Search results for: User Demand Evaluation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4159

Search results for: User Demand Evaluation

1819 Evaluation of TRIS-DMA-NVP Hydrogels for Making Silicone-Based Contact Lenses

Authors: N. P. D. Tran, H. Q. D. Nguyen, M. C. Yang

Abstract:

In this study, contact lenses were prepared through the polymerization of tris-(trimethyl-silyl-propyl-methacrylate) (TRIS), N,N-dimethylacrylamide (DMA), N-vinylpyrrolidone (NVP), and cross-linked with ethylene glycol dimethylacrylate (EGDMA). The equilibrium water content (EWC), oxygen permeability (Dk), light transmittance, and in vitro cytotoxicity of TRIS-DMA-NVP with various ratios were measured. The results showed that the EWC increased while the Dk decreased with the increase of NVP content. For the sample with 25 wt% NVP, the EWC attained 53% whereas the Dk decreased to 46 barrers. All these lenses exhibited light transmittance over than 95%. In addition, all these lenses exhibited no inhibition to the growth of L292 fibroblasts. Thus, this study showed that TRIS-DMA-NVP can be applicable for making contact lens.

Keywords: DMA, TRIS, NVP, silicone hydrogel, contact lens.

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1818 Adaptive PID Controller based on Reinforcement Learning for Wind Turbine Control

Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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1817 High Level Synthesis of Canny Edge Detection Algorithm on Zynq Platform

Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

Abstract:

Real time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Thus, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Edge detection is one of the basic building blocks of video and image processing applications. It is a common block in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: High Level Synthesis, Canny edge detection, Hardware accelerators, and Computer Vision.

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1816 Real-Time Physics Simulation Packages: An Evaluation Study

Authors: J.Zouhair, D.Ellison

Abstract:

This paper includes a review of three physics simulation packages that can be used to provide researchers with a virtual ground for modeling, implementing and simulating complex models, as well as testing their control methods with less cost and time of development. The inverted pendulum model was used as a test bed for comparing ODE, DANCE and Webots, while Linear State Feedback was used to control its behavior. The packages were compared with respect to model creation, solving systems of differential equation, data storage, setting system variables, control the experiment and ease of use. The purpose of this paper is to give an overview about our experience with these environments and to demonstrate some of the benefits and drawbacks involved in practice for each package.

Keywords: DANCE, Inverted Pendulum, ODE, Simulation Packages, Webots.

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1815 Optimal Maintenance Clustering for Rail Track Components Subject to Possession Capacity Constraints

Authors: Cuong D. Dao, Rob J.I. Basten, Andreas Hartmann

Abstract:

This paper studies the optimal maintenance planning of preventive maintenance and renewal activities for components in a single railway track when the available time for maintenance is limited. The rail-track system consists of several types of components, such as rail, ballast, and switches with different preventive maintenance and renewal intervals. To perform maintenance or renewal on the track, a train free period for maintenance, called a possession, is required. Since a major possession directly affects the regular train schedule, maintenance and renewal activities are clustered as much as possible. In a highly dense and utilized railway network, the possession time on the track is critical since the demand for train operations is very high and a long possession has a severe impact on the regular train schedule. We present an optimization model and investigate the maintenance schedules with and without the possession capacity constraint. In addition, we also integrate the social-economic cost related to the effects of the maintenance time to the variable possession cost into the optimization model. A numerical example is provided to illustrate the model.

Keywords: Rail-track components, maintenance, optimal clustering, possession capacity.

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1814 Production Throughput Modeling under Five Uncertain Variables Using Bayesian Inference

Authors: Amir Azizi, Amir Yazid B. Ali, Loh Wei Ping

Abstract:

Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.

Keywords: Bayesian inference, Uncertainty modeling, Monte Carlo Markov chain, Gibbs sampling, Production throughput

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1813 Performance Assessment of Computational Gridon Weather Indices from HOAPS Data

Authors: Madhuri Bhavsar, Anupam K Singh, Shrikant Pradhan

Abstract:

Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Keywords: Climate model, Computational Grid, GridApplication, Heterogeneous Grid

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1812 Market Segmentation and Conjoint Analysis for Apple Family Design

Authors: Abbas Al-Refaie, Nour Bata

Abstract:

A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.

