$). The red vehicle depicts the $ego$, all $tg$ are colored gray. The arrow indicates the driving direction. The color of the arrow visualizes the acceleration, where green stands for positive, red for negative acceleration and blue for steady drive. The two arrows in the middle of the lines additionally indicate the accelerations, positive as well as negative.}
	\label{fig:ScenarioExamples}
	\vspace{-0.2cm}
\end{figure}
Note, that a $tg$ (gray) is only shown in case it is located on the neighboring lane of the $ego$ (red). The first row depicts two scenarios of type approach (type A). In Fig. \ref{fig:ScenarioExamples}-$\mathrm{A_{1}}$, the $ego$ approaches the leader vehicle with a high relative velocity and brakes hard. This is a typical example for the A type scenarios, where the relative velocity and distance were estimated inappropriately by the $ego$. Fig. \ref{fig:ScenarioExamples}-$\mathrm{A_{2}}$ depicts a similar scenario, yet the consequences of such a scenario differs: first, the rear $tg$ on the same lane as the $ego$ does get affected and has to brake, which might emerge to a critical situation in a second phase. Second, the $ego$ does not have the chance to change the lane without risking a subsequent critical situation, as it would be enclosed by two other $tg$. That could cause a scenario as depicted in the below sub-figure $\mathrm{L_{2}}$.
The second row depicts two lane change scenarios. In Fig. \ref{fig:ScenarioExamples}-$\mathrm{L_{1}}$ the decision of $ego$ does not affect its environment. Contrary, in Fig. \ref{fig:ScenarioExamples}-$\mathrm{L_{2}}$ it causes the rear vehicle on the middle lane to brake, while the rear vehicle on the left lane starts accelerating due to the now given empty space, which closes the neighboring space on the left lane for the ego vehicle.
The last row shows two cut-in maneuvers. Fig. \ref{fig:ScenarioExamples}-$\mathrm{C_{1}}$ depicts a typical cut-in maneuver. Due to a relatively high distance to the new leader (the cut-in performing $tg$ in the very front), the $ego$ is only affected slightly and brakes decently, illustrated by a slightly transparent red arrow. In Fig. \ref{fig:ScenarioExamples}-$\mathrm{C_{2}}$ the cut-in performing $tg$ brakes, forcing the $ego$ to perform a hard braking maneuver, which in consequence forces the rear vehicle to react as well. A risk mitigating lane change maneuver of the $ego$ is limited to the left side and would influence the rear vehicle on the middle lane.

Summarizing the above, all three scenarios in the left column show typical scenarios chosen out of the resulting automatically generated clusters for demonstration purposes of each type. The risk level during those scenarios is rather low and the $ego$ could theoretically perform a lane change to further mitigate the risk level it is exposed to. Also, its behavior does not directly influence its surrounding vehicles. On the right side, the same scenario types are depicted. Still, the $ego$ has less options for risk mitigating actions and its decisions influence the surrounding vehicles. These examples demonstrate, that dividing scenarios into categories has to include all relevant entities and scenery features, which results in a large variety of categories. Obviously, discussing the scenarios on this abstracted level, the risk and the influence of the $ego$ decision is correlated to the traffic density, which is consistent with the observations on real highways. The important aspect is, that these structures can be identified in an unsupervised, data adaptive way by means of a very compact scenario description. The data set is provided to the xMURF algorithm without any other additional information or pre-defined rules. The set of clusters available at \cite{KruberGithub.2019} show many more constellations. The clusters differ in the number of vehicles, but also in other aspects as the velocity, accelerations and the general vehicle behavior described in Section~\ref{simulation_section}.
\subsection{Scenario classification}
To demonstrate how the selected clusters can be used to classify new scenarios, a new data set $\mathcal{D}_{2}$ is generated and processed as described in Section \ref{classification_section}.
In Table \ref{tb:Tabelle} the assignment rates for different ratios of $\bar{\kappa}_{c}$, given the data set $\mathcal{D}_{2}$, are depicted.
\begin{table}[h]
\centering
\begin{tabular}{ | c | c |}
  \hline
  Ratio of $\bar{\kappa}_{c}$ & Assigned Scenarios\\
  \hline
  1.00 & 34\%\\
  \hline
  0.75 & 55\%\\
  \hline
    0.50 & 81\%\\
  \hline
    0.25 & 98\%\\
    \hline
\end{tabular}
\caption{Assigned scenarios of validation the data set $\mathcal{D}_{2}$}
\label{tb:Tabelle}
\end{table}
Reducing the ratio leads to more datapoints being assigned, since the class membership criterion is less strict. The ratio of $\bar{\kappa}_{c}$ can be considered as an hyperparameter to adjust the required confidence measure of belonging to the class.

The classified scenarios of $\mathcal{D}_{2}$ can be compared with those from $\mathcal{D}_{1}$ by using the provided plot function, or by analyzing the data sets. The data sets are available at \cite{KruberGithub.2019}.
\section{CONCLUSIONS}
\label{conclusions_section}
The presented paper proposes an architecture to cluster traffic scenarios in an unsupervised way. The xMURF reveals the structure of the data and enables one to find similar scenarios and groups them in clusters. Compared to the previously presented work, this version is improved by introducing a path proximity and the ensemble noise method.
The method was examined with traffic simulation data. The main principles of the simulation and generation of the data is described in this paper. Additionally, the scenarios are available under \cite{KruberGithub.2019}. Finally, an approach to classify new scenarios based on a class dependent threshold, which takes the initial clustering process into account, is presented.

The proposed architecture can also be applied for other purposes, where one is interested in finding patterns of complex data sets and the output is not known beforehand.

\addtolength{\textheight}{-12cm}

\section*{ACKNOWLEDGMENT}
The authors acknowledge the financial support by the Federal Ministry of Education and Research of
Germany (BMBF) in the framework of FH-Impuls (project number 03FH7I02IA). The authors thank the AUDI AG department for Testing Total Vehicle for supporting this work.

