Search results for: learning management

Authors: Shao-Hsia Chang, Nan-Ying Yu

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The objective of this study was to test how advanced digital technology enables a more effective training on the handwriting of children with handwriting deficit. This study implemented the graphomotor apparatuses to a computer-assisted instruction system. In a randomized controlled trial, the experiments for verifying the intervention effect were conducted. Forty two children with handwriting deficit were assigned to computer-assisted instruction, sensorimotor training or control (no intervention) group. Handwriting performance was measured using the Elementary reading/writing test and computerized handwriting evaluation before and after 6 weeks of intervention. Analysis of variance of change scores were conducted to show whether statistically significant difference across the three groups. Significant difference was found among three groups. Computer group shows significant difference from the other two groups. Significance was denoted in near-point, far-point copy, dictation test, and writing from phonetic symbols. Writing speed and mean stroke velocity in near-, far-point and short paragraph copy were found significantly difference among three groups. Computer group shows significant improvement from the other groups. For clinicians and school teachers, the results of this study provide a motor control based insight for the improvement of handwriting difficulties.

Keywords: Dysgraphia, computerized handwriting evaluation, sensorimotor program, computer assisted program.

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: Natural language processing, end user development; natural language interfaces, human computer interaction, data recognition, dialog systems, spreadsheet.

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Authors: Jehad Al Dallal

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Class cohesion is an important object-oriented software quality attribute. It indicates how much the members in a class are related. Assessing the class cohesion and improving the class quality accordingly during the object-oriented design phase allows for cheaper management of the later phases. In this paper, the notion of distance between pairs of methods and pairs of attribute types in a class is introduced and used as a basis for introducing a novel class cohesion metric. The metric considers the methodmethod, attribute-attribute, and attribute-method direct interactions. It is shown that the metric gives more sensitive values than other well-known design-based class cohesion metrics.

Keywords: Object-oriented software quality, object-orienteddesign, class cohesion.

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Authors: Myo Min Aung, Yoon Seok Chang, Woo Ram Kim

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This paper presents a cold chain monitoring system which focuses on assessment of quality and dynamic pricing information about food in cold chain. Cold chain is composed of many actors and stages; however it can be seen as a single entity since a breakdown in temperature control at any stage can impact the final quality of the product. In a cold chain, the shelf life, quality, and safety of perishable food throughout the supply chain is greatly impacted by environmental factors especially temperature. In this paper, a prototype application is implemented to retrieve timetemperature history, the current quality and the dynamic price setting according to changing quality impacted by temperature fluctuations in real-time.

Keywords: Cold chain, monitoring, quality, temperature, traceability.

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Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) hold significant value for their capacity to undertake hazardous and labor-intensive operations over aquatic environments. Object detection tasks are significant in these applications. Nonetheless, the efficacy of USVs in object detection is impeded by several intrinsic challenges, including the intricate dispersal of obstacles, reflections emanating from coastal structures, and the presence of fog over water surfaces, among others. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. The MMW radar is a complementary tool to vision sensors, offering reliable environmental data. This approach involves the conversion of the radar’s 3D point cloud into a 2D radar pseudo-image, thereby standardizing the format for radar and vision data by leveraging a point transformer. Furthermore, this paper proposes the development of a multi-source object detection network, named RV-YOLOX, which leverages radar-vision integration specifically tailored for inland waterway environments. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: Inland waterways, object detection, YOLO, sensor fusion, self-attention, deep learning.

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: Computer-aided system, detection, image segmentation, morphology.

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Authors: A. Beduk, K. Eryesil, O. Esmen

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The aim of this study is to examine the relationship between organizational commitment which is defined as a strong belief in and acceptance of the organization’s goals and values, and burnout syndrome and organizational cynicism. Accordingly, a field research based on survey method was conducted on the employees of a health institution operating in the province of Konya. The findings of the research show that there is a positive statistically significant relationship between organizational cynicism and burnout while there is a negative statistically significant relationship between organizational commitment and burnout. Furthermore, it has been also realized that there is a negative and statistically significant relationship between organizational commitment and organizational cynicism.

Keywords: Burnout, organizational commitment, organizational cynicism, healthcare management.

