Selection of an Optimum Configuration of Solar PV Array under Partial Shaded Condition Using Particle Swarm Optimization

This paper presents an extraction of maximum energy from Solar Photovoltaic Array (SPVA) under partial shaded conditions by optimum selection of array size using Particle Swarm Optimization (PSO) technique. In this paper a detailed study on the output reduction of different SPVA configurations under partial shaded conditions have been carried out. A generalized MATLAB M-code based software model has been used for any required array size, configuration, shading patterns and number of bypass diodes. Comparative study has been carried out on different configurations by testing several shading scenarios. While the number of shading patterns and the rate of change are very low for stationary SPVA but these may be quite large for SPVA mounted on a mobile platforms. This paper presents the suitability of PSO technique to select optimum configuration for mobile arrays by calculating the global peak (GP) of different configurations and to transfer maximum power to the load.

Simulation Model of an Ultra-Light Overhead Conveyor System; Analysis of the Process in the Warehouse

Ultra-light overhead conveyor systems are rope-based conveying systems with individually driven vehicles. The vehicles can move automatically on the rope and this can be realized by energy and signals. The ultra-light overhead conveyor systems always must be integrated with a logistical process by finding a best way for a cheaper material flow in order to guarantee precise and fast workflows. This paper analyzes the process of an ultra-light overhead conveyor system using necessary assumptions. The analysis consists of three scenarios. These scenarios are based on raising the vehicle speeds with equal increments at each case. The correlation between the vehicle speed and system throughput is investigated. A discrete-event simulation model of an ultra-light overhead conveyor system is constructed using DOSIMIS-3 software to implement three scenarios. According to simulation results; the optimal scenario, hence the optimal vehicle speed, is found out among three scenarios. This simulation model demonstrates the effect of increased speed on the system throughput.

Genetic Algorithm for In-Theatre Military Logistics Search-and-Delivery Path Planning

Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Nuclear Power Generation and CO2 Abatement Scenarios in Taiwan

Taiwan was the first country in Asia to announce “Nuclear-Free Homeland" in 2002. In 2008, the new government released the Sustainable Energy Policy Guidelines to lower the nationwide CO2 emissions some time between 2016 and 2020 back to the level of year 2008, further abatement of CO2 emissions is planed in year 2025 when CO2 emissions will decrease to the level of year 2000. Besides, under consideration of the issues of energy, environment and economics (3E), the new government declared that the nuclear power is a carbon-less energy option. This study analyses the effects of nuclear power generation for CO2 abatement scenarios in Taiwan. The MARKAL-MACRO energy model was adopted to evaluate economic impacts and energy deployment due to life extension of existing nuclear power plants and build new nuclear power units in CO2 abatement scenarios. The results show that CO2 abatement effort is expensive. On the other hand, nuclear power is a cost-effective choice. The GDP loss rate in the case of building new nuclear power plants is around two thirds of the Nuclear-Free Homeland case. Nuclear power generation has the capacity to provide large-scale CO2 free electricity. Therefore, the results show that nuclear power is not only an option for Taiwan, but also a requisite for Taiwan-s CO2 reduction strategy.

Wireless Distributed Load-Shedding Management System for Non-Emergency Cases

In this paper, we present a cost-effective wireless distributed load shedding system for non-emergency scenarios. In power transformer locations where SCADA system cannot be used, the proposed solution provides a reasonable alternative that combines the use of microcontrollers and existing GSM infrastructure to send early warning SMS messages to users advising them to proactively reduce their power consumption before system capacity is reached and systematic power shutdown takes place. A novel communication protocol and message set have been devised to handle the messaging between the transformer sites, where the microcontrollers are located and where the measurements take place, and the central processing site where the database server is hosted. Moreover, the system sends warning messages to the endusers mobile devices that are used as communication terminals. The system has been implemented and tested via different experimental results.

A Comparative Study on Available IPv6 Platforms for Wireless Sensor Network

The low power wireless sensor devices which usually uses the low power wireless private area network (IEEE 802.15.4) standard are being widely deployed for various purposes and in different scenarios. IPv6 low power wireless private area network (6LoWPAN) was adopted as part of the IETF standard for the wireless sensor devices so that it will become an open standard compares to other dominated proprietary standards available in the market. 6LoWPAN also allows the integration and communication of sensor nodes with the Internet more viable. This paper presents a comparative study on different available IPv6 platforms for wireless sensor networks including open and close sources. It also discusses about the platforms used by these stacks. Finally it evaluates and provides appropriate suggestions which can be use for selection of required IPv6 stack for low power devices.

