Search results for: Robust Identification

Authors: Parvinder S. Sandhu, Harpreet Kaur, Amanpreet Singh

Abstract:

Automatic reusability appraisal is helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this research work, structural attributes of software components are explored using software metrics and quality of the software is inferred by different Neural Network based approaches, taking the metric values as input. The calculated reusability value enables to identify a good quality code automatically. It is found that the reusability value determined is close to the manual analysis used to be performed by the programmers or repository managers. So, the developed system can be used to enhance the productivity and quality of software development.

Keywords: Neural Network, Software Reusability, Software Metric, Accuracy, MAE, RMSE.

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Authors: Munir Majdalawieh, Adam Marks

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In today’s very competitive higher education industry (HEI), HEIs are faced with the primary concern of developing, deploying, and sustaining high quality academic programs. Today, the HEI has well-established accreditation systems endorsed by a country’s legislation and institutions. The accreditation system is an educational pathway focused on the criteria and processes for evaluating educational programs. Although many aspects of the accreditation process highlight both the past and the present (prove), the “program review” assessment is "forward-looking assessment" (improve) and thus transforms the process into a continuing assessment activity rather than a periodic event. The purpose of this study is to propose a conceptual measurement framework for program review to be used by HEIs to undertake a robust and targeted approach to proactively and continuously review their academic programs to evaluate its practicality and effectiveness as well as to improve the education of the students. The proposed framework consists of two main components: program review principles and the program review measurement matrix.

Keywords: Academic program, program review principles, curriculum development, accreditation, evaluation, assessment, review measurement matrix, program review process, information technologies supporting learning, learning/teaching methodologies and assessment.

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Authors: Sangbum Park, Namki Lee, Youngjoon Han, Hernsoo Hahn

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In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.

Keywords: accumulated histogram, water level detection, band pass filter.

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Authors: Z. Soleymani, M. Amirzadeh

Abstract:

Quality Function Deployment (QFD) was developed in 1960 in Japan and introduced in 1983 in America and Europe. The paper presents a real application of this technique in a way that the method of applying QFD in design and production aero fuel pumps has been considered. While designing a product and in order to apply system engineering process, the first step is identification customer needs then its transition to engineering parameters. Since each change in deign after production process leads to extra human costs and also increase in products quality risk, QFD can make benefits in sale by meeting customer expectations. Since the needs identified as well, the use of QFD tool can lead to increase in communications and less deviation in design and production phases, finally it leads to produce the products with defined technical attributes.

Keywords: Customer voice, engineering parameters, QFD, gear pump.

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Authors: Abdallah Al-Shammari

Abstract:

This study discusses the effect of uncertainty on production levels of a petrochemical complex. Uncertainly or variations in some model parameters, such as prices, supply and demand of materials, can affect the optimality or the efficiency of any chemical process. For any petrochemical complex with many plants, there are many sources of uncertainty and frequent variations which require more attention. Many optimization approaches are proposed in the literature to incorporate uncertainty within the model in order to obtain a robust solution. In this work, a stability analysis approach is applied to a deterministic LP model of a petrochemical complex consists of ten plants to investigate the effect of such variations on the obtained optimal production levels. The proposed approach can determinate the allowable variation ranges of some parameters, mainly objective or RHS coefficients, before the system lose its optimality. Parameters with relatively narrow range of variations, i.e. stability limits, are classified as sensitive parameters or constraints that need accurate estimate or intensive monitoring. These stability limits offer easy-to-use information to the decision maker and help in understanding the interaction between some model parameters and deciding when the system need to be re-optimize. The study shows that maximum production of ethylene and the prices of intermediate products are the most sensitive factors that affect the stability of the optimum solution

Keywords: Linear programming, Petrochemicals, stability analysis, uncertainty

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Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

Abstract:

Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear identification, NNARX.

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Authors: Shiva Subhedar, Abhishek Jain, Shivin Mittal

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Icons are not merely decorative elements in enterprise applications but very often used because of their many advantages such as compactness, visual appeal, etc. Despite these potential advantages, icons often cause usability problems when they are designed without consideration for their many potential downsides. The aim of the current study was to examine the effect of articulatory distance – the distance between the physical appearance of an interface element and what it actually means. In other words, will the subject find the association of the function and its appearance on the interface natural or is the icon difficult for them to associate with its function. We have calculated response time and quality of identification by varying icon concreteness, the context of usage and subject experience in the enterprise context. The subjects were asked to associate icons (prepared for study purpose) with given function options in context and out of context mode. Response time and their selection were recorded for analysis.

