Search results for: social network tools

Authors: Emad Amar, Tawfik Khattab, Fatma Zada

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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, prediction, RBF neural network, earthquake

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Authors: Hatim Laalej, Jon Stammers

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In machining, monitoring of tool wear is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Currently, the task of monitoring the wear on the cutting tool is carried out by the operator who performs manual inspections of the cutting tool, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from loss of productivity. The cutting tool consumable costs may also be higher than necessary when tools are changed before the end of their useful life. Furthermore, damage can be caused to the workpiece when tools are not changed soon enough leading to a significant increase in the costs of manufacturing. The present study is concerned with the development of break sensor printed on the flank surface of poly-crystalline diamond (PCD) cutting to perform on-line condition monitoring of the cutting tool used to machine Titanium Ti-6al-4v bar. The results clearly show that there is a strong correlation between the break sensor measurements and the amount of wear in the cutting tool. These findings are significant in that they help the user/operator of the machine tool to determine the condition of the cutting tool without the need of performing manual inspection, thereby reducing the manufacturing costs such as the machine down time.

Keywords: machining, manufacturing, tool wear, signal processing

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Authors: Nadia Selene Molina-Moreno, Maria Susana Avila-Garcia, Marco Bianchetti, Marcelina Pantoja-Flores

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Visual Programming Tools available are a great tool for introducing children to programming and to develop a skill set for algorithmic thinking. On the other hand, collaborative learning and pair programming within the context of programming activities, has demonstrated to have social and learning benefits. However, some of the online tools available for programming for children are not designed to allow simultaneous and equitable participation of the team members since they allow only for a single control point. In this paper, a report the work conducted with children playing a user role is presented. A preliminary study to cull ideas, insights, and design considerations for a formal programming course for children aged 8-10 using collaborative learning as a pedagogical approach was conducted. Three setups were provided: 1) lo-fi prototype, 2) PC, 3) a 46' multi-touch single display groupware limited by the application to a single touch entry. Children were interviewed at the end of the sessions in order to know their opinions about teamwork and the different setups defined. Results are mixed regarding the setup, but they agree to like teamwork.

Keywords: children, collaborative programming, visual programming, multi-touch tabletop, lo-fi prototype

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Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova

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In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterize a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.

Keywords: complexity, hypergraphs, reciprocity, metabolism

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Authors: Frankie Burgos, Emely Munar, Conrado Basa

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This paper aimed at developing an artificial neural network (ANN) model specifically for the Philippine Stock Exchange index closing value. The inputs to the ANN are US Dollar and Philippine Peso(USD-PHP) exchange rate, GDP growth of the country, quarterly inflation rate, 10-year bond yield, credit rating of the country, previous open, high, low, close values and volume of trade of the Philippine Stock Exchange Index (PSEi), gold price of the previous day, National Association of Securities Dealers Automated Quotations (NASDAQ), Standard and Poor’s 500 (S & P 500) and the iShares MSCI Philippines ETF (EPHE) previous closing value. The target is composed of the closing value of the PSEi during the 627 trading days from November 3, 2011, to May 30, 2014. MATLAB’s Neural Network toolbox was employed to create, train and simulate the network using multi-layer feed forward neural network with back-propagation algorithm. The results satisfactorily show that the neural network developed has the ability to model the PSEi, which is affected by both internal and external economic factors. It was found out that the inputs used are the main factors that influence the movement of the PSEi closing value.

Keywords: artificial neural networks, artificial intelligence, philippine stocks exchange index, stocks trading

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Authors: Aynur Bütün Ayhan, Utku Beyazıt

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Adolescents can be heavily influenced by social media content as they develop their identities and body images. Therefore, the intensive use of social media platforms may have important effects on their body image beliefs. In this context, the objective of the present study was to assess the relationship between adolescents' social media use and their body image concerns. The study included 265 adolescents (133 girls and 132 boys) between the ages of 15 and 17 who were attending a high school in Ankara, Türkiye. In the study, the adolescents were administered the Social Media Addiction Scale to assess their level of social media use and the Social Appearance Anxiety Scale to assess their social appearance anxiety. Prior to analysis, a normality test was applied, and it was determined that the data displayed a non-parametric distribution. As a result, a significant positive relationship (r=.322, p<.01) was found between adolescents' level of social use and social appearance anxiety. It was also determined that social media addiction and social appearance anxiety significantly differed (p<.05) according to adolescents' opinions about their own bodies, being influenced by body images they see on social media and weight perceptions. The findings suggest that social media use should be managed carefully for adolescents to develop a healthy body image.

