A Fast Sensor Relocation Algorithm in Wireless Sensor Networks

Sensor relocation is to repair coverage holes caused by node failures. One way to repair coverage holes is to find redundant nodes to replace faulty nodes. Most researches took a long time to find redundant nodes since they randomly scattered redundant nodes around the sensing field. To record the precise position of sensor nodes, most researches assumed that GPS was installed in sensor nodes. However, high costs and power-consumptions of GPS are heavy burdens for sensor nodes. Thus, we propose a fast sensor relocation algorithm to arrange redundant nodes to form redundant walls without GPS. Redundant walls are constructed in the position where the average distance to each sensor node is the shortest. Redundant walls can guide sensor nodes to find redundant nodes in the minimum time. Simulation results show that our algorithm can find the proper redundant node in the minimum time and reduce the relocation time with low message complexity.

Voice in Pre-service Teacher Development

Recently, Thai education system is engaged in serious and promising reforms. One of the crucial elements in most of these educational reforms is the teacher professional development. Teachers today are under growing pressure to perform. However, most new teachers are not adequately prepared to meet the expectation. Consequently, this paper seeks to investigate the opinion of mentor teachers and university supervisors about professional development in the aspect of learning management skill of the preservice teachers in Rajabhat Universities, then compare the opinion between the mentor teachers and university supervisors about professional development in the aspect of learning management skill of the pre-service teachers. The study involved a cohort of 40 university supervisors and 77 mentor teachers. The research concludes by showing that mentor teachers viewed pre-service teacher as a professional teacher with an effective learning management skill. However, in the perspective of the university supervisor, pre-service teachers still have inadequate learning management skill.

Chitosan/Casein Microparticles: Preparation, Characterization and Drug Release Studies

Microparticles carrier systems made from naturally occurring polymers based on chitosan/casein system appears to be a promising carrier for the sustained release of orally and parenteral administered drugs. In the current study we followed a microencapsulation technique based aqueous coacervation method to prepare chitosan/casein microparticles of compositions 1:1, 1:2 and 1:5 incorporated with chloramphenicol. Glutaraldehyde was used as a chemical cross-linking agent. The microparticles were prepared by aerosol method and studied by optical microscopy, infrared spectroscopy, thermo gravimetric analysis, swelling studies and drug release studies at various pH. The percentage swelling of the polymers are found to be in the order pH 4 > pH 10 > pH 7 and the increase in casein composition decrease the swelling percentage. The drug release studies also follow the above order.

Optimum Shape and Design of Cooling Towers

The aim of the current study is to develop a numerical tool that is capable of achieving an optimum shape and design of hyperbolic cooling towers based on coupling a non-linear finite element model developed in-house and a genetic algorithm optimization technique. The objective function is set to be the minimum weight of the tower. The geometric modeling of the tower is represented by means of B-spline curves. The finite element method is applied to model the elastic buckling behaviour of a tower subjected to wind pressure and dead load. The study is divided into two main parts. The first part investigates the optimum shape of the tower corresponding to minimum weight assuming constant thickness. The study is extended in the second part by introducing the shell thickness as one of the design variables in order to achieve an optimum shape and design. Design, functionality and practicality constraints are applied.

Hybrid Neuro Fuzzy Approach for Automatic Generation Control of Two -Area Interconnected Power System

The main objective of Automatic Generation Control (AGC) is to balance the total system generation against system load losses so that the desired frequency and power interchange with neighboring systems is maintained. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This paper deals with a novel approach of artificial intelligence (AI) technique called Hybrid Neuro-Fuzzy (HNF) approach for an (AGC). The advantage of this controller is that it can handle the non-linearities at the same time it is faster than other conventional controllers. The effectiveness of the proposed controller in increasing the damping of local and inter area modes of oscillation is demonstrated in a two area interconnected power system. The result shows that intelligent controller is having improved dynamic response and at the same time faster than conventional controller.

Enhanced Traveling Salesman Problem Solving by Genetic Algorithm Technique (TSPGA)

The well known NP-complete problem of the Traveling Salesman Problem (TSP) is coded in genetic form. A software system is proposed to determine the optimum route for a Traveling Salesman Problem using Genetic Algorithm technique. The system starts from a matrix of the calculated Euclidean distances between the cities to be visited by the traveling salesman and a randomly chosen city order as the initial population. Then new generations are then created repeatedly until the proper path is reached upon reaching a stopping criterion. This search is guided by a solution evaluation function.

Seismic Response Reduction of Structures using Smart Base Isolation System

In this study, control performance of a smart base isolation system consisting of a friction pendulum system (FPS) and a magnetorheological (MR) damper has been investigated. A fuzzy logic controller (FLC) is used to modulate the MR damper so as to minimize structural acceleration while maintaining acceptable base displacement levels. To this end, a multi-objective optimization scheme is used to optimize parameters of membership functions and find appropriate fuzzy rules. To demonstrate effectiveness of the proposed multi-objective genetic algorithm for FLC, a numerical study of a smart base isolation system is conducted using several historical earthquakes. It is shown that the proposed method can find optimal fuzzy rules and that the optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semi-active control algorithm.

