Search results for: online database

Authors: Yassine Jadi, Lin Jie

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In order to serve the society in an electronic manner, many developing countries have launched tremendous e-government projects. The strategies of development and implementation e-government system have reached different levels, and to ensure consistency of development, the governments need to evaluate e-government performance. The United nation has design e-government development ranking index (EGDI) that rely on three indexes, Online service index (OSI), Telecommunication Infrastructure index (TII), and human capital index( HCI) which are not reflecting the interaction between a government and their citizens. Based on data envelopment analyses (DEA) technique, we are using E-participating index (EPI) as an output of government effort to evaluate the performance of e-government system. Therefore, the ranking index can be achieved in efficiency manner.

Keywords: e-government, DEA, efficiency measurement, EGDI

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Authors: Konstantinos Sofianos, Michael Stefanidakis

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Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in the field of education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at any time, in any place, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

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Authors: Wided Bakari, Patrce Bellot, Mahmoud Neji

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With the development of electronic media and the heterogeneity of Arabic data on the Web, the idea of building a clean corpus for certain applications of natural language processing, including machine translation, information retrieval, question answer, become more and more pressing. In this manuscript, we seek to create and develop our own corpus of pair’s questions-texts. This constitution then will provide a better base for our experimentation step. Thus, we try to model this constitution by a method for Arabic insofar as it recovers texts from the web that could prove to be answers to our factual questions. To do this, we had to develop a java script that can extract from a given query a list of html pages. Then clean these pages to the extent of having a database of texts and a corpus of pair’s question-texts. In addition, we give preliminary results of our proposal method. Some investigations for the construction of Arabic corpus are also presented in this document.

Keywords: Arabic, web, corpus, search engine, URL, question, corpus building, script, Google, html, txt

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Authors: Yiwei Li, Mingyu Gao

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Integrating hybrid memories with heterogeneous processors could leverage heterogeneity in both compute and memory domains for better system efficiency. To ensure performance isolation, we introduce Hydrogen, a hardware architecture to optimize the allocation of hybrid memory resources to heterogeneous CPU-GPU systems. Hydrogen supports efficient capacity and bandwidth partitioning between CPUs and GPUs in both memory tiers. We propose decoupled memory channel mapping and token-based data migration throttling to enable flexible partitioning. We also support epoch-based online search for optimized configurations and lightweight reconfiguration with reduced data movements. Hydrogen significantly outperforms existing designs by 1.21x on average and up to 1.31x.

Keywords: hybrid memory, heterogeneous systems, dram cache, graphics processing units

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Authors: Spanova Yerkezhan, Amantay Ayan, Alimzhanova Laura

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This article discusses the concept of rebranding and its relationship to cybersecurity. Rebranding is the process of changing the appearance and image of a company or organization in order to appeal to new customers or change the perception of a company. It can be a powerful tool for businesses looking to renew their reputation or expand into new markets. In today's digital age, companies increasingly rely on technology and the internet to conduct business; rebranding can also present significant cybersecurity risks. This is because a rebranding effort can create new vulnerabilities for companies, particularly in terms of their online presence. This article explores the potential hazards associated with rebranding and provides recommendations for mitigating those risks. It also highlights the importance of considering cybersecurity in the rebranding process and how it can be integrated into the overall strategy for a successful and secure rebranding.

Keywords: rebranding, cybersecurity, cyberattack, logo, vulnerability

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Authors: Pijitra Jomsri

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Currently, the sources of cultures and tourist attractions are presented in online documentary form only. In order to make them more virtual, the researcher then collected and presented them in the form of Virtual Temple. The prototype, which is a replica of the actual location, was developed to the website and allows people who are interested in Rattanakosin Island can see in form of Panorama Pan View. By this way, anyone can access the data and appreciate the beauty of Rattanakosin Island in the virtual model like the real place. The result from the experiment showed that the levels of the knowledge on Thai temples in Rattanakosin Island increased; moreover, the users were highly satisfied with the systems. It can be concluded that virtual temples can support to publicize Thai arts, cultures and travels, as well as it can be utilized effectively.

