Search results for: calculation tasks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1109

Search results for: calculation tasks

389 The Experiences of South-African High-School Girls in a Fab Lab Environment

Authors: Nomusa Dlodlo, Ronald Noel Beyers

Abstract:

This paper reports on an effort to address the issue of inequality in girls- and women-s access to science, engineering and technology (SET) education and careers through raising awareness on SET among secondary school girls in South Africa. Girls participated in hands-on high-tech rapid prototyping environment of a fabrication laboratory that was aimed at stimulating creativity and innovation as part of a Fab Kids initiative. The Fab Kids intervention is about creating a SET pipeline as part of the Young Engineers and Scientists of Africa Initiative.The methodology was based on a real world situation and a hands-on approach. In the process, participants acquired a number of skills including computer-aided design, research skills, communication skills, teamwork skills, technical drawing skills, writing skills and problem-solving skills. Exposure to technology enhanced the girls- confidence in being able to handle technology-related tasks.

Keywords: Girls, design engineering, gender, science, women.

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388 Design of Encoding Calculator Software for Huffman and Shannon-Fano Algorithms

Authors: Wilson Chanhemo, Henry. R. Mgombelo, Omar F Hamad, T. Marwala

Abstract:

This paper presents a design of source encoding calculator software which applies the two famous algorithms in the field of information theory- the Shannon-Fano and the Huffman schemes. This design helps to easily realize the algorithms without going into a cumbersome, tedious and prone to error manual mechanism of encoding the signals during the transmission. The work describes the design of the software, how it works, comparison with related works, its efficiency, its usefulness in the field of information technology studies and the future prospects of the software to engineers, students, technicians and alike. The designed “Encodia" software has been developed, tested and found to meet the intended requirements. It is expected that this application will help students and teaching staff in their daily doing of information theory related tasks. The process is ongoing to modify this tool so that it can also be more intensely useful in research activities on source coding.

Keywords: Coding techniques, Coding algorithms, Codingefficiency, Encodia, Encoding software.

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387 A Numerical Method to Evaluate the Elastoplastic Material Properties of Fiber Reinforced Composite

Authors: M. Palizvan, M. H. Sadr, M. T. Abadi

Abstract:

The representative volume element (RVE) plays a central role in the mechanics of random heterogeneous materials with a view to predicting their effective properties. In this paper, a computational homogenization methodology, developed to determine effective linear elastic properties of composite materials, is extended to predict the effective nonlinear elastoplastic response of long fiber reinforced composite. Finite element simulations of volumes of different sizes and fiber volume fractures are performed for calculation of the overall response RVE. The dependencies of the overall stress-strain curves on the number of fibers inside the RVE are studied in the 2D cases. Volume averaged stress-strain responses are generated from RVEs and compared with the finite element calculations available in the literature at moderate and high fiber volume fractions. For these materials, the existence of an RVE is demonstrated for the sizes of RVE corresponding to 10–100 times the diameter of the fibers. In addition, the response of small size RVE is found anisotropic, whereas the average of all large ones leads to recover the isotropic material properties.

Keywords: Homogenization, periodic boundary condition, elastoplastic properties, RVE.

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386 A Novel Optimal Setting for Directional over Current Relay Coordination using Particle Swarm Optimization

Authors: D. Vijayakumar, R. K. Nema

Abstract:

Over Current Relays (OCRs) and Directional Over Current Relays (DOCRs) are widely used for the radial protection and ring sub transmission protection systems and for distribution systems. All previous work formulates the DOCR coordination problem either as a Non-Linear Programming (NLP) for TDS and Ip or as a Linear Programming (LP) for TDS using recently a social behavior (Particle Swarm Optimization techniques) introduced to the work. In this paper, a Modified Particle Swarm Optimization (MPSO) technique is discussed for the optimal settings of DOCRs in power systems as a Non-Linear Programming problem for finding Ip values of the relays and for finding the TDS setting as a linear programming problem. The calculation of the Time Dial Setting (TDS) and the pickup current (Ip) setting of the relays is the core of the coordination study. PSO technique is considered as realistic and powerful solution schemes to obtain the global or quasi global optimum in optimization problem.

Keywords: Directional over current relays, Optimization techniques, Particle swarm optimization, Power system protection.

