Search results for: decision uncertainty distance (DUD)

Authors: Y. A. Mahmood, A. Ahmadi, R. Karim, U. Kumar, A.K. Verma, N. Fransson

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The purpose of this paper isunavailability of the two main types of conveSwedish traction power supply (TPS) system, i.e.static converter. The number of outages and the ouused to analyze and compare the unavailability oconverters. The mean cumulative function (MCF)analyze the number of outages and the unavailabthe forced outage rate (FOR) concept has been uoutage rates. The study shows that the outagesfailure occur at a constant rate by calendar timconverter stations, while very few stations havedecreasing rate. It has also been found that the stata higher number of outages and a higher outage ratcompared to the rotary converter types. The resultsthat combining the number of outages and the fgives a better view of the converters performasupport for the maintenance decision. In fact, usingdoes not reflect reality. Comparing these two indein identifying the areas where extra resources are maintenance planning and where improvementsoutage in the TPS system.KeywordsFrequency Converter, Forced OuCumulative Function, Traction Power Supply, ESystems.

Keywords: Frequency Converter, Forced Outage Rate, Mean Cumulative Function, Traction Power Supply, Electrified Railway Systems.

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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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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Authors: Claudio D'Alonzo

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According to recent tendencies, progress on resource efficiency is possible and it will lead to economic, environmental, and social benefits. The passage to a circular economy system, in which all the materials and energy will maintain their value for as long as possible, waste is reduced and only a few resources are used, is one of the most relevant parts of the European Union's environmental policy to develop a sustainable, competitive and low-carbon economy. The concept of circular economy is to be found in Decision 1386/2013/EU of the European Parliament and of the Council on a General Union Environment Action Programme to 2020 named “Living well, within the limits of our planet”. To modernise waste management systems in the Union and to consolidate the European model as one of the most effective in the world, a revised waste legislative framework entered into force in July 2018. Regarding the Italian legislation, the laws to be modified are the Legislative Decree 3 April 2006, n. 152 and the laws ruling waste management, end-of-waste, by-products and, the regulatory principles regarding circular economy. European rules on end-of-waste are not fully harmonised and so there are legal challenges. The target to be achieved is full consistency between the laws implementing waste and chemicals policies. Only in this way, materials will be safe, fit-for-purpose and designed for durability; additionally, they will have a low environmental impact.

Keywords: Circular economy, end-of-waste, legislation, secondary raw materials.

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Authors: Lokesh Tharani, R.P.Yadav

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This paper presents the results related to the interference reduction technique in multistage multiuser detector for asynchronous DS-CDMA system. To meet the real-time requirements for asynchronous multiuser detection, a bit streaming, cascade architecture is used. An asynchronous multiuser detection involves block-based computations and matrix inversions. The paper covers iterative-based suboptimal schemes that have been studied to decrease the computational complexity, eliminate the need for matrix inversions, decreases the execution time, reduces the memory requirements and uses joint estimation and detection process that gives better performance than the independent parameter estimation method. The stages of the iteration use cascaded and bits processed in a streaming fashion. The simulation has been carried out for asynchronous DS-CDMA system by varying one parameter, i.e., number of users. The simulation result exhibits that system gives optimum bit error rate (BER) at 3rd stage for 15-users.

Keywords: Multi-user detection (MUD), multiple accessinterference (MAI), near-far effect, decision feedback detector, successive interference cancellation detector (SIC) and parallelinterference cancellation (PIC) detector.

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Authors: Khelood A. Mkalaf, Peter Gibson, John Flanagan

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This study investigates the relationship between the reliability of critical medical equipment (CME) and the effectiveness of CME maintenance management strategies in relation to patient outcomes in 84 public hospitals of a top 20 OECD country. The work has examined the effectiveness of CME maintenance management strategies used by the public hospital system of a large state run health organization. The conceptual framework was designed to examine the significance of the relationship between six variables: (1) types of maintenance management strategies, (2) maintenance services, (3) maintenance practice, (4) medical equipment reliability, (5) maintenance costs and (6) patient outcomes. The results provide interesting insights into the effectiveness of the maintenance strategies used. For example, there appears to be about a 1 in 10 000 probability of failure of anesthesia equipment, but these seem to be confined to specific maintenance situations. There are also some findings in relation to outsourcing of maintenance. For each of the variables listed, results are reported in relation to the various types of maintenance strategies and services. Decision-makers may use these results to evaluate more effective maintenance strategies for their CME and generate more effective patient outcomes.