Keywords: virtual sight-seeing, Rattanakosin Island, Thai temples, virtual temple

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Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: B. Madhevan, R. Sakkaravarthi, R. Diya

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The number and variety of mobile robot applications are increasing day by day, both in an industry and in our daily lives. First developed as a tool, nowadays mobile robots can be integrated as an entity in Internet-accessible resources. The present work is organized around four potential resources such as cloud computing, Internet of things, Big data analysis and Co-simulation. Further, the focus relies on integrating, analyzing and discussing the need for integrating Internet-accessible resources and the challenges deriving from such integration, and how these issues have been tackled. Hence, the research work investigates the concepts of the Internet-accessible resources from the aspect of the autonomous mobile robots with an overview of the performances of the currently available database systems. IaR is a world-wide network of interconnected objects, can be considered an evolutionary process in mobile robots. IaR constitutes an integral part of future Internet with data analysis, consisting of both physical and virtual things.

Keywords: internet-accessible resources, cloud computing, big data analysis, internet of things, mobile robot

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Authors: Taissir Fekih Romdhane

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This paper proposes a mobile web application named Pharmacy-Station that sells medicines and permits user to search for medications based on their symptoms, making it is easy to locate a specific drug online without the need to visit a pharmacy where it may be out of stock. This application is developed using the jQuery Mobile framework, which uses many web technologies and languages such as HTML5, PHP, JavaScript and CSS3. To test the proposed application, we used data from popular pharmacies in Saudi Arabia that included important information such as location, contact, and medicines in stock, etc. This document describes the different steps followed to create the Pharmacy-Station application along with screenshots. Finally, based on the results, the paper concludes with recommendations and further works planned to improve the Pharmacy-Station mobile application.

Keywords: pharmacy, mobile application, jquery mobile framework, search, medicine

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Authors: Mouhammd Alkasassbeh, Alaa Lasasmeh

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We live in an era of rapid development as a result of significant scientific growth. Like other technologies, wireless sensor networks (WSNs) are playing one of the main roles. Based on WSNs, ZigBee adds many features to devices, such as minimum cost and power consumption, and increasing the range and connect ability of sensor nodes. ZigBee technology has come to be used in various fields, including science, engineering, and networks, and even in medicinal aspects of intelligence building. In this work, we generated two main datasets, the first being based on tree topology and the second on star topology. The datasets were evaluated by three machine learning (ML) algorithms: J48, meta.j48 and multilayer perceptron (MLP). Each topology was classified into normal and abnormal (attack) network traffic. The dataset used in our work contained simulated data from network simulation 2 (NS2). In each database, the Bayesian network meta.j48 classifier achieved the highest accuracy level among other classifiers, of 99.7% and 99.2% respectively.

Keywords: IDS, Machine learning, WSN, ZigBee technology

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Authors: Jung-Ho Moon, Myung-Gon Yoon, Tae Kwon Ha

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High temperature deformation behavior of cast 310S stainless steel has been investigated in this study by performing tensile and compression tests at temperatures from 900 to 1200°C. Rectangular ingots of which the dimensions were 350×350×100 in millimeter were cast using vacuum induction melting. Phase equilibrium was calculated using the FactSage®, thermodynamic software and database. Thermal expansion coefficient was also measured on the ingot in the temperature range from room temperature to 1200°C. Tensile strength of cast 310S stainless steel was 9 MPa at 1200°C, which is a little higher than that of a wrought 310S. With temperature decreased, tensile strength increased rapidly and reached up to 72 MPa at 900°C. Elongation also increased with temperature decreased. Microstructure observation revealed that σ phase was precipitated along the grain boundary and within the matrix over 1200°C, which is detrimental to high temperature elongation.