A Multi-Objective Model for Supply Chain Network Design under Stochastic Demand

In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two objectives: (1) minimization the fixed and variable cost, (2) maximization the service level. A weighting method is utilized to solve this two objective problem and a numerical example is made to show the performance of the model.

ClassMATE: Enabling Ambient Intelligence in the Classroom

Ambient Intelligence (AmI) environments bring significant potential to exploit sophisticated computer technology in everyday life. In particular, the educational domain could be significantly enhanced through AmI, as personalized and adapted learning could be transformed from paper concepts and prototypes to real-life scenarios. In this paper, an integrated framework is presented, named ClassMATE, supporting ubiquitous computing and communication in a school classroom. The main objective of ClassMATE is to enable pervasive interaction and context aware education in the technologically augmented classroom of the future.

A Post Keynesian Environmental Macroeconomic Model for Agricultural Water Sustainability under Climate Change in the Murray-Darling Basin, Australia

Climate change has profound consequences for the agriculture of south-eastern Australia and its climate-induced water shortage in the Murray-Darling Basin. Post Keynesian Economics (PKE) macro-dynamics, along with Kaleckian investment and growth theory, are used to develop an ecological-economic system dynamics model of this complex nonlinear river basin system. The Murray- Darling Basin Simulation Model (MDB-SM) uses the principles of PKE to incorporate the fundamental uncertainty of economic behaviors of farmers regarding the investments they make and the climate change they face, particularly as regards water ecosystem services. MDB-SM provides a framework for macroeconomic policies, especially for long-term fiscal policy and for policy directed at the sustainability of agricultural water, as measured by socio-economic well-being considerations, which include sustainable consumption and investment in the river basin. The model can also reproduce other ecological and economic aspects and, for certain parameters and initial values, exhibit endogenous business cycles and ecological sustainability with realistic characteristics. Most importantly, MDBSM provides a platform for the analysis of alternative economic policy scenarios. These results reveal the importance of understanding water ecosystem adaptation under climate change by integrating a PKE macroeconomic analytical framework with the system dynamics modelling approach. Once parameterised and supplied with historical initial values, MDB-SM should prove to be a practical tool to provide alternative long-term policy simulations of agricultural water and socio-economic well-being.

Improvement over DV-Hop Localization Algorithm for Wireless Sensor Networks

In this paper, we propose improved versions of DVHop algorithm as QDV-Hop algorithm and UDV-Hop algorithm for better localization without the need for additional range measurement hardware. The proposed algorithm focuses on third step of DV-Hop, first error terms from estimated distances between unknown node and anchor nodes is separated and then minimized. In the QDV-Hop algorithm, quadratic programming is used to minimize the error to obtain better localization. However, quadratic programming requires a special optimization tool box that increases computational complexity. On the other hand, UDV-Hop algorithm achieves localization accuracy similar to that of QDV-Hop by solving unconstrained optimization problem that results in solving a system of linear equations without much increase in computational complexity. Simulation results show that the performance of our proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop and DV-Hop based algorithms in all considered scenarios.

Services and Applications for Smart Office Environments - A Survey of State-of-the-Art Usage Scenarios

This paper reports on a survey of state-of-the-art application scenarios for smart office environments. Based on an analysis of ongoing research activities and industry projects, functionalities and services of future office systems are extracted. In a second step, these results are used to identify the key characteristics of emerging products.

Minimizing Energy Consumption in Wireless Sensor Networks using Binary Integer Linear Programming

The important issue considered in the widespread deployment of Wireless Sensor Networks (WSNs) is an efficiency of the energy consumption. In this paper, we present a study of the optimal relay station planning problems using Binary Integer Linear Programming (BILP) model to minimize the energy consumption in WSNs. Our key contribution is that the proposed model not only ensures the required network lifetime but also guarantees the radio connectivity at high level of communication quality. Specially, we take into account effects of noise, signal quality limitation and bit error rate characteristics. Numerical experiments were conducted in various network scenarios. We analyzed the effects of different sensor node densities and distribution on the energy consumption.

Information Fusion for Identity Verification

In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..

A Multi-Agent Framework for Data Mining

A generic and extendible Multi-Agent Data Mining (MADM) framework, MADMF (the Multi-Agent Data Mining Framework) is described. The central feature of the framework is that it avoids the use of agreed meta-language formats by supporting a framework of wrappers. The advantage offered is that the framework is easily extendible, so that further data agents and mining agents can simply be added to the framework. A demonstration MADMF framework is currently available. The paper includes details of the MADMF architecture and the wrapper principle incorporated into it. A full description and evaluation of the framework-s operation is provided by considering two MADM scenarios.