Keywords: Critical medical equipment, maintenance strategy, patient outcomes, reliability.

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Authors: Xin Zhao, Yin-fan Zhu, Wei-ping Wang, Qun Li

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The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the inter- influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.

Keywords: Time-sliced influence diagrams, discrete event systems, dynamic-stochastic influence diagrams, modeling formalism, simulation algorithm.

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Authors: S. N. S. Thein, H. L. Yang, Z. B. Liu

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There are many modes of transport. Among them, maritime transport is a major transportation mode of international trade. In the Republic of the Union of Myanmar (Burma), water transportation served as one of the most important modes of transport for country's exports and imports. Getting the accurate information and data-gathering activity are the most important aspects for any study field. Therefore, in this research, a historical review of the development of ports in Myanmar and how they have changed had been carried out. All the relevant literature and documents have also been reviewed, studied, and organized. The sources of collected data are from reports, journals, internet, as well as from the publications of authorized organizations and international associations. To get better understanding about real situation of maritime transport and logistics in Myanmar; current condition of existing ports, expansion and on-going projects, and future port development plans are described successively. Hence, the main purpose of this study is to build up a comprehensive picture of maritime transport and logistics, in addition to border trade within ASEAN and Myanmar. It will help for academic researchers, decision makers, and stakeholders for national planning as well as for the local and foreign investors to recognize current situation of maritime transport and logistics in Myanmar.

Keywords: ASEAN, border trade, logistics, maritime transport, ports of Myanmar.

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Authors: Raphael de Oliveira Garcia, Samuel Rocha de Oliveira

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We have developed a new computer program in Fortran 90, in order to obtain numerical solutions of a system of Relativistic Magnetohydrodynamics partial differential equations with predetermined gravitation (GRMHD), capable of simulating the formation of relativistic jets from the accretion disk of matter up to his ejection. Initially we carried out a study on numerical methods of unidimensional Finite Volume, namely Lax-Friedrichs, Lax-Wendroff, Nessyahu-Tadmor method and Godunov methods dependent on Riemann problems, applied to equations Euler in order to verify their main features and make comparisons among those methods. It was then implemented the method of Finite Volume Centered of Nessyahu-Tadmor, a numerical schemes that has a formulation free and without dimensional separation of Riemann problem solvers, even in two or more spatial dimensions, at this point, already applied in equations GRMHD. Finally, the Nessyahu-Tadmor method was possible to obtain stable numerical solutions - without spurious oscillations or excessive dissipation - from the magnetized accretion disk process in rotation with respect to a central black hole (BH) Schwarzschild and immersed in a magnetosphere, for the ejection of matter in the form of jet over a distance of fourteen times the radius of the BH, a record in terms of astrophysical simulation of this kind. Also in our simulations, we managed to get substructures jets. A great advantage obtained was that, with the our code, we got simulate GRMHD equations in a simple personal computer.

Keywords: Finite Volume Methods, Central Schemes, Fortran 90, Relativistic Astrophysics, Jet.