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385 Multi-Sensor Target Tracking Using Ensemble Learning

Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

Abstract:

Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: Single classifier, machine learning, ensemble learning, multi-sensor target tracking.

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384 High Performance in Parallel Data Integration: An Empirical Evaluation of the Ratio Between Processing Time and Number of Physical Nodes

Authors: Caspar von Seckendorff, Eldar Sultanow

Abstract:

Many studies have shown that parallelization decreases efficiency [1], [2]. There are many reasons for these decrements. This paper investigates those which appear in the context of parallel data integration. Integration processes generally cannot be allocated to packages of identical size (i. e. tasks of identical complexity). The reason for this is unknown heterogeneous input data which result in variable task lengths. Process delay is defined by the slowest processing node. It leads to a detrimental effect on the total processing time. With a real world example, this study will show that while process delay does initially increase with the introduction of more nodes it ultimately decreases again after a certain point. The example will make use of the cloud computing platform Hadoop and be run inside Amazon-s EC2 compute cloud. A stochastic model will be set up which can explain this effect.

Keywords: Process delay, speedup, efficiency, parallel computing, data integration, E-Commerce, Amazon Elastic Compute Cloud (EC2), Hadoop, Nutch.

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383 Development of Roller-Based Interior Wall Painting Robot

Authors: Mohamed T. Sorour, Mohamed A. Abdellatif, Ahmed A. Ramadan, Ahmed A. Abo-Ismail

Abstract:

This paper describes the development of an autonomous robot for painting the interior walls of buildings. The robot consists of a painting arm with an end effector roller that scans the walls vertically and a mobile platform to give horizontal feed to paint the whole area of the wall. The painting arm has a planar twolink mechanism with two joints. Joints are driven from a stepping motor through a ball screw-nut mechanism. Four ultrasonic sensors are attached to the mobile platform and used to maintain a certain distance from the facing wall and to avoid collision with side walls. When settled on adjusted distance from the wall, the controller starts the painting process autonomously. Simplicity, relatively low weight and short painting time were considered in our design. Different modules constituting the robot have been separately tested then integrated. Experiments have shown successfulness of the robot in its intended tasks.

Keywords: Automated roller painting, Construction robots, Mobile robots, service robots, two link planar manipulator

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382 Theoretical Analysis of the Effect of Accounting for Special Methods in Similarity-Based Cohesion Measurement

Authors: Jehad Al Dallal

Abstract:

Class cohesion is an important object-oriented software quality attributes, and it refers to the degree of relatedness of class attributes and methods. Several class cohesion measures are proposed in the literature, and the impact of considering the special methods (i.e., constructors, destructors, and access and delegation methods) in cohesion calculation is not thoroughly theoretically studied for most of them. In this paper, we address this issue for three popular similarity-based class cohesion measures. For each of the considered measures we theoretically study the impact of including or excluding special methods on the values that are obtained by applying the measure. This study is based on analyzing the definitions and formulas that are proposed for the measures. The results show that including/excluding special methods has a considerable effect on the obtained cohesion values and that this effect varies from one measure to another. The study shows the importance of considering the types of methods that have to be accounted for when proposing a similarity-based cohesion measure.

Keywords: Object-oriented class, software quality, class cohesion measure, class cohesion, special methods.

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381 Online Monitoring Rheological Property of Polymer Melt during Injection Molding

Authors: Chung-Chih Lin, Chien-Liang Wu

Abstract:

The detection of the polymer melt state during manufacture process is regarded as an efficient way to control the molded part quality in advance. Online monitoring rheological property of polymer melt during processing procedure provides an approach to understand the melt state immediately. Rheological property reflects the polymer melt state at different processing parameters and is very important in injection molding process especially. An approach that demonstrates how to calculate rheological property of polymer melt through in-process measurement, using injection molding as an example, is proposed in this study. The system consists of two sensors and a data acquisition module can process the measured data, which are used for the calculation of rheological properties of polymer melt. The rheological properties of polymer melt discussed in this study include shear rate and viscosity which are investigated with respect to injection speed and melt temperature. The results show that the effect of injection speed on the rheological properties is apparent, especially for high melt temperature and should be considered for precision molding process.

Keywords: Injection molding, melt viscosity, shear rate, monitoring.

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380 Proffering a Brand New Methodology to Resource Discovery in Grid based on Economic Criteria Using Learning Automata

Authors: Ali Sarhadi, Mohammad Reza Meybodi, Ali Yousefi

Abstract:

Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.

