Search results for: environmental performance data

Authors: Hiroaki Nasu, Ryota Miyamoto, Yuta Kodera, Yasuyuki Nogami

Abstract:

To promote Industry 4.0 and Society 5.0 and so on, it is important to connect and share data so that every member can trust it. Blockchain (BC) technology is currently attracting attention as the most advanced tool and has been used in the financial field and so on. However, the data collaboration using BC has not progressed sufficiently among companies on the supply chain of the manufacturing industry that handle sensitive data such as product quality, manufacturing conditions, etc. There are two main reasons why data utilization is not sufficiently advanced in the industrial supply chain. The first reason is that manufacturing information is top secret and a source for companies to generate profits. It is difficult to disclose data even between companies with transactions in the supply chain. Blockchain mechanism such as Bitcoin using Public Key Infrastructure (PKI) requires plaintext to be shared between companies in order to verify the identity of the company that sent the data. Another reason is that the merits (scenarios) of collaboration data between companies are not specifically specified in the industrial supply chain. For these problems, this paper proposes a Business to Business (B2B) collaboration system using homomorphic encryption and BC technique. Using the proposed system, each company on the supply chain can exchange confidential information on encrypted data and utilize the data for their own business. In addition, this paper considers a scenario focusing on quality data, which was difficult to collaborate because it is top-secret. In this scenario, we show an implementation scheme and a benefit of concrete data collaboration by proposing a comparison protocol that can grasp the change in quality while hiding the numerical value of quality data.

Keywords: Business to business data collaboration, industrial supply chain, blockchain, homomorphic encryption.

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner, David Gabriel F. de Barros

Abstract:

Review researches are useful in terms of analysis of research problems. Between the types of review documents, we commonly find bibliometric studies. This type of application often helps the global visualization of a research problem and helps academics worldwide to understand the context of a research area better. In this document, a bibliometric view surrounding clustering techniques and sustainability problems is presented. The authors aimed at which issues mostly use clustering techniques and even which sustainability issue would be more impactful on today’s moment of research. During the bibliometric analysis, we found 10 different groups of research in clustering applications for sustainability issues: Energy; Environmental; Non-urban Planning; Sustainable Development; Sustainable Supply Chain; Transport; Urban Planning; Water; Waste Disposal; and, Others. Moreover, by analyzing the citations of each group, it was discovered that the Environmental group could be classified as the most impactful research cluster in the area mentioned. After the content analysis of each paper classified in the environmental group, it was found that the k-means technique is preferred for solving sustainability problems with clustering methods since it appeared the most amongst the documents. The authors finally conclude that a bibliometric assessment could help indicate a gap of researches on waste disposal – which was the group with the least amount of publications – and the most impactful research on environmental problems.

Keywords: Bibliometric assessment, clustering, sustainability, territorial partitioning.

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Authors: S. M. Dash, K. B. Lua, T. T. Lim

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This paper presents results of numerical and experimental studies on a two-dimensional (2D) flapping elliptic airfoil in a forward flight condition at Reynolds number of 5000. The study is motivated from an earlier investigation which shows that the deterioration in thrust performance of a sinusoidal heaving and pitching 2D (NACA0012) airfoil at high flapping frequency can be recovered by changing the effective angle of attack profile to square wave, sawtooth, or cosine wave shape. To better understand why such modifications lead to superior thrust performance, we take a closer look at the transient aerodynamic force behavior of an airfoil when the effective angle of attack profile changes gradually from a generic smooth trapezoidal profile to a sinusoid shape by modifying the base length of the trapezoid. The choice of using a smooth trapezoidal profile is to avoid the infinite acceleration condition encountered in the square wave profile. Our results show that the enhancement in the time-averaged thrust performance at high flapping frequency can be attributed to the delay and reduction in the drag producing valley region in the transient thrust force coefficient when the effective angle of attack profile changes from sinusoidal to trapezoidal.  

Keywords: Two-dimensional Flapping Airfoil, Thrust Performance, Effective Angle of Attack, CFD and Experiments.

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Authors: Sarisa Pinkham, Kanyarat Bussaban

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The research aims to approximate the amount of daily rainfall by using a pixel value data approach. The daily rainfall maps from the Thailand Meteorological Department in period of time from January to December 2013 were the data used in this study. The results showed that this approach can approximate the amount of daily rainfall with RMSE=3.343.

Keywords: Daily rainfall, Image processing, Approximation, Pixel value data.

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Authors: Widad Jakjoud, Mohamed Bahaj, Jamal Bakkas

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Through this paper we present a method for automatic generation of ontological model from any data source using Model Driven Architecture (MDA), this generation is dedicated to the cooperation of the knowledge engineering and software engineering. Indeed, reverse engineering of a data source generates a software model (schema of data) that will undergo transformations to generate the ontological model. This method uses the meta-models to validate software and ontological models.

