Multidimensional Data Mining by Means of Randomly Travelling Hyper-Ellipsoids

The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.

Genetic Algorithm Based Wavelength Division Multiplexing Networks Planning

This paper presents a new heuristic algorithm useful for long-term planning of survivable WDM networks. A multi-period model is formulated that combines network topology design and capacity expansion. The ability to determine network expansion schedules of this type becomes increasingly important to the telecommunications industry and to its customers. The solution technique consists of a Genetic Algorithm that allows generating several network alternatives for each time period simultaneously and shortest-path techniques to deduce from these alternatives a least-cost network expansion plan over all time periods. The multi-period planning approach is illustrated on a realistic network example. Extensive simulations on a wide range of problem instances are carried out to assess the cost savings that can be expected by choosing a multi-period planning approach instead of an iterative network expansion design method.

Assamese Numeral Corpus for Speech Recognition using Cooperative ANN Architecture

Speech corpus is one of the major components in a Speech Processing System where one of the primary requirements is to recognize an input sample. The quality and details captured in speech corpus directly affects the precision of recognition. The current work proposes a platform for speech corpus generation using an adaptive LMS filter and LPC cepstrum, as a part of an ANN based Speech Recognition System which is exclusively designed to recognize isolated numerals of Assamese language- a major language in the North Eastern part of India. The work focuses on designing an optimal feature extraction block and a few ANN based cooperative architectures so that the performance of the Speech Recognition System can be improved.

Impacts of Project-Overload on Innovation inside Organizations: Agent-Based Modeling

Market competition and a desire to gain advantages on globalized market, drives companies towards innovation efforts. Project overload is an unpleasant phenomenon, which is happening for employees inside those organizations trying to make the most efficient use of their resources to be innovative. But what are the impacts of project overload on organization-s innovation capabilities? Advanced engineering teams (AE) inside a major heavy equipment manufacturer are suffering from project overload in their quest for innovation. In this paper, Agent-based modeling (ABM) is used to examine the current reality of the company context, and of the AE team, where the opportunities and challenges for reducing the risk of project overload and moving towards innovation were identified. Project overload is more likely to stifle innovation and creativity inside teams. On the other hand, motivations on proper challenging goals are more likely to help individual to alleviate the negative aspects of low level of project overload.

Industrial Compressor Anti-Surge Computer Control

The paper presents a compressor anti-surge control system, that results in maximizing compressor throughput with pressure standard deviation reduction, increased safety margin between design point and surge limit line and avoiding possible machine surge. Alternative control strategies are presented.

Robot Vision Application based on Complex 3D Pose Computation

The paper presents a technique suitable in robot vision applications where it is not possible to establish the object position from one view. Usually, one view pose calculation methods are based on the correspondence of image features established at a training step and exactly the same image features extracted at the execution step, for a different object pose. When such a correspondence is not feasible because of the lack of specific features a new method is proposed. In the first step the method computes from two views the 3D pose of feature points. Subsequently, using a registration algorithm, the set of 3D feature points extracted at the execution phase is aligned with the set of 3D feature points extracted at the training phase. The result is a Euclidean transform which have to be used by robot head for reorientation at execution step.

A Growing Natural Gas Approach for Evaluating Quality of Software Modules

The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.

Finite Element Study of a DfD Beam-Column Connection

Design for Disassembly (DfD) aims to reuse the structural components instead of demolition followed by recycling of the demolition debris. This concept preserves the invested embodied energy of materials, thus reducing inputs of new embodied energy during materials reprocessing or remanufacturing. Both analytical and experimental research on a proposed DfD beam-column connection for use in residential apartments is currently investigated at the National University of Singapore in collaboration with the Housing and Development Board of Singapore. The present study reports on the results of a numerical analysis of the proposed connection utilizing finite element analysis. The numerical model was calibrated and validated by comparison against experimental results. Results of a parametric study will also be presented and discussed.

Application of Load Transfer Technique for Distribution Power Flow Analysis

Installation of power compensation equipment in some cases places additional buses into the system. Therefore, a total number of power flow equations and voltage unknowns increase due to additional locations of installed devices. In this circumstance, power flow calculation is more complicated. It may result in a computational convergence problem. This paper presents a power flow calculation by using Newton-Raphson iterative method together with the proposed load transfer technique. This concept is to eliminate additional buses by transferring installed loads at the new buses to existing two adjacent buses. Thus, the total number of power flow equations is not changed. The overall computational speed is expectedly shorter than that of solving the problem without applying the load transfer technique. A 15-bus test system is employed for test to evaluate the effectiveness of the proposed load transfer technique. As a result, the total number of iteration required and execution time is significantly reduced.