Keywords: Resource discovery, learning automata, neural network, economic policy

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379 Assessing Mobile Robotic Telepresence Based On Measures of Social Telepresence

Authors: A. Bagherzadhalimi, E. Di Maria

Abstract:

The feedbacks obtained regarding the sense of presence from pilot users operating a Mobile Robotic presence (MRP) system to visit a simulated museum are reported in this paper. The aim is to investigate how much the perception of system’s usefulness and ease of use is affected by operators’ sense of social telepresence (presence) in the remote location. Therefore, scenarios of visiting a museum are simulated and the user operators are supposed to perform some regular tasks inside the remote environment including interaction with local users, navigation and visiting the artworks. Participants were divided into two groups, those who had previous experience of operation and interaction with a MRP system and those who never had experience. Based on the results, both groups provided different feedbacks. Moreover, there was a significant association between user’s sense of presence and their perception of system usefulness and ease of use.

Keywords: Mobile Robotic Telepresence, Museum, Social Telepresence, Usability test.

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378 Customization of a Real-Time Operating System Scheduler with Aspect-Oriented Programming

Authors: Kazuki Abe, Myungryun Yoo, Takanori Yokoyama

Abstract:

Tasks of an application program of an embedded system are managed by the scheduler of a real-time operating system (RTOS). Most RTOSs adopt just fixed priority scheduling, which is not optimal in all cases. Some applications require earliest deadline first (EDF) scheduling, which is an optimal scheduling algorithm. In order to develop an efficient real-time embedded system, the scheduling algorithm of the RTOS should be selectable. The paper presents a method to customize the scheduler using aspectoriented programming. We define aspects to replace the fixed priority scheduling mechanism of an OSEK OS with an EDF scheduling mechanism. By using the aspects, we can customize the scheduler without modifying the original source code. We have applied the aspects to an OSEK OS and get a customized operating system with EDF scheduling. The evaluation results show that the overhead of aspect-oriented programming is small enough.

Keywords: aspect-oriented programming, embedded system, operating system, real-time system

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377 Operational risks Classification for Information Systems with Service-Oriented Architecture (Including Loss Calculation Example)

Authors: Irina Pyrlina

Abstract:

This article presents the results of a study conducted to identify operational risks for information systems (IS) with service-oriented architecture (SOA). Analysis of current approaches to risk and system error classifications revealed that the system error classes were never used for SOA risk estimation. Additionally system error classes are not normallyexperimentally supported with realenterprise error data. Through the study several categories of various existing error classifications systems are applied and three new error categories with sub-categories are identified. As a part of operational risks a new error classification scheme is proposed for SOA applications. It is based on errors of real information systems which are service providers for application with service-oriented architecture. The proposed classification approach has been used to classify SOA system errors for two different enterprises (oil and gas industry, metal and mining industry). In addition we have conducted a research to identify possible losses from operational risks.

Keywords: Enterprise architecture, Error classification, Oil&Gas and Metal&Mining industries, Operational risks, Serviceoriented architecture

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376 Ontology-based Concept Weighting for Text Documents

Authors: Hmway Hmway Tar, Thi Thi Soe Nyaunt

Abstract:

Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of digesting and generalizing large amounts of information. One of the issues of clustering is to extract proper feature (concept) of a problem domain. The existing clustering technology mainly focuses on term weight calculation. To achieve more accurate document clustering, more informative features including concept weight are important. Feature Selection is important for clustering process because some of the irrelevant or redundant feature may misguide the clustering results. To counteract this issue, the proposed system presents the concept weight for text clustering system developed based on a k-means algorithm in accordance with the principles of ontology so that the important of words of a cluster can be identified by the weight values. To a certain extent, it has resolved the semantic problem in specific areas.

Keywords: Clustering, Concept Weight, Document clustering, Feature Selection, Ontology

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375 Linear Programming Application in Unit Commitment of Wind Farms with Considering Uncertainties

Authors: M. Esmaeeli Shahrakht, A. Kazemi

Abstract:

Due to uncertainty of wind velocity, wind power generators don’t have deterministic output power. Utilizing wind power generation and thermal power plants together create new concerns for operation engineers of power systems. In this paper, a model is presented to implement the uncertainty of load and generated wind power which can be utilized in power system operation planning. Stochastic behavior of parameters is simulated by generating scenarios that can be solved by deterministic method. A mixed-integer linear programming method is used for solving deterministic generation scheduling problem. The proposed approach is applied to a 12-unit test system including 10 thermal units and 2 wind farms. The results show affectivity of piecewise linear model in unit commitment problems. Also using linear programming causes a considerable reduction in calculation times and guarantees convergence to the global optimum. Neglecting the uncertainty of wind velocity causes higher cost assessment of generation scheduling.

