Search results for: information%20technology%20%28IT%29

Authors: Hamid Yasinian

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Random epistemologies and hash tables have garnered minimal interest from both security experts and experts in the last several years. In fact, few information theorists would disagree with the evaluation of expert systems. In our research, we discover how flip-flop gates can be applied to the study of superpages. Though such a hypothesis at first glance seems perverse, it is derived from known results.

Keywords: synthesis, multi-processors, interactive model, moor’s law

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Authors: Sabahat Nadeem, Farman Ali Khan

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Emotions are considered as a vital factor affecting the process of information handling, level of attention, memory capacity and decision making. Latest e-Learning systems are therefore taking into consideration the effective state of learners to make the learning process more effective and enjoyable. One such use of user’s affective information is in the systems that tend to regulate users’ emotions to a state optimally desirable for learning. So for, this objective has been tried to be achieved with the help of teaching strategies, background music, guided imagery, video clips and odors. Nevertheless, we know that colors can affect human emotions. Relationship between color and emotions has a strong influence on how we perceive our environment. Similarly, the colors of the interface can also affect the user positively as well as negatively. This affective behavior of color and its use as emotion regulation agent is not yet exploited. Therefore, this research proposes a Color-based Emotion Regulation Model (CERM), a new framework that can automatically adapt its colors according to user’s emotional state and her personality type and can help in producing a desirable emotional effect, aiming at providing an unobtrusive emotional support to the users of e-learning environment. The evaluation of CERM is carried out by comparing it with classical non-adaptive, static colored learning management system. Results indicate that colors of the interface, when carefully selected has significant positive impact on learner’s emotions.

Keywords: effective learning, e-learning, emotion regulation, emotional design

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Authors: Iwuchukwu J. C., Mbah C.

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There seems to be dearth on information on how oil bean is being exploited, processed and conserved locally. This gap stifles initiatives on the evaluation of the suitability of the methods used and the invention of new and better methods. The study; therefore, assesses activities of processors in domestication/conservation and processing of oil bean (Pentaclethra macrophylla) Enugu State, South East Nigeria. Three agricultural zones, three blocks, nine circles and seventy-two respondents that were purposively selected made up the sample for the study. Data were presented in percentage, chart and mean score. The result shows that processors of oil bean in the area were middle-aged, married with relatively large household size and long years of experience in processing. They sourced oil bean they processed from people’s farmland and sourced information on processing of oil bean from friends and relatives. Activities involved in processing of oil bean were boiling, dehulling, washing, sieving, slicing, wrapping. However, the sequence of these activities varies among these processors. Little or nothing was done by the processors towards the conservation of the crop while poor storage and processing facilities and lack of knowledge on modern preservation technique were major constraints to processing of oil bean in the area. The study concluded that efforts should be made by governments and processors through cooperative group in provision of processing and storage facility for oil bean while research institute should conserve and generate improved specie of the crop to arouse interest of the farmers and processors on the crop which will invariably increase productivity.

Keywords: conservation, domestication, oil bean, processing

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Authors: Alireza Nikbakht Shahbazi, Emadeddin Shirali

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Since optimization issues of water resources are complicated due to the variety of decision making criteria and objective functions, it is sometimes impossible to resolve them through regular optimization methods or, it is time or money consuming. Therefore, the use of modern tools and methods is inevitable in resolving such problems. An accurate and essential utilization policy has to be determined in order to use natural resources such as water reservoirs optimally. Water reservoir programming studies aim to determine the final cultivated land area based on predefined agricultural models and water requirements. Dam utilization rule curve is also provided in such studies. The basic information applied in water reservoir programming studies generally include meteorological, hydrological, agricultural and water reservoir related data, and the geometric characteristics of the reservoir. The system of Dez dam water resources was simulated applying the basic information in order to determine the capability of its reservoir to provide the objectives of the performed plan. As a meta-exploratory method, genetic algorithm was applied in order to provide utilization rule curves (intersecting the reservoir volume). MATLAB software was used in order to resolve the foresaid model. Rule curves were firstly obtained through genetic algorithm. Then the significance of using rule curves and the decrease in decision making variables in the system was determined through system simulation and comparing the results with optimization results (Standard Operating Procedure). One of the most essential issues in optimization of a complicated water resource system is the increasing number of variables. Therefore a lot of time is required to find an optimum answer and in some cases, no desirable result is obtained. In this research, intersecting the reservoir volume has been applied as a modern model in order to reduce the number of variables. Water reservoir programming studies has been performed based on basic information, general hypotheses and standards and applying monthly simulation technique for a statistical period of 30 years. Results indicated that application of rule curve prevents the extreme shortages and decrease the monthly shortages.