Effects of Aggressive Ammonium Nitrate on Durability Properties of Concrete Using Sandstone and Granite Aggregates

The storage of chemical fertilizers in concrete building often leads to durability problems due to chemical attack. The damage of concrete is mostly caused by certain ammonium salts. The main purpose of the research is to investigate the durability properties of concrete being exposed to ammonium nitrate solution. In this investigation, experiments are conducted on concrete type G50 and G60. The leaching process is achieved by the use of 20% concentration solution of ammonium nitrate. The durability properties investigated are water absorption, volume of permeable voids, and sorptivity. Compressive strength, pH value, and degradation depth are measured after a certain period of leaching. A decrease in compressive strength and an increase in porosity are found through the conducted experiments. Apart from that, the experimental data shows that pH value decreases with increased leaching time while the degradation depth of concrete increases with leaching time. By comparing concrete type G50 and G60, concrete type G60 is more resistant to ammonium nitrate attack.

Impact of Computer-Mediated Communication on Virtual Teams- Performance: An Empirical Study

In a complex project environment, project teams face multi-dimensional communication problems that can ultimately lead to project breakdown. Team Performance varies in Face-to-Face (FTF) environment versus groups working remotely in a computermediated communication (CMC) environment. A brief review of the Input_Process_Output model suggested by James E. Driskell, Paul H. Radtke and Eduardo Salas in “Virtual Teams: Effects of Technological Mediation on Team Performance (2003)", has been done to develop the basis of this research. This model theoretically analyzes the effects of technological mediation on team processes, such as, cohesiveness, status and authority relations, counternormative behavior and communication. An empirical study described in this paper has been undertaken to test the “cohesiveness" of diverse project teams in a multi-national organization. This study uses both quantitative and qualitative techniques for data gathering and analysis. These techniques include interviews, questionnaires for data collection and graphical data representation for analyzing the collected data. Computer-mediated technology may impact team performance because of difference in cohesiveness among teams and this difference may be moderated by factors, such as, the type of communication environment, the type of task and the temporal context of the team. Based on the reviewed model, sets of hypotheses are devised and tested. This research, reports on a study that compared team cohesiveness among virtual teams using CMC and non-CMC communication mediums. The findings suggest that CMC can help virtual teams increase team cohesiveness among their members, making CMC an effective medium for increasing productivity and team performance.

Adaptation of Iterative Methods to Solve Fuzzy Mathematical Programming Problems

Based on the fuzzy set theory this work develops two adaptations of iterative methods that solve mathematical programming problems with uncertainties in the objective function and in the set of constraints. The first one uses the approach proposed by Zimmermann to fuzzy linear programming problems as a basis and the second one obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. We outline similarities between the two iterative methods studied. Selected examples from the literature are presented to validate the efficiency of the methods addressed.

The Stone in the Identity of the Landscape

The stone is a constituent part of the geological structure of the Territory, introducing himself as a subject that has always interconnected human and environment in the development of a discourse of meanings and symbols that reflect elements realized in different cultures and experiences. This action meant that the first settlements and their areas of influence gained importance in the field of humanization and spatial organization of the territory, not only for the appropriation that its inhabitants did, but mainly because the community regardless of their economic or social condition, used it as living space and cultural integration. These factors become decisive in the characterization of the landscape area in the northwest of Portugal, because the stone is a material that appears not only in the natural landscape, but is also a strong element in humanized landscape, becoming this relation the main characterization of the study area.

Prediction of the Epileptic Events 'Epileptic Seizures' by Neural Networks and Expert Systems

Many studies have focused on the nonlinear analysis of electroencephalography (EEG) mainly for the characterization of epileptic brain states. It is assumed that at least two states of the epileptic brain are possible: the interictal state characterized by a normal apparently random, steady-state EEG ongoing activity; and the ictal state that is characterized by paroxysmal occurrence of synchronous oscillations and is generally called in neurology, a seizure. The spatial and temporal dynamics of the epileptogenic process is still not clear completely especially the most challenging aspects of epileptology which is the anticipation of the seizure. Despite all the efforts we still don-t know how and when and why the seizure occurs. However actual studies bring strong evidence that the interictal-ictal state transition is not an abrupt phenomena. Findings also indicate that it is possible to detect a preseizure phase. Our approach is to use the neural network tool to detect interictal states and to predict from those states the upcoming seizure ( ictal state). Analysis of the EEG signal based on neural networks is used for the classification of EEG as either seizure or non-seizure. By applying prediction methods it will be possible to predict the upcoming seizure from non-seizure EEG. We will study the patients admitted to the epilepsy monitoring unit for the purpose of recording their seizures. Preictal, ictal, and post ictal EEG recordings are available on such patients for analysis The system will be induced by taking a body of samples then validate it using another. Distinct from the two first ones a third body of samples is taken to test the network for the achievement of optimum prediction. Several methods will be tried 'Backpropagation ANN' and 'RBF'.