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Authors: Anca E. Gurzau, Alexandru Coman, Eugen S. Gurzau, Marinela Penes, Daniela Dumitrescu, DorinMarchean, Ioan Chera

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The environment pollution with pesticides and heavy metals is a recognized problem nowadays, with extension to the global scale the tendency of amplification. Even with all the progress in the environmental field, both in the emphasize of the effect of the pollutants upon health, the linked studies environment-health are insufficient, not only in Romania but all over the world also. We aim to describe the particular situation in Romania regarding the uncontrolled use of pesticides, to identify and evaluate the risk zones for health and the environment in Romania, with the final goal of designing adequate programs for reduction and control of the risk sources. An exploratory study was conducted to determine the magnitude of the pesticide use problem in a population living in Saliste, a rural setting in Transylvania, Romania. The significant stakeholders in Saliste region were interviewed and a sample from the population living in Saliste area was selected to fill in a designed questionnaire. All the selected participants declared that they used pesticides in their activities for more than one purpose. They declared they annually applied pesticides for a period of time between 11 and 30 years, from 5 to 9 days per year on average, mainly on crops situated at some distance from the houses but high risk behavior was identified as the volunteers declared the use of pesticides in the backyard gardens, near their homes, where children were playing. The pesticide applicators did not have the necessary knowledge about safety and exposure. The health data must be correlated with exposure biomarkers in attempt to identify the possible health effects of the pesticides exposure. Future plans include educational campaigns to raise the awareness of the population on the danger of uncontrolled use of pesticides.

Keywords: Pesticides, health effects, Romania, Saliste.

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Authors: Tanya N. Beran, Michelle A. Drefs, Ghazwan Altabbaa, Nouf Al Harbi, Noof Al Baz, Elizabeth Oddone Paolucci

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Although interprofessional practice is a collaborative approach for problem solving among health professionals, its implementation can present challenges to its team members. In particular, they may feel pressured to agree with or conform to other members who share information that is contrary to their own understanding. Obtaining evidence of this phenomenon is challenging, as team members may underreport their conformity behaviors due to reasons such as social desirability. In this paper, a series of studies are reviewed in which several approaches to assessing conformity in the health care professions are tested. Simulations, questionnaires, and behavior checklists can be used to measure conformity behaviors. Insights from these studies show that a significant proportion of people conform either in the presence or absence of others, express a variety of verbal and nonverbal behaviors when considering whether to conform to others, may shift between conforming and moments later not conforming (and vice versa), and may not accurately report whether they conformed. A method of measuring conformity using the implicit bias test is also discussed. People at all levels in the healthcare system are encouraged to develop both formal and informal strategies to manage the conformity pressures that people face.

Keywords: Conformity, decision-making, interprofessional teams, medical simulation.

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Authors: Jung-Ho Moon, Tae Kwon Ha

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This paper presents a car parking monitoring system using wireless sensor networks. Multiple sensor nodes and a sink node, a gateway, and a server constitute a wireless network for monitoring a parking lot. Each of the sensor nodes is equipped with a 3-axis AMR sensor and deployed in the center of a parking space. Each sensor node reads its sensor values periodically and transmits the data to the sink node if the current and immediate past sensor values show a difference exceeding a threshold value. The sensor nodes and sink node use the 448 MHz band for wireless communication. Since RF transmission only occurs when sensor values show abrupt changes, the number of RF transmission operations is reduced and battery power can be conserved. The data from the sensor nodes reach the server via the sink node and gateway. The server determines which parking spaces are taken by cars based upon the received sensor data and reference values. The reference values are average sensor values measured by each sensor node when the corresponding parking spot is not occupied by a vehicle. Because the decision making is done by the server, the computational burden of the sensor node is relieved, which helps reduce the duty cycle of the sensor node.

Keywords: Car parking monitoring, magnetometer, sensor node, wireless sensor network.

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Authors: Chen Chou, Feng-Tyan Lin

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Big Data has been attracted a lot of attentions in many fields for analyzing research issues based on a large number of maternal data. Electronic Toll Collection (ETC) is one of Intelligent Transportation System (ITS) applications in Taiwan, used to record starting point, end point, distance and travel time of vehicle on the national freeway. This study, taking advantage of ETC big data, combined with urban planning theory, attempts to explore various phenomena of inter-city transportation activities. ETC, one of government's open data, is numerous, complete and quick-update. One may recall that living area has been delimited with location, population, area and subjective consciousness. However, these factors cannot appropriately reflect what people’s movement path is in daily life. In this study, the concept of "Living Area" is replaced by "Influence Range" to show dynamic and variation with time and purposes of activities. This study uses data mining with Python and Excel, and visualizes the number of trips with GIS to explore influence range of Tainan city and the purpose of trips, and discuss living area delimited in current. It dialogues between the concepts of "Central Place Theory" and "Living Area", presents the new point of view, integrates the application of big data, urban planning and transportation. The finding will be valuable for resource allocation and land apportionment of spatial planning.