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Authors: S. Velmurugan, K. B. Akhilesh

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In the past few decades, researchers have witnessed a paradigm shift in Human Resource Management-from individual performance to organizational outcomes with the role of Human resource (HR) managers becoming increasingly significant to the organization. In such a context, it is important to examine HR practices from a strategic perspective on the sustained competitive advantage (SCA) of the organizations. The present study explores how Indian organisations look at their human resources strategically when faced with competitive environment. Also, it explores strategic initiatives being taken to manage human resources within the organisations and how these initiatives promote SCA in terms of enhancing the overall customer-centric delivery of goods and services.

Keywords: Strategic HRM, Strategic HRM Initiatives, Consequences, and Sustained Competitive Advantage.

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Authors: Hamza A. Ali, Waleed A. J. Rasheed

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The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.

Keywords: Classification, Recognition, Neural Networks, Pattern Recognition, Generalization.

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Authors: Davinder Singh, Jaimal Singh Khamba, Tarun Nanda

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The importance of MSMEs in India became crucial in rural areas because it promoted economic growth. MSMEs play a significant role in the economic growth of the country owing to production, exports and employment. Technology development reflect a critical way in which organization respond to either technological or market challenges. The present survey examines the characteristics of technology development in MSMEs. The results show that Indian MSMEs do not co-operate with universities and R&D institutes. Government policies also affect the technology development activities. The awareness about the R&D infrastructure is very low as shown by the results in the study. There is a need to understand and assess the real needs of the MSMEs and accordingly devise approaches that ensure their sustainable growth.

Keywords: MSMEs, technology development, networks, financial management and R&D infrastructure.

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Authors: F.Katlane, M.S.Naceur, M.A.Loghmari

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Automatic methods of detecting changes through satellite imaging are the object of growing interest, especially beca²use of numerous applications linked to analysis of the Earth’s surface or the environment (monitoring vegetation, updating maps, risk management, etc...). This work implemented spatial analysis techniques by using images with different spatial and spectral resolutions on different dates. The work was based on the principle of control charts in order to set the upper and lower limits beyond which a change would be noted. Later, the a contrario approach was used. This was done by testing different thresholds for which the difference calculated between two pixels was significant. Finally, labeled images were considered, giving a particularly low difference which meant that the number of “false changes” could be estimated according to a given limit.

Keywords: multi-scale, a contrario approach, significantthresholds, change detection.

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: Automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation.

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Authors: E. J. Cilliers

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It is the living conditions in the cities that determine the future of our livelihood. “To change life, we must first change space"- Henri Lefebvre. Sustainable development is a utopian aspiration for South African cities (especially the case study of the Gauteng City Region), which are currently characterized by unplanned growth and increasing urban sprawl. While the reasons for poor environmental quality and living conditions are undoubtedly diverse and complex, having political, economical and social dimensions, it is argued that the prevailing approach to layout planning in South Africa is part of the problem. This article seeks a solution to the problem of sustainability, from a spatial planning perspective. The spatial planning tool, the urban development boundary, is introduced as the concept that will ensure empty talk being translated into a sustainable vision. The urban development boundary is a spatial planning tool that can be used and implemented to direct urban growth towards a more sustainable form. The urban development boundary aims to ensure planned urban areas, in contrast to the current unplanned areas characterized by urban sprawl and insufficient infrastructure. However, the success of the urban development boundary concept is subject to effective implementation measures, as well as adequate and efficient management. The concept of sustainable development can function as a driving force underlying societal change and transformation, but the interface between spatial planning and environmental management needs to be established (as this is the core aspects underlying sustainable development), and authorities needs to understand and implement this interface consecutively. This interface can, however, realize in terms of the objectives of the planning tool – the urban development boundary. The case study, the Gauteng City Region, is depicted as a site of economic growth and innovation, but there is a lack of good urban and regional governance, impacting on the design (layout) and function of urban areas and land use, as current authorities make uninformed decisions in terms of development applications, leading to unsustainable urban forms and unsustainable nodes. Place and space concepts are thus critical matters applicable to planning of the Gauteng City Region. The urban development boundary are thus explored as a planning tool to guide decision-making, and create a sustainable urban form, leading to better environmental and living conditions, and continuous sustainability.