Keywords: Load uncertainty, linear programming, scenario generation, unit commitment, wind farm.

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374 Palmprint based Cancelable Biometric Authentication System

Authors: Ying-Han Pang, Andrew Teoh Beng Jin, David Ngo Chek Ling

Abstract:

A cancelable palmprint authentication system proposed in this paper is specifically designed to overcome the limitations of the contemporary biometric authentication system. In this proposed system, Geometric and pseudo Zernike moments are employed as feature extractors to transform palmprint image into a lower dimensional compact feature representation. Before moment computation, wavelet transform is adopted to decompose palmprint image into lower resolution and dimensional frequency subbands. This reduces the computational load of moment calculation drastically. The generated wavelet-moment based feature representation is used to generate cancelable verification key with a set of random data. This private binary key can be canceled and replaced. Besides that, this key also possesses high data capture offset tolerance, with highly correlated bit strings for intra-class population. This property allows a clear separation of the genuine and imposter populations, as well as zero Equal Error Rate achievement, which is hardly gained in the conventional biometric based authentication system.

Keywords: Cancelable biometric authenticator, Discrete- Hashing, Moments, Palmprint.

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373 Analysis of Relation between Unlabeled and Labeled Data to Self-Taught Learning Performance

Authors: Ekachai Phaisangittisagul, Rapeepol Chongprachawat

Abstract:

Obtaining labeled data in supervised learning is often difficult and expensive, and thus the trained learning algorithm tends to be overfitting due to small number of training data. As a result, some researchers have focused on using unlabeled data which may not necessary to follow the same generative distribution as the labeled data to construct a high-level feature for improving performance on supervised learning tasks. In this paper, we investigate the impact of the relationship between unlabeled and labeled data for classification performance. Specifically, we will apply difference unlabeled data which have different degrees of relation to the labeled data for handwritten digit classification task based on MNIST dataset. Our experimental results show that the higher the degree of relation between unlabeled and labeled data, the better the classification performance. Although the unlabeled data that is completely from different generative distribution to the labeled data provides the lowest classification performance, we still achieve high classification performance. This leads to expanding the applicability of the supervised learning algorithms using unsupervised learning.

Keywords: Autoencoder, high-level feature, MNIST dataset, selftaught learning, supervised learning.

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372 Mode III Interlaminar Fracture in Woven Glass/Epoxy Composite Laminates

Authors: Farhad Asgari Mehrabadi, Mohammad Reza Khoshravan

Abstract:

In the present study, fracture behavior of woven fabric-reinforced glass/epoxy composite laminates under mode III crack growth was experimentally investigated and numerically modeled. Two methods were used for the calculation of the strain energy release rate: the experimental compliance calibration (CC) method and the Virtual Crack Closure Technique (VCCT). To achieve this aim ECT (Edge Crack Torsion) was used to evaluate fracture toughness in mode III loading (out of plane-shear) at different crack lengths. Load–displacement and associated energy release rates were obtained for various case of interest. To calculate fracture toughness JIII, two criteria were considered including non-linearity and maximum points in load-displacement curve and it is observed that JIII increases with the crack length increase. Both the experimental compliance method and the virtual crack closure technique proved applicable for the interpretation of the fracture mechanics data of woven glass/epoxy laminates in mode III.

Keywords: Mode III, Fracture, Composite, Crack growth Finite Element.

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371 Development of an ArcGIS Toolbar for Trend Analysis of Climatic Data

Authors: Arnab Bandyopadhyay, Anubhab Pal, Subhajit Debnath

Abstract:

Climate change is a cumulative change in weather patterns over a period of time. Trend analysis using non-parametric Mann-Kendall test may help to determine the existence and magnitude of any statistically significant trend in the climatic data. Another index called Sen slope may be used to quantify the magnitude of such trends. A toolbar extension to ESRI ArcGIS named Arc Trends has been developed in this study for performing the above mentioned tasks. To study the temporal trend of meteorological parameters, 32 years (1971-2002) monthly meteorological data were collected for 133 selected stations over different agro-ecological regions of India. Both the maximum and minimum temperatures were found to be rising. A significant increasing trend in the relative humidity and a consistent significant decreasing trend in the wind speed all over the country were found. However, a general increase in rainfall was not found in recent years.