Keywords: Big Data, ITS, influence range, living area, central place theory, visualization.

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Authors: Cai Guoqiang, Jia Limin, Zhou Liming, Liang yu, Li xi

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This paper analysis the integrated use of safety monitoring with the domestic and international latest research on rail safety protection system, and focus on the implementation of an organic whole system, with the monitoring and early warning, risk assessment, predictive control and emergency rescue system. The system framework, contents and system structure of Security system is proposed completely. It-s pointed out that the Security system is a negative feedback system composed of by safety monitoring and warning system, risk assessment and emergency rescue system. Safety monitoring and warning system focus on the monitoring target monitoring, early warning, tracking, integration of decision-making, for objective and subjective risks factors. Risk assessment system analysis the occurrence of a major Security risk mechanism, determines the standard of the future short, medium and long term safety conditions, and give prop for development of safety indicators, accident analysis and safety standards. Emergency rescue system is with the goal of rapid and effective rescue work for accident, to minimize casualties and property losses.

Keywords: rail safety protection, monitoring and early warning, risk assessment, emergency rescue.

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Authors: Aikaterini Fountoulaki, Nikos Karacapilidis, Manolis Manatakis

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This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Artificial Neural Networks (ANNs) to aid decision making about the acceptance or rejection of an inspected sample. For any type of inspection, ANNs are trained by data from corresponding tables of a standard-s sampling plan schemes. Once trained, ANNs can give closed-form solutions for any acceptance quality level and sample size, thus leading to an automation of the reading of the sampling plan tables, without any need of compromise with the values of the specific standard chosen each time. The proposed methodology provides enough flexibility to quality control engineers during the inspection of their samples, allowing the consideration of specific needs, while it also reduces the time and the cost required for these inspections. Its applicability and advantages are demonstrated through two numerical examples.

Keywords: Acceptance Sampling, Neural Networks, Statistical Quality Control.

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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Authors: K. Westmoreland Bowers, Matthew W. Ragas, Jeffrey C. Neely

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The purpose of this study was to assess the value of Second Life among post-secondary instructors with experience using Second Life as an educational tool. Using Everett Rogers-s diffusion of innovations theory, survey respondents (N = 162), were divided into three adopter categories: innovators, early adopters and the early majority. Respondents were from 15 countries and 25 academic disciplines, indicating the considerable potential this innovation has to be adopted across many different borders and in many areas of academe. Nearly 94% of respondents said they plan to use Second Life again as an educational tool. However, no significant differences were found in instructors- levels of satisfaction with Second Life as an educational tool or their perceived effect on student learning across adopter categories. On the other hand, instructors who conducted class fully in Second Life were significantly more satisfied than those who used Second Life as only a small supplement to a real-world class. Overall, personal interest factors, rather than interpersonal communication factors, most influenced respondents- decision to adopt Second Life as an educational tool. In light of these findings, theoretical implications are discussed and practical suggestions are provided.

Keywords: Second Life, Virtual Worlds, Educational Technology, Diffusion of Innovations

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Authors: Mohd Iskandar Illyas Tan, Raziah Noor Razali, Zuhra Junaida Husny

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The purpose of this study is i) to investigate the driving factors and barriers of the adoption of Information and Communication Technology (ICT) in Halal logistic and ii) to develop an ICT adoption framework for Halal logistic service provider. The Halal LSPs selected for the study currently used ICT service platforms, such as accounting and management system for Halal logistic business. The study categorizes the factors influencing the adoption decision and process by LSPs into four groups: technology related factors, organizational and environmental factors, Halal assurance related factors, and government related factors. The major contribution in this study is the discovery that technology related factors (ICT compatibility with Halal requirement) and Halal assurance related factors are the most crucial factors among the Halal LSPs applying ICT for Halal control in transportation-s operation. Among the government related factors, ICT requirement for monitoring Halal included in Halal Logistic Standard on Transportation (MS2400:2010) are the most influencing factors in the adoption of ICT with the support of the government. In addition, the government related factors are very important in the reducing the main barriers and the creation of the atmosphere of ICT adoption in Halal LSP sector.

