Rule of Procedure of the Assembly of States parties to the Rome Statute of the International Criminal Court

In this Essay, the author intends to elaborate only on those Rules that are unique, or were the subject of lengthy discussion in the working group. It is practically impossible to discuss all rules contained in the Rules of Procedure. Before beginning, one point needs to be clarified. There are a number of rules in the Rules of Procedure that simply repeat the provisions of the Statute. This was a conscious decision made by the working group, which included harmless repetitions in order to provide a handy set of rules for future delegates to the Assembly that will cover all aspects of its activities

Protection Considerations of Future Distribution Networks with Large Penetration of Single Phase Residential Rooftop Photovoltaic Systems

Solar Photovoltaics now constitute a significant part of electrical power generation for many utilities around the world. This penetration of PVs introduces many technical challenges. This thesis has investigated the impact of high penetration level of single phase rooftop PVs on protection of low voltage and medium voltage and distribution networks and proposed necessary recommendation to improve the performance of protection systems of these networks

Improving the Learning Experience of Power System Protection Students using Computer-based Simulations and Practical Experiments

This paper presents a survey on the activities carried out to improve the learning experience of electrical engineering undergraduate students in power system protection unit in Curtin University, Australia. The unit was conducted initially based on lectures and tutorials where only two sessions on computer simulation and one session of laboratory demonstration were conducted. In academic year of 2013, to improve the learningexperience of students, several computer-based simulations and laboratory experiments were prepared. The students are introduced with two power system analysis software, namely ETAP and PSCAD/EMTDC which are used to demonstrate the overcurrent relays performance and their coordination as well as the time transient analysis of different faults in an electric network where some protection relays are applied. A practical setupcomposed of LabVolt electrical modules and SEL relays is used to simulate an electric network. Several tests are built up to simulate fault and protection layout for transformer and induction motor. Finally, a secondary injection test set is used to introduce the concepts of relay testing and commissioning

Motivating Power System Protection Course Students by Practical and Computer-Based Activities

This paper presents several methods for motivating students taking a power system protection (PSP) course. The paper reviews the laboratory activities developed for the PSP course at Curtin University, Australia; these methods are applicable and can be used for PSP course instruction at any institution. These activities were developed to improve the learning experience of the electrical engineering undergraduate and postgraduate students enrolled in this course. Initially, the PSP course at Curtin University consisted of lectures and tutorials accompanied by two sessions of software-based simulations and one session of laboratory demonstration. To motivate the students, several computer-based simulations and practical laboratory experiments were developed. PSCAD and ETAP power system analysis software tools are introduced and used to demonstrate the performance and coordination of different protection relays from steady-state and dynamic points of view. Also, a practical setup composed of a LabVolt power system simulator and industrial relays is used to carry out several practical experiments. The experiments help students observe the performance of protection systems for transformers and induction motors during faults and abnormal operating conditions. Finally, the concept of relay testing and commissioning is introduced by relay standalone experiments using a secondary injection relay test set. The results of these activities were evaluated according to the students’ satisfaction, comments, total scores, and interest in PSP

Contributions of Single–Phase Rooftop PVs on Short Circuits Faults in Residential Feeders

Sensitivity analysis results are presented to investigate the presence of single–phase rooftop Photovoltaic Cells (PV) in low voltage residential feeders, during short circuits in the overhead lines. The PV rating and location in the feeder and the fault location are considered as the variables of the sensitivity analysis. The single–phase faults are the main focus of this paper and the PV effect on fault current, current in distribution transformer secondary and the voltage at each bus of the feeder are investigated, during fault. Furthermore, to analyze the bus voltages and fault current in the presence of multiple PVs, each with different rating and location, a stochastic analysis is carried out to investigate the expected probability density function of these parameters, considering the uncertainties of PV rating and location as well as fault location