Keywords: Temporal trend, climate change, ArcGIS, Mann- Kendall test, Sen slope

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370 Vehicle Type Classification with Geometric and Appearance Attributes

Authors: Ghada S. Moussa

Abstract:

With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management.

This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: Appearance attributes, Geometric attributes, Support vector machine, Vehicle classification.

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369 Dynamics of the Moving Ship at Complex and Sudden Impact of External Forces

Authors: Bo Liu, Liangtian Gao, Idrees Qasim

Abstract:

The impact of the storm leads to accidents even in the case of vessels that meet the computed safety criteria for stability. That is why, in order to clarify the causes of the accident and shipwreck, it is necessary to study the dynamics of the ship under the complex sudden impact of external forces. The task is to determine the movement and landing of the ship in the complex and sudden impact of external forces, i.e. when the ship's load changes over a relatively short period of time. For the solution, a technique was used to study the ship's dynamics, which is based on the compilation of a system of differential equations of motion. A coordinate system was adopted for the equation of motion of the hull and the determination of external forces. As a numerical method of integration, the 4th order Runge-Kutta method was chosen. The results of the calculation show that dynamic deviations were lower for high-altitude vessels. The study of the movement of the hull under a difficult situation is performed: receiving of cargo, impact of a flurry of wind and subsequent displacement of the cargo. The risk of overturning and flooding was assessed.

Keywords: Dynamics, statics, roll, trim, dynamic load, tilt, vertical displacement.

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368 Performance Analysis of List Scheduling in Heterogeneous Computing Systems

Authors: Keqin Li

Abstract:

Given a parallel program to be executed on a heterogeneous computing system, the overall execution time of the program is determined by a schedule. In this paper, we analyze the worst-case performance of the list scheduling algorithm for scheduling tasks of a parallel program in a mixed-machine heterogeneous computing system such that the total execution time of the program is minimized. We prove tight lower and upper bounds for the worst-case performance ratio of the list scheduling algorithm. We also examine the average-case performance of the list scheduling algorithm. Our experimental data reveal that the average-case performance of the list scheduling algorithm is much better than the worst-case performance and is very close to optimal, except for large systems with large heterogeneity. Thus, the list scheduling algorithm is very useful in real applications.

Keywords: Average-case performance, list scheduling algorithm, mixed-machine heterogeneous computing system, worst-case performance.

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367 Reliability-Based Ductility Seismic Spectra of Structures with Tilting

Authors: Federico Valenzuela-Beltran, Sonia E. Ruiz, Alfredo Reyes-Salazar, Juan Bojorquez

Abstract:

A reliability-based methodology which uses structural demand hazard curves to consider the increment of the ductility demands of structures with tilting is proposed. The approach considers the effect of two orthogonal components of the ground motions as well as the influence of soil-structure interaction. The approach involves the calculation of ductility demand hazard curves for symmetric systems and, alternatively, for systems with different degrees of asymmetry. To get this objective, demand hazard curves corresponding to different global ductility demands of the systems are calculated. Next, Uniform Exceedance Rate Spectra (UERS) are developed for a specific mean annual rate of exceedance value. Ratios between UERS corresponding to asymmetric and to symmetric systems located in soft soil of the valley of Mexico are obtained. Results indicate that the ductility demands corresponding to tilted structures may be several times higher than those corresponding to symmetric structures, depending on several factors such as tilting angle and vibration period of structure and soil.