Classification of Fuzzy Petri Nets, and Their Applications

Petri Net (PN) has proven to be effective graphical, mathematical, simulation, and control tool for Discrete Event Systems (DES). But, with the growth in the complexity of modern industrial, and communication systems, PN found themselves inadequate to address the problems of uncertainty, and imprecision in data. This gave rise to amalgamation of Fuzzy logic with Petri nets and a new tool emerged with the name of Fuzzy Petri Nets (FPN). Although there had been a lot of research done on FPN and a number of their applications have been anticipated, but their basic types and structure are still ambiguous. Therefore, in this research, an effort is made to categorize FPN according to their structure and algorithms Further, literature review of the applications of FPN in the light of their classifications has been done.

UAV Position Estimation Using Remote Radio Head With Adaptive Power Control

The adaptive power control of Code Division Multiple Access (CDMA) communications using Remote Radio Head (RRH) between multiple Unmanned Aerial Vehicles (UAVs) with a link-budget based Signal-to-Interference Ratio (SIR) estimate is applied to four inner loop power control algorithms. It is concluded that Base Station (BS) can calculate not only UAV distance using linearity between speed and Consecutive Transmit-Power-Control Ratio (CTR) of Adaptive Step-size Closed Loop Power Control (ASCLPC), Consecutive TPC Ratio Step-size Closed Loop Power Control (CS-CLPC), Fixed Step-size Power Control (FSPC), but also UAV position with Received Signal Strength Indicator (RSSI) ratio of RRHs.

Towards a Sustained Use of Renewable Energy Sources in Romania

The paper presents the potential for RES in Romania and the results of the Romanian national research project “Romania contribution to the European targets regarding the development of renewable energy sources - PROMES". The objective of the project is the development of energy generation from renewable energy sources (RES) in Romania by drawing up scenarios and prognosis harmonized with national and European targets, RES development effects modeling (environmental, economic, social etc.), research of the impact of the penetration of RES into the main, implementation of an advanced software system tool for RES information recording and communication, experimental research based on demonstrative applications. The expected results are briefly presented, as well as the social, economic and environmental impact.

Ranking - Convex Risk Minimization

The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.

An Environmental Impact Tool to Assess National Energy Scenarios

The Long-range Energy and Alternatives Planning (LEAP) energy planning system has been developed for South Africa, for the 2005 base year and a limited number of plausible future scenarios that may have significant implications (negative or positive) in terms of environmental impacts. The system quantifies the national energy demand for the domestic, commercial, transport, industry and agriculture sectors, the supply of electricity and liquid fuels, and the resulting emissions. The South African National Energy Research Institute (SANERI) identified the need to develop an environmental assessment tool, based on the LEAP energy planning system, to provide decision-makers and stakeholders with the necessary understanding of the environmental impacts associated with different energy scenarios. A comprehensive analysis of indicators that are used internationally and in South Africa was done and the available data was accessed to select a reasonable number of indicators that could be utilized in energy planning. A consultative process was followed to determine the needs of different stakeholders on the required indicators and also the most suitable form of reporting. This paper demonstrates the application of Energy Environmental Sustainability Indicators (EESIs) as part of the developed tool, which assists with the identification of the environmental consequences of energy generation and use scenarios and thereby promotes sustainability, since environmental considerations can then be integrated into the preparation and adoption of policies, plans, programs and projects. Recommendations are made to refine the tool further for South Africa.

Communicative Competence in Technical Oral Presentation: That “Magic“ Perceived by ESL Educators versus Content Experts

Till date, English as a Second Language (ESL) educators involved in teaching language and communication to engineering students face an uphill task in developing graduate communicative competency. This challenge is accentuated by the apparent lack of English for Specific Purposes (ESP) materials for engineering students in the engineering curriculum. As such, most ESL educators are forced to play multiple roles. They don tasks such as curriculum designers, material writers and teachers with limited knowledge of the disciplinary content. Previous research indicates that prospective professional engineers should possess some sub-sets of competency: technical, linguistic oral immediacy, meta-cognitive and rhetorical explanatory competence. Another study revealed that engineering students need to be equipped with technical and linguistic oral immediacy competence. However, little is known whether these competency needs are in line with the educators- perceptions of communicative competence. This paper examines the best mix of communicative competence subsets that create the magic for engineering students in technical oral presentations. For the purpose of this study, two groups of educators were interviewed. These educators were language and communication lecturers involved in teaching a speaking course and content experts who assess students- technical oral presentations at tertiary level. The findings indicate that these two groups differ in their perceptions

Design and Simulation of a New Self-Learning Expert System for Mobile Robot

In this paper, we present a novel technique called Self-Learning Expert System (SLES). Unlike Expert System, where there is a need for an expert to impart experiences and knowledge to create the knowledge base, this technique tries to acquire the experience and knowledge automatically. To display this technique at work, a simulation of a mobile robot navigating through an environment with obstacles is employed using visual basic. The mobile robot will move through this area without colliding with any obstacle and save the path that it took. If the mobile robot has to go through a similar environment again, then it will apply this experience to help it move through quicker without having to check for collision.