Keywords: Market segmentation, conjoint analysis, market strategies, optimization.

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1811 LFSR Counter Implementation in CMOS VLSI

Authors: Doshi N. A., Dhobale S. B., Kakade S. R.

Abstract:

As chip manufacturing technology is suddenly on the threshold of major evaluation, which shrinks chip in size and performance, LFSR (Linear Feedback Shift Register) is implemented in layout level which develops the low power consumption chip, using recent CMOS, sub-micrometer layout tools. Thus LFSR counter can be a new trend setter in cryptography and is also beneficial as compared to GRAY & BINARY counter and variety of other applications. This paper compares 3 architectures in terms of the hardware implementation, CMOS layout and power consumption, using Microwind CMOS layout tool. Thus it provides solution to a low power architecture implementation of LFSR in CMOS VLSI.

Keywords: Chip technology, Layout level, LFSR, Pass transistor

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1810 Eclectic Rule-Extraction from Support Vector Machines

Authors: Nahla Barakat, Joachim Diederich

Abstract:

Support vector machines (SVMs) have shown superior performance compared to other machine learning techniques, especially in classification problems. Yet one limitation of SVMs is the lack of an explanation capability which is crucial in some applications, e.g. in the medical and security domains. In this paper, a novel approach for eclectic rule-extraction from support vector machines is presented. This approach utilizes the knowledge acquired by the SVM and represented in its support vectors as well as the parameters associated with them. The approach includes three stages; training, propositional rule-extraction and rule quality evaluation. Results from four different experiments have demonstrated the value of the approach for extracting comprehensible rules of high accuracy and fidelity.

Keywords: Data mining, hybrid rule-extraction algorithms, medical diagnosis, SVMs

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1809 Optimizing Feature Selection for Recognizing Handwritten Arabic Characters

Authors: Mohammed Z. Khedher, Gheith A. Abandah, Ahmed M. Al-Khawaldeh

Abstract:

Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features.

Keywords: Arabic handwritten characters, Feature extraction, Off-line recognition, Optical character recognition.

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1808 Satisfaction on English Language Learning with Online System

Authors: Suwaree Yordchim, Toby J. Gibbs

Abstract:

The objective is to study the satisfaction on English with an online learning. Online learning system mainly consists of English lessons, exercises, tests, web boards, and supplementary lessons for language practice. The sample groups are 80 Thai students studying English for Business Communication, majoring in Hotel and Lodging Management. The data are analyzed by mean, standard deviation (S.D.) value from the questionnaires. The results were found that the most average of satisfaction on academic aspects are technological searching tool through E-learning system that support the students’ learning (4.51), knowledge evaluation on pre-post learning and teaching (4.45), and change for project selections according to their interest, subject contents including practice in the real situations (4.45), respectively.

Keywords: English Learning, Online System, Satisfaction.

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1807 Nearly Zero-Energy Regulation and Buildings Built with Prefabricated Technology: The Case of Hungary

Authors: András Horkai, Attila Talamon, Viktória Sugár

Abstract:

There is an urgent need nowadays to reduce energy demand and the current level of greenhouse gas emission and use renewable energy sources increase in energy efficiency. On the other hand, the European Union (EU) countries are largely dependent on energy imports and are vulnerable to disruption in energy supply, which may, in turn, threaten the functioning of their current economic structure. Residential buildings represent a significant part of the energy consumption of the building stock. Only a small part of the building stock is exchanged every year, thus it is essential to increase the energy efficiency of the existing buildings. Present paper focuses on the buildings built with industrialized technology only, and their opportunities in the boundaries of nearly zero-energy regulation. Current paper shows the emergence of panel construction method, and past and present of the ‘panel’ problem in Hungary with a short outlook to Europe. The study shows as well as the possibilities for meeting the nearly zero and cost optimized requirements for residential buildings by analyzing the renovation scenarios of an existing residential typology.

Keywords: Budapest, energy consumption, industrialized technology, nearly zero-energy buildings.