Keywords: social media, adolescent, social appearence, anxiety

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Authors: O. G. Omogunloye, J. B. Olaleye, O. E. Abiodun, J. O. Odumosu, O. G. Ajayi

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The focus of the study is to proffer easy formulation and computation of least square observation equation’s design matrix by using an efficient book keeping strategy. Usually, for a large network of many triangles and stations, a rigorous task is involved in the computation and placement of the values of the differentials of each observation with respect to its station coordinates (latitude and longitude), in their respective rows and columns. The efficient book keeping strategy seeks to eliminate or reduce this rigorous task involved, especially in large network, by simple skillful arrangement and development of a short program written in the Matlab environment, the formulation and computation of least square observation equation’s design matrix can be easily achieved.

Keywords: design, differential, geodetic, matrix, network, station

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Authors: Jaskaran Singh Sidhu

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Aim: The purpose of this study is to find the relationship between wellness among sportsmen and non sportsmen. Methodology: The present study is an experimental study for 80 senior secondary volleyball players of 16-19 years of age from Ludhiana District of Punjab (India), and 80 non-sportsperson were taken from senior secondary school of Ludhiana district. The sample for this study was taken through a random sampling technique. Tools: A five point scale havinf 50 items was used to acess the wellness Statistical Analysis: To find out the relationship among the variables exists or not, a t-test was used to test the significance of the difference between the means. Statistics for each characteristic were calculated; Mean, Standard deviation, Standard error of Mean. Data were analyzed using SPSS (statistical package for the social sciences). Statistical significance was set at p < 0.05. Results: Substantial deviations were noted at p<0.5 in the totality of wellness. Sportsmen show significant differences exist at p<0.5 in three parameters of wellness i.e., physical wellness, mental wellness, and social wellness. In spiritual and emotional wellness attributes, non-sportsmen shows significant difference at p<0.5. Conclusion: From the data interpretation it reflects that overall wellness can be improved by participation in sports. It further noted in study that participation in sports promote the attributes of wellness i.e., physical wellness, mental wellness, emotional wellness and social wellness.

Keywords: physical, mental, social, emotional, wellness, spiritual

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Authors: Lukáš Mazánek, Zdeňka Konečná

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The article is devoted to the area of personnel marketing. A comprehensive review of scientific literature and articles published predominantly in personnel-oriented journals was carried out, followed by a qualitative exploratory research with the aim to explore and explain the perception of personnel marketing. Due to the lack of research in this field in Czech Republic, we have focused on Czech HR managers, more specifically, on how they understand the tasks of personnel marketing, which tools they use and whether the companies they work for try to be a preferred employer. The answers from our respondents were used to help us determine what is important within this field. All of the respondents strive to be a preferred employer and try to achieve it by using an extensive range of marketing tools. The most frequently used tools are advertising, job fairs presentations, employee care and employer brand promotion.

Keywords: Czech Republic, personnel marketing, preferred employer, qualitative research study

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Authors: Carmen Aguilera-Carnerero

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Islamophobia, the unfounded hostility towards Muslims and Islam, has been deeply studied in the last decades from different perspectives ranging from anthropology, sociology, media studies, and linguistics. In the past few years, we have witnessed how the birth of social media has transformed formerly passive audiences into an active group that not only receives and digests information but also creates and comments publicly on any event of their interest. In this way, average citizens now have been entitled with the power of becoming potential opinion leaders. This rise of social media in the last years gave way to a different way of Islamophobia, the so called ‘cyberIslamophobia’. Considerably less attention, however, has been given to the study of islamophobic images that accompany the texts in social media. This paper attempts to analyse a corpus of 300 images of islamophobic nature taken from social media (from Twitter and Facebook) from the years 2014-2017 to see: a) how hate speech is visually constructed, b) how cyberislamophobia is articulated through images and whether there are differences/similarities between the textual and the visual elements, c) the impact of those images in the audience and their reaction to it and d) whether visual cyberislamophobia has undergone any process of permeating popular culture (for example, through memes) and its real impact. To carry out this task, we have used Critical Discourse Analysis as the most suitable theoretical framework that analyses and criticizes the dominant discourses that affect inequality, injustice, and oppression. The analysis of images was studied according to the theoretical framework provided by the visual framing theory and the visual design grammar to conclude that memes are subtle but very powerful tools to spread Islamophobia and foster hate speech under the guise of humour within popular culture.