Keywords: stainless steel, STS 310S, high temperature deformation, microstructure, mechanical properties

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Authors: Sujin Hwang, Hyerang Park, Hyunchul Kim

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The purpose of this study is to find the effectiveness of the admission simplification policy. The number of online news articles about ‘high school record’ was collected and semantically analyzed to identify and analyze the social awareness during 2014 to 2015. The main results of the study are as follows: First, there was a difference in expectations that the burden of the examinees would decrease as announced by KCUE. Thus, there was still a strain on the university entrance exam after the enforcement of the policy. Second, private tutoring is expanding in different forms, rather than reducing the policy. It is different from the prediction that examinees can prepare for university admissions without the private tutoring. Thus, the college admission rules currently enforced needs to be improved. The reasonable college admission system changes are discussed.

Keywords: education policy, private tutoring, shadow education, education admission policy

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Authors: Selina Studer, Maria Kleinstäuber, Cornelia Weise

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Background: Finding words to report what you have been through may be challenging, especially when dealing with stressful or highly emotional experiences. Photovoice (PV) represents a possible way of facilitating experience reporting. In this approach, people take photos about a particular topic (in our study: worries about the future) and talk about the topic based on the photos. So far, the benefits of Photovoice have been quantitatively insufficiently tested. There is a lack of randomized controlled trials investigating PV in comparison to other methods. This study aimed to fill this research gap. Methods: 65 participants took part in the study and were randomly assigned to the PV group, the writing group (WG), or the control group (CG). The PV group received the task to take photos of worries regarding the future for one week and send max. 5 of them to the interviewer before the interview. The WG had to write down the worries about the future and send max. 5 of them to the interviewer before the interview. The control group did not receive a specific assignment. The semi-structured interview consisted of six open-ended questions and was applied to all future worries. The questions included the content of the future worries, the meaning, and how the worry expressed itself emotionally and physically. The interview was recorded and later transcribed. After the interview, online questionnaires were filled out. They covered a range of variables such as access to emotional content, ability to describe feelings, the extent of self-disclosure, and relationship quality. Results: Contrary to our hypotheses, one-way ANOVA revealed no differences between the three conditions concerning all variables (access to emotional content, ability to describe feelings, the extent of self-disclosure, and so on), all p's > 0.14, BF₀₁ = 1.78-7.66. In a subsequent step, the words in the transcribed interviews were analyzed. The LIWC program counted how many emotional words occurred in the text and assigned them to predefined categories. Planned contrasts revealed that the PV reported more negative emotional words compared to the two groups t(62) = 2.62, p = .011, and also compared to the WG only, t(62) = 2.36, p = .022, BF₀₁ = 0.62. Conclusions and implications: The applied self-report instruments did not reveal any differences between the groups. However, the PV group used more negative emotional words than the other two groups. The discrepancy between self-report and observation variables regarding emotionality is noticeable. It is suggested that the highly educated and above-average female sample may not have needed PV to access emotional content. It is possible that the approach would yield clearer results in a clinical sample. This and other approaches are currently being investigated in a follow-up study.

Keywords: photovoice, controlled randomized study, online intervention, emotional awareness, self-disclosure, data triangulation, interviews

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Authors: Watheq Mansour, Waleed Bin Owais, Mohammad Basheer Kotit, Khaled Khan

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Efficient query processing is one of the utmost requisites in any business environment to satisfy consumer needs. This paper investigates the various types of indexing models, viz. primary, secondary, and multi-level. The investigation is done under the ambit of various types of queries to which each indexing model performs with efficacy. This study also discusses the inherent advantages and disadvantages of each indexing model and how indexing models can be chosen based on a particular environment. This paper also draws parallels between various indexing models and provides recommendations that would help a Database administrator to zero-in on a particular indexing model attributed to the needs and requirements of the production environment. In addition, to satisfy industry and consumer needs attributed to the colossal data generation nowadays, this study has proposed two novel indexing techniques that can be used to index highly unstructured and structured Big Data with efficacy. The study also briefly discusses some best practices that the industry should follow in order to choose an indexing model that is apposite to their prerequisites and requirements.