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1806 Improving Worm Detection with Artificial Neural Networks through Feature Selection and Temporal Analysis Techniques

Authors: Dima Stopel, Zvi Boger, Robert Moskovitch, Yuval Shahar, Yuval Elovici

Abstract:

Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Keywords: Artificial Neural Networks, Feature Selection, Temporal Analysis, Worm Detection.

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1805 Analysis of Creative City Indicators in Isfahan City, Iran

Authors: Reza Mokhtari Malek Abadi, Mohsen Saghaei, Fatima Iman

Abstract:

This paper investigates the indices of a creative city in Isfahan. Its main aim is to evaluate quantitative status of the creative city indices in Isfahan city, analyze the dispersion and distribution of these indices in Isfahan city. Concerning these, this study tries to analyze the creative city indices in fifteen area of Isfahan through secondary data, questionnaire, TOPSIS model, Shannon entropy and SPSS. Based on this, the fifteen areas of Isfahan city have been ranked with 12 factors of creative city indices. The results of studies show that fifteen areas of Isfahan city are not equally benefiting from creative indices and there is much difference between the areas of Isfahan city.

Keywords: Grading, creative city, creative city evaluation indicators, regional planning model.

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1804 Accounting Policies in Polish and International Legal Regulations

Authors: Piotr Prewysz Kwinto, Grażyna Voss

Abstract:

Accounting policies are a set of solutions compliant with legal regulations that an entity selects and adopts, and which guarantee a proper quality of financial statements. Those solutions may differ depending on whether the entity adopts national or international accounting standards. The aim of this article is to present accounting principles (policies) in Polish and international legal regulations and their adoption in selected Polish companies listed on the Warsaw Stock Exchange. The research method adopted in this work is the analysis and evaluation of legal conditions in Polish companies.

Keywords: Accounting policies, International Financial Reporting Standards, Financial statement, Method of measuring.

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1803 Structural Safety Evaluation of Zip-Line Due to Dynamic Impact Load

Authors: Bu Seog Ju, Jae Sang Kim, Woo Young Jung

Abstract:

In recent year, with recent increase of interest towards leisure sports, increased number of Zip-Line or Zip-Wire facilities has built. Many researches have been actively conducted on the emphasis of the cable and the wire at the bridge. However, very limited researches have been conducted on the safety of the Zip-Line structure. In fact, fall accidents from Zip-Line have been reported frequently. Therefore, in this study, the structural safety of Zip-Line under dynamic impact loading condition were evaluated on the previously installed steel cable for leisure (Zip-Line), using 3-dimensional nonlinear Finite Element (FE) model. The result from current study would assist assurance of systematic stability of Zip-Line.

Keywords: Zip-Line, Wire, Cable, 3D FE Model, Safety.

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1802 Fenton’s Oxidation as Post-Treatment of a Mature Municipal Landfill Leachate

Authors: Susana Cortez, Pilar Teixeira, Rosário Oliveira, Manuel Mota

Abstract:

Mature landfill leachates contain some macromolecular organic substances that are resistant to biological degradation. Recently, Fenton-s oxidation has been investigated for chemical treatment or pre-treatment of mature landfill leachates. The aim of this study was to reduce the recalcitrant organic load still remaining after the complete treatment of a mature landfill leachate by Fenton-s oxidation post-treatment. The effect of various parameters such as H2O2 to Fe2+ molar ratio, dosage of Fe2+ reagent, initial pH, reaction time and initial chemical oxygen demand (COD) strength, that have an important role on the oxidation, was analysed. A molar ratio H2O2/Fe2+ = 3, a Fe2+ dosage of 4 mmol·L-1, pH 3, and a reaction time of 40 min were found to achieve better oxidation performances. At these favorable conditions, COD removal efficiency was 60.9% and 31.1% for initial COD of 93 and 743 mg·L-1 respectively (diluted and non diluted leachate). Fenton-s oxidation also presented good results for color removal. In spite of being extremely difficult to treat this leachate, the above results seem rather encouraging on the application of Fenton-s oxidation.

Keywords: Fenton's oxidation, mature landfill leachate, recalcitrant organic matter.

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1801 Hybrid Neuro Fuzzy Approach for Automatic Generation Control of Two -Area Interconnected Power System

Authors: Gayadhar Panda, Sidhartha Panda, C. Ardil

Abstract:

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

Keywords: Automatic Generation Control (AGC), Dynamic Model, Two-area Power System, Fuzzy Logic Controller, Neural Network, Hybrid Neuro-Fuzzy(HNF).