Keywords: optimization, rule curve, genetic algorithm method, Dez dam reservoir

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Authors: Erika R. Chambriard, Sandro C. Izidoro, Davidson P. Mendes, Douglas E. V. Pires

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Work-related illnesses and disorders have been a constant aspect of work. Although their nature has changed over time, from musculoskeletal disorders to illnesses related to psychosocial aspects of work, its impact on the life of workers remains significant. Despite significant efforts worldwide to protect workers, the disparity between changes in work legislation and actual benefit for workers’ health has been creating a significant economic burden for social security and health systems around the world. In this context, this study aims to propose, test and validate a modular prototype that allows for work environmental aspects to be assessed, monitored and better controlled. The main focus is also to provide a historical record of working conditions and the means for workers to obtain comprehensible and useful information regarding their work environment and legal limits of occupational exposure to different types of environmental variables, as means to improve prevention of work-related accidents and disorders. We show the developed prototype provides useful and accurate information regarding the work environmental conditions, validating them with standard occupational hygiene equipment. We believe the proposed prototype is a cost-effective and adequate approach to work environment monitoring that could help elucidate the links between work and occupational illnesses, and that different industry sectors, as well as developing countries, could benefit from its capabilities.

Keywords: Arduino prototyping, occupational health and hygiene, work environment, work-related disorders prevention

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Authors: Shavindrie Cooray

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It is vital that students are supported in having balanced conversations about topics that might be controversial. This process is crucial to the development of critical thinking skills. This can be difficult to attain in e-learning environments, with some research finding students report a perceived loss in the quality of knowledge exchange and performance. This research investigated if Systems Theory could be applied to structure the discussion, improve information sharing, and reduce conflicts when students are working in online environments. This research involved 160 participants across four categories of student groups at a college in the Northeastern US. Each group was provided with a shared problem, and each group was expected to make a proposal for a solution. Two groups worked face-to-face; the first face to face group engaged with the problem and each other with no intervention from a facilitator; a second face to face group worked on the problem using Systems tools to facilitate problem structuring, group discussion, and decision-making. There were two types of virtual teams. The first virtual group also used Systems tools to facilitate problem structuring and group discussion. However, all interactions were conducted in a synchronous virtual environment. The second type of virtual team also met in real time but worked with no intervention. Findings from the study demonstrated that the teams (both virtual and face-to-face) using Systems tools shared more information with each other than the other teams; additionally, these teams reported an increased level of disagreement amongst their members, but also expressed more confidence and satisfaction with the experience and resulting decision compared to the other groups.

Keywords: e-learning, virtual teams, systems approach, conflicts

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Authors: Khumbuzile M. Ngcobo, Seraphin D. Eyono Obono

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Science and technology has a major impact on many societal domains such as communication, medicine, food, transportation, etc. However, this dominance of modern technology can have a negative unintended impact on indigenous systems, and in particular on indigenous foods. This problem serves as a motivation to this study whose aim is to examine the perceptions of learners on the usefulness of Information and Communication Technologies (ICT's) for learning about indigenous foods. This aim will be subdivided into two types of research objectives. The design and identification of theories and models will be achieved using literature content analysis. The objective on the empirical testing of such theories and models will be achieved through the survey of Hospitality studies learners from different schools in the iLembe and Umgungundlovu Districts of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after the assessment of the validity and the reliability of the data. The main hypothesis behind this study is that there is a connection between the demographics of learners, their perceptions on the usefulness of ICTs for learning about indigenous foods and the following personality an e-learning related theories constructs: computer self-efficacy, trust in ICT systems, and conscientiousness; as suggested by existing studies on learning theories. This hypothesis was fully confirmed by the survey conducted by this study except for the demographic factors where gender and age were not found to be determinant factors of learners’ perceptions on the usefulness of ICT's for learning about indigenous foods.