\bibliographystyle{IEEEtran}

redpajama_set_name: RedPajamaArXiv


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text:
Texas billionaire H. Ross Perot dies at 89
By: Melissa Hudson Facebook | Twitter
Posted: Jul 9, 2019 12:16 PM EST
By DAVID KOENIG AP Business Writer
As a boy in Texarkana, Texas, Perot delivered newspapers from the back of a pony. He earned his billions in a more modern way, however. After attending the U.S. Naval Academy and becoming a salesman for IBM, he went his own way — creating and building Electronic Data Systems Corp., which helped other companies manage their computer networks.
Yet the most famous event in his business career didn't involve sales and earnings; he financed a private commando raid in 1979 to free two EDS employees who were being held in a prison in Iran. The tale was turned into a book and a movie.
Perot's wealth, fame and confident prescription for the nation's economic ills propelled his 1992 campaign against President George H.W. Bush and Democratic challenger Bill Clinton. Some Republicans blamed him for Bush's loss to Clinton as Perot garnered the largest percentage of votes for a third-party candidate since former President Theodore Roosevelt's 1912 bid.
During the campaign, Perot spent $63.5 million of his own money and bought 30-minute television spots. He used charts and graphs to make his points, summarizing them with a line that became a national catchphrase: "It's just that simple."
Facebook's new currency plan is under scrutiny in Congress
Fundraising goal met on park honoring slain Indiana teens