Keywords: Icons, icon concreteness, icon recognition, HCI.

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Authors: Svitov David, Alyamkin Sergey

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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax.

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Authors: E. Barkanov, E. Skukis, M. Wesolowski, A. Chate

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New nondestructive technique, namely an inverse technique based on vibration tests, to characterize nonlinear mechanical properties of adhesive layers in sandwich composites is developed. An adhesive layer is described as a viscoelastic isotropic material with storage and loss moduli which are both frequency dependent values in wide frequency range. An optimization based on the planning of experiments and response surface technique to minimize the error functional is applied to decrease considerably the computational expenses. The developed identification technique has been tested on aluminum panels and successfully applied to characterize viscoelastic material properties of 3M damping polymer ISD-112 used as a core material in sandwich panels.

Keywords: Adhesive layer, finite element method, inverse technique, sandwich panel, vibration test, viscoelastic material properties.

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Authors: Jyh-Cherng Gu, Ming-Ta Yang, Chao-Fong Yan, Hsin-Yung Chung, Yung-Ruei Chang, Yih-Der Lee, Chen-Min Chan, Chia-Hao Hsu

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There are a number of Distributed Generations (DGs) installed in microgrid, which may have diverse path and direction of power flow or fault current. The overcurrent protection scheme for the traditional radial type distribution system will no longer meet the needs of microgrid protection. Integrating the Intelligent Electronic Device (IED) and a Supervisory Control and Data Acquisition (SCADA) with IEC 61850 communication protocol, the paper proposes a Microgrid Protection Management System (MPMS) to protect power system from the fault. In the proposed method, the MPMS performs logic programming of each IED to coordinate their tripping sequence. The GOOSE message defined in IEC 61850 is used as the transmission information medium among IEDs. Moreover, to cope with the difference in fault current of microgrid between grid-connected mode and islanded mode, the proposed MPMS applies the group setting feature of IED to protect system and robust adaptability. Once the microgrid topology varies, the MPMS will recalculate the fault current and update the group setting of IED. Provided there is a fault, IEDs will isolate the fault at once. Finally, the Matlab/Simulink and Elipse Power Studio software are used to simulate and demonstrate the feasibility of the proposed method.

Keywords: IEC 61850, IED, Group Setting, Microgrid.

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Authors: Hiromitsu Ogawa, Manato Ono, Naohiro Ban, Yoshihisa Ishida

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This paper describes the two stage control using a disturbance observer and a Kalman filter. The system feedback uses the estimated state when it controls the speed. After the change-over point, its feedback uses the controlled plant output when it controls the position. To change the system continually, a change-over point has to be determined pertinently, and the controlled plant input has to be adjusted by the addition of the appropriate value. The proposed method has noise-reduction effect. It changes the system continually, even if the controlled plant identification has the error. Although the conventional method needs a speed sensor, the proposed method does not need it. The proposed method has a superior robustness compared with the conventional two stage control.

Keywords: Disturbance observer, kalman filter, optimal control, two stage control.

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Authors: Y. Deng, X. Li, C. Kwan, B. Raj, R. Stern

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The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environmental noise such as tank noise, helicopter noise, etc. In this paper, we proposed a novel continuous acoustic feature adaptation algorithm for on-line accent and environmental adaptation. Implemented by incremental singular value decomposition (SVD), the algorithm captures local acoustic variation and runs in real-time. This feature-based adaptation method is then integrated with conventional model-based maximum likelihood linear regression (MLLR) algorithm. Extensive experiments have been performed on the NATO non-native speech corpus with baseline acoustic model trained on native American English. The proposed feature-based adaptation algorithm improved the average recognition accuracy by 15%, while the MLLR model based adaptation achieved 11% improvement. The corresponding word error rate (WER) reduction was 25.8% and 2.73%, as compared to that without adaptation. The combined adaptation achieved overall recognition accuracy improvement of 29.5%, and WER reduction of 31.8%, as compared to that without adaptation.