Keywords: cyberIslamophobia, visual grammar, social media, popular culture

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Authors: Laura Rodriguez Amaya

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Advances in science, technology, engineering, and mathematics (STEM) are viewed as important to countries’ national economies and their capacities to be competitive in the global economy. However, many countries experience low numbers of students entering these disciplines. To strengthen the professional STEM pipelines, it is important that students are retained in these disciplines at universities. Scholars agree that to retain students in universities’ STEM degrees, it is necessary that STEM course content shows the relevance of these academic fields to their daily lives. By increasing students’ understanding on the importance of these degrees and careers, students’ motivation to remain in these academic programs can also increase. An effective way to make STEM content relevant to students’ lives is the use of geospatial technologies and geovisualization in the classroom. The Geospatial Revolution, and the science and technology associated with it, has provided scientists and engineers with an incredible amount of data about Earth and Earth systems. This data can be used in the classroom to support instruction and make content relevant to all students. The purpose of this study was to find out the prevalence use of geospatial technologies and geovisualization as teaching practices in a USA university. The Teaching Practices Inventory survey, which is a modified version of the Carl Wieman Science Education Initiative Teaching Practices Inventory, was selected for the study. Faculty in the STEM disciplines that participated in a summer learning institute at a 4-year university in the USA constituted the population selected for the study. One of the summer learning institute’s main purpose was to have an impact on the teaching of STEM courses, particularly the teaching of gateway courses taken by many STEM majors. The sample population for the study is 97.5 of the total number of summer learning institute participants. Basic descriptive statistics through the Statistical Package for the Social Sciences (SPSS) were performed to find out: 1) The percentage of faculty using geospatial technologies and geovisualization; 2) Did the faculty associated department impact their use of geospatial tools?; and 3) Did the number of years in a teaching capacity impact their use of geospatial tools? Findings indicate that only 10 percent of respondents had used geospatial technologies, and 18 percent had used geospatial visualization. In addition, the use of geovisualization among faculty of different disciplines was broader than the use of geospatial technologies. The use of geospatial technologies concentrated in the engineering departments. Data seems to indicate the lack of incorporation of geospatial tools in STEM education. The use of geospatial tools is an effective way to engage students in deep STEM learning. Future research should look at the effect on student learning and retention in science and engineering programs when geospatial tools are used.

Keywords: engineering education, geospatial technology, geovisualization, STEM

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Authors: Qian Liu, Steve Furber

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To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

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Authors: Jian Xu, Xiaochun Yun, Yongzheng Zhang, Yafei Sang, Zhenyu Cheng

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Network attack prevention is a critical research area of information security. Network attack would be oppressed if attribution techniques are capable to trace back to the attackers after the hacking event. Therefore attributing these attacks to a particular identification becomes one of the important tasks when analysts attempt to differentiate and profile the attacker behind a piece of attack trace. To assist analysts in expose attackers behind the scenes, this paper researches on the connections between attribution traces and proposes probabilistic relevance based attribution patterns. This method facilitates the evaluation of the plausibility relevance between different traceable identifications. Furthermore, through analyzing the connections among traces, it could confirm the existence probability of a certain organization as well as discover its affinitive partners by the means of drawing relevance matrix from attribution traces.

Keywords: attribution trace, probabilistic relevance, network attack, attacker identification

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Authors: Hsin Hua He

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The purpose of this study is to strengthen the social cohesion of the local community by injecting the cultural and creative concept into the industrial heritage transformation. The paradigms of industrial heritage research tend to explore from the perspective of space analysis, which concerned less about the cultural regeneration and the development of local culture. The paradigms of cultural quarter research use to from the perspective of creative economy and urban planning, concerned less about the social impacts and the interaction between residents and industrial sites. This research combines these two research areas of industrial heritage and cultural quarter, and focus on the social and cultural aspects. The transformation from the industrial heritage into a cultural park not only enhances the cultural capital and the quality of residents’ lives, but also preserves the unique local values. Internally it shapes the local identity, while externally establishes the image of the city. This paper uses Westergasfabriek Cultural Park in Amsterdam as the case study, through literature analysis, field work, and depth interview to explore how the cultural regeneration transforms industrial heritage. In terms of the planners’ and residents’ point of view adopt the theory of community participation, social capital, and sense of place to analyze the social impact of the industrial heritage transformation. The research finding is through cultural regeneration policies like holding cultural activities, building up public space, social network and public-private partnership, and adopting adaptive reuse to fulfil the people’s need and desire and reach the social cohesion. Finally, the study will examine the transformation of Taiwan's industrial heritage into cultural and creative quarters. The results are expected to use the operating experience of the Amsterdam cases and provide directions for Taiwan’s industrial heritage management to meet the cultural, social, economic symbiosis.