Keywords: Urban planning, sustainable urban form, urbandevelopment boundary, planning tool.

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of project scheduling and material ordering has been increasingly addressed within last decades as an approach to improve the project execution costs. Therefore, we have taken the problem into consideration in this paper, aiming to maximize schedules quality robustness, in addition to minimize the relevant costs. In this regard, a bi-objective mathematical model is developed to formulate the problem. Moreover, it is possible to utilize the all-unit discount for materials purchasing. The problem is then solved by the E-constraint method, and the Pareto front is obtained for a variety of robustness values. The applicability and efficiency of the proposed model is tested by different numerical instances, finally.

Keywords: E-constraint method, material ordering, project management, project scheduling.

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Authors: Noor Ayuni Che Zakaria, Takashi Komeda, Cheng Yee Low, Kaoru Inoue, Fazah Akhtar Hanapiah

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Previous studies have shown that there are arguments regarding the reliability and validity of the Ashworth and Modified Ashworth Scale towards evaluating patients diagnosed with upper limb disorders. These evaluations depended on the raters’ experiences. This initiated us to develop an upper limb disorder part-task trainer that is able to simulate consistent upper limb disorders, such as spasticity and rigidity signs, based on the Modified Ashworth Scale to improve the variability occurring between raters and intra-raters themselves. By providing consistent signs, novice therapists would be able to increase training frequency and exposure towards various levels of signs. A total of 22 physiotherapists and occupational therapists participated in the study. The majority of the therapists agreed that with current therapy education, they still face problems with inter-raters and intra-raters variability (strongly agree 54%; n = 12/22, agree 27%; n = 6/22) in evaluating patients’ conditions. The therapists strongly agreed (72%; n = 16/22) that therapy trainees needed to increase their frequency of training; therefore believe that our initiative to develop an upper limb disorder training tool will help in improving the clinical education field (strongly agree and agree 63%; n = 14/22).

Keywords: Upper limb disorders, Clinical education tool, Inter/intra-raters variability, Spasticity, Modified Ashworth Scale.

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Authors: Jiakai Li, Gursel Serpen, Steven Selman, Matt Franchetti, Mike Riesen, Cynthia Schneider

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This paper presents the development of a Bayesian belief network classifier for prediction of graft status and survival period in renal transplantation using the patient profile information prior to the transplantation. The objective was to explore feasibility of developing a decision making tool for identifying the most suitable recipient among the candidate pool members. The dataset was compiled from the University of Toledo Medical Center Hospital patients as reported to the United Network Organ Sharing, and had 1228 patient records for the period covering 1987 through 2009. The Bayes net classifiers were developed using the Weka machine learning software workbench. Two separate classifiers were induced from the data set, one to predict the status of the graft as either failed or living, and a second classifier to predict the graft survival period. The classifier for graft status prediction performed very well with a prediction accuracy of 97.8% and true positive values of 0.967 and 0.988 for the living and failed classes, respectively. The second classifier to predict the graft survival period yielded a prediction accuracy of 68.2% and a true positive rate of 0.85 for the class representing those instances with kidneys failing during the first year following transplantation. Simulation results indicated that it is feasible to develop a successful Bayesian belief network classifier for prediction of graft status, but not the graft survival period, using the information in UNOS database.

Keywords: Bayesian network classifier, renal transplantation, graft survival period, United Network for Organ Sharing

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Authors: Somorjeet Sharma Shamurailatpam, Rabindra Das, A. Suchitra Devi

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Computer and video display users might complain about Asthenopia, burning, dry eyes etc. The management of dry eyes is often not in the lines of severity. Following systematic evaluation and grading, dry eye disease is one condition that can be practiced at all levels of ophthalmic care. In the present study, different spectrum causing dry eye and prevalence of dry eye disease in computer users of Manipur, India are determined with 600 individuals (300 cases and 300 control). Individuals between 15 and 50 years who used computers for more than 3 hrs a day for 1 year or more were included. Tear break up time (TBUT) and Schirmer’s test were conducted. It shows that 33 (20.4%) out of 164 males and 47 (30.3%) out of 136 females have dry eye. Possible explanation for the observed result is discussed.