Keywords: e-learning, indigenous foods, information and communication technologies, learning theories, personality

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Authors: Ziba R. Tehrani, Sanaz Moayer

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In the age of the knowledge-based economy, knowledge management has become a key factor in sustainable competitive advantage. Knowledge management is discovering, acquiring, developing, sharing, maintaining, evaluating, and using right knowledge in right time by right person in organization; which is accomplished by creating a right link between human resources, information technology, and appropriate structure, to achieve organisational goals. Studying knowledge management financial institutes shows the knowledge management in banking system is not different from other industries but because of complexity of bank’s environment, the implementation is more difficult. The bank managers found out that implementation of knowledge management will bring many advantages to financial institutes, one of the most important of which is reduction of threat to lose subsequent information of personnel job quit. Also Special attention to internal conditions and environment of the financial institutes and avoidance from copy-making in designing the knowledge management is a critical issue. In this paper, it is tried first to define knowledge management concept and introduce existing models of knowledge management; then some of the most important models which have more similarities with other models will be reviewed. In second step according to bank requirements with focus on knowledge management approach, most major objectives of knowledge management are identified. For gathering data in this stage face to face interview is used. Thirdly these specified objectives are analysed with the response of distribution of questionnaire which is gained through managers and expert staffs of ‘Karafarin Bank’. Finally based on analysed data, some features of exiting models are selected and a new conceptual model will be proposed.

Keywords: knowledge management, financial institute, knowledge management model, organisational knowledge

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Authors: Muhammad Ajmair

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This empirical study followed structural vector auto regression (SVAR) approach proposed by the so-called AB-model of Amisano and Giannini (1997) to check the impact of relevant macroeconomic determinants on economic growth in Pakistan. Before that auto regressive distributive lag (ARDL) bound testing technique and time varying parametric approach along with general to specific approach was employed to find out relevant significant determinants of economic growth. To our best knowledge, no author made such a study that employed auto regressive distributive lag (ARDL) bound testing and time varying parametric approach with general to specific approach in empirical literature, but current study will bridge this gap. Annual data was taken from World Development Indicators (2014) during period 1976-2014. The widely-used Schwarz information criterion and Akaike information criterion were considered for the lag length in each estimated equation. Main findings of the study are that remittances received, gross national expenditures and inflation are found to be the best relevant positive and significant determinants of economic growth. Based on these empirical findings, we conclude that government should focus on overall economic growth augmenting factors while formulating any policy relevant to the concerned sector.

Keywords: economic growth, gross national expenditures, inflation, remittances

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Authors: Y. H. Wang, C. C. Hsieh

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Good service design can increase organization revenue and consumer satisfaction while reducing labor and time costs. The problems facing consumers in the original serve model for eyewear and optical industry includes the following issues: 1. Insufficient information on eyewear products 2. Passively dependent on recommendations, insufficient selection 3. Incomplete records on progression of vision conditions 4. Lack of complete customer records. This study investigates the case of Kobayashi Optical, applying the Theory of Inventive Problem Solving (TRIZ) to develop innovative solutions for eyewear and optical industry. Analysis results raise the following conclusions and management implications: In order to provide customers with improved professional information and recommendations, Kobayashi Optical is suggested to establish customer purchasing records. Overall service efficiency can be enhanced by applying data mining techniques to analyze past consumer preferences and purchase histories. Furthermore, Kobayashi Optical should continue to develop a 3D virtual trial service which can allow customers for easy browsing of different frame styles and colors. This 3D virtual trial service will save customer waiting times in during peak service times at stores.

Keywords: theory of inventive problem solving (TRIZ), service design, augmented reality (AR), eyewear and optical industry

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Authors: Thuy Hang Le

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Traditional agroforestry systems are land-use practices still widespread in tropical and subtropical countries, while in Europe have significantly decreased due to land-use intensification, land abandonment, and urbanization. Nevertheless, scientific evidence reveals that traditional agroforestry systems significantly support biodiversity and ecosystem services and may positively contribute to socioeconomic rural regional development. We worked out a review that follows the PRISMA approach and compiled comprehensive information on traditional agroforestry systems in Europe. Based on the differentiation of different land-use systems, also considering the agricultural as well as forestry components, we compiled information regarding current distribution, management (agrodiversity), biodiversity and agrobiodiversity, ecosystem and landscape services, threats, and restoration initiatives. From a total of 3,304 studies that dealt with agroforestry systems in Europe, both “modern” (e.g., buffer strip) and “traditional” (e.g., meadow orchards), we filtered out 158 studies from 35 European countries which represent the basis for in-depth investigation. We found, for example, that the traditional pastoral agroforestry system in the Mediterranean region, the so-called Dehesa, can harbor up to 300 plant species as well as 238 bird species, of which 134 are breeding birds. With regard to carbon storage, the traditional orchard agroforestry system in Germany stocks ranged between 6.5 and 9.8 Mg C ha−1, showing significantly higher values compared to an intensively used grassland with around 3.4 to 6.7 Mg C ha−1. With the remarkably high benefit for biodiversity and ecosystem services provided, the important role and multifunctionality of traditional agroforestry systems in Europe should be acknowledged and promoted.