Keywords: Asymmetric yielding, tilted structures, seismic performance, structural reliability

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366 Measuring the Comprehensibility of a UML-B Model and a B Model

Authors: Rozilawati Razali, Paul W. Garratt

Abstract:

Software maintenance, which involves making enhancements, modifications and corrections to existing software systems, consumes more than half of developer time. Specification comprehensibility plays an important role in software maintenance as it permits the understanding of the system properties more easily and quickly. The use of formal notation such as B increases a specification-s precision and consistency. However, the notation is regarded as being difficult to comprehend. Semi-formal notation such as the Unified Modelling Language (UML) is perceived as more accessible but it lacks formality. Perhaps by combining both notations could produce a specification that is not only accurate and consistent but also accessible to users. This paper presents an experiment conducted on a model that integrates the use of both UML and B notations, namely UML-B, versus a B model alone. The objective of the experiment was to evaluate the comprehensibility of a UML-B model compared to a traditional B model. The measurement used in the experiment focused on the efficiency in performing the comprehension tasks. The experiment employed a cross-over design and was conducted on forty-one subjects, including undergraduate and masters students. The results show that the notation used in the UML-B model is more comprehensible than the B model.

Keywords: Model comprehensibility, formal and semi-formal notation, empirical assessment.

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365 Urban Big Data: An Experimental Approach to Building-Value Estimation Using Web-Based Data

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: Big data, building-value analysis, machine learning, price prediction.

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364 Comparison of MFCC and Cepstral Coefficients as a Feature Set for PCG Biometric Systems

Authors: Justin Leo Cheang Loong, Khazaimatol S Subari, Muhammad Kamil Abdullah, Nurul Nadia Ahmad, RosliBesar

Abstract:

Heart sound is an acoustic signal and many techniques used nowadays for human recognition tasks borrow speech recognition techniques. One popular choice for feature extraction of accoustic signals is the Mel Frequency Cepstral Coefficients (MFCC) which maps the signal onto a non-linear Mel-Scale that mimics the human hearing. However the Mel-Scale is almost linear in the frequency region of heart sounds and thus should produce similar results with the standard cepstral coefficients (CC). In this paper, MFCC is investigated to see if it produces superior results for PCG based human identification system compared to CC. Results show that the MFCC system is still superior to CC despite linear filter-banks in the lower frequency range, giving up to 95% correct recognition rate for MFCC and 90% for CC. Further experiments show that the high recognition rate is due to the implementation of filter-banks and not from Mel-Scaling.

Keywords: Biometric, Phonocardiogram, Cepstral Coefficients, Mel Frequency

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363 An Optical Flow Based Segmentation Method for Objects Extraction

Authors: C. Lodato, S. Lopes

Abstract:

This paper describes a segmentation algorithm based on the cooperation of an optical flow estimation method with edge detection and region growing procedures. The proposed method has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. The addressed problem consists in extracting whole objects from background for producing images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The first task of the algorithm exploits the cues from motion analysis for moving area detection. Objects and background are then refined using respectively edge detection and region growing procedures. These tasks are iteratively performed until objects and background are completely resolved. The developed method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

Keywords: Motion Detection, Object Extraction, Optical Flow, Segmentation.

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362 Rainfall–Runoff Simulation Using WetSpa Model in Golestan Dam Basin, Iran

Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

Abstract:

Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km2, and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: Watershed simulation, WetSpa, stream flow, flood prediction.

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361 Computer Graphics and Understanding Semiotics in Design

Authors: Manoj Majhi, Debkumar Chakrabaty

Abstract:

The objective of the paper was to understand the use of an important element of design, namely color in a Semiotic system. Semiotics is the study of signs and sign processes, it is often divided into three branches namely (i) Semantics that deals with the relation between signs and the things to which they refer to mean, (ii) Syntactics which addresses the relations among signs in formal structures and (iii) Pragmatics that relates between signs and its effects on they have on the people who use them to create a plan for an object or a system referred to as design. Cubism with its versatility was the key design tool prevalent across the 20th century. In order to analyze the user's understanding of interaction and appreciation of color through the movement of Cubism, an exercise was undertaken in Dept. of Design, IIT Guwahati. This included tasks to design a composition using color and sign process to the theme 'Between the Lines' on a given tessellation where the users relate their work to the world they live in, which in this case was the college campus of IIT Guwahati. The findings demonstrate impact of the key design element color on the principles of visual perception based on image analysis of specific compositions.

Keywords: Color in Semiotics, Cubism and novice designer, visual perception, multimedia and communication.

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360 Predictive Analysis for Big Data: Extension of Classification and Regression Trees Algorithm

Authors: Ameur Abdelkader, Abed Bouarfa Hafida

Abstract:

Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: Predictive analysis, big data, predictive analysis algorithms. CART algorithm.

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