Keywords: Information and communication technology (ICT), Halal logistic, Halal transportation, Technology adoption

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

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During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: Cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation.

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Authors: Raghad Jawad Ahmed

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Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Keywords: Color image segmentation, Genetic algorithm, Markov random field, Scale space filter.

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Authors: Muhamad Abduh, Jarita Duasa, Mohd. Azmi Omar

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Unlike its conventional counterpart, Islamic principles forbid Islamic banks to take any interest-related income and thus makes deposits from depositors as an important source of fund for its operational and financing. Consequently, the risk of deposit withdrawal by depositors is an important aspect that should be wellmanaged in Islamic banking. This paper aims to investigate factors that influence depositors- withdrawal behavior in Islamic banks, particularly in Malaysia, using the framework of theory of reasoned action. A total of 368 respondents from Klang valley are involved in the analysis. The paper finds that all the constructs variable i.e. normative beliefs, subjective norms, behavioral beliefs, and attitude towards behavior are perceived to be distinct by the respondents. In addition, the structural equation model is able to verify the structural relationships between subjective norms, attitude towards behavior and behavioral intention. Subjective norms gives more influence to depositors- decision on deposit withdrawal compared to attitude towards behavior.

Keywords: Islamic bank, structural equation model, theory of reasoned action, withdrawal behavior

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Authors: S. K. Satpathy, S. Panda, K. K. Nagwanshi, S. K. Nayak, C. Ardil

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Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.

Keywords: Filtering, Decision Based Algorithm, noise, imagerestoration.

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Authors: Satyanadh Gundimada, Vijayan K Asari

Abstract:

A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.

Keywords: Discriminant analysis, intra-class probability distribution, principal component analysis, phase congruency.

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Authors: Masoud Mahdavi, Mojtaba Farzaneh Moghadam

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The seismic forces caused by the waves created in the depths of the earth during the earthquake hit the structure and cause the building to vibrate. Creating large seismic forces will cause low-strength sections in the structure to suffer extensive surface damage. The use of new steel shear walls in steel structures has caused the strength of the building and its main members (columns) to increase due to the reduction and depreciation of seismic forces during earthquakes. In the present study, an attempt was made to evaluate a type of steel shear wall that has regular holes in the inner sheet by modeling the finite element model with Abacus software. The shear wall of the steel plate, measuring 6000 × 3000 mm (one floor) and 3 mm thickness, was modeled with four different pores with a cross-sectional area. The shear wall was dynamically subjected to a time history of 5 seconds by three accelerators, El Centro, Imperial Valley and Kobe. The results showed that increasing the distance between the geometric center of the hole and the geometric center of the inner plate in the steel shear wall (increasing the R_CS index) caused the total maximum acceleration to be transferred from the perimeter of the hole to horizontal and vertical beams. The results also show that there is no direct relationship between R_CS index and total acceleration in steel shear wall and R_CS index is separate from the peak ground acceleration value of earthquake.

Keywords: Hollow Steel plate shear wall, time history analysis, finite element method, Abaqus Software.

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Authors: Mohamed Haffar, Lombe Ngome Enongene, Mohammed Hamdan, Gbolahan Gbadamosi

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Despite the considerable body of literature investigating the influence of National Culture (NC) dimensions on consumer behaviour, there is a lack of studies comparing the influence of NC in Africa with Western European countries. This study is intended to fill the vacuum in knowledge by exploring how NC affects consumer buyer behavior in Nigeria and the United Kingdom. The primary data were collected through in depth, semi-structured interviews conducted with three groups of individuals: British students, Nigerian students in the United Kingdom, and Nigerian-based students. This approach and new frontier to analyze culture and consumer behaviour could help understand residual cultural threads of people (that are ingrained in their being) irrespective of exposure to other cultures. The findings of this study show that Nigerian and British consumers differ remarkably in cultural orientations such as symbols, values and psychological standpoints. This ultimately affects the choices made at every stage of the decision building process, and proves beneficial for international retail marketing.