Keywords: biodiversity, ecosystem services, landscape services, traditional agroforestry systems

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Authors: N. Bazyar Shourabi, K. Nyarko, C. Scott, M. Jeihnai

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Ground drones have the potential to reduce the cost and time of making last-mile deliveries. They also have the potential to make a huge impact on human life. Despite this potential, little work has gone into developing a suitable feasibility model for ground drone delivery in dense urban areas. Today, most of the experimental ground delivery drones utilize sidewalks only, with just a few of them starting to use bike lanes, which a significant portion of some urban areas have. This study works on the feasibility of using bike lanes in conjunction with sidewalks for ground drone applications in last-mile delivery for dense urban areas. This work begins with surveying bike lanes and sidewalks within the city of Boston using Geographic Information System (GIS) software to determine the percentage of coverage currently available within the city. Then six scenarios are examined. Based on this research, a mathematical model is developed. The daily cost of delivering packages using each scenario is calculated by the mathematical model. Comparing the drone delivery scenarios with the traditional method of package delivery using trucks will provide essential information concerning the feasibility of implementing routing protocols that combine the use of sidewalks and bike lanes. The preliminary results of the model show that ground drones that can travel via sidewalks or bike lanes have the potential to significantly reduce delivery cost.

Keywords: ground drone, intelligent transportation system, last-mile delivery, sidewalk robot

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Authors: Pachawo Bisani, Goodall Nyirenda

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The Malawi National Antiretroviral Therapy (NART) Electronic Medical Record (EMR) system was designed and developed with guidance from the Ministry of Health through the Department of HIV and AIDS (DHA) with the aim of supporting the management of HIV patient data and reporting in high prevalence ART clinics. As of 2021, the system has been scaled up to over 206 facilities across the country. The system is integrated with the clinical decision support system (CDSS) to assist healthcare providers in making a decision about an individual patient at a particular point in time. Despite NART EMR undergoing several evaluations and assessments, little has been done to evaluate the clinical decision support system in the NART EMR system. Hence, the study aimed to evaluate the use of CDSS in the NART EMR system in Malawi. The study adopted a mixed-method approach, and data was collected through interviews, observations, and questionnaires. The study has revealed that the CDSS tools were integrated into the ART clinic workflow, making it easy for the user to use it. The study has also revealed challenges in system reliability and information accuracy. Despite the challenges, the study further revealed that the system is effective and efficient, and overall, users are satisfied with the system. The study recommends that the implementers focus more on the logic behind the clinical decision-support intervention in order to address some of the concerns and enhance the accuracy of the information supplied. The study further suggests consulting the system's actual users throughout implementation.

Keywords: clinical decision support system, electronic medical record system, usability, antiretroviral therapy

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Authors: Wiem Daoud Ben Amor, Luis Martínez López, Hela Moalla Frikha

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Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain contexts where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ARAS-ELH). Within the ARAS-ELH approach, the DM can diagnose the results (the ranking of the alternatives) in a decomposed style, i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e the collective final results of all experts able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ARAS-ELH technique makes it easier for decision-makers to understand the results. Finally, An MCGDM case study is given to illustrate the proposed approach.

Keywords: additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Caroline Hoorn

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Post-matriculants in disadvantaged communities such as Douglas encounter a number of career challenges. The transition to the democratic dispensation in 1994, coupled with the rapid changes in the information domain that are characteristic of post-industrial life, complicate the career development trajectories of disadvantaged youth. The career development stories and experiences of disadvantaged youth in provinces such as the Northern Cape have not been told, leading to their marginalisation. It is against this background that the study explored the gendered dimensions of career development narratives, experiences, and choices of post-matriculants in the Douglas community in the Northern Cape. Using a qualitative, narrative approach, the researcher elicited career development stories from 23 participants in Douglas using semi-structured interviews. Two main themes were highlighted through the narratives; (1) willingness to challenge the traditional male dominated career script (2) breaking gender barriers. The study showed that gender did not have any influence on the career choices of the post-matriculants. The perceptions around career choices and gender were being challenged partly by the urge to affirm equality and the constant reminder of the poverty-stricken conditions prevalent in the households. A preferred gender is not required to be attached to the fulfilment of outcomes in a knowledge-based economy. Thus, it is not an issue of gender or masculinity but knowledge and skills. Furthermore, the study revealed that the career choices being considered are still the traditionally stereotypical careers like nursing, teaching, and social work, which demonstrates a lack of information to a broader pool of career options to select from.

