Search results for: adaptive speed observer
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2231

Search results for: adaptive speed observer

1061 Recurrent Radial Basis Function Network for Failure Time Series Prediction

Authors: Ryad Zemouri, Paul Ciprian Patic

Abstract:

An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.

Keywords: Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.

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1060 Horizontal Aspects of Planning Climate Change Adapted Management of Wetlands

Authors: Ákos Malatinszky, Szilvia Ádám

Abstract:

Climate change causes severe effects on natural habitats, especially wetlands. These challenges require the adaptation of their management to probable effects of climate change. A compilation of necessary changes in land management was collected in a Hungarian area being both national park and Natura 2000 SAC and SCI site in favor of increasing the resilience and reducing vulnerability. Several factors, such as ecological aspects, nature conservation and climatic adaptation should be combined with social and economic factors during the process of developing climate change adapted management on vulnerable wetlands. Planning adaptive management should be determined by a priority order of conservation aims and evaluation of factors at the determined planning unit. Mowing techniques, frequency and exact date should be observed as well as grazing species and their breed, due to different grazing, group forming and trampling habits. Integrating landscape history and historical land development into the planning process is essential.

Keywords: Adaptation, climate change, management, wetland.

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1059 A Balanced Cost Cluster-Heads Selection Algorithm for Wireless Sensor Networks

Authors: Ouadoudi Zytoune, Youssef Fakhri, Driss Aboutajdine

Abstract:

This paper focuses on reducing the power consumption of wireless sensor networks. Therefore, a communication protocol named LEACH (Low-Energy Adaptive Clustering Hierarchy) is modified. We extend LEACHs stochastic cluster-head selection algorithm by a modifying the probability of each node to become cluster-head based on its required energy to transmit to the sink. We present an efficient energy aware routing algorithm for the wireless sensor networks. Our contribution consists in rotation selection of clusterheads considering the remoteness of the nodes to the sink, and then, the network nodes residual energy. This choice allows a best distribution of the transmission energy in the network. The cluster-heads selection algorithm is completely decentralized. Simulation results show that the energy is significantly reduced compared with the previous clustering based routing algorithm for the sensor networks.

Keywords: Wireless Sensor Networks, Energy efficiency, WirelessCommunications, Clustering-based algorithm.

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1058 A Formative Assessment Model within the Competency-Based-Approach for an Individualized E-learning Path

Authors: El Falaki Brahim, Khalidi Idrissi Mohammed, Bennani Samir

Abstract:

E-learning is not restricted to the use of new technologies for the online content, but also induces the adoption of new approaches to improve the quality of education. This quality depends on the ability of these approaches (technical and pedagogical) to provide an adaptive learning environment. Thus, the environment should include features that convey intentions and meeting the educational needs of learners by providing a customized learning path to acquiring a competency concerned In our proposal, we believe that an individualized learning path requires knowledge of the learner. Therefore, it must pass through a personalization of diagnosis to identify precisely the competency gaps to fill, and reduce the cognitive load To personalize the diagnosis and pertinently measure the competency gap, we suggest implementing the formative assessment in the e-learning environment and we propose the introduction of a pre-regulation process in the area of formative assessment, involving its individualization and implementation in e-learning.

Keywords: Competency-Based-Approach, E-learning, Formative assessment, learner model, Modeling, pre-regulation process

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1057 On the Dynamic Behaviour of a Four-Bar Linkage Driven by a Velocity Controlled DC Motor

Authors: Giovanni Incerti

Abstract:

The dynamic behaviour of a four-bar linkage driven by a velocity controlled DC motor is discussed in the paper. In particular the author presents the results obtained by means of a specifically developed software, which implements the mathematical models of all components of the system (linkage, transmission, electric motor, control devices). The use of this software enables a more efficient design approach, since it allows the designer to check, in a simple and immediate way, the dynamic behaviour of the mechanism, arising from different values of the system parameters.

Keywords: Four-bar linkage, Speed control, Dynamic analysis.