Keywords: cultural regeneration, community participation, social capital, sense of place, industrial heritage transformation

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Authors: Liu Yi Hui

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The COVID-19 pandemic in 2020 has globally affected all aspects of life, with social distancing and quarantine orders causing turmoil and learning in community colleges being temporarily paused. In fact, this is the first time that adult education has faced such a severe challenge. It forces researchers to reflect on the impact of pandemics on adult education and ways to respond. Distance learning appears to be one of the pedagogical tools capable of dealing with interpersonal isolation and social distancing caused by the pandemic. This research aims to examine whether the impact of social distancing during COVID-19 will lead to increased acceptance of technology and, subsequently, an increase in adults ’ willingness to participate in distance learning. The hypothesis that social distancing and the desire to participate in distance learning affects learners’ tendency to accept technology is investigated. Teachers ’ participation in distance education and acceptance of technology are used as adjustment variables with the relationship to “social distancing,” “participation in distance learning,” and “acceptance of technology” of learners. A questionnaire survey was conducted over a period of twelve months for teachers and learners at all community colleges in Taiwan who enrolled in a basic unit course. Community colleges were separated using multi-stage cluster sampling, with their locations being metropolitan, non-urban, south, and east as criteria. Using the G*power software, 660 samples were selected and analyzed. The results show that through appropriate pedagogical strategies or teachers ’ own acceptance of technology, adult learners’ willingness to participate in distance learning could be influenced. A diverse model of participation can be developed, improving adult education institutions’ ability to plan curricula to be flexible to avoid the risk associated with epidemic diseases.

Keywords: social distancing, adult learning, community colleges, technology acceptance model

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Authors: Petr Sulc, Hana Maresova

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This contribution focuses on online educational tools and language teaching, specifically on literary education in a multi-user virtual environment. The goal of this contribution is to give a basic overview of online language education and teaching in a virtual environment. The main goal of the research survey is to compare language (literary) education in a virtual environment with the traditional way of teaching in a typical classroom. The research concept will be mixed: a didactic test, the grounded theory method, and semi-structured questioning will be used. Kitely’s multi-user virtual environment and printed worksheets will be used for the comparison.

Keywords: online educational tools, virtual environment, virtual teaching objects, literary education, didactic test

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Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

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One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: malware detection, network security, targeted attack, computational intelligence

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Authors: A. Irudaya Veni Mary, M. Victor Louis Anthuvan, P. Christie, A. Indira

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In India, social enterprises are working to create social value in various fields including education; health; women and child development; environment protection and community development. Although social enterprises have brought about tremendous changes in the lives of beneficiaries, the importance of their works is not understood thoroughly. One of the ways to prove themselves is to measure the impact, which in recent times has received much attention. This paper focuses on the study of social value created by the social enterprises in the field of community development. It also aims to put forth a research tool for measuring the social value created by the social enterprises in the field of community development. A close-ended interview schedule was prepared to measure the social value creation and it was administered among 60 beneficiaries of two social enterprises who work in the field of community development. The study results show that the social enterprises have brought four types of impact in the life of their beneficiaries; economic impact, social impact, political impact and cultural impact. This study is limited to the social enterprises those who work towards community development. This empirical finding will enable the reader to understand various types of social value created by the social enterprises working in the field of community development. This study will also serve as guide for social enterprises in community development activities to measure their impact and thereby improve their operation towards the betterment of the society. This paper is derived from an empirical research carried out to describe the different types of social value created by the social enterprises in India.

Keywords: social enterprise, social entrepreneurs, social impact, social value, tool for social impact measurement

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Asnawi Mohd Busrah, Au Mau Teng, Tan Chin Hooi, Lau Chee Chong

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This paper describes value based planning (VBP) methodology incorporating risk assessment as an enhanced and more practical approach to evaluate distribution network projects in Peninsular Malaysia. Assessment indicators associated with economics, performance and risks are formulated to evaluate distribution projects to quantify their benefits against investment. The developed methodology is implemented in a web-based software customized to capture investment and network data, compute assessment indicators and rank the proposed projects according to their benefits. Value based planning approach addresses economic factors in the power distribution planning assessment, so as to minimize cost solution to the power utility while at the same time provide maximum benefits to customers.