RF Permeability Test in SOC Structure for Establishing USN(Ubiquitous Sensor Network)

Recently, as information industry and mobile communication technology are developing, this study is conducted on the new concept of intelligent structures and maintenance techniques that applied wireless sensor network, USN (Ubiquitous Sensor Network), to social infrastructures such as civil and architectural structures on the basis of the concept of Ubiquitous Computing that invisibly provides human life with computing, along with mutually cooperating, compromising and connecting networks each other by having computers within all objects around us. Therefore, the purpose of this study is to investigate the capability of wireless communication of sensor node embedded in reinforced concrete structure with a basic experiment on an electric wave permeability of sensor node by fabricating molding with variables of concrete thickness and steel bars that are mostly used in constructing structures to determine the feasibility of application to constructing structures with USN. At this time, with putting the pitches of steel bars, the thickness of concrete placed, and the intensity of RF signal of a transmitter-receiver as variables and when wireless communication module was installed inside, the possible communication distance of plain concrete and the possible communication distance by the pitches of steel bars was measured in the horizontal and vertical direction respectively. Besides, for the precise measurement of diminution of an electric wave, the magnitude of an electric wave in the range of used frequencies was measured by using Spectrum Analyzer. The phenomenon of diminution of an electric wave was numerically analyzed and the effect of the length of wavelength of frequencies was analyzed by the properties of a frequency band area. As a result of studying the feasibility of an application to constructing structures with wireless sensor, in case of plain concrete, it shows 45cm for the depth of permeability and in case of reinforced concrete with the pitches of 5cm, it shows 37cm and 45cm for the pitches of 15cm.

Effect of Process Parameters on the Proximate Composition, Functional and Sensory Properties

Flour from Mucuna beans (Mucuna pruriens) were used in producing texturized meat analogue using a single screw extruder to monitor modifications on the proximate composition and the functional properties at high moisture level. Response surface methodology based on Box Behnken design at three levels of barrel temperature (110, 120, 130°C), screw speed (100,120,140rpm) and feed moisture (44, 47, 50%) were used in 17 runs. Regression models describing the effect of variables on the product responses were obtained. Descriptive profile analyses and consumer acceptability test were carried out on optimized flavoured extruded meat analogue. Responses were mostly affected by barrel temperature and moisture level and to a lesser extent by screw speed. Optimization results based on desirability concept indicated that a barrel temperature of 120.15°C, feed moisture of 47% and screw speed of 119.19 rpm would produce meat analogue of preferable proximate composition, functional and sensory properties which reveals consumers` likeness for the product.

Fatigue Analysis of Crack Growing Rate and Stress Intensity Factor for Stress Corrosion Cracking in a Pipeline System

Environment-assisted cracking (EAC) is one of the most serious causes of structural failure over a broad range of industrial applications including offshore structures. In EAC condition there is not a definite relation such as Paris equation in Linear Elastic Fracture Mechanics (LEFM). According to studying and searching a lot what the researchers said either a material has contact with hydrogen or any other corrosive environment, phenomenon of electrical and chemical reactions of material with its environment will be happened. In the literature, there are many different works to consider fatigue crack growing and solve it but they are experimental works. Thus, in this paper, authors have an aim to evaluate mathematically the pervious works in LEFM. Obviously, if an environment is more sour and corrosive, the changes of stress intensity factor is more and the calculation of stress intensity factor is difficult. A mathematical relation to deal with the stress intensity factor during the diffusion of sour environment especially hydrogen in a marine pipeline is presented. By using this relation having and some experimental relation an analytical formulation will be presented which enables the fatigue crack growth and critical crack length under cyclic loading to be predicted. In addition, we can calculate KSCC and stress intensity factor in the pipeline caused by EAC.