Keywords: career development, gender, narratives, post-matriculants

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Authors: Yao Fu, Xingli Zhang, Jiannong Shi

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Visual working memory (VWM) capacity is the ability to maintain and manipulate short-term information which is not currently available. It is well known for its significance to form the basis of numerous cognitive abilities and its limitation in holding information. VWM span, the most popular measurable indicator, is found to reach the adult level (3-4 items) around 12-13 years’ old, while less is known about the precision development of the VWM capacity. By using simultaneously delayed responses paradigm, the present study investigates the development of VWM precision among 6-18-year-old children and young adults, besides its possible relationships with fluid intelligence and span. Results showed that precision and span both increased with age, and precision reached the maximum in 16-17 age-range. Moreover, when remembering 3 simultaneously presented items, the probability of remembering target item correlated with fluid intelligence and the probability of wrap errors (misbinding target and non-target items) correlated with age. When remembering more items, children had worse performance than adults due to their wrap errors. Compared to span, VWM precision was effective predictor of intelligence even after controlling for age. These results suggest that unlike VWM span, precision developed in a slow, yet longer fashion. Moreover, decreasing probability of wrap errors might be the main reason for the development of precision. Last, precision correlated more closely with intelligence than span in childhood and adolescence, which might be caused by the probability of remembering target item.

Keywords: fluid intelligence, precision, visual working memory, wrap errors

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Authors: Siddhartha Paul, Debabrata Das

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Closed-loop supply chain (CLSC) management focuses on integrating forward and reverse flow of material as well as information to maximize value creation over the entire life-cycle of a product. Bullwhip effect in supply chain management refers to the phenomenon where a small variation in customers’ demand results in larger variation of orders at the upstream levels of supply chain. Since the quality and quantity of products returned to the collection centers (as a part of reverse logistics process) are uncertain, bullwhip effect is inevitable in CLSC. Therefore, in the present study, first, through an extensive literature survey, we identify all the important factors related to forward as well as reverse supply chain which causes bullwhip effect in CLSC. Second, we develop a system dynamics model to study the interrelationship among the factors and their effect on the performance of overall CLSC. Finally, the results of the simulation study suggest that demand forecasting, lead times, information sharing, inventory and work in progress adjustment rate, supply shortages, batch ordering, price variations, erratic human behavior, parameter correcting, delivery time delays, return rate of used products, manufacturing and remanufacturing capacity constraints are the important factors which have a significant influence on system’s performance, specifically on bullwhip effect in a CLSC.

Keywords: bullwhip effect, closed-loop supply chain, system dynamics, variance ratio

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Chia-Chen Chen, Mu-Yen Chen

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In recent years, with the vigorous growth of hardware and software technologies of smart mobile devices coupling with the rapid increase of social network influence, mobile commerce also presents the commercial operation mode of the future mainstream. For the time being, SoLoMo has become one of the very popular commercial models, its full name and meaning mainly refer to that users can obtain three key service types through smart mobile devices (Mobile) and omnipresent network services, and then link to the social (Social) web site platform to obtain the information exchange, again collocating with position and situational awareness technology to get the service suitable for the location (Local), through anytime, anywhere and any personal use of different mobile devices to provide the service concept of seamless integration style, and more deriving infinite opportunities of the future. The study tries to explore the use intention of users with SoLoMo mobile application formula, proposing research model to integrate TAM, ISSM, IDT and network externality, and with questionnaires to collect data and analyze results to verify the hypothesis, results show that perceived ease-of-use (PEOU), perceived usefulness (PU), and network externality have significant impact on the use intention with SoLoMo mobile application formula, and the information quality, relative advantages and observability have impacts on the perceived usefulness, and further affecting the use intention.

Keywords: SoLoMo (social, local, and mobile), technology acceptance model, innovation diffusion theory, network externality

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Authors: Ayse Tarhan, Mustafa Ilkan, Mohammad Karimzadeh

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Science was considered as part of philosophy in ancient Greece. By the nineteenth century, it was understood that philosophy was very inclusive and that social and human sciences such as literature, history, and psychology should be separated and perceived as an autonomous branch of science. The computer was also first seen as a tool of mathematical science. Over time, computer science has grown by encompassing every area in which technology exists, and its growth compelled the division of computer science into different disciplines, just as philosophy had been divided into different branches of science. Now there is almost no branch of science in which computers are not used. One of the newer autonomous disciplines of computer science is digital humanities, and one of the areas of digital humanities is literature. The material of literature is words, and thanks to the software tools created using computer programming languages, data that a literature researcher would need months to complete, can be achieved quickly and objectively. In this article, three different tools that literary researchers can use in their work will be introduced. These studies were created with the computer programming languages Python and R and brought to the world of literature. The purpose of introducing the aforementioned studies is to set an example for the development of special tools or programs on Ottoman language and literature in the future and to support such initiatives. The first example to be introduced is the Stylometry tool developed with the R language. The other is The Metrical Tool, which is used to measure data in poems and was developed with Python. The latest literature analysis tool in this article is Voyant Tools, which is a multifunctional and easy-to-use tool.