redpajama_set_name: RedPajamaCommonCrawl


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Very few people stay at the same job their entire career. As you learn and grow, your skills and experience expand. Sometimes, better opportunities just land in our laps. Sometimes, we are totally done with a position, boss or company.
So, no matter the reason you are leaving, extend courtesy and consideration when you resign.
When you leave a role, your position needs to be replaced and there is always a learning curve for your replacement. Provide enough notice so your position and duties are covered.
A two-week resignation notice is normal, and I don't recommend you go over that length of time for various reasons.
Be aware, however, access to sensitive documents or being in a management position may lead to an immediate dismissal. So, remember it is done for reasons that have nothing to do with how you are viewed by your employer.
Your formal resignation notice should be brief and to the point. There is no need to gloat or go into detail about why you have chosen to accept another position. State a better fitting job opportunity has presented itself and leave it at that. If you have constructive criticism, do it during your exit interview.
If you resign, you need to make sure you are absolutely ready to leave. If you are hesitant about actually leaving, don't resign. Your hesitancy will be felt by both the hiring company and your current employer and could have disastrous results.
Often, your employer will try to match a salary or offer other enticements into staying. People who use "I have a new, better paying job" as a ploy to get a raise aren't respected and won't benefit in the long run. Being indecisive keeps someone else from being offered a position they deserve and want. If you have any doubts, don't even start applying elsewhere.
Give your notice at the end of the week whenever possible. Ask your manager or HR for a private meeting. You'll allow everyone involved time to reflect on how to best plan for your last two weeks. It also slows panic and rumors.
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text:
Top things to see in Ba Na Hills
jacky_travel
Ba Na Hills is one of the most popular attraction around Danang city. There are many things to see in Ba Na Hills. Ba Na Hills is a mountaintop resort complex that looks like a medieval castle, but inside these stone walls are modern accommodations, world class restaurants and a Fantasy Park full of exciting rides. Here are the top things to see in Ba Na Hills.
Located just 35 kilometers away from Danang city on Nui Chua mountain, Ba Na Hills is a tourist destination for domestic and foreign travelers. With a cooler and moderate climate, Ba Na Hill station was praised as 'Da Lat of Da Nang city' ever since the hill station's inauguration in 1919, built by the French.
In 2018, the opening of the Golden Bridge has given to Ba Na hills the popularity like never before. But if you don't know much about the other things to see in Ba Na Hills other than the Golden Bridge, then our article will help you to spend a wonderful day there.
Firstly, the name 'Ba Na' comes from Katu language. Katu language comes from the local ethnic minority group residing in the area, which means 'my mountain'.
There are three parts of Ba Na Hills:
Lower part: Le Jardin D'Amour Garden, Debay Cellar, Golden Bridge,…
Upper part: French Village, Fantasy Park,…
Mountaintop: Tru Vu Tea Corner, Spiritual Zone,…
Ride the cable cars
Visitors can only get to Ba Na Hills via cable cars. Ba Na Hills cable car system is one of the most impressive ten cable car lines on earth.
The cable car system at Ba Na Hills was completed in 2013 and holds several Guinness World Records, including the widest gap between stations and the greatest change in elevation. You will have a spectacular view on Danang and on a natural landscape from the cable car.
With three lines of cable cars of total 25 kilometers in length, the longest ride takes you about 20 minutes to get to the mountaintop. The lines departing from Da Nang are:
Dream Spring Station – Ba Na Station
By taking this short line, you can visit Linh Ung Pagoda with the giant Buddha statue and take funicular to Le Jardin D'Amour – a lovely French garden. After that, take the Debay – Morin cable car to Chua mountaintop to visit resort complex and Fantasy Park.
Toc Tien Station – L'Indochine Station
This is the line that holds several world records: longest one-wire sling, greatest elevation between station, longest unpatched wire and heaviest cable roll in the world. The ride takes you around 20 minutes and travel over the beautiful Toc Tien waterfall.
Hoi An Station – Marseille Station
From Hoi An Station, the cable car ride will take you to Marseille Station which is located just next to the famous Golden Bridge. From this station you must take a funicular to the garden Le Jardin D'Armour and Linh Ung Pagoda. To visit the mountaintop, take another cable car at Bordeaux Station.
You might think the cable car fee is too expensive but actually it's inclusive many activities you can enjoy on Ba Na Hills and the scenery during the ride is absolutely worth every of your penny. Especially, from the cabin you can admire the beautiful panoramic view of mountains and sea.
Walk on the famous Golden Bridge
The Golden Bridge is one the most famous things to see in Ba Na Hills. This attraction was famous even before its opening in 2018. Since it's officially opening, the bridge has created a worldwide phenomenon and become one of the most beautiful landscape on earth according to Time magazine.
Why is the Golden Bridge so famous for tourists all over the world? The most obvious reason is its staggering appearance – a delicate gilded bridge being lifted by two giant stone hands, with an amazing view on Da Nang city.
It's safe to say that Golden Bridge is the most instagrammable man-made construction in Vietnam right now. For the most gorgeous pictures, come to visit Ba Na Hills in summertime !
The French Village
The French village in Ba Na Hills is a miniature Europe with medieval French architecture beautifully designed on every of its corner and alley.
You might actually feel like you are in the French Alps. When the mists come up at night, or when the clouds fog cover the entire mountaintop, the illusion is even more complete. The cobblestone streets and European-style buildings are remarkably well-built considering that this resort is in Vietnam and at an elevation of 1,500 metres (4,921 feet).
Any visitor would gasp at the sight of the village when see it at the first time. French village is a complete town complex that consists all most everything: a church, a square with fountain, shops, eateries and hotels. With little to none fusion with other architecture style and the cool mountain air, these monuments are the things to see in Ba Na Hills !
Not only the architecture and the ambience, there are a lot street artists performing on the streets of French village. They will also take pictures with you. At night, these small yet gorgeous French town sparkles with the colorful lights on.
If you want to stay longer at French village, Mercure Hotel should be your choice, not only for its luxury accommodation services but also because it look just like any other French building here, making feel like you're not staying at a hotel but rather a local residence.
Le Jardin D'Amour Flower Gardens
This beautiful garden is located at the lower part of Ba Na Hills, together with Linh Ung Pagoda, the giant Buddha white statue and Debay Wine Cellar. To get to the complex, you'll take a short funicular ride.
Le Jardin D'Amour welcomes you with its gorgeous beauty of 9 different gardens which tell 9 different love stories. This is the paradise of those who are fans of flowers and European architecture, you'll have the chance to admire the quintessence of them both. A harmony that will please every visitor who sets foot here.
The nine gardens are: Love Garden, Mystery Garden, Legendary Garden, Memory Garden, Heaven Garden, Grape Garden, Brain Storming Garden, Dream Spring Garden, and Sacred Garden.
Love Garden is the most popular of them.
The Wax Museum
If you would like to meet the most famous people of the world and take a photo with them, the wax museum is one the things to see in Ba Na Hills. There are some approximations on the wax statues but most of them seems to be real.
The Alpine Coaster
The Alpine Coaster is for children and people who like roller coasters. The Alpine Coaster will make you feel like in a speed car. The cars can go up to 40km/h (24 mph), but don't worry, each car comes with its own braking system so you can go as fast or slow as you want. The Alpine Coaster is one the things to see in Ba Na Hills for children.
The 4D Death Race experience
Featuring a large 3D screen and moving seats, the Death Race lets guests feel the thrills of flying in a Formula 1 air race — but from the comfort of an air-conditioned theatre. There are even machines for wind, steam and smoke to further trick the senses. Your children will be very happy to try this attraction which is one of the famous things to see in Ba Na Hills for children.
The Drop Tower
Go from stunning beauty to cavernous terror in the blink if an eye at the Drop Tower, the wildest ride at Ba Na Hills. At the top, riders can look out the glass dome and see as far as the clouds will allow. Then, without warning, you're dropped 29 metres (95 feet) into a cave based on two Jules Verne novels: Journey to the Centre of the Earth (1864) and Twenty Thousand Leagues Under the Sea (1870).
Taste wine at 100-year-old Debay Wine Cellar
Since you're at the garden, do not forget to visit the 100-year old wine cellar – Debay Cellar, built by the French in 1923. The cellar was dug in 100 meters long, through Ba Na Mountain, to maintain a continuous temperature of 16 – 20 degrees Celsius. A special material was used in the creating of the cellar you might never hear about. It's litsea cubeba resin, in Vietnamese, called 'mang tang' which can only be found in this area. Come to this Debay cellar, you can enjoy the finest wine in Da Nang, and even Vietnam.
Ba Na Hills Ticket Fees
Ba Na Hills Cable Car ticket cost 700,000 VND per adult and 550,000VND per child for round-trip ticket.
You can join our Ba Na Hills group tour with daily departure from Danang to visit easily Ba Na Hills park. So, you will not get lost in Ba Na Hills and it is a cheap and easy way to visit Ba Na Hills from Danang.
Ba Na Hills is open everyday from 7 am to 10 pm. It takes a whole day to visit all the things to see in Ba Na Hills.
When is the best time to visit Ba Na Hills
The best time to visit Ba Na Hills is from January to August with dry weather.
If you're visiting Ba Na Hills to take pictures of Golden Bridge, come during April to August but it is often crowded at this period especially on the Golden Bridge. The Golden Bridge is sometimes in the fog but from April to August the weather will be clear.
From September to March the Golden Bridge will be empty and it will be much better to pose for your Instagram pictures. However, don't forget to bring umbrella because in September and October it's supposed to rain because it is rainy season in Central Vietnam.
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text:
Home Perspectives The other side of the coin
The other side of the coin
George S. Hishmeh
Benjamin Netanyahu may have a point when he claimed that Syria had allowed Palestinian youths to jump the border fence separating northern Israel from Syria's Golan Heights, which has been occupied since the 1967 war with Israel, in a bid to deflect attention from the bloody turmoil against the Syrian regime of Bashar al-Assad.
But, in actual fact and as it turned out, the world attention was focused more on Israel's lethal response, shooting down nearly two dozen unarmed Palestinian youths who were climbing the border fence that Israel established 44 years ago after occupying Syria's strategic Golan Heights. This Palestinian action was a repeat performance of what happened three weeks ago when young Palestinians resorted to the same tactic to mark Israel's establishment in May 1948 which led to their dispossession and disbursement from their homeland.
It also once again served as an eyeopener about the brutal policies of the Israeli regime since all western powers, particularly the U.S., remain by all accounts beholden to Israel and their wealthy Jewish supporters. All keep mum about these bloody Israel reactions and their continued settlement expansion in the West Bank where now more than a half-million settlers have moved since the 1967 war.
More so, these ruthless Israeli measures, championed by the right-wing government led by Prime Minister Netanyahu, have now sowed serious dissension within Israeli society –" a significant development that the western media hardly exposes thus allowing western governments to make only perfunctory responses. But in the case of Arab autocrats, the western governments have taken, though belatedly, salutary countermeasures as in freezing the assets of government leaders and their families.
Wouldn't it be more logical, for example, for the U.S. to freeze its financial support of Israel, which amounts to more than three billion dollars annually, in the hope that Israel can work out a decent settlement with its neighbors?
But thanks to some American supporters especially well-placed journalists, like Washington Post columnist Charles Krauthammer, Israel has a glorified image. Lately, however, and in the wake of the Arab Spring that is toppling Arab autocrats, several American Jewish groups and activists have turned their guns on the Israeli establishment.
For example, Jerome Segal, president of the Jewish Peace Lobby, took Charles Krauthammer, a prominent Washington Post columnists who regularly appears in talk shows, to task for "misrepresent(ing) both the Israeli and Palestinian positions in past negotiations about borders, "the 1967 lines and land swaps" –" two issues highlighted by President Barack Obama during his recent speech on the Middle East.
Krauthammer reported, erroneously, that the Palestinians have three times rejected this formula –" "at Camp David 2000, Taba 2001, and the 2008 Olmert-Abbas negotiations," explaining that "everytime, the Palestinians said no and walked away" insisting that their position remains "the 1967 lines. Period."
Segal countered in a letter published in The Washington Post that the agreement on swaps failed because at Camp David the Israelis "initially proposed swaps on a nine-for-one basis." They also sought, Segal explained, that the Israelis sought annexation of settlement "blocs' that include "considerably more land than just where settlers reside." For the Palestinians, he went on , favcing a map that looks like Swiss cheese." Furthermore, "the two sides have not bee able to agree on whether, when Israel retains Jewish neighborhoods in (Arab) East Jerusalem, these areas will count as areas for which Israel has to provide compensation."
Segal concluded: "Were the Netanyahu government to state its willingness to accept one-for-one land swaps, negotiations could probably resume promptly and a compromise could be reached."
There are many similar interactions that are now surfacing, probably because more Americans are fed up with the extremist views of Israeli leaders and what Obama said on May 19 that the Arab revolutions underway have made the resolution of the Israel-Palestinian conflict "more urgent than ever."
A former senator, Mike Gravel, pointed out that during his 12 years in the U.S. senate he "enjoyed the support of a number of Jewish organizations, most notably the American Israel Public Affairs Committee (AIPAC), the preeminent 'pro-Israel" lobbying organization."
But as a result of a conflict with AIPAC over his intention to vote on a draft resolution offering military aid to Egypt, Saudi Arabia and Israel –" AIPAC did not want Egypt and Saudi Arabia included; he realized that "political positions and decisions within AIPAC were and continue to be profoundly influenced by the Israeli government."
He wrote last month in Counterpunch: "Until Israel's leadership and policies change, we will not see regional peace. Unless American leaders acquire more balanced approach, and become more supportive of Palestinian aspirations for freedom, the United States will not be able to act as a fair broker for peace."
In a recent letter to President Obama signed by many prominent former U.S. officials including Zbigniew Brzezinski, former Congressmen Lee H. Hamilton wrote, "if we do not put forward a clear framework for a fair and workable two-state solution to the conflict, the peace process will in effect have been abandoned, for all other approaches have been tried –" over and over again –" and have failed.
All this is going on without any significant Arab presence except for an occasional Op-Ed from an Arab-American university professor or activist. But what is urgently needed is a well-financed Arab-American advocacy group to energize new thinking in the United States.
aipac
American Israel Public Affairs Committee (AIPAC)
Previous articleLetter from the Arab World: The Speeches Revisited
Next articleWhat about the GM Seed?
George S. Hishmeh is a Washington-based columnist/writer for several Mideast newspapers and a founding member of The Jerusalem Fund. He is featured on Media Monitors Network (MMN) with the courtesy of The Palestine Center.