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1800 Confronting the Uncertainty of Systemic Innovation in Public Welfare Services

Authors: Harri Jalonen

Abstract:

Faced with social and health system capacity constraints and rising and changing demand for welfare services, governments and welfare providers are increasingly relying on innovation to help support and enhance services. However, the evidence reported by several studies indicates that the realization of that potential is not an easy task. Innovations can be deemed inherently complex to implement and operate, because many of them involve a combination of technological and organizational renewal within an environment featuring a diversity of stakeholders. Many public welfare service innovations are markedly systemic in their nature, which means that they emerge from, and must address, the complex interplay between political, administrative, technological, institutional and legal issues. This paper suggests that stakeholders dealing with systemic innovation in welfare services must deal with ambiguous and incomplete information in circumstances of uncertainty. Employing a literature review methodology and case study, this paper identifies, categorizes and discusses different aspects of the uncertainty of systemic innovation in public welfare services, and argues that uncertainty can be classified into eight categories: technological uncertainty, market uncertainty, regulatory/institutional uncertainty, social/political uncertainty, acceptance/legitimacy uncertainty, managerial uncertainty, timing uncertainty and consequence uncertainty.

Keywords: Systemic innovation, uncertainty, welfare services

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1799 The Study of Fabricating the Field Emission Lamps with Carbon nano-Materials

Authors: K. J. Chung, C.C.Chiang, Y.M. Liu, N. W. Pu, M. D. Ger

Abstract:

Fabrication and efficiency enhancement of non-mercury, high efficiency and green field emission lamps using carbon nano-materials such as carbon nanotubes as cathode field emitters was studied. Phosphor was coated on the ITO glass or metal substrates as the anode. The luminescence efficiency enhancement was carried out by upgrading the uniform of the emitters, improving electron and thermal conductivity of the phosphor and the optimization of the design of different cathode/anode configurations. After evaluation of the aforementioned parameters, the luminescence efficiency of the field emission lamps was raised.

Keywords: Field emission lamps, carbon nano-materials, luminescence efficiency

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1798 Hand Gesture Interpretation Using Sensing Glove Integrated with Machine Learning Algorithms

Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

Abstract:

In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove.

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1797 Spatial Services in Cloud Environment

Authors: Sašo Pečnik, Borut Žalik

Abstract:

Cloud Computing is an approach that provides computation and storage services on-demand to clients over the network, independent of device and location. In the last few years, cloud computing became a trend in information technology with many companies that transfer their business processes and applications in the cloud. Cloud computing with service oriented architecture has contributed to rapid development of Geographic Information Systems. Open Geospatial Consortium with its standards provides the interfaces for hosted spatial data and GIS functionality to integrated GIS applications. Furthermore, with the enormous processing power, clouds provide efficient environment for data intensive applications that can be performed efficiently, with higher precision, and greater reliability. This paper presents our work on the geospatial data services within the cloud computing environment and its technology. A cloud computing environment with the strengths and weaknesses of the geographic information system will be introduced. The OGC standards that solve our application interoperability are highlighted. Finally, we outline our system architecture with utilities for requesting and invoking our developed data intensive applications as a web service.

Keywords: Cloud Computing, Geographic Information System, Open Geospatial Consortium, Interoperability, Spatial data, Web- Services.

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1796 An Efficient Biometric Cryptosystem using Autocorrelators

Authors: R. Bremananth, A. Chitra

Abstract:

Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

Keywords: Autocorrelators, biometrics cryptography, irispatterns, wavelets.

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1795 A Domain Specific Modeling Language Semantic Model for Artefact Orientation

Authors: Bunakiye R. Japheth, Ogude U. Cyril

Abstract:

Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: Control process, metrics of engineering, structured abstraction, semantic model.

