The paper we presents mathematical model for analysis of transitional processes in three-phase induction motor, that is, wave forms of currents and voltages in time domain and phase coordinates. Model is suitable for relay protection of the motor from disturbances and for estimation of electrical energy quality in the distribution network. New constructions of induction motors present more progressive technical solutions comparing with classical variants and reliable entity only within selected system of protection from expected disturbances (failures and disorders followed by asymmetries). Measuring process is not required due to application of simulation in selected MATLAB package.

This paper presents some considerations regarding design, modeling and control solutions for Photovoltaic Panel-Converter (PVPC) system. Different control approaches and corresponding models are derived, developed and tested, to control output characteristics and performance of both overall PVPC system and each subsystem to meet desired output characteristics, performance and both and/or either voltages and currents requirements. The proposed approaches and models allow designer have the maximum output numerical visual and graphical data to select, evaluate and control the PVPC system output characteristics for a given PVPC system parameters, under given working conditions of PV panel. The proposed models and approaches were implemented and tested in MATLAB/Simulink.

This paper addresses three issues of motion planning for zero-moment point (ZMP)-based biped robots. First, three methods have been compared for smooth transition of biped locomotion from the single support phase (SSP) to the double support phase (DSP) and vice versa. All these methods depend on linear pendulum mode (LPM) to predict the trajectory of the center of gravity (COG) of the biped. It has been found that the three methods could give the same motion of the COG for the biped. The second issue is investigation of the foot trajectory with different walking patterns especially during the DSP. The characteristics of foot rotation can improve the stability performance with uniform configurations. Last, a simple algorithm has been proposed to compensate for ZMP deviations due to approximate model of the LPM. The results show that keeping the stance foot flat at beginning of the DSP is necessary for balancing the biped robot.

The optimal resources allocation to tasks was the primary objective of the research dealing with scheduling problems. These problems are characterized by their complexity, known as NP-hard in most cases. Currently with the evolution of technology, classical methods are inadequate because they degrade system performance (inflexibility, inefficient resources using policy, etc.). In the context of parallel and distributed systems, several computing units process multitasking applications in concurrent way. Main goal of such process is to schedule tasks and map them on the appropriate machines to achieve the optimal overall system performance (Minimize the Make-span and balance the load among the machines). In this paper we present a Time Petri Net (TPN) based approach to solve the scheduling problem by mapping each entity (tasks, resources and constraints) to correspondent one in the TPN. In this case, the scheduling problem can be reduced to finding an optimal sequence of transitions leading from an initial marking to a final one. Our approach improves the classical mapping algorithms by introducing a control over resources allocation and by taking into consideration the resource balancing aspect leading to an acceptable state of the system. The approach is applied to a specific class of problems where the machines are parallel and identical. This class is analyzed by using the TiNA (Time Net Analyzer) tool software developed in the LAAS laboratory (Toulouse, France).

Universities gather large volumes of data with reference to their students in electronic form. The advances in the data mining field make it possible to mine these educational data and find information that allow for innovative ways of supporting both teachers and students. This paper presents a case study on predicting performance of students at the end of a university degree at an early stage of the degree program, in order to help universities not only to focus more on bright students but also to initially identify students with low academic achievement and find ways to support them. The data of four academic cohorts comprising 347 undergraduate students have been mined with different classifiers. The results show that it is possible to predict the graduation performance in 4th year at university using only pre-university marks and marks of 1st and 2nd year courses, no socio-economic or demographic features, with a reasonable accuracy. Furthermore courses that are indicators of particularly good or poor performance have been identified.

Particle Swarm Optimization is swarm based optimization technique. Swarm consists of particles and the particles fly through the problem space in Particle Swarm Optimization (PSO). Confinement methods and parameters such as Inertia Weight, Neighborhood of the particle have major impact on PSO performance. The paper presents variations of the PSO with adaptive random link neighborhood. The work carried out considers linearly decreasing inertia weight and different confinement methods. The performance of adaptive random link PSO by geometrical updation of velocity with confinement methods is tested here.

This article describes an ongoing research which intends to develop a plagiarism detection system for Arabic documents. We developed different heuristics to generate effective queries for document retrieval from the Web. The performance of those heuristics was empirically evaluated against a sizeable corpus in terms of precision, recall and f-measure. We found that a systematic combination of different heuristics greatly improves the performance of the document retrieval system.

The amount of cane fiber carried by cane carrier varies due to non-uniformity of cane supply. The continuous variation of cane in chute during the cane juice extraction inversely affects the cane juice extraction efficiency of mill. This paper deals with the development and performance comparison of conventional controller and fuzzy controller to maintain the cane level in chute during juice extraction. The conventional controller is developed using VHDL language and simulated by using Xilinx ISE 14.5 version. The fuzzy controller is developed and simulated by using fuzzy toolbox of ‘MATLAB® version 7.11.0.584 (R2020b).

This work lays down a foundation for text prediction of an inflected and under-resourced language Urdu. The interface developed is not limited to a T9 (Text on 9 keys) application used in embedded devices, which can only predict a word after typing initial characters. It is capable of predicting a word like T9 and also a sequence of word after a word in a continuous manner for fast document typing. It is based on N-gram language model. This stochastic interface deals with three N-gram levels from unary to ternary independently. The uni-gram mode is being in use for applications like T9, while the bi-gram and tri-gram modes are being in use for sentence prediction. The measures include a percentage of keystrokes saved, keystrokes until completion and a percentage of time saved during the typing. Two different corpora are merged to build a sufficient amount of data. The test data is divided into a test and a held out data equally for an experimental purpose. This whole exercise enables the QASKU system outperforms the FastType with almost 15% more saved keystrokes.

The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overcoming the premature convergence & stagnation problems as in basic PSO algorithm & Particle swarm optimization with shrinkage factor & inertia weight approach (PSO-SFIWA). In this paper SMIB system along with PID damped SVC controller is considered for study. The generator speed deviation is used as an auxiliary signal to SVC, to generate the desired damping. This controller improves the dynamic performance of power system by reducing the steady-state error. The controller parameters are optimized using basic PSO, PSO-SFIWA & Advanced Adaptive PSO. Computational results show that Advanced Adaptive based SVC controller is able to find better quality solution as compare to conventional PSO & PSO-SFIWA Techniques.