Keywords: Asthenopia, computer vision syndrome, dry eyes, Schirmer’s test, tear breakup time.

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Authors: Rade M. Ciric

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The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.

Keywords: Engineering education, power distribution network, syllabus implementation, outcome evaluation.

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Authors: N. Nor Azman, M. F. Kamarudin, S. I. Ong, N. Maaulot

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PERMATApintar^® National Gifted Center is, to the author’s best of knowledge, the first center in Malaysia that provides a platform for Malaysian talented students with high ability in thinking. This center has built a teaching and learning biology curriculum that suits the ability of these gifted students. The level of PERMATApintar^® biology curriculum is basically higher than the national biology curriculum. Here, the foundation students are exposed to the PERMATApintar^® biology curriculum at the age of as early as 11 years old. This center practices a 4-time-a-year examination system to monitor the academic performances of the students. Generally, most of the time, male students show no or low interest towards biology subject compared to female students. This study is to investigate the association of students’ gender and their academic performances in biology examination. A total of 39 students’ scores in twelve sets of biology examinations in 3 years have been collected and analyzed by using the statistical analysis. Based on the analysis, there are no significant differences between male and female students against the biology academic performances with a significant level of p = 0.05. This indicates that gender is not associated with the scores of biology examinations among the students. Another result showed that the average score for male studenta was higher than the female students. Future research can be done by comparing the biology academic achievement in Malaysian National Examination (Sijil Pelajaran Malaysia, SPM) between the Foundation 3 students (Grade 9) and Level 2 students (Grade 11) with similar PERMATApintar^® biology curriculum.

Keywords: Academic performances, biology, gender differences, gifted students.

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Authors: S. M. Abdur Razzak, M. A. Rashid, Y. Namihira, A. Sayeem

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A simple microstructure optical fiber design based on an octagonal cladding structure is presented for simultaneously controlling dispersion and leakage properties. The finite difference method with anisotropic perfectly matched boundary layer is used to investigate the guiding properties. It is demonstrated that octagonal photonic crystal fibers with four rings can assume negative ultra-flattened dispersion of -19 + 0.23 ps/nm/km in the wavelength range of 1.275 μm to 1.68 μm, nearly zero ultra-flattened dispersion of 0 ± 0.40 ps/nm/km in a 1.38 to 1.64 μm, and low confinement losses less than 10-3 dB/km in the entire band of interest.

Keywords: Finite difference modeling, group velocity dispersion, optical fiber design, photonic crystal fiber.

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Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

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Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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Authors: Babak Tashakori Bafghi, Laleh Tashakori, Reza Allahyari Soeini, Mohammad Mokhtari

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Supplier selection is a multi criteria decision-making process that comprises tangible and intangible factors. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. For the first, time in this paper, the idea of the algorithm " Knapsack " is used to select suppliers Moreover, an attempt has to be made to take the advantage of a simple numerical method for solving model .This is an innovation to resolve any ambiguity in choosing suppliers. This model has been tried in the suppliers selected in a competitive environment and according to all desired standards of quality and quantity to show the efficiency of the model, an industry sample has been uses.

Keywords: Knapsack, linear programming, supplier select, supply chain management.

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Authors: Zhang Lei, Zhan Haiyang, Gu Miao

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A universal software platform is developed for improving the defects in the practical one. This software platform has distinct advantages in modularization, information management, and the interfaces. Several technologies such as computer technology, virtualization technology, network technology, etc. are combined together in this software platform, and four working modes are introduced in this article including single mode, distributed mode, cloud mode, and the centralized mode. The application area of the software platform is extended through the switch between these working modes. The software platform can arrange the thermal vacuum test process automatically. This function can improve the reliability of thermal vacuum test.

Keywords: Software platform, thermal vacuum test, control and measurement, work mode.

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Authors: Wei Sun, Yan Dong

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There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.

Keywords: Robotics, computational thinking, programming, young children, flowcharts.