Categorization and Estimation of Relative Connectivity of Genes from Meta-OFTEN Network

The most common result of analysis of highthroughput data in molecular biology represents a global list of genes, ranked accordingly to a certain score. The score can be a measure of differential expression. Recent work proposed a new method for selecting a number of genes in a ranked gene list from microarray gene expression data such that this set forms the Optimally Functionally Enriched Network (OFTEN), formed by known physical interactions between genes or their products. Here we present calculation results of relative connectivity of genes from META-OFTEN network and tentative biological interpretation of the most reproducible signal. The relative connectivity and inbetweenness values of genes from META-OFTEN network were estimated.

Study of Single Network Adjustment Using QOCA Software in Korea

For this study, this researcher conducted a precision network adjustment with QOCA, the precision network adjustment software developed by Jet Propulsion Laboratory, to perform an integrated network adjustment on the Unified Control Points managed by the National Geographic Information Institute. Towards this end, 275 Unified Control Points observed in 2008 were selected before a network adjustment is performed on those 275 Unified Control Points. The RMSE on the discrepancies of coordinates as compared to the results of GLOBK was ±6.07mm along the N axis, ±2.68mm along the E axis and ±6.49mm along the U axis.

Increasing the Efficacy of Educators Teaching Online

In order to provide and maintain effective pedagogy for the burgeoning virtual reality community, it is vital to have trained faculty in the institutions of higher education who will teach these courses and be able to make full use of their academic knowledge and expertise. As the number of online courses continues to grow, there is a need for these institutions to establish mentoring programs that will support the novice online instructor. The environment in which this takes place and the factors that ensure its success are critical to the adoption of the new instructional delivery format taught by both seasoned educators and adjunct instructors. Effective one-on-one mentoring promotes a professional, compassionate and collegial faculty who will provide a consistent and rigorous academic program for students online.

HIV Modelling - Parallel Implementation Strategies

We report on the development of a model to understand why the range of experience with respect to HIV infection is so diverse, especially with respect to the latency period. To investigate this, an agent-based approach is used to extract highlevel behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A network of independent matrices mimics the chain of lymph nodes. Dealing with massively multi-agent systems requires major computational effort. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach and, using the MPI library, are here implemented, tested and optimized. Our current focus is on the various implementations of the data transfer across the network. Three communications strategies are proposed and tested, showing that the most efficient approach is communication based on the natural lymph-network connectivity.

The Influence of Electrode Heating On the Force Generated On a High Voltage Capacitor with Asymmetrical Electrodes

When a high DC voltage is applied to a capacitor with strongly asymmetrical electrodes, it generates a mechanical force that affects the whole capacitor. This is caused by the motion of ions generated around the smaller of the two electrodes and their subsequent interaction with the surrounding medium. If one of the electrodes is heated, it changes the conditions around the capacitor and influences the process of ionisation, thus changing the value of the generated force. This paper describes these changes and gives reasons behind them. Further the experimental results are given as proof of the ionic mechanism of the phenomenon.

Software Tools for System Identification and Control using Neural Networks in Process Engineering

Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering. The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field. SIMULINK is properly a widely used graphical code development environment which allows system-level developers to perform rapid prototyping and testing. Such graphical based programming environment involves block-based code development and offers a more intuitive approach to modeling and control task in a great variety of engineering disciplines. In this paper a SIMULINK based Neural Tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column including non linear hydrodynamic effects. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.

A Dynamic Programming Model for Maintenance of Electric Distribution System

The paper presents dynamic programming based model as a planning tool for the maintenance of electric power systems. Every distribution component has an exponential age depending reliability function to model the fault risk. In the moment of time when the fault costs exceed the investment costs of the new component the reinvestment of the component should be made. However, in some cases the overhauling of the old component may be more economical than the reinvestment. The comparison between overhauling and reinvestment is made by optimisation process. The goal of the optimisation process is to find the cost minimising maintenance program for electric power distribution system.

Business Diversification Strategies in the Italian Energy Markets

The liberalization and privatization processes have forced public utility companies to face new competitive challenges, implementing strategies to gain market share and, at the same time, keep the old customers. To this end, many companies have carried out mergers, acquisitions and conglomerations in order to diversify their business. This paper focuses on companies operating in the free energy market in Italy. In the last decade, this sector has undergone profound changes that have radically changed the competitive scenario and have led companies to implement diversification strategies of the business. Our work aims to evaluate the economic and financial performances obtained by energy companies, following the beginning of the liberalization process, verifying the possible relationship with the implemented diversification strategies.