Search results for: multiple data

Authors: Supattra Kanchanopast

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The purpose of this research was to identify factors that influenced the trust of e-commerce within retail businesses. In order to achieve the objectives of this research, the researcher collected data from random e-commerce users in Bangkok. The data was comprised of the results of 382 questionnaires. The data was analyzed by using descriptive statistics, which included frequency, percentages, and the standard deviation of pertinent factors. Multiple regression analysis was also used. The findings of this research revealed that the majority of the respondents were female, 25-40 years old, and graduated a bachelor degree. The respondents mostly worked in private sectors and had monthly income between 15,000-25,000 baht. The findings also indicate that information quality factors, website design factors, service quality factor, security factor and advertising factors as significant factors effecting customer trust of e-commerce in online retail. The hypotheses testing revealed that these factors in e-commerce had an effect on customer’s trust in the same direction with high level.

Keywords: e-commerce, online retail, Retail business, trust, website

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Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry

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Lead time is an important measure of supply chain performance. It impacts both customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines from the company records were considered for this study. The sample data includes information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each sage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered after the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impact on lead time. Data analysis on the stages of lead time indicates that stage 2 consumes over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each of the 3 stages. Recommendation was given to resolve the problem.

Keywords: lead time reduction, customer satisfaction, service quality, statistical analysis

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Authors: Man Guo, Wenyong Tan

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By combining spatial syntax with data obtained from field visits, this paper interprets the internal relationship between spatial morphology and spatial cognition in Lidukou Village. By comparing the obtained data, it is recognized that the spatial integration degree of Lidukou Village is positively correlated with the spatial cognitive intention of local villagers. The part with a higher spatial cognitive degree within the village is distributed along the axis mainly composed of Shuxiang Road. And the accessibility of historical relics is weak, and there is no systematic relationship between them. Aiming at the morphological problem of Lidukou Village, optimization strategies have been proposed from multiple perspectives, such as optimizing spatial mechanisms and shaping spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

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Authors: Sean Goltz, Michael Mayo

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The purpose of this research is to use Global-Regulation.com database of the world laws, focusing on tax treaties between countries, in order to create an AI-driven tax simulator that will run an AI agent through potential tax scenarios across countries. The AI agent goal is to identify the scenario that will result in minimum tax liability based on tax treaties between countries. The results will be visualized by a three dimensional matrix. This will be an online web application. Multinational corporations are running their business through multiple countries. These countries, in turn, have a tax treaty with many other countries to regulate the payment of taxes on income that is transferred between these countries. As a result, planning the best tax scenario across multiple countries and numerous tax treaties is almost impossible. This research propose to use Global-Regulation.com database of word laws in English (machine translated by Google and Microsoft API’s) in order to create a simulator that will include the information in the tax treaties. Once ready, an AI agent will be sent through the simulator to identify the scenario that will result in minimum tax liability. Identifying the best tax scenario across countries may save multinational corporations, like Google, billions of dollars annually. Given the nature of the raw data and the domain of taxes (i.e., numbers), this is a promising ground to employ artificial intelligence towards a practical and beneficial purpose.

Keywords: taxation, law, multinational, corporation

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Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Pedro F. D. Oliveira, Rangel S. Maia, Aline S. Paula

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As the electric energy consumption grows, the necessity of energy transmission lines increases. One of the problems caused by an oscillatory response to dynamical loads (such as wind effects) in transmission lines is the cable fatigue. Thus, the dynamical behavior of transmission cables understanding and its control is extremely important. The socioeconomic damage caused by a failure in these cables can be quite significant, from large economic losses to energy supply interruption in large regions. Dynamic Vibration Absorbers (DVA) are oscillatory elements used to mitigate the vibration of a primary system subjected to harmonic excitation. The positioning of Stockbridge (DVA for overhead transmission lines) plays an important role in mitigating oscillations of transmission lines caused by airflows. Nowadays, the positioning is defined by technical standards or commercial software. The aim of this paper is to conduct an analysis of multiple DVAs performances in cable conductors of overhead transmission lines. The cable is analyzed by a finite element method and the model is calibrated by experimental results. DVAs performance is analyzed by evaluating total cable energy, and a study of multiple DVAs positioning is conducted. The results are compared to the existing regulations showing situations where proper positioning, different from the standard, can lead to better performance of the DVA. Results also show situations where the use of multiple DVAs is appropriate.