Keywords: Meta model, model, ontology, data source.

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Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian R. Murray

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The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: Interoperability, Case Study, Health Data Standards, Medical Data Exchange, Saudi Arabia.

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Authors: C. Kalamani, K. Paramasivam

Abstract:

In VLSI, testing plays an important role. Major problem in testing are test data volume and test power. The important solution to reduce test data volume and test time is test data compression. The Proposed technique combines the bit maskdictionary and 2n pattern run length-coding method and provides a substantial improvement in the compression efficiency without introducing any additional decompression penalty. This method has been implemented using Mat lab and HDL Language to reduce test data volume and memory requirements. This method is applied on various benchmark test sets and compared the results with other existing methods. The proposed technique can achieve a compression ratio up to 86%.

Keywords: Bit Mask dictionary, 2n pattern run length code, system-on-chip, SOC, test data compression.

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Authors: Ho-Hyun Park, Woosik Kim, Miae Woo

Abstract:

It is expected that ubiquitous era will come soon. A ubiquitous environment has features like peer-to-peer and nomadic environments. Such features can be represented by peer-to-peer systems and mobile ad-hoc networks (MANETs). The features of P2P systems and MANETs are similar, appealing for implementing P2P systems in MANET environment. It has been shown that, however, the performance of the P2P systems designed for wired networks do not perform satisfactorily in mobile ad-hoc environment. Subsequently, this paper proposes a method to improve P2P performance using cross-layer design and the goodness of a node as a peer. The proposed method uses routing metric as well as P2P metric to choose favorable peers to connect. It also utilizes proactive approach for distributing peer information. According to the simulation results, the proposed method provides higher query success rate, shorter query response time and less energy consumption by constructing an efficient overlay network.

Keywords: Ad-hoc Networks, Cross-layer, Peer-to-Peer, Performance Analysis.

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Authors: Hsueh-Chih, Chen, Yau-Ting, Sung, Tsai-Wen, Lin, Hung-Teng, Chou

Abstract:

It has formed an essential issue that Climate Change, composed of highly knowledge complexity, reveals its significant impact on human existence. Therefore, specific national policies, some of which present the educational aspects, have been published for overcoming the imperative problem. Accordingly, the study aims to analyze as well as integrate the relationship between Climate Change and environmental education and apply the perspective of concept map to represent the knowledge contents and structures of Climate Change; by doing so, knowledge contents of Climate Change could be represented in an even more comprehensive way and manipulated as the tool for environmental education. The method adapted for this study is knowledge conversion model compounded of the platform for experts and teachers, who were the participants for this study, to cooperate and combine each participant-s standpoints into a complete knowledge framework that is the foundation for structuring the concept map. The result of this research contains the important concepts, the precise propositions and the entire concept map for representing the robust concepts of Climate Change.

Keywords: Climate Change, knowledge complexity, concept map.

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Authors: Do-Kyu, Hwang, Ho-Young Kim, Ho-Hyeoung Choi, Gi-Beom Park, Jae-Hoon Lee

Abstract:

Currently there are many use of threaded reinforcing bars in construction fields because those do not need additional screw processing when connecting reinforcing bar by threaded coupler. In this study, reinforced concrete bridge piers using threaded rebar coupler system at the plastic hinge area were tested to evaluate seismic performance. The test results showed that threads of the threaded rebar coupler system could be loosened while under tension-compression cyclic loading because tolerance and rib face angle of a threaded rebar coupler system are greater than that of a conventional ribbed rebar coupler system. As a result, cracks were concentrated just outside of the mechanical coupler and stiffness of reinforced concrete bridge pier decreased. Therefore, it is recommended that connection ratio of mechanical couplers in one section shall be below 50% in order that cracks are not concentrated just outside of the mechanical coupler. Also, reduced stiffness of the specimen should be considered when using the threaded rebar coupler system.

Keywords: Reinforced concrete column, seismic performance, threaded rebar coupler, threaded reinforcing bar.

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Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

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The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: Automatic bias control, optical fiber communication, optical modulation, optical devices.

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Authors: Sung Ho Ha, Seong Hyeon Joo

Abstract:

Data mining techniques have been used in medical research for many years and have been known to be effective. In order to solve such problems as long-waiting time, congestion, and delayed patient care, faced by emergency departments, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees. The methodology is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques. The methodology is expected to help physicians to make a faster and more accurate classification of chest pain diseases.

Keywords: Data mining, medical decisions, medical domainknowledge, chest pain.