Keywords: National culture, consumer behaviour, international business, Nigeria, UK.

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Authors: Saba Shams Bidhendi, Steven Goh, Andrew Wandel

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The implementation of lean manufacturing initiatives has produced significant impacts in improving operational performance and reducing manufacturing wastes in the production process. However, selecting an appropriate set of lean strategies is critical to avoid misapplication of the lean manufacturing techniques and consequential increase in non-value-adding activities. To the author’s best knowledge, there is currently no methodology to select lean strategies that considers their impacts on manufacturing wastes and performance metrics simultaneously. In this research, a multi-objective methodology is proposed that suggests an appropriate set of lean initiatives based on their impacts on performance metrics and manufacturing wastes and within manufacturers’ resource limitation. The proposed methodology in this research suggests the best set of lean initiatives for implementation that have highest impacts on identified critical performance metrics and manufacturing wastes. Therefore, manufacturers can assure that implementing suggested lean tools improves their production performance and reduces manufacturing wastes at the same time. A case study was conducted to show the effectiveness and validate the proposed model and methodologies.

Keywords: Lean manufacturing, Lean strategies, manufacturing wastes, manufacturing performance metrics, decision making, optimisation.

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Authors: Martin Lisý, Marek Baláš, Michal Špiláček, Zdeněk Skála

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This paper shortly describes various types of biomass and a growing number of facilities utilizing the biomass in the Czech Republic. The considerable part of this paper deals with energy parameters of the most frequently used types of biomass and results of their gasification testing. Sixteen most used "Czech" woody plants and grasses were selected; raw, element and biochemical analyses were performed and basic calorimetric values, ash composition, and ash characteristic temperatures were identified. Later, each biofuel was tested in a fluidized bed gasifier. The essential part of this paper provides results of the gasification of selected biomass types. Operating conditions are described in detail with a focus on individual fuels properties. Gas composition and impurities content are also identified. In terms of operating conditions and gas quality, the essential difference occurred mainly between woody plants and grasses. The woody plants were evaluated as more suitable fuels for fluidized bed gasifiers. Testing results significantly help with a decision-making process regarding suitability of energy plants for growing and with a selection of optimal biomass-treatment technology.

Keywords: Biomass Growing, Biomass Types, Gasification.

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Authors: J. J. Gyimah, E. Kissi, S. Osei-Tutu, C. D. Adobor, T. Adjei-Kumi, E. Osei-Tutu

Abstract:

Price fluctuation contract is imperative and of paramount essence in the construction industry as it provides adequate relief and cushioning for changes in the prices of input resources during construction. As a result, several methods have been devised to better help in arriving at fair recompense in the event of price changes. However, stakeholders often appear not to be satisfied with the existing methods of fluctuation evaluation, ostensibly because of the challenges associated with them. The aim of this study was to identify the challenges to usage of building construction cost indices in Ghana. Data were gathered from contractors and quantity surveying firms. The study utilized survey questionnaire approach to elicit responses from the contractors and the consultants. Data gathered were analyzed scientifically, using the Relative Importance Index (RII) to rank the problems associated with the existing methods. The findings revealed the following among others: late release of data; inadequate recovery of costs; and work items of interest not included in the published indices as the main challenges of the existing methods. Findings provided useful lessons for policy makers and practitioners in decision making towards the usage and improvement of available indices.

Keywords: Building construction cost indices, challenges, usage, Ghana.

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: Algorithm recommendation, meta-learning, bioinformatics, hierarchical classification.

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Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

Abstract:

This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control.

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Authors: Sanjeev Gupta, Mayank Dave

Abstract:

The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.

Keywords: Cluster head, data reliability, real time communication, wireless sensor networks.

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