Keywords: dynamical vibration absorber, finite element method, overhead transmission lines, structural dynamics

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Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Chothmal

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In this paper, we present a route discovery process which uses the signal strength on a link as a parameter of its inclusion in the route discovery method. The proposed signal-to-interference and noise ratio (SINR) based multipath reactive routing protocol is named as SINR-MP protocol. The proposed SINR-MP routing protocols has two following two features: a) SINR-MP protocol selects routes based on the SINR of the links during the route discovery process therefore it select the routes which has long lifetime and low frame error rate for data transmission, and b) SINR-MP protocols route discovery process is multipath which discovers more than one SINR based route between a given source destination pair. The multiple routes selected by our SINR-MP protocol are node-disjoint in nature which increases their robustness against link failures, as failure of one route will not affect the other route. The secondary route is very useful in situations where the primary route is broken because we can now use the secondary route without causing a new route discovery process. Due to this, the network overhead caused by a route discovery process is avoided. This increases the network performance greatly. The proposed SINR-MP routing protocol is implemented in the trail version of network simulator called Qualnet.

Keywords: ad hoc networks, quality of service, video streaming, H.264/SVC, multiple routes, video traces

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: particle swarm optimization, GIS, traffic data, outliers

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Authors: Laura Bellassen, Idit Shachar

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Multiple sclerosis (MS) is a chronic neurological disorder characterized by demyelination of the central nervous system (CNS), leading to a wide range of physical and cognitive impairments. Myeloid cells in the CNS, such microglia and border associated macrophage cells, participate in the neuroinflammation in MS. Activation of those cells in MS contributes to the inflammatory response in the CNS and recruitment of immune cells in the this compartment. SLAMF5 is a cell surface receptor that functions as a homophilic adhesion molecule, whose signaling can activate or inhibit leukocyte function. In the current study we followed the expression and function of SLAMF5 in myeloid cells in the CNS and in the periphery in the murine model for MS, the experimental autoimmune encephalomyelitis model (EAE). Our results show that SLAMF5 deficiency or blocking decreases the expression of activation molecules and costimulatory molecules such as MHCII and CD80, resulting in delayed onset and reduced progression of the disease. Moreover, blocking SLAMF5 in peripheral monocytes derived from MS patients and iPSC-derived microglia cells, controls the expression of HLA-DR and CD80. Thus, SLAMF5 is a regulator of myeloid cells function and can serve as a therapeutic target in autoimmune disorders as Multiple Sclerosis.

Keywords: multiple sclerosis, EAE model, myeloid cells, new antibody, neuroimmunology

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Authors: Vasantha Gouri Prathapagiri

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Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

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Authors: M. Habibi

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The time-resolved studies of soft and hard X-ray were carried out over a wide range of argon pressures by employing an array of eight filtered photo PIN diodes and a scintillation detector, simultaneously. In 50% of the discharges, the soft X-ray is seen to be emitted in short multiple pulses corresponding to different compression, whereas it is a single pulse for hard X-rays corresponding to only the first strong compression. It should be stated that multiple compressions dominantly occur at low pressures and high pressures are mostly in the single compression regime. In 43% of the discharges, at all pressures except for optimum pressure, the first period is characterized by two or more sharp peaks.The X–ray signal intensity during the second and subsequent compressions is much smaller than the first compression.

Keywords: plasma focus device, SXR, HXR, Pin-diode, argon plasma

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Authors: Chulsang Yoo, Gildo Kim

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Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, unsuitable data. The results are as follows: (1) The radar rain rate equation including KDP, was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied. Acknowledgments: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).