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Authors: X. Mercilin Raajini, R. Raja Kumar, P. Indumathi, V. Praveen

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Many cluster based routing protocols have been proposed in the field of wireless sensor networks, in which a group of nodes are formed as clusters. A cluster head is selected from one among those nodes based on residual energy, coverage area, number of hops and that cluster-head will perform data gathering from various sensor nodes and forwards aggregated data to the base station or to a relay node (another cluster-head), which will forward the packet along with its own data packet to the base station. Here a Game Theory based Diligent Energy Utilization Algorithm (GTDEA) for routing is proposed. In GTDEA, the cluster head selection is done with the help of game theory, a decision making process, that selects a cluster-head based on three parameters such as residual energy (RE), Received Signal Strength Index (RSSI) and Packet Reception Rate (PRR). Finding a feasible path to the destination with minimum utilization of available energy improves the network lifetime and is achieved by the proposed approach. In GTDEA, the packets are forwarded to the base station using inter-cluster routing technique, which will further forward it to the base station. Simulation results reveal that GTDEA improves the network performance in terms of throughput, lifetime, and power consumption.

Keywords: Cluster head, Energy utilization, Game Theory, LEACH, Sensor network.

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Authors: M. V. Ramana Rao, T. Adilakshmi

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Based on application requirements, nodes are static or mobile in Wireless Sensor Networks (WSNs). Mobility poses challenges in protocol design, especially at the link layer requiring mobility adaptation algorithms to localize mobile nodes and predict link quality to be established with them. This study implements XMAC and Berkeley Media Access Control (BMAC) routing protocols to evaluate performance under WSN’s static and mobility conditions. This paper gives a comparative study of mobility-aware MAC protocols. Routing protocol performance, based on Average End to End Delay, Average Packet Delivery Ratio, Average Number of hops, and Jitter is evaluated.

Keywords: Wireless Sensor Network (WSN), Medium Access Control (MAC), Berkeley Media Access Control (BMAC), mobility.

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Authors: Cesar Hernández, Diego Giral, Ingrid Páez

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This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics are used. These metrics are accumulative average of failed handoffs, accumulative average of handoffs performed, accumulative average of transmission bandwidth, and accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.

Keywords: Cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks.

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: Data mining, textile production, decision trees, classification.

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Authors: Chen Zhang, Wei Yaping

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With the rapid expansion of city scale and the excessive concentration of population, achieving relative equality of extracurricular education resources and improving spatial service performance of relevant facilities become necessary arduous tasks. In urban space, extracurricular education facilities should offer better service to its targeted area and promote the equality and efficiency of education, which is accomplished by the allocation of facilities. Based on questionnaire and survey for local students in Hangzhou City in 2009, this study classifies extracurricular education facilities in meg-city and defines the equalization of these facilities. Then it is suggested to establish extracurricular education facilities system according to the development level of city and demands of local students, and to introduce a spatial analysis method into urban planning through the aspects of spatial distribution, travel cost and spatial service scope. Finally, the practice of nine sub-districts of Hangzhou is studied.

Keywords: extracurricular education facilities, equalization, spatial service performance, meg-city

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Authors: Mahdi Esmaeili, Mansour Tarafdar

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The goal of data mining algorithms is to discover useful information embedded in large databases. One of the most important data mining problems is discovery of frequently occurring patterns in sequential data. In a multidimensional sequence each event depends on more than one dimension. The search space is quite large and the serial algorithms are not scalable for very large datasets. To address this, it is necessary to study scalable parallel implementations of sequence mining algorithms. In this paper, we present a model for multidimensional sequence and describe a parallel algorithm based on data parallelism. Simulation experiments show good load balancing and scalable and acceptable speedup over different processors and problem sizes and demonstrate that our approach can works efficiently in a real parallel computing environment.

Keywords: Sequential Patterns, Data Mining, ParallelAlgorithm, Multidimensional Sequence Data

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Authors: V. Vicente E. Mujica, Gustavo Gonzalez

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The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: Terrestrial-satellite networks, latency, on-orbit satellite payload, simulation.

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Authors: Rohitash Chandra, Christian W. Omlin

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We present a hybrid architecture of recurrent neural networks (RNNs) inspired by hidden Markov models (HMMs). We train the hybrid architecture using genetic algorithms to learn and represent dynamical systems. We train the hybrid architecture on a set of deterministic finite-state automata strings and observe the generalization performance of the hybrid architecture when presented with a new set of strings which were not present in the training data set. In this way, we show that the hybrid system of HMM and RNN can learn and represent deterministic finite-state automata. We ran experiments with different sets of population sizes in the genetic algorithm; we also ran experiments to find out which weight initializations were best for training the hybrid architecture. The results show that the hybrid architecture of recurrent neural networks inspired by hidden Markov models can train and represent dynamical systems. The best training and generalization performance is achieved when the hybrid architecture is initialized with random real weight values of range -15 to 15.