text:
Former Gary, Indiana, Mayor Richard Hatcher dead at 86
Former Gary Mayor Richard Hatcher, who became one of the first black mayors of a big U.S. city when he was elected in 1967, has died. He was 86.
Former Gary, Indiana, Mayor Richard Hatcher dead at 86 Former Gary Mayor Richard Hatcher, who became one of the first black mayors of a big U.S. city when he was elected in 1967, has died. He was 86. Check out this story on IndyStar.com: https://www.indystar.com/story/news/2019/12/14/former-gary-indiana-mayor-richard-hatcher-dead-86/2650645001/
Hatcher died Friday night at a Chicago hospital, Indiana state Rep. Ragen Hatcher, a Gary Democrat, said.
Hatcher had to overcome opposition from the local Democratic machine to become mayor of what was then Indiana's second-largest city in a surprise victory in 1967. He went on to serve five terms.
Hatcher became the political face of Gary and a political force for blacks after his ground-breaking election. He organized the 1972 National Black Political Convention in Gary and served as chairman of Jesse Jackson's Democratic presidential campaign in 1984 and vice chairman four years later.
Richard Hatcher (Photo: Robert Scheer/IndyStar)
But his mayorship was also marred by the steel city's deterioration.
The election of Hatcher, then a 34-year-old activist, lawyer and City Council president, sparked high emotions in Gary. He defeated incumbent A. Martin Katz in the primary by more than 2,300 votes, prompting a celebration that forced police to shut down a six-block section of Broadway for four hours.
The celebration was short-lived. When Hatcher refused to allow Lake County Democratic leaders to pick the city's police chief, city attorney and fill other major positions in Hatcher's administration, party Chairman John Krupa told him the party wouldn't support Hatcher during the general election. Not only that, the party worked for his Republican opponent, Joseph Radigan.
Although Gary hadn't had a Republican mayor since 1938, it was a difficult challenge for a campaign that had spent most of its money on the primary and now had no party to back it. Hatcher managed to raise $8,000 to run full-page campaign ads in The New York Times and the Post-Tribune in Gary. The ad read, "Richard Hatcher is battling bigotry and ignorance. And he needs your help."
Those ads brought in more than $250,000, drew invitations to appear on TV and radio shows and attracted the attention of Sen. Robert Kennedy, Vice President Hubert Humphrey and others who held fundraisers.
"It was unbelievable," Hatcher, who kept a framed copy of the ad on his office wall, said during a 2011 interview with The Associated Press. "We ended up having enough money to run a decent campaign."
He gave credit for his election to the work of the city's black residents, who made up slightly more than half the city's population of the about 175,000 residents in 1967 but trailed whites in the number of registered voters.
"There was a tremendous spirit in the city and the black community was very united," he said. "I think I received about 7% of the white vote. The other white candidates divided up the white vote, they really split it, which made it possible for me to win."
During his inauguration speech, Hatcher said his primary goal was to make the city a decent place to live for his "brothers and sisters."
"Gary is a rising sun. Together, we shall beat a way; together, we shall turn darkness into light, despair into hope and promise into progress," he said.
Please support the work of IndyStar reporters and visual journalists by becoming a subscriber today. Get unlimited digital access here!
Hatcher attracted hundreds of millions of dollars in federal money to Gary in his 20 years in office, some of which was used to build low-cost housing and the first public housing units in the city in nearly two decades. He also got federal funds to pay for jobs training, repaved deteriorating streets and put many inner-city neighborhoods on regular garbage collection for the first time.
The changes extended to City Hall. When he was elected, only two of the city's department heads were black. A decade later, 25 of the city's 40 department heads, including the police and fire chiefs, were black.
Even before he became mayor, Hatcher was making changes. As a member of the Gary City Council, he helped pass an open housing law to end the practice that forced blacks to live primarily in the city's midtown section because of restrictive property covenants.
But Hatcher couldn't stop Gary's decline, which coincided with that of the U.S. steel industry. The company town, founded in 1906 by U.S. Steel Chairman Elbert H. Gary, had flourished as the industry did. While Hatcher was in office, U.S. Steel cut its workforce from 35,000 in the early 1970s to 25,000 by the early 1980s.
Businesses were shuttered as banks and shops moved to the suburbs. Crime increased, and by 1984, Gary had the nation's highest per-capita homicide rate.
Many white residents fled the city. The percentage of blacks grew to 71% by 1980, up from 53% a decade earlier.
By the time Hatcher left office in 1987, the city had lost 50,000 residents. When Hatcher lost the primary, police again shut down Broadway so people could celebrate.
Richard Gordon Hatcher was born July 10, 1933, in Michigan City, Ind. He was one of 13 children whose father molded railroad car wheels and whose mother was a factory worker. He graduated from Indiana University, earned a law degree from Valparaiso University and moved to Gary after becoming a deputy prosecutor.
Despite the city's troubles, Hatcher said he was proud of his accomplishments in office. "Maybe for some people in Gary it may not be better. But for others it may seem very much better," he said in 2011.
He married his wife, Ruthellyn, in 1976. They raised their three daughters, Ragen, Rachelle and Renee, in the city he loved.
"The thing I can say I am most proud of is the way the people of Gary have continued to persist in their efforts to create a better city for their children and for themselves," he said in 2011. "We have some really wonderful people in the city."
Read or Share this story: https://www.indystar.com/story/news/2019/12/14/former-gary-indiana-mayor-richard-hatcher-dead-86/2650645001/
Workweek warmup to follow weekend cold snap
Royal Caribbean blames 'reckless' grandfather in tot's death
Buying legal weed at dispensary closest to Indy
What a ban on holding cellphones while driving could look like
Man shot on west side while his child was in car