Keywords: speaker adaptation; environment adaptation; robust speech recognition; SVD; non-native speech recognition

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Authors: Ashraf M. A. Ahmad

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Delivering streaming video over wireless is an important component of many interactive multimedia applications running on personal wireless handset devices. Such personal devices have to be inexpensive, compact, and lightweight. But wireless channels have a high channel bit error rate and limited bandwidth. Delay variation of packets due to network congestion and the high bit error rate greatly degrades the quality of video at the handheld device. Therefore, mobile access to multimedia contents requires video transcoding functionality at the edge of the mobile network for interworking with heterogeneous networks and services. Therefore, to guarantee quality of service (QoS) delivered to the mobile user, a robust and efficient transcoding scheme should be deployed in mobile multimedia transporting network. Hence, this paper examines the challenges and limitations that the video transcoding schemes in mobile multimedia transporting network face. Then handheld resources, network conditions and content based mobile and wireless video transcoding is proposed to provide high QoS applications. Exceptional performance is demonstrated in the experiment results. These experiments were designed to verify and prove the robustness of the proposed approach. Extensive experiments have been conducted, and the results of various video clips with different bit rate and frame rate have been provided.

Keywords: Content, Object detection, Transcoding, Texture, Temporal, Video.

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Authors: Juhan Kim, Howon Kim

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EPC Class-1 Generation-2 UHF tags, one of Radio frequency identification or RFID tag types, is expected that most companies are planning to use it in the supply chain in the short term and in consumer packaging in the long term due to its inexpensive cost. Because of the very cost, however, its resources are extremely scarce and it is hard to have any valuable security algorithms in it. It causes security vulnerabilities, in particular cloning the tags for counterfeits. In this paper, we propose a product authentication solution for anti-counterfeiting at application level in the supply chain and mobile RFID environment. It aims to become aware of distribution of spurious products with fake RFID tags and to provide a product authentication service to general consumers with mobile RFID devices like mobile phone or PDA which has a mobile RFID reader. We will discuss anti-counterfeiting mechanisms which are required to our proposed solution and address requirements that the mechanisms should have.

Keywords: EPC, RFID, Anti-Counterfeiting, Mobile RFIDenvironment.

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.

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Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: Pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor.

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Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

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More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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Authors: Emma Dwi Ariyani, Dini Hadiani

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This article reports the descriptive analysis of self-compassion in polytechnic students. It has been long believed that self-compassion can improve students’ motivation in completing their studies. This research was conducted with the aim to see the degree of self-compassion in polytechnic students in Indonesia by using Neff's Self-Compassion Scale (short form) measurement tool consisting of 12 items. The research method used was descriptive study with survey technique on 255 students. The results showed that 78% of students had low self-compassion and 22% had high self-compassion. This revealed that polytechnic students still criticize themselves harshly, make a poor judgment and bad self-appraisal, and they also cannot accept their imperfection and consider it as a self-judgment. The students also tend to think that they are the only ones that experience failure and suffering. This can lead to a sense of isolation (self-isolation). Furthermore, the students are often too concerned with aspects that are not liked both in themselves and in life (over-identification). Improving the students’ level of self-compassion can be done by building an educational climate that not only criticizes the students but provides feedback as well. This should focus on the students’ real behavior rather than the students’ general character.

Keywords: Descriptive study, polytechnic students, Indonesia, self-compassion.

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Authors: Hashem Dehghanniri

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Crime scripting is a simple and effective crime modeling technique that aims to improve understanding of security analysts about security and crime incidents. Low-quality scripts provide a wrong, incomplete, or sophisticated understanding of the crime commission process, which oppose the purpose of their application, e.g., identifying effective and cost-efficient situational crime prevention (SCP) measures. One important and overlooked factor in generating quality scripts is the crime scripting method. This study investigates the problems within the existing crime scripting practices and proposes a crime scripting approach that contributes to generating quality crime scripts. It was validated by experienced crime scripters. This framework helps analysts develop better crime scripts and contributes to their effective application, e.g., SCP measures identification or policy-making.

Keywords: Attack modeling, crime commission process, crime script, situational crime prevention.