Keywords: CSU-HIDRO algorithm, dual polarization radar, JPOLE algorithm, radar rainfall estimation algorithm

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Authors: A. Brahma

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The drying of hydraulics materials is unavoidable and conducted to important spontaneous deformations. In this study, we show that it is possible to describe the drying shrinkage of the high-performance concrete by a simple expression. A multiple regression model was developed for the prediction of the drying shrinkage of the high-performance concrete. The assessment of the proposed model has been done by a set of statistical tests. The model developed takes in consideration the main parameters of confection and conservation. There was a very good agreement between drying shrinkage predicted by the multiple regression model and experimental results. The developed model adjusts easily to all hydraulic concrete types.

Keywords: hydraulic concretes, drying, shrinkage, prediction, modeling

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Authors: Deborah L. Smith

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To review our program and determine the best redesign options, department members gathered feedback and input through focus groups, analysis of data, and a review of the current research to ensure that the changes proposed were not based solely on the state’s new professional standards. In designing course assignments and assessments, we listened to a variety of constituents, including students, other institutions of higher learning, MDE webinars, host teachers, literacy clinic personnel, and other disciplinary experts. As a result, we are designing a program that is more inclusive of a variety of field experiences for growth. We have determined ways to improve our program by connecting academic disciplinary knowledge, educational psychology, and community building both inside and outside the classroom for professional learning communities. The state’s release of new professional standards led my department members to question what is working and what needs improvement in our program. One aspect of our program that continues to be supported by research and data analysis is the function of supervised field experiences with meaningful feedback. We seek to expand in this area. Other data indicate that we have strengths in modeling a variety of approaches such as cooperative learning, discussions, literacy strategies, and workshops. In the new program, field assignments will be connected to multiple courses, and efforts to scaffold student learning to guide them toward best evidence-based practices will be continuous. Despite running a program that meets multiple sets of standards, there are areas of need that we directly address in our redesign proposal. Technology is ever-changing, so it’s inevitable that improving digital skills is a focus. In addition, scaffolding procedures for English Language Learners (ELL) or other students who struggle is imperative. Diversity, equity, and inclusion (DEI) has been an integral part of our curriculum, but the research indicates that more self-reflection and a deeper understanding of culturally relevant practices would help the program improve. Connections with professional learning communities will be expanded, as will leadership components, so that teacher candidates understand their role in changing the face of education. A pilot program will run in academic year 22/23, and additional data will be collected each semester through evaluations and continued program review.

Keywords: DEI, field experiences, program redesign, teacher preparation

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Authors: Keunhong Chae, Seokho Yoon

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We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.

Keywords: code acquisition, optical CDMA, optical orthogonal code, serial algorithm

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Authors: Chih-Hung Chen, Yih-Shyang Cheng, Yu-Hsin Tu

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Holographic optical elements (HOEs) have recently been one of the most suitable components in optoelectronic technology owing to the requirement of the product system with compact size. Computer-generated holography (CGH) is a well-known technology for HOEs production. In some cases, a well-designed diffractive optical element with multifunctional components is also an important issue and needed for an advanced optoelectronic system. Spatial light modulator (SLM) is one of the key components that has great capability to display CGH pattern and is widely used in various applications, such as an image projection system. As mentioned to multifunctional components, such as phase and amplitude modulation of light, high-resolution hologram with multiple-exposure procedure is also one of the suitable candidates. However, holographic recording under multiple exposures, the diffraction efficiency of the final hologram is inevitably lower than that with single exposure process. In this study, a two-step holographic recording method, including the master hologram fabrication and the replicated hologram production, will be designed. Since there exist a reduction factor M² of diffraction efficiency in multiple-exposure holograms (M multiple exposures), so it seems that single exposure would be more efficient for holograms replication. In the second step of holographic replication, a stable optical system with one-shot copying is introduced. For commercial application, one may utilize this concept of holographic copying to obtain duplications of HOEs with higher optical performance.