text:
Micromphalia is a genus of gastropods belonging to the family Charopidae.

Species:

Micromphalia abax
Micromphalia caledonica
Micromphalia vieillardi

References

Charopidae
Gastropod genera

redpajama_set_name: RedPajamaWikipedia


text:
package org.apache.logging.log4j.core.pattern;

import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertNotNull;
import static org.junit.Assert.assertTrue;

import java.util.List;
import java.util.Map;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.core.Appender;
import org.apache.logging.log4j.core.LoggerContext;
import org.apache.logging.log4j.core.config.Configuration;
import org.apache.logging.log4j.core.config.ConfigurationFactory;
import org.apache.logging.log4j.status.StatusLogger;
import org.apache.logging.log4j.test.appender.ListAppender;
import org.junit.AfterClass;
import org.junit.BeforeClass;
import org.junit.Test;

/**
 * Unit tests for {@code throwable} pattern.
 */
public class ThrowableTest {
    private static final String CONFIG = "log4j-throwable.xml";
    private static Configuration config;
    private static ListAppender app;
    private static LoggerContext ctx;

    @BeforeClass
    public static void setupClass() {
        System.setProperty(ConfigurationFactory.CONFIGURATION_FILE_PROPERTY, CONFIG);
        ctx = (LoggerContext) LogManager.getContext(false);
        config = ctx.getConfiguration();
        for (final Map.Entry<String, Appender> entry : config.getAppenders().entrySet()) {
            if (entry.getKey().equals("List")) {
                app = (ListAppender) entry.getValue();
                break;
            }
        }
    }

    @AfterClass
    public static void cleanupClass() {
        System.clearProperty(ConfigurationFactory.CONFIGURATION_FILE_PROPERTY);
        ctx.reconfigure();
        StatusLogger.getLogger().reset();
    }

    org.apache.logging.log4j.Logger logger = LogManager.getLogger("LoggerTest");

    @Test
    public void testException() {
        final Throwable cause = new NullPointerException("null pointer");
        final Throwable parent = new IllegalArgumentException("IllegalArgument", cause);
        logger.error("Exception", parent);
        final List<String> msgs = app.getMessages();
        assertNotNull(msgs);
        assertTrue("Incorrect number of messages. Should be 1 is " + msgs.size(), msgs.size() == 1);
        assertFalse("No suppressed lines", msgs.get(0).contains("suppressed"));
        app.clear();
    }
}

redpajama_set_name: RedPajamaGithub


Things have been frantic at Johnson HQ lately as we prepare for a 3 nights only run of Shadow of Brel again at Tabula Rasa – just to warm me up for a tour to Durban where I'll be hosted at the wonderful Rhumbelow theatre. I love working in Durban, the whole atmosphere is great – the press and audience, not to mention the weather, are very warm. I think they're in for a treat with this one, Sanjin Muftic's direction is simple and effective, really letting the raw power of Brel's lyrics drive the show.
But before I trot up to Durbs we'll be opening a brand new show at Tabula Rasa: Stories of Crime and Passion. This will be my first time being directed by Jon Keevy, the talented designer of Yawazzi Productions. We've worked together many times before and we're both very excited about Stories – the song selection is all based around tales of, well I suppose it's a little obvious, crime and passion. We're looking at songs by Johnny Cash, Cole Porter, Aerosmith, Kenny Rogers, the Decemberists, Nick Cave, Fiona Apple, Tori Amos and many others. It's going to be quite a task choosing from such great material, let alone finding a new arrangement for each one.
Back to work now – have to sort out all our SAMRO registrations before these dreams can come true!
This entry was posted in Updates and Shows and tagged Brel, Cabaret, Durban, Jon Keevy, Piano, Rhumbelow Theatre, Sanjin Muftic, Shadow of Brel, Stories of crime and passion, Tabula Rasa, Yawazzi. Bookmark the permalink.