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Authors: Nomataru P. Gontse, Lavanithum Joseph

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Deafness coupled with a lack of support and resources in developing countries poses a serious threat to the well- being of children. The mismatch between the needs of persons with disabilities and the resources available to them is a key factor in service provision in resource constrained contexts. Furthermore, deafness in children is the most common childhood sensory disorder in developing countries, and as such seriously affected with regard to resource constraints. This paper discusses the issues and research protocol for a Ph.D. study that aims to develop a practice guideline that is contextually sensitive and includes an interdisciplinary approach that will improve the outcomes of learners and the relationships in hearing households with deaf learners in rural areas of the Eastern Cape, one of the poorest provinces in South Africa. The guideline developed will consider the lived experiences of deaf children and their hearing families on the impact deafness has on their relationships and communication at home. Ethical clearance for the study has been obtained. The methodology is a mixed-methods approach in the form of a survey using questionnaires and semi-structured interviews with deaf learners in primary and high school and their hearing parents to get their perspective on the impact deafness has on their relationships and communication at home. The study is conducted using adolescent learners from Grades 7 to 12 (excluding learners younger than 12 years and older than 21 years). An audiologist, teachers, and support staff will also give their views on how the intervention is currently done and possible suggestions on how management can be done differently. Data collection will be conducted in isiXhosa by the researcher, as isiXhosa is dominant in this region. The interviews will be conducted in South African Sign Language by the sign language interpreter for deaf learners and educational professionals. An expected outcome for this study is the development of recommendations and a practice guideline for deaf children diagnosed late from rural or under-resourced environments. To ensure the implementation of the findings, in the end, professionals will be given feedback on the outcomes of the study so that they can identify areas within their practices that require updated knowledge. The developed guideline is expected to have an impact on the Department of Education policies both regionally and nationally, providing recommendations for a strategic management plan and practice guidelines for this vulnerable and marginalized population. The IsiXhosa specific context could be generalized to other similar contexts.

Keywords: Deafness, family-centred approach, early identification, rural communities.

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Authors: Hwan Su Jung, Ahn Jun Gil, Jong Tae Kim

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Power management techniques are necessary to save power in the microprocessor. By changing the frequency and/or operating voltage of processor, DVFS can control power consumption. In this paper, we perform a case study to find optimal power state transition for DVFS. We propose the equation to find the optimal ratio between executions of states while taking into account the deadline of processing time and the power state transition delay overhead. The experiment is performed on the Cortex-M4 processor, and average 6.5% power saving is observed when DVFS is applied under the deadline condition.

Keywords: Deadline, Dynamic Voltage Frequency Scaling, Power State Transition.

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Authors: Mehran Garmehi, Yasser Mansouri

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There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.

Keywords: QoS, Differentiated Service (DiffServ), FuzzyController, Delay.

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Authors: Majid Abdolrazzagh-Nezhad, Salwani Abdullah

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The job-shop scheduling problem (JSSP) is an important decision facing those involved in the fields of industry, economics and management. This problem is a class of combinational optimization problem known as the NP-hard problem. JSSPs deal with a set of machines and a set of jobs with various predetermined routes through the machines, where the objective is to assemble a schedule of jobs that minimizes certain criteria such as makespan, maximum lateness, and total weighted tardiness. Over the past several decades, interest in meta-heuristic approaches to address JSSPs has increased due to the ability of these approaches to generate solutions which are better than those generated from heuristics alone. This article provides the classification, constraints and objective functions imposed on JSSPs that are available in the literature.

Keywords: Job-shop scheduling, classification, constraints, objective functions.

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Authors: A. Todorut, T. Heput

Abstract:

In technological processes, in addition to the main product, result a large amount of materials, called wastes, but due to the possibilities of recovery, by means of recycling and reusing it can fit in the category of by-products. These large amounts of dust from the steel industry are a major problem in terms of environmental and human health, landscape, etc. Solving these problems, the impressive amounts of waste can be done through their proper management and recovery for every type of waste. In this article it was watched the capitalizing through pelleting and briquetting of small and powdery waste aiming to obtain the sponge iron as raw material, used in blast furnaces and electric arc furnaces. The data have been processed in the Excel spreadsheet program, being presented in the form of diagrams.

Keywords: Agglomeration, industry, iron, pellets, wastes.

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: Structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm.

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