Analysing of Indoor Radio Wave Propagation on Ad-hoc Network by Using TP-LINK Router

This paper presents results of measurements campaign carried out at a carrier frequency of 24GHz with the help of TPLINK router in indoor line-of-sight (LOS) scenarios. Firstly, the radio wave propagation strategies are analyzed in some rooms with router of point to point Ad hoc network. Then floor attenuation is defined for 3 floors in experimental region. The free space model and dual slope models are modified by considering the influence of corridor conditions on each floor. Using these models, indoor signal attenuation can be estimated in modeling of indoor radio wave propagation. These results and modified models can also be used in planning the networks of future personal communications services.

Ductile Crack Growth in Surface Cracked Pressure Vessels

Pressure vessels are usually operating at temperatures where the conditions of linear elastic fracture mechanics are no longer met because massive plasticity precedes crack propagation. In this work the development of a surface crack in a pressure vessel subject to bending and tension under elastic-plastic fracture mechanics conditions was investigated. Finite element analysis was used to evaluate the hydrostatic stress, the J-integral and crack growth for semi-elliptical surface-breaking cracks. The results showed non-uniform stress triaxiality and crack driving force around the crack front at large deformation levels. Different ductile crack extensions were observed which emphasis the dependent of ductile tearing on crack geometry and type of loading. In bending the crack grew only beneath the surface, and growth was suppressed at the deepest segment. This contrasts to tension where the crack breaks through the thickness with uniform growth along the entire crack front except at the free surface. Current investigations showed that the crack growth developed under linear elastic fracture mechanics conditions will no longer be applicable under ductile tearing scenarios.

Dissertation by Portfolio - A Break from Traditional Approaches

Much has been written about the difficulties students have with producing traditional dissertations. This includes both native English speakers (L1) and students with English as a second language (L2). The main emphasis of these papers has been on the structure of the dissertation, but in all cases, even when electronic versions are discussed, the dissertation is still in what most would regard as a traditional written form. Master of Science Degrees in computing disciplines require students to gain technical proficiency and apply their knowledge to a range of scenarios. The basis of this paper is that if a dissertation is a means of showing that such a student has met the criteria for a pass, which should be based on the learning outcomes of the dissertation module, does meeting those outcomes require a student to demonstrate their skills in a solely text based form, particularly in a highly technical research project? Could it be possible for a student to produce a series of related artifacts which form a cohesive package that meets the learning out comes of the dissertation?

Measurement of UHF Signal Strength Propagating from Road Surface with Vehicle Obstruction

Radio wave propagation on the road surface is a major problem on wireless sensor network for traffic monitoring. In this paper, we compare receiving signal strength on two scenarios 1) an empty road and 2) a road with a vehicle. We investigate the effect of antenna polarization and antenna height to the receiving signal strength. The transmitting antenna is installed on the road surface. The receiving signal is measured 360 degrees around the transmitting antenna with the radius of 2.5 meters. Measurement results show the receiving signal fluctuation around the transmitting antenna in both scenarios. Receiving signal with vertical polarization antenna results in higher signal strength than horizontal polarization antenna. The optimum antenna elevation is 1 meter for both horizon and vertical polarizations with the vehicle on the road. In the empty road, the receiving signal level is unvarying with the elevation when the elevation is greater than 1.5 meters.

Analytical Crack Propagation Scenario for Gear Teeth and Time-Varying Gear Mesh Stiffness

In this paper an analytical crack propagation scenario is proposed which assumes that a crack propagates in the tooth root in both the crack depth direction and the tooth width direction, and which is more reasonable and realistic for non-uniform load distribution cases than the other presented scenarios. An analytical approach is used for quantifying the loss of time-varying gear mesh stiffness with the presence of crack propagation in the gear tooth root. The proposed crack propagation scenario can be applied for crack propagation modelling and monitoring simulation, but further research is required for comparison and evaluation of all the presented crack propagation scenarios from the condition monitoring point of view.

Assessing Habitat-Suitability Models with a Virtual Species at Khao Nan National Park, Thailand

This study examined a habitat-suitability assessment method namely the Ecological Niche Factor Analysis (ENFA). A virtual species was created and then dispatched in a geographic information system model of a real landscape in three historic scenarios: (1) spreading, (2) equilibrium, and (3) overabundance. In each scenario, the virtual species was sampled and these simulated data sets were used as inputs for the ENFA to reconstruct the habitat suitability model. The 'equilibrium' scenario gives the highest quantity and quality among three scenarios. ENFA was sensitive to the distribution scenarios but not sensitive to sample sizes. The use of a virtual species proved to be a very efficient method, allowing one to fully control the quality of the input data as well as to accurately evaluate the predictive power of the analyses.