Dental Republic speciaizes in Indirect Orthodontic Braces. They look like traditional braces, but are placed on the teeth with an upgraded procedure. In the indirect bonding method, the brackets are positioned using tray molds of your teeth for increased accuracy.
How are Indirect Braces different from traditional braces?
Are brackets better than clear aligners?
Is the procedure comfortable for me?
How often do I have to get them adjusted?
How much do traditional indirect braces cost?
Indirect bonding allows for more precise placement of brackets compared to the original technique of mounting each one by hand. This is because we make a custom mold of your teeth to work off of. Indirect orthodontics allow the brackets to be placed precisely in the molded tray that will then be placed in your mouth to ensure proper position while bonding. This procedure takes far less time and effort to complete which provides added comfort to the patient. The ease of this indirect method also helps when the patient is young and cannot hold still for long. Not having to hand place brackets in the back of the mouth also eliminates discomfort to patients.
Brackets are bonded onto each tooth and wired together with small rubberbands to cause pressure. This constant pressure slowly moves teeth.
Neither is a better choice than the other. They work in the same way to move teeth into the correct position. Some things to think about in your decision are aesthetics, cost, how long you will have to wear them for, and the effects each will have on your teeth, depending on factors such as severity of overbite or crookedness of teeth.
Yes. With the indirect bonding method, only a tray is inserted in your mouth to adhere the brackets to your teeth instead of hands trying to place each bracket individualy, which can get tiring for the patient from holding still and feling discomfort during the back molars bracket placement. The procedure also takes less than 30 minutes, so you will not have to wait long. There are less than 10 minutes where we must keep your teeth dry with retractors that some may find uncomfortable.
The entire procedure typically takes 30 minutes.
The wire is adjusted about once a month.
There is no upper limit of age for braces if you are in good oral and medical health. However, you have to be old enough to have your permanent teeth and in good oral and medical health.
Currently, you can get started with traditional indirect orthodontics at Dental Republic for only $99.
Straight teeth give our clients the added confidence in their image. Straight teeth makes it easier to floss and brush because there are less food traps; therefore, less chance of cavities and periodontal disease. Straight teeth reduce stress on your Temporal Mandibular Joint created by misaligned teeth. Straight teeth reduce the wear and tear of the surfaces of your teeth through grinding. Cavity detection by your dentist is easier, according to our supporting dentist.


text:
HomeSuluPNP confirms decapitated head belongs to Robert Hall
PNP confirms decapitated head belongs to Robert Hall
Admin Tuesday, June 21, 2016
MANILA, Philippines - The Philippine National Police (PNP) has confirmed on Tuesday, June 21 that the decapitated head by Islamist militant group Abu Sayyaf in Sulu belongs to Canadian kidnap victim Robert Hall.
"The head that was recovered from Sulu is indeed that of Mr. Robert Hall," said Chief Supt. Emmanuel Aranas, director of the PNP crime laboratory.
DNA results confirmed head recovered in Sulu belongs to Mr. Robert Hall. Photo Credit: PTV
On June 13, AFP Western Command spokesperson Major Filemon Tan Jr. said the head was recovered in front of the gate of Jolo Cathedral at around 8:45 pm, just hours after the ransom deadline had lapsed.
Before confirming that the head belongs to Hall, Tan added that the Scene of the Crime Operatives (SOCO) still need to carry out DNA test on the head.
In September 2015, Hall along with three other people were captured by Abu Sayyaf from a resort in Samal Islands. Initially, the militants demanded a ransom of P1 billion each for the captives but later reduced it to P300 million each early in 2016.
However, both the Canadian and Philippine government have a policy against paying ransom in such cases.
"This is precisely why the Government of Canada will not and cannot pay ransoms for hostages to terrorists groups, as doing so would endanger the lives of more Canadians," Canadian Prime Minister Justin Trudeau said in a statement on June 13.
"We are more committed than ever to working with the Government of the Philippines and international partners to pursue those responsible for these heinous acts and bring them to justice, however long it takes," Trudeau added.
Abu Sayyaf Breaking News News and Events Robert Hall Samal Islands Sulu