Multi-robot Coverage and Redeployment Algorithms

In this thesis, we focus on two classes of multi-robot task allocation and deployment problems motivated by applications in ride-sourcing transportation networks and service robots: 1) coverage control with multiple robots, and 2) robots servicing tasks arriving sequentially over time. The first problem considers the deployment of multiple robots to cover a domain. The multi-robot problem consists of multiple robots with sensors on-board observing the spatially distributed events in an environment. The objective is to maximize the sensing quality of the events via optimally distributing the robots in the environment. This problem has been studied extensively in the literature and several algorithms have been proposed for different variants of this problem. However, there has been a lack of theoretical results on the quality of the solutions provided by these algorithms. In this thesis, we provide a new distributed multi-robot coverage algorithm with theoretical guarantees on the solution quality, run-time complexity, and communication complexity. The theoretical bound on the solution quality holds for on-board sensors where the sensing quality of the sensors is a sub-additive function of the distance to the event location in convex and non-convex environments. A natural extension of the multi-robot coverage control problem is considered in this thesis where each robot is equipped with a set of different sensors and observes different event types in the environment. Servicing a task in this problem corresponds to sensing an event occurring at a particular location and does not involve visiting the task location. Each event type has a different distribution over the domain. The robots are heterogeneous in that each robot is capable of sensing a subset of the event types. The objective is to deploy the robots into the domain to maximize the total coverage of the multiple event types. We propose a new formulation for the heterogeneous coverage problem. We provide a simple distributed algorithm to maximize the coverage. Then, we extend the result to the case where the event distribution is unknown before the deployment and provide a distributed algorithm and prove the convergence of the approach to a locally optimal solution. The third problem considers the deployment of a set of autonomous robots to efficiently service tasks that arrive sequentially in an environment over time. Each task is serviced when a robot visits the corresponding task location. Robots can then redeploy while waiting for the next task to arrive. The objective is to redeploy the robots taking into account the next N task arrivals. We seek to minimize a linear combination of the expected cost to service tasks and the redeployment cost between task arrivals. In the single robot case, we propose a one-stage greedy algorithm and prove its optimality. For multiple robots, the problem is NP-hard, and we propose two constant-factor approximation algorithms, one for the problem with a horizon of two task arrivals and the other for the infinite horizon when the redeployment cost is weighted more heavily than the service cost. Finally, we extend the second problem to scenarios where the robots are self-interested service units maximizing their payoff. The payoff of a robot is a linear combination of its relocation cost and its expected revenue from servicing the tasks in its vicinity. In this extension, the global objective is either to minimize the expected time or minimize the maximum time to respond to the tasks. We introduce two indirect control methods to relocate the self-interested service units: 1) an information sharing method, and 2) a method that incentivizes relocation with payments. We prove NP-hardness of finding the optimal controls and provide algorithms to find the near-optimal control. We quantify the performance of the proposed algorithms with analytical upper-bounds and real-world data from ride-sourcing applications

A Linear Regression Model to Predict the Critical Temperature of a Superconductor

Since the superconductivity has been introduced, almost all studies in this area have been striving to predict the critical temperature ($T_{c}$) through the features extracted from the superconductor\u27s chemical formula. In this study, thus, we are interested in exploring the linear association between $T_{c}$ and the related features

A Recommender System for Movie Ratings with Matrix Factorization Algorithm

Nowadays, a Recommender System is a technologythat aims to predict preferences based on the user’s selections.These systems are applied in numerous fields, such as movies,music, news, books, research articles, search queries, social tags,and various products. In this study, we use this potential tool topredict the ratings of users’ preferences in MovieLens datasets. Todo so, we applied the matrix factorization algorithm and calculatethe RMSE as our evaluation metric. The results represent thatRMSE estimated for the train and test set are 0.83 and 0.93 thatare very close one another. This results indicates that our modelperformance is wel

Analysis of Credit Approval by Decision Tree

Nowadays, machine learning algorithms are com-monly used by the financial institutions or bankers to evaluatethe applications’ requires for credit card. In this study, we usedthe decision tree algorithm to predict credit card approval basedon the other associated features applicants like age, employmentstatus, Education Level, etc. Our results shows that the applicants’Prior Default and Debt, and Employed have more contributionin the credit card approval

Distributed Task Allocation and Task Sequencing for Robots with Motion Constraints

This thesis considers two routing and scheduling problems. The first problem is task allocation and sequencing for multiple robots with differential motion constraints. Each task is defined as visiting a point in a subset of the robot configuration space -- this definition captures a variety of tasks including inspection and servicing, as well as one-in-a-set tasks. Our approach is to transform the problem into a multi-vehicle generalized traveling salesman problem (GTSP). We analyze the GTSP insertion methods presented in literature and we provide bounds on the performance of the three insertion mechanisms. We then develop a combinatorial-auction-based distributed implementation of the allocation and sequencing algorithm. The number of the bids in a combinatorial auction, a crucial factor in the runtime, is shown to be linear in the size of the tasks. Finally, we present extensive benchmarking results to demonstrate the improvement over existing distributed task allocation methods. In the second part of this thesis, we address the problem of computing optimal paths through three consecutive points for the curvature-constrained forward moving Dubins vehicle. Given initial and final configurations of the Dubins vehicle and a midpoint with an unconstrained heading, the objective is to compute the midpoint heading that minimizes the total Dubins path length. We provide a novel geometrical analysis of the optimal path and establish new properties of the optimal Dubins' path through three points. We then show how our method can be used to quickly refine Dubins TSP tours produced using state-of-the-art techniques. We also provide extensive simulation results showing the improvement of the proposed approach in both runtime and solution quality over the conventional method of uniform discretization of the heading at the mid-point, followed by solving the minimum Dubins path for each discrete heading