Keywords: DH, literature, information technologies, stylometry, the metrical tool, voyant tools

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Authors: Abdul Rahman Chamseddine

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The Companions of the Prophet Muhammad, the Sahaba, are regarded as the first link between him and later believers who did not know him or learn from him directly. This makes the Sahaba a link in the chain between God and the ummah (community). Apart from their role in spreading the Prophet’s teachings, they came to be regarded as role models, representing the Islamic ideal of life as prescribed by the Prophet himself. According to Hadith, the Prophet had promised some Sahaba unqualified admission to paradise. It is commonly agreed that the Sahaba have the following attributes in common: God is well pleased with them; they will surely go to paradise; they are perfectly trustworthy; and they are the authorities from whom Muslims can learn all matters related to their religion. No other generation of Muslims has received the attention received by the Companions of the Prophet. In spite of the importance of the Sahaba in Islam, we still know comparatively little about them. There are at least two reasons for this. First, there is the overall scarcity of information surviving from the early period. At the death of the Prophet, it is said, there were more than 100,000 Companions. As we shall see, this is a complex issue, involving the definition of the term Sahaba. However, only few Companions of the Prophet are known to us. Ibn Hajar al-‘Asqalani, who wrote in the fifteenth century A.D., was only able to collect facts about 11,000 of them (including those whose status as Sahaba was disputed). Ibn Sa‘d, Ibn ‘Abd al-Barr and Ibn al-Athir, all of whom lived earlier than Ibn Hajar, included in their respective works fewer lives of Sahaba than he did. If we consider Ibn Hajar’s Isaba as the most complete biographical account of the Sahaba that remains available, we have information, presumably, on approximately one tenth of them. The remaining nine tenths are apparently lost from the historical record. Second, discussion of the Sahaba tends to focus on those considered the most important among them such as ‘Uthman, ‘Ali and Mu‘awiya, while others, who together number in the thousands, are less well-known. This paper will try to study the origins of the term Sahaba that became exclusive to the Companions of the Prophet and not a synonym of the word companions in general.

Keywords: companions, Hadith, Islamic history, Muhammad, Sahaba, transmission

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Authors: A. Peyvan, D. Li, J. Komperda, F. Mashayek

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Turbulence can be observed in a variety fluid motions in nature and industrial applications. Recent investment in high-speed aircraft and propulsion systems has revitalized fundamental research on turbulent flows. In these systems, capturing chaotic fluid structures with different length and time scales is accomplished through the Direct Numerical Simulation (DNS) approach since it accurately simulates flows down to smallest dissipative scales, i.e., Kolmogorov’s scales. The discontinuous spectral element method (DSEM) is a high-order technique that uses spectral functions for approximating the solution. The DSEM code has been developed by our research group over the course of more than two decades. Recently, the code has been improved to run large cases in the order of billions of solution points. Running big simulations requires a considerable amount of RAM. Therefore, the DSEM code must be highly parallelized and able to start on multiple computational nodes on an HPC cluster with distributed memory. However, some pre-processing procedures, such as determining global element information, creating a global face list, and assigning global partitioning and element connection information of the domain for communication, must be done sequentially with a single processing core. A separate code has been written to perform the pre-processing procedures on a local machine. It stores the minimum amount of information that is required for the DSEM code to start in parallel, extracted from the mesh file, into text files (pre-files). It packs integer type information with a Stream Binary format in pre-files that are portable between machines. The files are generated to ensure fast read performance on different file-systems, such as Lustre and General Parallel File System (GPFS). A new subroutine has been added to the DSEM code to read the startup files using parallel MPI I/O, for Lustre, in a way that each MPI rank acquires its information from the file in parallel. In case of GPFS, in each computational node, a single MPI rank reads data from the file, which is specifically generated for the computational node, and send them to other ranks on the node using point to point non-blocking MPI communication. This way, communication takes place locally on each node and signals do not cross the switches of the cluster. The read subroutine has been tested on Argonne National Laboratory’s Mira (GPFS), National Center for Supercomputing Application’s Blue Waters (Lustre), San Diego Supercomputer Center’s Comet (Lustre), and UIC’s Extreme (Lustre). The tests showed that one file per node is suited for GPFS and parallel MPI I/O is the best choice for Lustre file system. The DSEM code relies on heavily optimized linear algebra operation such as matrix-matrix and matrix-vector products for calculation of the solution in every time-step. For this, the code can either make use of its matrix math library, BLAS, Intel MKL, or ATLAS. This fact and the discontinuous nature of the method makes the DSEM code run efficiently in parallel. The results of weak scaling tests performed on Blue Waters showed a scalable and efficient performance of the code in parallel computing.