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1794 Extension of the Client-Centric Approach under Small Buffer Space

Authors: Hsiang-Fu Yu, Yu-Chan Hsu, Chun Fang, Hao-Yun Yang

Abstract:

Periodic broadcast is a cost-effective solution for large-scale distribution of popular videos because this approach guarantees constant worst service latency, regardless of the number of video requests. An essential periodic broadcast method is the client-centric approach (CCA), which allows clients to use smaller receiving bandwidth to download broadcast data. An enhanced version, namely CCA++, was proposed to yield a shorter waiting time. This work further improves CCA++ in reducing client buffer requirements. The new scheme decreases the buffer requirements by as much as 52% when compared to CCA++. This study also provides an analytical evaluation to demonstrate the performance advantage, as compared with particular schemes.

Keywords: Periodic broadcast, client-centric approach, buffer space, multimedia communications.

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1793 Expectation-Confirmation Model of Information System Continuance: A Meta-Analysis

Authors: Hui-Min Lai, Chin-Pin Chen, Yung-Fu Chang

Abstract:

The expectation-confirmation model (ECM) is one of the most widely used models for evaluating information system continuance, and this model has been extended to other study backgrounds, or expanded with other theoretical perspectives. However, combining ECM with other theories or investigating the background problem may produce some disparities, thus generating inaccurate conclusions. Habit is considered to be an important factor that influences the user’s continuance behavior. This paper thus critically examines seven pairs of relationships from the original ECM and the habit variable. A meta-analysis was used to tackle the development of ECM research over the last 10 years from a range of journals and conference papers published in 2005–2014. Forty-six journal articles and 19 conference papers were selected for analysis. The results confirm our prediction that a high effect size for the seven pairs of relationships was obtained (ranging from r=0.386 to r=0.588). Furthermore, a meta-analytic structural equation modeling was performed to simultaneously test all relationships. The results show that habit had a significant positive effect on continuance intention at p<=0.05 and that the six other pairs of relationships were significant at p<0.10. Based on the findings, we refined our original research model and an alternative model was proposed for understanding and predicting information system continuance. Some theoretical implications are also discussed.

Keywords: Expectation-confirmation theory, expectation- confirmation model, meta-analysis, meta-analytic structural equation modeling.

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1792 An Expert System Designed to Be Used with MOEAs for Efficient Portfolio Selection

Authors: K. Metaxiotis, K. Liagkouras

Abstract:

This study presents an Expert System specially designed to be used with Multiobjective Evolutionary Algorithms (MOEAs) for the solution of the portfolio selection problem. The validation of the proposed hybrid System is done by using data sets from Hang Seng 31 in Hong Kong, DAX 100 in Germany and FTSE 100 in UK. The performance of the proposed system is assessed in comparison with the Non-dominated Sorting Genetic Algorithm II (NSGAII). The evaluation of the performance is based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it. The results show that the proposed hybrid system is efficient for the solution of this kind of problems.

Keywords: Expert Systems, Multiobjective optimization, Evolutionary Algorithms, Portfolio Selection.

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1791 Prediction for the Pressure Drop of Gas-Liquid Cylindrical Cyclone in Sub-Sea Production System

Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

Abstract:

With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: Dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation; pressure drop.

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1790 Highlighting of the Factors and Policies Affecting CO2 Emissions Level in Malaysian Transportation Sector

Authors: M. S. Indati, H. A. Bekhet

Abstract:

Global CO2 emission and increasing fuel consumption to meet energy demand has become a threat in recent decades. Effort to reduce the CO2 emission is now a matter of priority in most countries of the world including Malaysia. Transportation has been identified as the most intensive sector of carbon-based fuels and achievement of the voluntary target to meet 40% carbon intensity reduction set at the 15th Conference of the Parties (COP15) means that the emission from the transport sector must be reduced accordingly. This posed a great challenge to Malaysia and effort has to be made to embrace suitable and appropriate energy policy for sustainable energy and emission reduction of this sector. The focus of this paper is to analyze the trends of Malaysia’s energy consumption and emission of four different transport sub-sectors (road, rail, aviation and maritime). Underlying factors influencing the growth of energy consumption and emission trends are discussed. Besides, technology status towards energy efficiency in transportation sub-sectors is presented. By reviewing the existing policies and trends of energy used, the paper highlights prospective policy options towards achieving emission reduction in the transportation sector.

Keywords: CO2 Emission, Energy policy, Fuel consumption, Transportation sector, Malaysia.

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