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Authors: Belkacem Selma, Boumediene Selma, Samira Chouraqui, Hanifi Missoum, Tourkia Guerzou

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. Earthquake prediction to prevent the loss of human lives and even property damage is an important factor; that, is why it is crucial to develop techniques for predicting this natural disaster. This study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 104 J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines have been analyzed. The results obtained show that the ANN is able to predict earthquake parameters with  high accuracy; the classification accuracy through neural networks is more than 94%, and the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: Earthquake prediction, artificial intelligence, AI, Artificial Neural Network, ANN, seismic bumps.

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Authors: Jijimon Alakkalam Joseph

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The UN 2030 Agenda for Sustainable Development claims to be a comprehensive and integrated plan of action for prosperity for people and the planet, including almost all dimensions of human existence. Nevertheless, the religious dimension of human existence has been kept away from development discussions. Care for the earth is one of the vital aspects of sustainable development. Farmers all over the world contribute much to environmental protection. Most farmers are religious believers and religious ideologies influence their agricultural practices. This nexus between faith and agriculture has forced policymakers to include religion in development discussions. This paper delves deeper into this religion and sustainable development connection. Buddhism and Christianity have contributed much to environmental protection in Taiwan. However, interviews conducted among 40 Taiwanese farmers (10 male and female farmers from Buddhism and Christianity) show that their faith experiences make them relate to the natural environment differently. Most of the Buddhist farmers interviewed admitted that they chose their religious adherence, while most of the Christian farmers inherited their faith. The in-depth analysis of the interview data collected underlines the close relationship between religion and sustainable development. More importantly, concerning their intention to care for the earth, farmers whose religious adherence is ‘chosen’ are self-motivated and more robust compared to those whose religious adherence is ‘inherited’.

Keywords: Buddhism, Christianity, environmental protection, sustainable development.

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Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

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This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: Hit-or/and-Miss Operator/Transform, HMT, binary morphological operation, shape detection, binary images processing.

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Authors: Young-Il Kim, Bong-Jae Yi, Jae-Ju Song, Jin-Ho Shin, Jung-Il Lee

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Firstly, research and development on RFID focuses on manufacturing and retail sectors, because it can improve supply chain efficiency. But, now a variety of field is considered the next research area for Radio Frequency Identification (RFID). Although RFID is infancy, RFID technology has great potential in power industry to significantly reduce cost, and improve quality of power supply. To complement the limitation of RFID, we adopt the WSN (Wireless Sensor Network) technology. However, relevant experience is limited, the challenge will be to derive requirement from business practice and to determine whether it is possible or not. To explore this issue, we conduct a case study on implementing power facility management system using RFID/WSN in Korea Electric Power Corporation (KEPCO). In this paper we describe requirement from power industry. And we introduce design and implementation of the test bed.

Keywords: Power Facility Management, RFID/WSN, Transmission Tower, Underground Tunnel, ZigBee.

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Authors: Olaf Hallan Graven, Lachlan MacKinnon

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One major issue that is regularly cited as a block to the widespread use of online assessments in eLearning, is that of the authentication of the student and the level of confidence that an assessor can have that the assessment was actually completed by that student. Currently, this issue is either ignored, in which case confidence in the assessment and any ensuing qualification is damaged, or else assessments are conducted at central, controlled locations at specified times, losing the benefits of the distributed nature of the learning programme. Particularly as we move towards constructivist models of learning, with intentions towards achieving heutagogic learning environments, the benefits of a properly managed online assessment system are clear. Here we discuss some of the approaches that could be adopted to address these issues, looking at the use of existing security and biometric techniques, combined with some novel behavioural elements. These approaches offer the opportunity to validate the student on accessing an assessment, on submission, and also during the actual production of the assessment. These techniques are currently under development in the DECADE project, and future work will evaluate and report their use..

Keywords: E-learning, remote identification, assessment.