Keywords: value based planning, distribution network, value of loss load (VoLL), energy not served (ENS)

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Authors: S. K. Ashiquer Rahman

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The innovative knowledge threshold significantly shifted education from traditional to an online version which was an emergent state of arts for academic programs of any higher education institutions; the substantive situation thus raises the importance of deliberative integration of education, Knowledge, technology and sustainability as well as knowledge platforms, e.g., ePLANETe. In fact, the concept of 'ePLANETe' an innovative knowledge platform and its functionalities as an experimental digitized platform for contributing sustainable assessment of academic programs of higher education institution(HEI). Besides, this paper assessed and define the common sustainable development challenges of higher education(HE) and identified effective approach and tools of 'ePLANETe’ that is enable to practices sustainability assessment of academic programs through the deliberation methodologies. To investigate the effectiveness of knowledge tools and approach of 'ePLANETe’, I have studied sustainable challenges digitized pedagogical content as well as evaluation of academic programs of two public universities in France through the 'ePLANETe’ evaluation space. The investigation indicated that the effectiveness of 'ePLANETe’s tools and approach perfectly fit for the quality assessment of academic programs, implementation of sustainable challenges, and dynamic balance of ecosystem within the university communities and academic programs through 'ePLANETe’ evaluation process and space. The study suggests to the relevant higher educational institution’s authorities and policymakers could use this approach and tools for assessing sustainability and enhancing the sustainability competencies of academic programs for quality education

Keywords: ePLANETe, deliberation, evaluation, competencies

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Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo

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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.

Keywords: the bluff body wakes, low-order modeling, neural network, system identification

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Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

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A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.

Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)

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Authors: Klara Królewiak-Detsi, Anna Orylska, Anna Gorgolewska, Marta Boczkowska, Agata Graczykowska

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This study investigates the communication between students and teachers in inclusive education in Poland. Specifically, we examine the communication and interaction of students with special educational needs during online learning compared to traditional face-to-face instruction. Our research questions are (1) how children with special educational needs communicate with their teachers and peers during online learning, and (2) what strategies can improve their communication skills. We conducted five focus groups with: (1) 55 children with special educational needs, (2) 65 typically developing pupils, (3) 28 professionals (psychologists and special education therapists), (4) 16 teachers, and (5) 16 parents of children with special educational needs. Our analysis focused on primary schools and used thematic analysis according to the 6-step procedure of Braun and Clarke. Our findings reveal that children with disabilities faced more difficulties communicating and interacting with others online than in face-to-face lessons. The online tools used for education were not adapted to the needs of children with disabilities, and schools lacked clear guidelines on how to pursue inclusive education online. Based on the results, we offer recommendations for online communication training and tools that are dedicated to children with special educational needs. Additionally, our results demonstrate that typically developing pupils are better in interpersonal relations and more often and effectively use social support. Children with special educational needs had similar emotional and communication challenges compared to their typically developing peers. In conclusion, our study highlights the importance of providing adequate support for the online education of children with special educational needs in inclusive classrooms.

Keywords: Inclusive education, Special educational needs, Social skills development, Online communication

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Authors: Juan José Mesas, Luis Sainz

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The motivation for the development of this paper lies in the need for energy networks to reduce losses, improve performance, optimize their operation and try to benefit from the interconnection capacity with other networks enabled for other energy carriers. These interconnections generate interdependencies between some energy networks and others, which requires suitable models and methods for their analysis. Traditionally, the modeling and study of energy networks have been carried out independently for each energy carrier. Thus, there are well-established models and methods for the steady-state analysis of electrical networks, gas networks, and thermal networks separately. What is intended is to extend and combine them adequately to be able to face in an integrated way the steady-state analysis of networks with multiple energy carriers. Firstly, the added value of multi-energy networks, their operation, and the basic principles that characterize them are explained. In addition, two current aspects of great relevance are exposed: the storage technologies and the coupling elements used to interconnect one energy network with another. Secondly, the characteristic equations of the different energy networks necessary to carry out the steady-state analysis are detailed. The electrical network, the natural gas network, and the thermal network of heat and cold are considered in this paper. After the presentation of the equations, a particular case of the steady-state analysis of a specific multi-energy network is studied. This network is represented graphically, the interconnections between the different energy carriers are described, their technical data are exposed and the equations that have previously been presented theoretically are formulated and developed. Finally, the two iterative numerical resolution methods considered in this paper are presented, as well as the resolution procedure and the results obtained. The pros and cons of the application of both methods are explained. It is verified that the results obtained for the electrical network (voltages in modulus and angle), the natural gas network (pressures), and the thermal network (mass flows and temperatures) are correct since they comply with the distribution, operation, consumption and technical characteristics of the multi-energy network under study.