Keywords: holographic replication, holography, one-shot copying, optical element

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Authors: Moyosooore A. Babalola, Ayodeji S. Ogunleye

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The main focus of the study was to determine the profitability of investment in the Oil Palm value chain of Osun State, Nigeria in 2015. The specific objectives were to describe the socio-economic characteristics of Oil Palm investors (producers, processors and marketers), to determine the profitability of the investment to investors in the Oil Palm value chain, and to determine the factors affecting the profitability of the investment of the oil palm investors in Osun state. A sample of 100 respondents was selected in this cross-sectional survey. Multiple stage sampling procedure was used for data collection of producers and processors while purposive sampling was used for marketers. Data collected was analyzed using the following analytical tools: descriptive statistics, budgetary analysis and regression analysis. The results of the gross margin showed that the producers and processors were more profitable than the marketers in the oil palm value chain with their benefit-cost ratios as 1.93, 1.82 and 1.11 respectively. The multiple regression analysis showed that education and years of experience were significant among marketers and producers while age and years of experience had significant influence on the gross margin of processors. Based on these findings, improvement on the level of education of oil palm investors is recommended in order to address the relatively low access to post-primary education among the oil palm investors in Osun State. In addition to this, it is important that training be made available to oil palm investors. This will improve the quality of their years of experience, ensuring that it has a positive influence on their gross margin. Low access to credit among processors and producer could be corrected by making extension services available to them. Marketers would also greatly benefit from subsidized prices on oil palm products to increase their gross margin, as the huge percentage of their total cost comes from acquiring palm oil.

Keywords: oil palm, profitability analysis, regression analysis, value chain

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Authors: Fadi Awawdeh, O. Alsayyed, S. Al-Shará

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Considering the inhomogeneities of media, the variable-coefficient Sharma-Tasso-Olver (STO) equation is hereby investigated with the aid of symbolic computation. A newly developed simplified bilinear method is described for the solution of considered equation. Without any constraints on the coefficient functions, multiple kink solutions are obtained. Parametric analysis is carried out in order to analyze the effects of the coefficient functions on the stabilities and propagation characteristics of the solitonic waves.

Keywords: Hirota bilinear method, multiple kink solution, Sharma-Tasso-Olver equation, inhomogeneity of media

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Authors: Sheila S. Silang

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This research seeks to make an impact analysis on multiple intelligence as the basis for differentiated classroom instruction in TLE. It will also address the felt need of how TLE subject could be taught effectively exhausting all the possible means.This study seek the effect of giving different instruction according to the ability of the students in the following objectives: 1. student’s technological skills enhancement, 2. learning potential improvements 3. having better linkage between school and community in a need for soliciting different learning devices and materials for the learner’s academic progress. General Luna, Quezon is composed of twenty seven barangays. There are only two public high schools. We are aware that K-12 curriculum is focused on providing sufficient time for mastery of concepts and skills, develop lifelong learners, and prepare graduates for tertiary education, middle-level skills development, employment, and entrepreneurship. The challenge is with TLE offerring a vast area of specializations, how would Multiple Intelligence play its vital role as basis in classroom instruction in acquiring the requirement of the said curriculum? 1.To what extent do the respondent students manifest the following types of intelligences: Visual-Spatial, Body-Kinesthetic, Musical, Interpersonal, Intrapersonal, Verbal-Linguistic, Logical-Mathematical and Naturalistic. What media should be used appropriate to the student’s learning style? Visual, Printed Words, Sound, Motion, Color or Realia 3. What is the impact of multiple intelligence as basis for differentiated instruction in T.L.E. based on the following student’s ability? Learning Characteristic and Reading Ability and Performance 3. To what extent do the intelligences of the student relate with their academic performance? The following were the findings derived from the study: In consideration of the vast areas of study of TLE, and the importance it plays in the school curriculum coinciding with the expectation of turning students to technologically competent contributing members of the society, either in the field of Technical/Vocational Expertise or Entrepreneurial based competencies, as well as the government’s concern for it, we visualize TLE classroom teachers making use of multiple intelligence as basis for differentiated classroom instruction in teaching the subject .Somehow, multiple intelligence sample such as Linguistic, Logical-Mathematical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Spatial abilities that an individual student may have or may not have, can be a basis for a TLE teacher’s instructional method or design.