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Authors: Diana Cotoros, Mihaela Baritz, Anca Stanciu

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Some theoretical and experimental aspects related to the conceptual analyses concerning the direct correspondence identification between the shape, area and orientation of plantar pressure and obtaining adequate corrective insoles by rapid prototyping are presented in this paper. In the first part of the paper there is the theoretical-correlative concept, which is the fundament of correspondence deduction between plantar surface characteristics and respectively corrective insoles. In the second part of the paper the experimental equipment used to analyze and perform the correspondence stages and then the integral ones between the analyzed foot shapes and the ones with corrective insoles is presented. In the final parte the results used to adapt the insoles obtained by rapid prototyping but also some specific aspects and conclusions of the conceptual analysis of direct and rapid correspondence are shown.

Keywords: Insoles, plantar surface, rapid prototyping, correspondence concept

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Authors: Abdulmajeed Bashir Mlitan, Ethan Hack

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Soil samples were collected from and around Alkomos cement factory, Alkomos town, Libya. Soil physiochemical properties were determined. In addition, olive leaves were scanned for their fungal content. This work can conclude that the results obtained for the examined physiochemical characteristics of soil in the area studied prove that cement dust from the Alkomos cement factory in Libya has had a significant impact on the soil. The affected soil properties are pH and total calcium content. These characteristics were found to be higher than those in similar soils from the same area. The increment of soil pH in the same area may be a result of precipitation of cement dust over the years. Different responses were found in each season and each site. For instance, the dominance of fungi of soil and leaves was lowest at 100 m from the factory and the evenness and diversity increased at this site compared to the control area and 250 m from the factory.

Keywords: Pollution, Soil Microbial, Alkomos, Libya.

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Authors: Ismail Karaca, Ridvan Saracoglu, Omer Soner

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Fuzzy Logic, an advanced method to support decision-making, is used by various scientists in many disciplines. Fuzzy programming is a product of fuzzy logic, fuzzy rules, and implication. In marine science, fuzzy programming for ships is dramatically increasing together with autonomous ship studies. In this paper, a program to support the decision-making process for ship navigation has been designed. The program is produced in fuzzy logic and rules, by taking the marine accidents and expert opinions into account. After the program was designed, the program was tested by 46 ship accidents reported by the Transportation Safety Investigation Center of Turkey. Wind speed, sea condition, visibility, day/night ratio have been used as input data. They have been converted into a risk factor within the Fuzzy Logic Designer application and fuzzy rules set by marine experts. Finally, the expert's meteorological risk factor for each accident is compared with the program's risk factor, and the error rate was calculated. The main objective of this study is to improve the navigational safety of ships, by using the advance decision support model. According to the study result, fuzzy programming is a robust model that supports safe navigation.

Keywords: Calculation of risk factor, fuzzy logic, fuzzy programming for ship, safe navigation of ships.

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Authors: Boualem El Kechebour, Djilali Benouar

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The objective of this work is to present a expertise on flooding hazard analysis and how to reduce the risk. The analysis concerns the disaster induced by the flood on November 10/11, 2001 in the Bab El Oued district of the city of Algiers.The study begins by an expertise of damages in related with the urban environment and the history of the urban growth of the site. After this phase, the work is focalized on the identification of the existing correlations between the development of the town and its vulnerability. The final step consists to elaborate the interpretations on the interactions between the urban growth, the sewerage network and the vulnerability of the urban system.In conclusion, several recommendations are formulated permitting the mitigation of the risk in the future. The principal recommendations concern the new urban operations and the existing urbanized sites.

Keywords: urban growth, sewerage network, vulnerability of town, flooding risk, mitigation

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Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno

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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to real-world data

Keywords: Rule induction, decision table, missing data, noise.

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Authors: Hanaa Farouk Saleh

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The main purposes of this study are to develop a scale that reflects emerging theoretical understandings of new media credibility, based on the evolution of credibility studies in western researches, identification of the determinants of credibility in the media and its components by comparing traditional and new media credibility scales and building accumulative scale to test new media credibility. This approach was built on western researches using conceptualizations of media credibility, which focuses on four principal components: Source (journalist), message (article), medium (newspaper, radio, TV, web, etc.), and organization (owner of the medium), and adding user and cultural context as key components to assess new media credibility in particular. This study’s value lies in its contribution to the conceptualization and development of new media credibility through the creation of a theoretical measurement tool. Future studies should explore this scale to test new media credibility, which represents a promising new approach in the efforts to define and measure credibility of all media types.

Keywords: Credibility scale, media credibility components, new media credibility scale, scale development.

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