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1056 Apoptosis Inspired Intrusion Detection System

Authors: R. Sridevi, G. Jagajothi

Abstract:

Artificial Immune Systems (AIS), inspired by the human immune system, are algorithms and mechanisms which are self-adaptive and self-learning classifiers capable of recognizing and classifying by learning, long-term memory and association. Unlike other human system inspired techniques like genetic algorithms and neural networks, AIS includes a range of algorithms modeling on different immune mechanism of the body. In this paper, a mechanism of a human immune system based on apoptosis is adopted to build an Intrusion Detection System (IDS) to protect computer networks. Features are selected from network traffic using Fisher Score. Based on the selected features, the record/connection is classified as either an attack or normal traffic by the proposed methodology. Simulation results demonstrates that the proposed AIS based on apoptosis performs better than existing AIS for intrusion detection.

Keywords: Apoptosis, Artificial Immune System (AIS), Fisher Score, KDD dataset, Network intrusion detection.

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1055 Object Tracking in Motion Blurred Images with Adaptive Mean Shift and Wavelet Feature

Authors: Iman Iraei, Mina Sharifi

Abstract:

A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: Mean shift, object tracking, blur extent, wavelet transform, motion blur.

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1054 Fuel Cell/DC-DC Convertor Control by Sliding Mode Method

Authors: Farzad Abdous

Abstract:

Fuel cell's system requires regulating circuit for voltage and current in order to control power in case of connecting to other generative devices or load. In this paper Fuel cell system and convertor, which is a multi-variable system, are controlled using sliding mode method. Use of weighting matrix in design procedure made it possible to regulate speed of control. Simulation results show the robustness and accuracy of proposed controller for controlling desired of outputs.

Keywords: DC-DC converter, Fuel cell, PEM, Slides mode control.

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1053 Gender based Barriers to Effective Collaboration: A Case Study on Children's Safeguard Partnerships

Authors: L. McAllister, A. Dudau

Abstract:

This paper explores gender related barriers to interagency collaboration in statutory children safeguard partnerships against a theoretical framework that considers individuals, professions and organisations interacting as part of a complex adaptive system. We argue that gender-framed obstacles to effective communication between culturally discrepant agencies can ultimately impact on the effectiveness of policy delivery,. We focused our research on three partnership structures in Sefton Metropolitan Borough in order to observe how interactions occur, whether the agencies involved perceive their occupational environment as being gender affected and whether they believe this can hinder effective collaboration with other biased organisations. Our principal empirical findings indicate that there is a general awareness amongst professionals of the role that gender plays in each of the agencies reviewed, that gender may well constitute a barrier to effective communication, but there is a sense in which there is little scope for change in the short term. We aim to signal here, however, the need to change against the risk of service failure.

Keywords: Children's safeguard, gender, gendered professions, inter-agency collaboration, partnerships.

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1052 Achieving High Availability by Implementing Beowulf Cluster

Authors: A.F.A. Abidin, N.S.M. Usop

Abstract:

A computer cluster is a group of tightly coupled computers that work together closely so that in many respects they can be viewed as though they are a single computer. The components of a cluster are commonly, but not always, connected to each other through fast local area networks. Clusters are usually deployed to improve performance and/or availability over that provided by a single computer, while typically being much more cost-effective than single computers of comparable speed or availability. This paper proposed the way to implement the Beowulf Cluster in order to achieve high performance as well as high availability.

Keywords: Beowulf Cluster, grid computing, GridMPI, MPICH.

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1051 A Proposal to Mobile Payment Implementing 2AF+

Authors: Nael Hirzallah, Sana Nseir

Abstract:

Merchants are competing to offer the use of mobile payment to encourage shopping. many mobile payment systems were made available in various locations worldwide; however, they have various drawbacks. This paper proposes a new mobile payment system that discusses the main drawbacks of these systems, namely security and speed of transaction. The proposal is featured by being simple to use by customers and merchants. Furthermore, the proposed system depends on a new authentication factor that is introduced in this paper and called by Two-Factors Authentication Plus, (2FA+).

Keywords: Electronic Commerce, Payment schemes, Mobile Payment, Authentication Factors, Mobile Applications.

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1050 Model of Controled Six Phase Induction Motor

Authors: R. Rinkeviciene, B. Kundrotas, S. Lisauskas

Abstract:

In this paper, the authors take a look at advantages of multiphase induction motors comparing them with three phase ones and present the applications where six-phase induction motors are used. They elaborate the mathematical model of six-phase induction motor with two similar stator three phase winding, shifted by 30 degrees in space and three phase winding in rotor, in synchronous reference frame for soft starting and scalar control. The authors simulate and discuss results of speed and torque starting transients.

Keywords: Model, scalar control, six-phase induction motor.