Keywords: Deterministic finite-state automata, genetic algorithm, hidden Markov models, hybrid systems and recurrent neural networks.

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Authors: Ahmad Rouhani

Abstract:

Iran has several potential for using renewable energies, so use them could significantly contribute to energy supply. The purpose of this paper is to identify the potential of the country and select the appropriate DG technologies with consideration the potential and primary energy resources in the regions. In this context, hybrid energy systems proportionate with the potential of different regions will be determined based on technical, economic, and environmental aspect. In the following the proposed structure will be optimized in terms of size and cost. DG technologies used in this project include photovoltaic system, wind turbine, diesel generator and battery bank. The HOMER software is applied for choosing the appropriate structure and the optimization of system sizing. The results have been analyzed in terms of technical and economic. The performance and the cost of each project demonstrate the appropriate structure of hybrid energy system in that region.

Keywords: Feasibility, Hybrid Energy System, Iran, Renewable Energy.

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Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

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The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling the human behaviour. However, the exclusive use of this technology still seems insufficient to control the vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: Accuracy assessment, AI-Driven Mobility, Artificial Intelligence, automated vehicles.

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Authors: Sidhartha Panda, N. P. Padhy

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.

Keywords: Thyristor Controlled Series Compensator, geneticalgorithm; particle swarm optimization; Phillips-Heffron model;power system stability.

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Authors: Rahmat A, Radin Rafeeuddin R. D., Norasrudin S., Mastura M.

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The objective of the study is to investigate the effect of a footballer-s postural on selected physical fitness components. Twenty-one (21) subjects of the university male footballers under the Sport Excellence Center programme were photographed using qualitative analysis. The postural variables were stratified manually into normal and anomalies group and their flexibility, strength and SAQ performance were compared using the Mann-Whitney Test. The AROM assessment and SAQ test reported no significance difference (Z=-.398, p=0.711, p>0.05), similar to the lower body strength was shown with no significance different (Z=-.493, p=0.640, p>0.05). In contrast, only 1 RM strength test for the upper body strength test shown with a significance different (Z=- 2.537, p=0.009, p<0.05) the. Hence, the Body posture among the football athletes with anomalies does not influence selected physical fitness components. This study has proven, that postural anomalies will not affect or influence the physical performance the respective athletes.

Keywords: Postural Analysis, Anomalies, Flexibility, Strength, SAQ.

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Authors: Aaron J. Small, Craig A. Fletcher

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This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.

Keywords: Rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design.

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Authors: Napisporn Memongkol, Runchana Sinthavalai, Nattapong Seneeratanaprayune Weerawat Ounsaneha, Chanisada Choosuk

Abstract:

The objective of this research is to develop the performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency Medical Institute of Thailand (EMIT) was considered using strategic analysis to developed Strategy Map (SM) and identified the Success Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited only with the first dimension of National Strategic Plan (infrastructure and information technology development). Besides, the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators were developed from the analysis results of SM and SFs.

Keywords: Emergency Medical Service, Performance Indicator, Success Factor, Thailand

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

Abstract:

Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: Feature selection, multi-objective evolutionary computation, unsupervised classification, behavior assessment system for children.

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Authors: Rein Kuusik, Grete Lind

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Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).

Keywords: data mining, monotone systems, pattern, rule.

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Authors: G. Bhushan, S. Dhingra, K. K. Dubey

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This paper presents the evaluation of performance (BSFC and BTE), combustion (P_max) and emission (CO, NO_x, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: Karanja biodiesel, single cylinder direct injection diesel engine, response surface methodology, central composite rotatable design, genetic algorithm.

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Authors: Kee-Leong Tan, Karyn Wei-Ju Khoo, Hui-Na Chua

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Service discovery is a very important component of Service Oriented Architectures (SOA). This paper presents two alternative approaches to customise the query results of private service registry such as Universal Description, Discovery and Integration (UDDI). The customisation is performed based on some pre-defined and/or real-time changing parameters. This work identifies the requirements, designs and additional mechanisms that must be applied to UDDI in order to support this customisation capability. We also detail the implements of the approaches and examine its performance and scalability. Based on our experimental results, we conclude that both approaches can be used to customise registry query results, but by storing personalization parameters in external resource will yield better performance and but less scalable when size of query results increases. We believe these approaches when combined with semantics enabled service registry will enhance the service discovery methods within a private UDDI registry environment.

Keywords: Service Oriented Architecture (SOA), Web service, Service discovery, registry, UDDI

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