text:
Cryptids and Legendary Creatures
Hodge Podge
Little-Known History
Otherworldly Phenomena
Religious Curiosities
Strange Anomalies
Tour Mexico
Is the Lost Library of Atlantis Located in the Yucatan?
Posted June 20, 2016 June 22, 2016 Robert Bitto
http://mexicounexplained.com/wp-content/uploads/2016/06/HallofRecords.mp3
In this segment we explore the Lost Continent of Atlantis and its connection to Ancient Mexico, specifically, the location of the supposed lost Hall of Records of Atlantean civilization that was established in the final days of the fabled continent. Did this ancient library of forgotten wisdom really exist, and if so, where is it?
First, we have to explain the basic theories of Atlantis. Atlantis has been described as a large landmass and a series of adjacent interconnected islands that existed somewhere in what is now the Atlantic Ocean. It was the home of an advanced civilization that flourished for hundreds of years. Depending on which version of the Atlantis story one reads, the civilization either met with an environmental catastrophe – volcanoes, floods, a comet, etc. – or it sank beneath the waves because its technology became so advanced that its own people destroyed their home. In whichever version is promoted, there always seems to be a lesson for us in modern times. The first recorded account of Atlantis comes from the ancient Greek philosopher Plato in one of his dialogues written in 360 BC. Here is a quote from Plato himself:
"For it is related in our records how once upon a time your State stayed the course of a mighty host, which, starting from a distant point in the Atlantic ocean, was insolently advancing to attack the whole of Europe, and Asia to boot. For the ocean there was at that time navigable; for in front of the mouth which you Greeks call, as you say, 'the pillars of Heracles,' there lay an island which was larger than Libya and Asia together; and it was possible for the travelers of that time to cross from it to the other islands, and from the islands to the whole of the continent over against them which encompasses that veritable ocean. For all that we have here, lying within the mouth of which we speak, is evidently a haven having a narrow entrance; but that yonder is a real ocean, and the land surrounding it may most rightly be called, in the fullest and truest sense, a continent. Now in this island of Atlantis there existed a confederation of kings, of great and marvelous power, which held sway over all the island, and over many other islands also and parts of the continent."
So, Plato puts Atlantis "beyond the Pillars of Hercules," which is beyond what we call The Strait of Gibraltar, the narrow water passage connecting the Mediterranean Sea with the Atlantic. Plato recounts that it is larger than "Libya and Asia" together, which may mean that it was larger than modern-day northern Africa and Turkey, which is also called Asia Minor. We are dealing with, simply put, a large landmass which once existed in the middle of the Atlantic Ocean and is now gone. It is unknown whether Plato is describing a place of myth or a real location. There are no other accounts of Atlantis in any other ancient texts or oral histories before Plato. That does not mean that Atlantis did not exist, but it does raise some interesting questions as to whether or not Plato was creating this older super-civilization to make a point, or several points, as was often the case in his dialogs.
Most scholars agree that all subsequent accounts of the lost continent build upon Plato's original description. There have been many writers going back to early Medieval times who have built upon the Atlantis legend and have filled in the blanks, so as to flesh out the myth. Whether or not some of these earlier writers are basing Atlantis on other oral histories independent of Plato is unknown and unprovable.
Atlantis seemed to "rise again" in the popular imagination in the late 19th Century when two things were happening simultaneously: people were trying to understand the origins of the ancient civilizations of the Americas and there was an increase in an interest in mysticism in Europe and America. Since the arrival of the conquistadors there has always been speculation as to the starting point of the great civilizations of the New World, and even where the first people came from. Atlantis seemed to be a more popular theory in the 19th Century, and it was regarded much as the "ancient aliens" theories are today. The rise in mysticism and the popularity of Atlantis is a curious thing; it was in the late 1800s when various mediums and self-proclaimed prophets and psychics were starting to claim that they were making contact with entities or spirits during séances and readings who had once lived in Atlantis. Enter Edgar Cayce.
Edgar Cayce was born in 1877 in Kentucky, and early on he was seen as a "different" and highly intelligent child. By his early 20s Cayce was making predictions and doing psychic readings. He is known as "The Sleeping Prophet" because he would go into a trance during his readings and speak with spirits who would give him information. During his trances Cayce was said to access the Akashic Record. One of the first descriptions of the Akashic Record was in 1927 by mystic Alice Bailey in her book, Light of the Soul about The Yoga Sutras of Patanjali. Bailey states:
"The akashic record is like an immense photographic film, registering all the desires and earth experiences of our planet. Those who perceive it will see pictured thereon: The life experiences of every human being since time began, the reactions to experience of the entire animal kingdom, the aggregation of the thought-forms of a karmic nature (based on desire) of every human unit throughout time. Herein lies the great deception of the records. Only a trained occultist can distinguish between actual experience and those astral pictures created by imagination and keen desire."
So, Cacye was supposedly accessing the memories of Atlantis through this Akashic Record and had entities speak through him about their histories and experiences. In all of Cayce's 14,000 readings, there were 700 of them about Atlantis. A foundation called the Association of Research and Enlightenment in Virginia Beach, Virginia has catalogued most of Cayce's readings. In the 700 readings about Atlantis we find out a lot of the society of the civilization and about its destruction. The islanders apparently knew that a cataclysm was coming and prepared for it by storing the records of Atlantis in three different places on Earth. From a reading made in September of 1939 here are Cacye's words:
"Before that we find the entity was in the Atlantean land, when there were the constructive forces as to the activities of the children of the Law of One – in all of those influences during the periods when the land was being broken up. We find the entity was as the leading influence for the considering of ways and means in which there would be the preserving of records, as well as ways, means and manners in which either the few or the numbers might be preserved from the destruction of the lands.
It would be well if this entity were to seek either of the three phases of the ways and means in which those records of the activities of individuals were preserved:
the one in the Atlantean land that sank, which will rise and is rising again
another in the place of the records that leadeth from the Sphinx to the hall of records, in the Egyptian land
and another in the Aryan or Yucatan land, where the temple there is overshadowing same"
So here, Cayce is describing the three depositories of the records of Atlantis: On one of the outlying Atlantean islands that sank and would rise again, underneath the Great Sphinx in Egypt and somewhere in the Yucatan. This is very vague, but with time Cayce fine-tuned and clarified the Mexican connection to the fabled Hall of Records. In later readings the Sleeping Prophet told of an Atlantean nobleman from the house of Atlan named Iltar. Iltar knew of the eminent collapse of the only home he knew, so he fled with 10 other men in a boat and sailed to the modern northwest coast of the Yucatan, possibly landing on the shores of the present-day Mexican state of Campeche. He and the 10 men carried with them 32 stone tablets full of ancient wisdom and historical events. Here we will go to another reading of Cayce's regarding Iltar's arrival. He came and integrated
"with the activities of the people there, the development into a civilization that rose much in the same manner as that which had been in the Atlantean land."
So, according to Cayce, the Atlanteans began to "help along" the ancient civilization of Mexico at the time, which would have been over 12,000 years ago. To continue with Cayce:
"The first temples that were erected by Iltar and his followers were destroyed at the period of change physically in the contours of the land."
Some interpret this to mean that Iltar's coastal settlement was destroyed by the eventual tidal waves that engulfed the area as a result of Atlantis' sinking. So, the first Hall of Records and any other buildings were destroyed and the records were moved inland to safety. Cayce does not give too many details of where the new location could be, although he did say in a December 1933 reading that "altar stones had been uncovered in the past few months" and some have interpreted this to refer to a huge Maya site called Piedras Negras which is located in the far northwest corner of Guatemala where that country shares borders with the Mexican states of Campeche and Chiapas. The site is located on the Usumacinta River which is navigable from Mexico's Gulf Coast this far inland. Between 1931 and 1939 the University of Pennsylvania conducted excavations of the site and it was very likely that Cayce had heard of their findings in the press at the time. A few curious things about this location is that the original name of the site in Maya was Yo'k'ib' which means "Great Gateway." There is also something found at Piedras Negras that is not found anywhere else in Ancient Mesoamerica: A giant altar in the shape of a feline paw, several meters long. For those who would wish to make an Egyptian connection, alas, this paw is sphinx-less.
Cayce's Association for Research and Enlightenment, the ARE, sent an expedition to Piedras Negras in April of 2004 to scout out possible locations of the Hall of Records. The site is accessible only by river and the 2004 expedition is documented on YouTube. The short documentary chronicles this brief expedition where no digging took place, only exploring for possible locations. If the lost library is there, it will take a lot of work to find it as only a fraction of one percent of Piedras Negras has been excavated and explored. Some believers in Cayce's readings think that the Piedras Negras site is incorrect for a number of reasons, one being that the city doesn't date back 12,000 years. The earliest habitation of the site dates back to just a few centuries BC. Others counter that perhaps the city grew up around the Hall of Records. There is evidence of a massive cave and tunnel system underneath the ruins and the ruins themselves were built on top of much older buildings. Those who think that the location is elsewhere point to skeletons found off the Caribbean coast of Mexico that have been dated by the University of California at Riverside to be 13,000 years old. Perhaps there was no need for Iltar to go so far inland and that Cayce's followers made the mistake of making the Piedras Negras connection early on in the 1930s and refused to give it up in the face of new finds.
Some people may question the whole story of the lost Atlantean library as a hoax of a charlatan, of a man seeking publicity and who made up stories about things that could never be verified. Others point to Cayce's amazing rate of accuracy for his predictions and for other things that came through in his readings. In those 14,000 trance-induced sessions Edgar Cayce supposedly predicted the stock market crash of 1929, World War II, the discovery of the Dead Sea Scrolls and a whole list of other things that have come to pass. So, if we assume that Atlantis was real and that Cayce was truly gifted, is there a surprise waiting for us in the jungles of Mexico in the form of ancient wisdom? As more and more becomes known about Ancient Mexico and more things are uncovered to add to our expanding knowledge of the area, perhaps one day we will be surprised and hear of an incredible discovery of mysterious stone tablets that give us a direct connection to the mythical Atlantis.
REFERENCES USED (Not a formal bibliography)
Atlantis by Edgar Cayce
The Yucatan Hall of Records by Greg Little
The Lost Hall of Records by John van Auken and Lora Little
The Maya: Edgar Cayce Readings by Carolyn Hatt
YouTube link to Association for Research and Enlightenment's 2004 expedition of discovery to Piedras Negras: https://www.youtube.com/watch?v=wsKMBFDZ7YU
atlantisEdgar Caycehall of recordsIltarPiedras NegrasPlatoyucatan
⟵The Mysterious Doña Marina, the Most Important Woman in Mexican History
The Lechuza⟶
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Robert Bitto
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Tlaloc, Beyond the Rain God
The Final Days of the Tarascan Empire
Four Legends from Mexico City
Juan Chávez, Legendary Mexican Bandit
Xoloitzcuintli: Sacred Dog of the Ancient Mexicans
Emily on The Vampire Witches of Central Mexico
Rani Sharma on Vikings in Ancient Mexico? The Story of Votan
Robert Bitto on The Vampire Witches of Central Mexico
THE RAKE . on The Vampire Witches of Central Mexico
Robert Bitto on The Lost Treasure of Emperor Maximilian
© Mexico Unexplained
Ancient Mysteries (34)
Cryptids and Legendary Creatures (15)
Little-Known History (34)
Myths and Legends (19)
Otherworldly Phenomena (15)
Religious Curiosities (21)
Tlaloc, Beyond the Rain God July 8, 2019
The Final Days of the Tarascan Empire July 1, 2019
Four Legends from Mexico City June 23, 2019
Juan Chávez, Legendary Mexican Bandit June 17, 2019
Xoloitzcuintli: Sacred Dog of the Ancient Mexicans June 10, 2019
The Magnificent Murals of Bonampak June 3, 2019