Keywords: education, multiple, differentiated classroom instruction, impact analysis

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Authors: Ruth Leitch, Joanne Hughes

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This paper presents the findings of a three-year government-funded study (ILiAD) that aimed to understand the reasons for differential educational achievement within and between socially and economically deprived areas in Northern Ireland. Previous international studies have concluded that there is a positive correlation between deprivation and underachievement. Our preliminary secondary data analysis suggested that the factors involved in educational achievement within multiple deprived areas may be more complex than this, with some areas of high multiple deprivation having high levels of student attainment, whereas other less deprived areas demonstrated much lower levels of student attainment, as measured by outcomes on high stakes national tests. The study proposed that no single explanation or disparate set of explanations could easily account for the linkage between levels of deprivation and patterns of educational achievement. Using a social capital perspective that centralizes the connections within and between individuals and social networks in a community as a valuable resource for educational achievement, the ILiAD study involved a multi-level case study analysis of seven community sites in Northern Ireland, selected on the basis of religious composition (housing areas are largely segregated by religious affiliation), measures of multiple deprivation and differentials in educational achievement. The case study approach involved three (interconnecting) levels of qualitative data collection and analysis - what we have termed Micro (or community/grassroots level) understandings, Meso (or school level) explanations and Macro (or policy/structural) factors. The analysis combines a statistical mapping of factors with qualitative, in-depth data interpretation which, together, allow for deeper understandings of the dynamics and contributory factors within and between the case study sites. Thematic analysis of the qualitative data reveals both cross-cutting factors (e.g. demographic shifts and loss of community, place of the school in the community, parental capacity) and analytic case studies of explanatory factors associated with each of the community sites also permit a comparative element. Issues arising from the qualitative analysis are classified either as drivers or inhibitors of educational achievement within and between communities. Key issues that are emerging as inhibitors/drivers to attainment include: the legacy of the community conflict in Northern Ireland, not least in terms of inter-generational stress, related with substance abuse and mental health issues; differing discourses on notions of ‘community’ and ‘achievement’ within/between community sites; inter-agency and intra-agency levels of collaboration and joined-up working; relationship between the home/school/community triad and; school leadership and school ethos. At this stage, the balance of these factors can be conceptualized in terms of bonding social capital (or lack of it) within families, within schools, within each community, within agencies and also bridging social capital between the home/school/community, between different communities and between key statutory and voluntary organisations. The presentation will outline the study rationale, its methodology, present some cross-cutting findings and use an illustrative case study of the findings from a community site to underscore the importance of attending to community differences when trying to engage in research to understand and improve educational attainment for all.

Keywords: educational achievement, multiple deprivation, community case studies, social capital

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Authors: Eun Kyong Park

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This study explores the relationships between immigrant parents’ beliefs about bilingualism, family literacy practices, and their children’s identity development in Sydney, Australia. This project examines how these parents’ ideological beliefs and knowledge are related to their provision of family literacy practices and management of the environment for their bilingual children based on family language policy (FLP). This is a follow-up study of the author’s prior thesis that presented Korean immigrant mothers’ beliefs and decision-making in support of their children’s bilingualism. It includes fathers’ perspectives within the participating families as a whole by foregrounding their perceptions of bilingual and identity development. It adopts a qualitative approach with twelve immigrant mothers and fathers living in a Korean-Australian community whose child attends one of the communities Korean language programs. This time, it includes introspective and self-evocative auto-ethnographic data. The initial data set collected from the first part of this study demonstrated the mothers provided rich, diverse, and specific family literacy activities for their children. These mothers selected specific practices to facilitate their child’s bilingual development at home. The second part of data has been collected over a three month period: 1) a focus group interview with mothers; 2) a brief self-report of fathers; 3) the researcher’s reflective diary. To analyze these multiple data, thematic analysis and coding were used to reveal the parents’ ideologies surrounding bilingualism and bilingual identities. It will highlight the complexity of language and literacy practices in the family domain interrelated with sociocultural factors. This project makes an original contribution to the field of bilingualism and FLP and a methodological contribution by introducing auto-ethnographic input of this community’s lived practices. This project will empower Korean-Australian immigrant families and other multilingual communities to reflect their beliefs and practices for their emerging bilingual children. It will also enable educators and policymakers to access authentic information about how bilingualism is practiced within these immigrant families in multiple ways and to help build the culturally appropriate partnership between home and school community.