Keywords: indexing, hashing, latent semantic indexing, B-tree

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Authors: Dung Nguyen, Yu Wei, Eric Henderson

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Analytical tools have been used for decades to assist in the development of forest plans. In 2016, a new decision support system, PRISM, was jointly developed by United States Forest Service (USFS) Northern Region and Colorado State University to support the forest planning process. Prism has a friendly user interface with functionality for database management, model development, data visualization, and sensitivity analysis. The software is tailored for USFS planning, but it is flexible enough to support planning efforts by other forestland owners and managers. Here, the core capability of PRISM and its applications in developing plans for several United States national forests are presented. The strengths of PRISM are also discussed to show its potential of being a preferable tool for managers and experts in the domain of forest management and planning.

Keywords: decision support, forest management, forest plan, graphical user interface, software

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Authors: Laidi Maamar, Hanini Salah

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The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: Sung Ho Ahn, Jintae Hong, Chang Young Joung, Tae Ho Yang, Sung Ho Heo, Seo Yun Jang

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The performances of nuclear fuels and materials are qualified at an irradiation system in research reactors operating under the commercial nuclear power plant conditions. Fuel centerline temperature, coolant temperature, neutron flux, deformations of fuel stack and swelling are important parameters needed to analyze the nuclear fuel performances. The dimensional stability of nuclear fuels is a key parameter measuring the fuel densification and swelling. In this study, the fuel stack elongation is measured using a LVDT. A mockup LVDT instrumented fuel rod is developed. The performances of mockup LVDT instrumented fuel rod is evaluated by experiments.

Keywords: axial deformation, elongation measurement, in-pile instrumentation, LVDT

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Authors: Zhengrong Wu, Haibo Yang

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In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

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Authors: Asaolu Olugbenga Stephen, Afolabi Olusegun Temitope

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Lack of proper solid waste management is one of the main causes of environmental pollution and degradation in many cities, especially in developing countries. The aim of this study was to estimate the quantity of waste generated per capita per day, determine the composition and identify the potentials for recycling of waste generated. Characterization of wastes from selected households in the residential areas was done for over a 7 day period. The weight of each sorted category of waste was recorded in a structured database that calculated the proportion of each waste component. The results indicated that 85.4% of the sampled waste characterized was found to be recyclable; with an estimated average waste generated of 1.82kg/capita/day. The various solid waste fractions were organic (64.6%), plastics (15.6%), metals (9.2%), glass materials (1.6%) and unclassified (8.9%). It was concluded from this study that a large proportion of the waste generated from OAU campus residential area was recyclable and that there is a need to enact policy on waste recycling within the university campus.

Keywords: recycling, household wastes, residential, solid waste management

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Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

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The study attempts to analyze the impact of credit risk management practices of Indian scheduled commercial banks on their non-performing assets (NPAs). The data on credit risk practices was collected by administering a questionnaire to risk managers/executives at different banks. The data on NPAs (from 2012 to 2016) is sourced from Prowess, a database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was estimated using cross-sectional regression method. As expected, the findings suggest that there is a negative relationship between credit risk management and NPA growth in Indian banks. The study has implications for Indian banks given the high level of losses, and the implementation of Basel III norms by the central bank, i.e. Reserve Bank of India (RBI). Evidence on credit risk management in Indian banks, and their relationship with non-performing assets held by them.

Keywords: credit risk, identification, Indian Banks, NPAs, ownership

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Authors: Hashini E. Mohottala

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We report the combine use of Wikispaces (WikiS) and Group Problem Solving (GPS) sessions conducted in the introductory level physics classes. As a part of this new teaching tool, some essay type problems were posted on the WikiS in weekly basis and students were encouraged to participate in problem solving without providing numerical final answers but the steps. Wikispace is used as a platform for students to meet online and create discussions. Each week students were further evaluated on problem solving skills opening up more opportunity for peer interaction through GPS. Each group was given a different problem to solve and the answers were graded. Students developed a set of skills in decision-making, problem solving, communication, negotiation, critical and independent thinking and teamwork through the combination of WikiS and GPS.