Usually the funny animal videos I share are heavily cat-based. Not so today. I enjoyed watching the techniques employed by the dogs navigating stairs – particularly the various "I am a toboggan" methods, the black lab doing the showgirl sidestep up the stairs and Mr. Handstand strutting his stuff. Enjoy the video below.


Btcforclicks is a program where you can earn free bitcoins, to view ads .
Unlike some of the sites that Mike has reviewed this one does not have instant payouts and requires you to reach a minimum balance of at least .01 mBTC what mean 0.0001 Btc which certainly hurts this review a bit as it requires more time and doesn't give an immediate payout to your Microwallet account.
You can earn between 0.000045 Btc and 0.0001 every day from this site, for free, if you watch all the ads every day .
To cash-out your earnings, you will need at least 0.0001 Btc on your balance in Btcclicks .
you will earn 10 %% on your affiliate, just on the first level of affiliation .


The Yellow Ribbon Program a provision of the law that created the Post-9/11 GI Bill. The Yellow Ribbon Program is available for Institutions of Higher Education (degree granting institutions) in the U.S. or at a branch of such institution located outside the U.S. The program allows approved institutions of higher learning and the VA to partially or fully fund tuition and fee expenses that exceed the established thresholds under the Post-9/11 GI Bill.


Listing provided courtesy of David Craft, RE/MAX DFW Associates.
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Home for sale at 2149 N Aspenwood Drive Grapevine, TX 76051.
Description: The home at 2149 N Aspenwood Drive Grapevine, TX 76051 with the MLS Number 14062622 is currently listed at $374,500 and has been on the Grapevine market for 13 days.
You are viewing the MLS property details of the home for sale at 2149 N Aspenwood Drive Grapevine, TX 76051, which includes 3 bedrooms, 2 bathrooms and has approximately 1784 sq.ft. of living area.