Keywords: coupling elements, energy carriers, multi-energy networks, steady-state analysis

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Authors: Xiaoping Qiu, Binci You, Yue Hu

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The executive time of the workflow network has an important effect on the efficiency of the business process. In this paper, the activity executive time is divided into the service time and the waiting time, then the lead time can be extracted from the waiting time. The executive time formulas of the three basic structures in the workflow network are deduced based on the activity lead time. Taken the process of e-commerce logistics as an example, insert appropriate lead time for key activities by using Petri net, and the executive time optimization model is built to minimize the waiting time with the time-cost constraints. Then the solution program-using VC++6.0 is compiled to get the optimal solution, which reduces the waiting time of key activities in the workflow, and verifies the role of lead time in the timeliness of e-commerce logistics.

Keywords: electronic business, execution time, lead time, optimization model, petri net, time workflow network

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Authors: K. Myška, L. Pilařová

Abstract:

The article deals with possibilities of using cheap mobile devices with the combination of free or open source software tools as an alternative to professional hardware and software equipment. Especially in social work, it is important to find cheap yet functional solution that can compete with complex but expensive solutions for digitizing paper materials. Our research was focused on the analysis of cheap and affordable solutions for digitizing the most frequently used paper materials that are being commonly used by terrain workers in social work. We used comparative analysis as a research method. Social workers need to process data from paper forms quite often. It is still more affordable, time and cost-effective to use paper forms to get feedback in many cases. Collecting data from paper quizzes and questionnaires can be done with the help of professional scanners and software. These technologies are very powerful and have advanced options for digitizing and processing digitized data, but are also very expensive. According to results of our study, the combination of open source software and mobile phone or cheap scanner can be considered as a cost-effective alternative to professional equipment.

Keywords: digitalization, e-learning, mobile devices, questionnaire

Procedia PDF Downloads 151

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

Procedia PDF Downloads 176

Authors: Radwan Al Dwairi, Sara Melhem

Abstract:

Today’s billions of individuals are linked together in real-time using different types of social platforms. Despite the increasing importance of social media marketing activities in enhancing customers’ intention to purchase online; still, the majority of research has concentrated on the impact of such tools on customer satisfaction or retention and neglecting its real role in enhancing brand reputation and awareness, which in turn impact customers’ intention to purchase online. In response, this study aims to close this gap by conducting an empirical study using a qualitative approach by collecting a sample of data from 216 respondents in this domain. Results of the study reveal the significant impact of word-of-mouth, interactions, and influencers on a brand reputation, where the latter positively and significantly impacted customers’ intention to purchase via social platforms. In addition, results show the significant impact of brand reputation on enhancing customers' purchase intention.

Keywords: brand awareness, brand reputation, EWOM, influencers, interaction

Procedia PDF Downloads 95

Authors: Lene Granzau Juel-Jacobsen

Abstract:

The problem of beautification is an obvious concern of photography, claiming reference to reality, but it also lies at the very heart of social theory. As we become accustomed to sophisticated visualizations of statistical data in pace with the development of software programs, we should not only be inclined to ask new types of research questions, but we also need to confront social theories based on such visualization techniques with new types of questions. Correspondence Analysis, GIS analysis, Social Network Analysis, and Perceptual Maps are current examples of visualization techniques popular within the social sciences and neighboring disciplines. This article discusses correspondence analysis, arguing that the graphic plot of correspondence analysis is to be interpreted much similarly to a photograph. It refers no more evidently or univocally to reality than a photograph, representing social life no more truthfully than a photograph documents. Pierre Bourdieu’s theoretical corpus, especially his theory of fields, relies heavily on correspondence analysis. While much attention has been directed towards critiquing the somewhat vague conceptualization of habitus, limited focus has been placed on the equally problematic concepts of social space and field. Based on a re-reading of the Distinction, the article argues that the concepts rely on ‘a small graphic lie’ very similar to a photograph. Like any other piece of art, as Bourdieu himself recognized, the graphic display is a politically and morally loaded representation technique. However, the correspondence analysis does not necessarily serve the purpose he intended. In fact, it tends towards the pitfalls he strove to overcome.

Keywords: datavisualization, correspondance analysis, bourdieu, Field, visual representation

Procedia PDF Downloads 68