Keywords: bilingualism, beliefs, identity, family language policy, Korean immigrant parents in Australia

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

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Authors: M. A. At-Tasneem, N. T. Rao, T. M. Y. S. Tuan Ya, M. S. Idris, M. Ammar

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River flow over micro hydro power (MHP) turbines of multiple arrays arrangement is simulated with computational fluid dynamics (CFD) software to obtain the flow characteristics. In this paper, CFD software is used to simulate the water flow over MHP turbines as they are placed in a river. Multiple arrays arrangement of MHP turbines lead to generate large amount of power. In this study, a river model is created and simulated in CFD software to obtain the water flow characteristic. The process then continued by simulating different types of arrays arrangement in the river model. A MHP turbine model consists of a turbine outer body and static propeller blade in it. Five types of arrangements are used which are parallel, series, triangular, square and rhombus with different spacing sizes. The velocity profiles on each MHP turbines are identified at the mouth of each turbine bodies. This study is required to obtain the arrangement with increasing spacing sizes that can produce highest power density through the water flow variation.

Keywords: micro hydro power, CFD, arrays arrangement, spacing sizes, velocity profile, power

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Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

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Authors: Hoda A. Abdel Hafez

Abstract:

Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

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Authors: Jonathan Heng, Yoong Cheah Huei

Abstract:

A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

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Authors: Karima Afif, Jacinthe Clouthier, Marie-Ève Gaboury-Bonhomme, Véronique Provencher, Morgane Leclercq

Abstract:

This paper investigates how food banks have secured and improved their supply chain resilience to pursue their mission during COVID-19. More specifically, the implications of the COVID-19 outbreak on the food aid needs, donations, operations, and mission of food banks are explored. To develop an in-depth understanding of the reactions and actions that they have been taken, a qualitative approach has been adopted using a multiple case study design. Data from two focus groups, 12 semi-structured interviews with key informants covering all supply chain levels, and field notes from 7 workplace observations in donation points, food bank facilities, and community-based organizations in Québec (Canada) are triangulated. The results highlight that the pandemic has significantly and unpredictably increased the number of food aid demands, causing significant operational challenges for the food banks supply chain, as well as an unprecedented shortage of donations to food banks. Besides, the sanitary measures have required several adaptative strategies. These implications have caused food banks to enhance their operational flexibility, optimize their logistics operations, enhance their human resources management, and expand collaboration within their supply chain.

Keywords: supply chain resilience, food banks, food donations, food aid, COVID-19

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

Abstract:

University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

Procedia PDF Downloads 82

Authors: Bella Llego

Abstract:

The purpose of this study was to explain and empirically test the influence of attitude towards work, job satisfaction and organizational commitment of SSRU employee’s evaluation and performance. Data used in this study was primary data which were collected through Organizational Commitment Questionnaire with 1-5 Likert Scale. The respondent of this study was 200 managerial and non-managerial staff of SSRU. The statistics to analyze the data provide the descriptive by the mean, standard deviation and test hypothesis by the use of multiple regression. The result of this study is showed that attitude towards work have positive but not significant effect to job satisfaction and employees evaluation and performance. Different with attitude towards work, the organizations commitment has positive and significant influence on job satisfaction and employee performance at SSRU. It means every improvement in organization’s commitment has a positive effect toward job satisfaction and employee evaluation and performance at SSRU.

Keywords: attitude towards work, employee’s evaluation and performance, jobs satisfaction, organization commitment

Procedia PDF Downloads 454