Keywords: group problem solving (GPS), wikispace (WikiS), physics education, learning

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Authors: Maria Cecilia G. Cantos, Lorena W. Rabago, Bartolome T. Tanguilig III

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This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in. The system was developed to help the students to check their academic result, manage profile, make self-enlistment and assist the students to manage their academic status that can be viewed also in mobile phones. Developing class schedules in a traditional way is a long process that involves making many numbers of choices. With Hill Climbing Algorithm, however, the process of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database.

Keywords: hill climbing algorithm, integrated system, mobile web-based, student information system

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Said Fares, Mary Fares

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It is well documented that introductory computer programming courses are difficult and that failure rates are high. The aim of this project was to reduce the high failure and withdrawal rates in learning to program. This paper presents a number of changes in module organization and instructional delivery system in teaching CS1. Daily out of class help sessions and tutoring services were applied, interactive lectures and laboratories, online resources, and timely feedback were introduced. Five years of data of 563 students in 21 sections was collected and analyzed. The primary results show that the failure and withdrawal rates were cut by more than half. Student surveys indicate a positive evaluation of the modified instructional approach, overall satisfaction with the course and consequently, higher success and retention rates.

Keywords: failure rate, interactive learning, student engagement, CS1

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Authors: S. Jagadeesh Kumar

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Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

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Authors: Vikram Munjal, Harpreet Munjal

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A few years ago we could hardly think of Libraries' strategic plan that includes the bold and amazing prediction of a mostly digital environment for a library system. However, sheer hard work by the engineers, academicians, and librarians made it feasible. However, it requires huge expenditure and now a day‘s spending for electronic resources (e-resources) have been growing much more rapidly than have the materials budgets of which such resources are usually a part. And many libraries are spending a huge amount on e-resources. Libraries today are in the midst of a profound shift toward reliance on e-resources, and this reliance seems to have deepened in recent years as libraries have shed paper journal subscriptions to help pay for online access. This has been exercised only to cater user behavior and attitudes that seem to be changing even more quickly in this dynamic scenario.

Keywords: radio frequency identification, management, scanning, barcodes, checkout and tags

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Authors: Salwa Aftab, Sehrish Riaz

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The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: academic performance, correlation, grade sensitivity, learning motivation, regression

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Authors: Mohammad Yousuf Khan, Bhavya Alankar

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Blockchain is a promising technology with its features such as immutability and decentralized database. It has applications in various fields such as pharmaceutical, finance, & the food industry. At the core of its heart lies its feature, traceability which is the most desired key in supply chains. However, supply chains have always been hit rock bottom by scandals and controversies. In this review paper, we have explored the advancement and research gaps of blockchain technology (BT) in supply chain management (SCM). We have used the Prisma framework for systematic literature review (SLR) and included a minuscule amount of grey literature to reduce publication bias. We found that supply chain traceability and transparency is the most researched objective in SCM. There was hardly any research in supply chain resilience. Further, we found that 40 % of the papers were application based. Most articles have focused on the advantages of BT, rather than analyzing it critically. This study will help identify gaps and suitable actions to be followed for an efficient implementation of BT in SCM.

Keywords: blockchain technology, supply chain management, supply chain transparency, supply chain resilience

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Authors: Mohsen Shirani, Shadi Asadzandi, Micaela Demichela

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This paper presents the results of a study to assess crucial aspects and the strength of the scientific basis of a typically interdisciplinary, applied field: food supply chain risk assessment research. Our approach is based on an advanced scientometrics analysis with novel elements to assess the influence and dissemination of research results and to measure interdisciplinary. This paper aims to describe the quantity and quality of the publication trends in food supply chain risk assessment. The population under study was composed of 266 articles from database web of science. The results were analyzed based on date of publication, type of document, language of the documents, source of publications, subject areas, authors and their affiliations, and the countries involved in developing the articles.

Keywords: food supply chain, risk assessment, scientometrics, web of science

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