Keywords: computational fluid dynamics, direct numerical simulation, spectral element, turbulent flow

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Authors: Satish Kumar Peddapelli

Abstract:

This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have become popular and considerable interest by researcher are given on them. A fast Space-Vector Pulse Width Modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analysed.

Keywords: five-level inverter, space vector pulse wide modulation, diode clamped inverter, electrical engineering

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Authors: Anitha Muralidhara, Victor Engelen, Christophe Len, Pascal Pandard, Guy Marlair

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Production of bio-based chemicals and materials from lignocellulosic biomass is gaining tremendous importance in advanced bio-refineries while aiming towards progressive replacement of petroleum based chemicals in transportation fuels and commodity polymers. One such attempt has resulted in the production of key furan derivatives (FD) such as furfural, HMF, MMF etc., via acid catalyzed dehydration (ACD) of C6 and C5 sugars, which are further converted into key chemicals or intermediates (such as Furandicarboxylic acid, Furfuryl alcohol etc.,). In subsequent processes, many high potential FD are produced, that can be converted into high added value polymers or high energy density biofuels. During ACD, an unavoidable polyfuranic byproduct is generated which is called humins. The family of FD is very large with varying chemical structures and diverse physicochemical properties. Accordingly, the associated risk profiles may largely vary. Hazardous Material (Haz-mat) classification systems such as GHS (CLP in the EU) and the UN TDG Model Regulations for transport of dangerous goods are one of the preliminary requirements for all chemicals for their appropriate classification, labelling, packaging, safe storage, and transportation. Considering the growing application routes of FD, it becomes important to notice the limited access to safety related information (safety data sheets available only for famous compounds such as HMF, furfural etc.,) in these internationally recognized haz-mat classification systems. However, these classifications do not necessarily provide information about the extent of risk involved when the chemical is used in any specific application. Factors such as thermal stability, speed of combustion, chemical incompatibilities, etc., can equally influence the safety profile of a compound, that are clearly out of the scope of any haz-mat classification system. Irrespective of the bio-based origin, FD has so far received inconsistent remarks concerning their toxicity profiles. With such inconsistencies, there is a fear that, a large family of FD may also follow extreme judgmental scenarios like ionic liquids, by ranking some compounds as extremely thermally stable, non-flammable, etc., Unless clarified, these messages could lead to misleading judgements while ranking the chemical based on its hazard rating. Safety is a key aspect in any sustainable biorefinery operation/facility, which is often underscored or neglected. To fill up these existing data gaps and to address ambiguities and discrepancies, the current study focuses on giving preliminary insights on safety assessment of FD and their potential targeted by-products. With the available information in the literature and obtained experimental results, physicochemical safety, environmental safety as well as (a scenario based) fire safety profiles of key FD, as well as side streams such as humins and levulinic acid, will be considered. With this, the study focuses on defining patterns and trends that gives coherent safety related information for existing and newly synthesized FD in the market for better functionality and sustainable applications.