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1049 An Improved Conjugate Gradient Based Learning Algorithm for Back Propagation Neural Networks

Authors: N. M. Nawi, R. S. Ransing, M. R. Ransing

Abstract:

The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.

Keywords: Adaptive gain variation, back-propagation, activation function, conjugate gradient, search direction.

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1048 The Use of Dynamically Optimised High Frequency Moving Average Strategies for Intraday Trading

Authors: Abdalla Kablan, Joseph Falzon

Abstract:

This paper is motivated by the aspect of uncertainty in financial decision making, and how artificial intelligence and soft computing, with its uncertainty reducing aspects can be used for algorithmic trading applications that trade in high frequency. This paper presents an optimized high frequency trading system that has been combined with various moving averages to produce a hybrid system that outperforms trading systems that rely solely on moving averages. The paper optimizes an adaptive neuro-fuzzy inference system that takes both the price and its moving average as input, learns to predict price movements from training data consisting of intraday data, dynamically switches between the best performing moving averages, and performs decision making of when to buy or sell a certain currency in high frequency.

Keywords: Financial decision making, High frequency trading, Adaprive neuro-fuzzy systems, moving average strategy.

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1047 Chip Formation during Turning Multiphase Microalloyed Steel

Authors: V.Sivaraman, S. Sankaran, L. Vijayaraghavan

Abstract:

Machining through turning was carried out in a lathe to study the chip formation of Multiphase Ferrite (F-B-M) microalloyed steel. Taguchi orthogonal array was employed to perform the machining. Continuous and discontinuous chips were formed for different cutting parameters like speed, feed and depth of cut. Optical and scanning electron microscope was employed to identify the chip morphology.

Keywords: Multiphase microalloyed steel, chip formation, Taguchi technique, turning, cutting parameters

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1046 Study on Sharp V-Notch Problem under Dynamic Loading Condition Using Symplectic Analytical Singular Element

Authors: Xiaofei Hu, Zhiyu Cai, Weian Yao

Abstract:

V-notch problem under dynamic loading condition is considered in this paper. In the time domain, the precise time domain expanding algorithm is employed, in which a self-adaptive technique is carried out to improve computing accuracy. By expanding variables in each time interval, the recursive finite element formulas are derived. In the space domain, a Symplectic Analytical Singular Element (SASE) for V-notch problem is constructed addressing the stress singularity of the notch tip. Combining with the conventional finite elements, the proposed SASE can be used to solve the dynamic stress intensity factors (DSIFs) in a simple way. Numerical results show that the proposed SASE for V-notch problem subjected to dynamic loading condition is effective and efficient.

Keywords: V-notch, dynamic stress intensity factor, finite element method, precise time domain expanding algorithm.

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1045 Multiple Power Flow Solutions Using Particle Swarm Optimization with Embedded Local Search Technique

Authors: P. Acharjee, S. K. Goswami

Abstract:

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.

Keywords: critical conditions, ill-conditioned systems, localsearch technique, multiple power flow solutions, particle swarmoptimization.

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1044 Approximate Range-Sum Queries over Data Cubes Using Cosine Transform

Authors: Wen-Chi Hou, Cheng Luo, Zhewei Jiang, Feng Yan

Abstract:

In this research, we propose to use the discrete cosine transform to approximate the cumulative distributions of data cube cells- values. The cosine transform is known to have a good energy compaction property and thus can approximate data distribution functions easily with small number of coefficients. The derived estimator is accurate and easy to update. We perform experiments to compare its performance with a well-known technique - the (Haar) wavelet. The experimental results show that the cosine transform performs much better than the wavelet in estimation accuracy, speed, space efficiency, and update easiness.

Keywords: DCT, Data Cube

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1043 Tool for Fast Detection of Java Code Snippets

Authors: Tomáš Bublík, Miroslav Virius

Abstract:

This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and subgraph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.

Keywords: AST, Java, tree matching, Scripthon, source code recognition

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1042 Evaluation of Edge Configuration in Medical Echo Images Using Genetic Algorithms

Authors: Ching-Fen Jiang

Abstract:

Edge detection is usually the first step in medical image processing. However, the difficulty increases when a conventional kernel-based edge detector is applied to ultrasonic images with a textural pattern and speckle noise. We designed an adaptive diffusion filter to remove speckle noise while preserving the initial edges detected by using a Sobel edge detector. We also propose a genetic algorithm for edge selection to form complete boundaries of the detected entities. We designed two fitness functions to evaluate whether a criterion with a complex edge configuration can render a better result than a simple criterion such as the strength of gradient. The edges obtained by using a complex fitness function are thicker and more fragmented than those obtained by using a simple fitness function, suggesting that a complex edge selecting scheme is not necessary for good edge detection in medical ultrasonic images; instead, a proper noise-smoothing filter is the key.