Keywords: furanics, humins, safety, thermal and fire hazard, toxicity

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Authors: Yuliya Kovalenko

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Given the social nature of people, it is interesting to explore strategies of responding to psycho-traumatic situations in individuals of different ethnic and religious identity. This would allow to substantially expand the idea of human behavior in general, and coping behavior, in particular. This paper investigated the weighted impact of ethnic and religious identities on the patterns of coping behavior. This cross-cultural research empirically revealed intergroup differences in coping strategies and behavior in the samples of young students and teachers of different ethnic identities (Egyptians N=216 and Ukrainians N=109) and different religious identities (Egyptian Muslims N=147 and Christians, including Egyptian Christians N=68 and Ukrainian Christians N = 109). The empirical data were obtained using the questionnaires SACS and COPE. Statistical analysis and interpretation of the results were performed with IBM SPSS-23.0. It was found that, compared to the religious identity, the ethnic identity of the subjects appeared more predictive of coping behavior. It was shown that the constant exchange of information and the unity of biological and social contributed to a more homogeneous picture in the society where Christians and Muslims were integrated into a single cultural space. It was concluded that depending on their ethnic identity, individuals would form a specific hierarchy of coping strategies resulting in a specific pattern of coping with certain stressors. The Egyptian subjects revealed the following pattern of coping with various kinds of academic stress: 'seeking social support', 'problem solving', 'adapting', 'seeking information'. The coping pattern demonstrated by the Ukrainian subjects could be presented as 'seeking information', 'adapting', 'seeking social support', 'problem solving'. There was a tendency in the group of Egyptians to engage in more collectivist coping strategies (with the predominant coping strategy 'religious coping'), in contrast to the Ukrainians who displayed more individualistic coping strategies (with 'planning' and 'active coping' as the mostly used coping strategies). At the same time, it was obvious that Ukrainians should not be unambiguously attributed to the individualistic coping behavior due to their reliance on 'seeking social support' and 'social contact'. The final conclusion was also drawn from the peculiarities of developing religious identity, including religiosity, in Egyptians (formal religious education of both Muslims and Christians) and Ukrainians (more spontaneous process): Egyptians seem to learn to resort to the religious coping, which could be an indication that, in principle, it is possible and necessary to train individuals in desirable coping behavior.

Keywords: coping behavior, cross-cultural research, ethnic and religious identity, hierarchical pattern of coping

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: Young Yoon, Jinsoo Kim

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The adoption of information and communication technologies (ICT) in all industry is growing under industry 4.0. Many oil companies also are increasingly adopting ICT to improve the efficiency of existing operations, take more accurate and quicker decision making and reduce entire cost by optimization. It is true that ICT is playing an important role in the process of unconventional oil and gas development and companies must take advantage of ICT to gain competitive advantage. In this study, real option approach has been applied to Unconventional gas R&D project to evaluate ICT of them. Many unconventional gas reserves such as shale gas and coal-bed methane(CBM) has developed due to technological improvement and high energy price. There are many uncertainties in unconventional development on the three stage(Exploration, Development, Production). The traditional quantitative benefits-cost method, such as net present value(NPV) is not sufficient for capturing ICT value. We attempted to evaluate the ICT valuation by applying the compound option model; the model is applied to real CBM project case, showing how it consider uncertainties. Variables are treated as uncertain and a Monte Carlo simulation is performed to consider variables effect. Acknowledgement—This work was supported by the Energy Efficiency & Resources Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20152510101880) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-205S1A3A2046684).

Keywords: information and communication technologies, R&D, real option, unconventional gas

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Authors: Francesca Spagnoli, Shenja van der Graaf, Pieter Ballon

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Humans do not behave rationally. We are emotional, easily influenced by others, as well as by our context. The study of human behaviour became a supreme endeavour within many academic disciplines, including economics, sociology, and clinical and social psychology. Understanding what motivates humans and triggers them to perform certain activities, and what it takes to change their behaviour, is central both for researchers and companies, as well as policy makers to implement efficient public policies. While numerous theoretical approaches for diverse domains such as health, retail, environment have been developed, the methodological models guiding the evaluation of such research have reached for a long time their limits. Within this context, digitisation, the Information and communication technologies (ICT) and wearable, the Internet of Things (IoT) connecting networks of devices, and new possibilities to collect and analyse massive amounts of data made it possible to study behaviour from a realistic perspective, as never before. Digital technologies make it possible to (1) capture data in real-life settings, (2) regain control over data by capturing the context of behaviour, and (3) analyse huge set of information through continuous measurement. Within this complex context, this paper describes a new framework for initiating behavioural change, capitalising on the digital developments in applied research projects and applicable both to academia, enterprises and policy makers. By applying this model, behavioural research can be conducted to address the issues of different domains, such as mobility, environment, health or media. The Modular Behavioural Analysis Approach (MBAA) is here described and firstly validated through a concrete use case within the domain of health. The results gathered have proven that disclosing information about health in connection with the use of digital apps for health, can be a leverage for changing behaviour, but it is only a first component requiring further follow-up actions. To this end, a clear definition of different 'behavioural profiles', towards which addressing several typologies of interventions, it is essential to effectively enable behavioural change. In the refined version of the MBAA a strong focus will rely on defining a methodology for shaping 'behavioural profiles' and related interventions, as well as the evaluation of side-effects on the creation of new business models and sustainability plans.

Keywords: behavioural change, framework, health, nudging, sustainability

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