Keywords: edge detection, ultrasonic images, speckle noise

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1041 Learning Objects Content Presentation Adaptation Model Considering Students' Learning Styles

Authors: Zenaide Carvalho da Silva, Andrey Ricardo Pimentel, Leandro Rodrigues Ferreira

Abstract:

Learning styles (LSs) correspond to the individual preferences of a person regarding the modes and forms in which he/she prefers to learn throughout the teaching/learning process. The content presentation of learning objects (LOs) using knowledge about the students’ LSs offers them digital educational resources tailored to their individual learning preferences. In this context, the most relevant characteristics of the LSs along with the most appropriate forms of LOs' content presentation were mapped and associated. Such was performed in order to define the composition of an adaptive model of LO's content presentation considering the LSs, which was called Adaptation of Content Presentation of Learning Objects Considering Learning Styles (ACPLOLS). LO prototypes were created with interfaces that were adapted to students' LSs. These prototypes were based on a model created for validation of the approaches that were used, which were established through experiments with the students. The results of subjective measures of students' emotional responses demonstrated that the ACPLOLS has reached the desired results in relation to the adequacy of the LOs interface, in accordance with the Felder-Silverman LSs Model.

Keywords: Adaptation, interface, learning styles, learning objects, students.

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1040 A Prediction-Based Reversible Watermarking for MRI Images

Authors: Nuha Omran Abokhdair, Azizah Bt Abdul Manaf

Abstract:

Reversible watermarking is a special branch of image watermarking, that is able to recover the original image after extracting the watermark from the image. In this paper, an adaptive prediction-based reversible watermarking scheme is presented, in order to increase the payload capacity of MRI medical images. The scheme divides the image into two parts, Region of Interest (ROI) and Region of Non-Interest (RONI). Two bits are embedded in each embeddable pixel of RONI and one bit is embedded in each embeddable pixel of ROI. The experimental results demonstrate that the proposed scheme is able to achieve high embedding capacity. This is mainly caused by two reasons. First, the pixels that were excluded from data embedding due to overflow/underflow are used for data embedding. Second, large location map that need to be added to watermark data as overhead is eliminated and thus lower data embedding capacity is prevented. Moreover, the scheme provides good visual quality to the watermarked image.

Keywords: Medical image watermarking, reversible watermarking, Difference Expansion, Prediction-Error Expansion.

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1039 ASC – A Stream Cipher with Built – In MAC Functionality

Authors: Kai-Thorsten Wirt

Abstract:

In this paper we present the design of a new encryption scheme. The scheme we propose is a very exible encryption and authentication primitive. We build this scheme on two relatively new design principles: t-functions and fast pseudo hadamard transforms. We recapitulate the theory behind these principles and analyze their security properties and efficiency. In more detail we propose a streamcipher which outputs a message authentication tag along with theencrypted data stream with only little overhead. Moreover we proposesecurity-speed tradeoffs. Our scheme is faster than other comparablet-function based designs while offering the same security level.

Keywords: Cryptography, Combined Primitives, Stream Cipher, MAC, T-Function, FPHT.

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1038 Some Studies on Temperature Distribution Modeling of Laser Butt Welding of AISI 304 Stainless Steel Sheets

Authors: N. Siva Shanmugam, G. Buvanashekaran, K. Sankaranarayanasamy

Abstract:

In this research work, investigations are carried out on Continuous Wave (CW) Nd:YAG laser welding system after preliminary experimentation to understand the influencing parameters associated with laser welding of AISI 304. The experimental procedure involves a series of laser welding trials on AISI 304 stainless steel sheets with various combinations of process parameters like beam power, beam incident angle and beam incident angle. An industrial 2 kW CW Nd:YAG laser system, available at Welding Research Institute (WRI), BHEL Tiruchirappalli, is used for conducting the welding trials for this research. After proper tuning of laser beam, laser welding experiments are conducted on AISI 304 grade sheets to evaluate the influence of various input parameters on weld bead geometry i.e. bead width (BW) and depth of penetration (DOP). From the laser welding results, it is noticed that the beam power and welding speed are the two influencing parameters on depth and width of the bead. Three dimensional finite element simulation of high density heat source have been performed for laser welding technique using finite element code ANSYS for predicting the temperature profile of laser beam heat source on AISI 304 stainless steel sheets. The temperature dependent material properties for AISI 304 stainless steel are taken into account in the simulation, which has a great influence in computing the temperature profiles. The latent heat of fusion is considered by the thermal enthalpy of material for calculation of phase transition problem. A Gaussian distribution of heat flux using a moving heat source with a conical shape is used for analyzing the temperature profiles. Experimental and simulated values for weld bead profiles are analyzed for stainless steel material for different beam power, welding speed and beam incident angle. The results obtained from the simulation are compared with those from the experimental data and it is observed that the results of numerical analysis (FEM) are in good agreement with experimental results, with an overall percentage of error estimated to be within ±6%.

Keywords: Laser welding, Butt weld, 304 SS, FEM.

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1037 Intuition Operator: Providing Genomes with Reason

Authors: Grigorios N. Beligiannis, Georgios A. Tsirogiannis, Panayotis E. Pintelas

Abstract:

In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge faster towards the optimal solution of a problem. This new genetic operator is called ''intuition'' operator. Generally speaking, one can claim that this operator is a way to include any heuristic or any other local knowledge, concerning the problem, that cannot be embedded in the fitness function. Simulation results show that the use of this operator increases significantly the performance of the classic Genetic Algorithm by increasing the convergence speed of its population.

Keywords: Genetic algorithms, intuition operator, reasonable genomes, complex search space, nonlinear fitness functions

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1036 Desalination of Salt Water by Collision with Surface Coated with Nano Particles

Authors: Hesham Muhammad Ibrahim

Abstract:

This paper introduces and proves new concept of salt dissolving in water as very tiny solid sodium chloride particles of nanovolumes, from this point of view salt water can be desalinated by collision with special surface characterized by smoothness upon nano level, high rigidity, high hardness under appropriate conditions of water launching in the form of thin laminar flow under suitable speed and angle of incidence to get desalinated water.

Keywords: Desalination by collision, nano coating, water desalination, water repellent surface.

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1035 Overcrowding and Adequate Housing: The Potential of Adaptability

Authors: Inês Ramalhete, Hugo Farias, Rui da Silva Pinto

Abstract:

Adequate housing has been a widely discussed theme in academic circles related to low-cost housing, whereas its physical features are easy to deal with, overcrowding (related to social, cultural and economic aspects) is still ambiguous, particularly regarding the set of indicators that can accurately reflect and measure it. This paper develops research on low-cost housing models for developing countries and what is the best method to embed overcrowding as an important parameter for adaptability. A critical review of international overcrowding indicators and their application in two developing countries, Cape Verde and Angola, is presented. The several rationales and the constraints for an accurate assessment of overcrowding are considered, namely baseline data (statistics), which can induce misjudgments, as well as social and cultural factors (such as personal choices of residents). This paper proposes a way to tackle overcrowding through housing adaptability, considering factors such as physical flexibility, functional ambiguity, and incremental expansion schemes. Moreover, a case-study is presented to establish a framework for the theoretical application of the proposed approach.

Keywords: Adaptive housing, low-cost housing, overcrowding.

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1034 Comparative Analysis of Machine Learning Tools: A Review

Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

Abstract:

Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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1033 Parallel Block Backward Differentiation Formulas For Solving Large Systems of Ordinary Differential Equations

Authors: Zarina Bibi, I., Khairil Iskandar, O.

Abstract:

In this paper, parallelism in the solution of Ordinary Differential Equations (ODEs) to increase the computational speed is studied. The focus is the development of parallel algorithm of the two point Block Backward Differentiation Formulas (PBBDF) that can take advantage of the parallel architecture in computer technology. Parallelism is obtained by using Message Passing Interface (MPI). Numerical results are given to validate the efficiency of the PBBDF implementation as compared to the sequential implementation.

Keywords: Ordinary differential equations, parallel.

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1032 Power System Contingency Analysis Using Multiagent Systems

Authors: Anant Oonsivilai, Kenedy A. Greyson

Abstract:

The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.

Keywords: Agents, model, negotiation, optimal dispatch, powersystems.

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