Search results for: academic social network

Authors: Behrooz Daneshmand

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Software Defined Networking (SDN) is designed to meet the future needs of 5G mobile networks. The SDN architecture offers a new solution that involves separating the control plane from the data plane, which is usually paired together. Network functions traditionally performed on specific hardware can now be abstracted and virtualized on any device, and a centralized software-based administration approach is based on a central controller, facilitating the development of modern applications and services. These plan standards clear the way for a more adaptable, speedier, and more energetic network beneath computer program control compared with a conventional network. We accept SDN gives modern inquire about openings to security, and it can significantly affect network security research in numerous diverse ways. Subsequently, the SDN architecture engages systems to effectively screen activity and analyze threats to facilitate security approach modification and security benefit insertion. The segregation of the data planes and control and, be that as it may, opens security challenges, such as man-in-the-middle attacks (MIMA), denial of service (DoS) attacks, and immersion attacks. In this paper, we analyze security threats to each layer of SDN - application layer - southbound interfaces/northbound interfaces - controller layer and data layer. From a security point of see, the components that make up the SDN architecture have a few vulnerabilities, which may be abused by aggressors to perform noxious activities and hence influence the network and its administrations. Software-defined network assaults are shockingly a reality these days. In a nutshell, this paper highlights architectural weaknesses and develops attack vectors at each layer, which leads to conclusions about further progress in identifying the consequences of attacks and proposing mitigation strategies.

Keywords: software-defined networking, security, SDN, 5G/IMT-2020

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Authors: Jett Black, Jordyn Godsey, Gaby G. Dagher, Steve Cutchin

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Despite the growing interest in distributed ledger technology, many data visualizations of blockchain are limited to monotonous tabular displays or overly abstract graphical representations that fail to adequately educate individuals on blockchain components and their functionalities. To address these limitations, it is imperative to develop data visualizations that offer not only comprehensive insights into these domains but education as well. This research focuses on providing a conceptual understanding of the consensus process that underlies blockchain technology. This is accomplished through the implementation of a dynamic network visualization and an interactive educational tool called BlueVision. Further, a controlled user study is conducted to measure the effectiveness and usability of BlueVision. The findings demonstrate that the tool represents significant advancements in the field of blockchain visualization, effectively catering to the educational needs of both novice and proficient users.

Keywords: blockchain, visualization, consensus, distributed network

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Authors: Tamanna Rimi

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A large body of literature has discussed the determinants of migration decision. However, the potential role of individual risk attitudes on migration decision has so far been overlooked. The research on migration literature has studied how the expected income differential influences migration flows for a risk neutral individual. However, migration takes place when there is no expected income differential or even the variability of income appears as lower than in the current location. This migration puzzle motivates a recent trend in the literature that analyzes how attitudes towards risk influence the decision to migrate. However, the significance of risk attitudes on migration decision has been addressed mostly in a theoretical perspective in the mainstream migration literature. The efficient outcome of labor market and overall economy are largely influenced by migration in many countries. Therefore, attitudes towards risk as a determinant of migration should get more attention in empirical studies. To author’s best knowledge, this is the first study that has examined the relationship between relative risk aversion and migration decision in US market. This paper considers movement across United States as a means of migration. In addition, this paper also explores the network effect due to the increasing size of one’s own ethnic group to a source location on the migration decision and how attitudes towards risk vary with network effect. Two ethnic groups (i.e. Asian and Hispanic) have been considered in this regard. For the empirical estimation, this paper uses two sources of data: 1) U.S. census data for social, economic, and health research, 2010 (IPUMPS) and 2) University of Michigan Health and Retirement Study, 2010 (HRS). In order to measure relative risk aversion, this study uses the ‘Two Sample Two-Stage Instrumental Variable (TS2SIV)’ technique. This is a similar method of Angrist (1990) and Angrist and Kruegers’ (1992) ‘Two Sample Instrumental Variable (TSIV)’ technique. Using a probit model, the empirical investigation yields the following results: (i) risk attitude has a significantly large impact on migration decision where more risk averse people are less likely to migrate; (ii) the impact of risk attitude on migration varies by other demographic characteristics such as age and sex; (iii) people with higher concentration of same ethnic households living in a particular place are expected to migrate less from their current place; (iv) the risk attitudes on migration vary with network effect. The overall findings of this paper relating risk attitude, migration decision and network effect can be a significant contribution addressing the gap between migration theory and empirical study in migration literature.

Keywords: migration, network effect, risk attitude, U.S. market

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Authors: Renato Roda

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With the emergence of the so-called 'Knowledge Society', the implementation of policies to attract, grow and retain talents, in an academic context as well, has become critical –both in the perspective of didactics and research and as far as administration and institutional management are concerned. At the same time, the contemporary philanthropic entities/organizations, which are evolving from traditional types of social support towards new styles of aid, envisaged to go beyond mere monetary donations, face the challenge of brand-new forms of complexity in supporting such specific dynamics of the global human capital market. In this sense, it becomes unavoidable for the philanthropic foundation, while carrying out their daily charitable tasks, to resort to innovative ways to facilitate the acquisition and the promotion of talents by academic and research institutions. In order to deepen such a specific perspective, this paper features the case of Turin, former 'factory city' of Italy’s North West, headquarters -and main reference territory- of Italy’s largest and richest private formerly bank-based philanthropic foundation, the Fondazione Compagnia di San Paolo. While it was assessed and classified as 'medium' in the city Global Talent Competitiveness Index (GTCI) of 2020, Turin has nevertheless acquired over the past months status of impact laboratory for a whole series of innovation strategies in the competition for the acquisition of excellence human capital. Leading actors of this new city vision are the foundations with their specifically adjusted financial engagement and a consistent role of stimulus towards innovation for research and education institutions.

Keywords: human capital, post-Fordism, private foundation, war on talents

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Authors: Young-Kwang Lee, Eun-Gu Ji, Min-Joo Kim, Seung-Jae Oh

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The purpose of this study is to develop a social participation activity scale for the elderly. As a result of exploratory factor analysis, confirmatory factor analysis was conducted using maximum likelihood method using bundled items. In conclusion, thirteen items of social participation activity scale seemed appropriate. Finally, convergent validity and discriminant validity were verified on the scale with the fit. The convergent validity was based on the variance extracted value. In other words, the hypothesis that the variables are the same is rejected and the validity is confirmed. This study extensively considered the measurement items of the social participation activity scale used to measure social participation activities of the elderly. In the future, it will be meaningful that it can be used as a tool to verify the effectiveness of services in organizations that provide social welfare services to elderly people such as comprehensive social welfare centers and the elderly comprehensive social welfare centers.

Keywords: elderly, social participation, scale development, validity

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Authors: Dounyazad Sour

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This research examines international doctoral students’ reflections on their journey and experiences of studying for a PhD in the UK. Since the early 1990s, the international students’ number in the UK has increased. The significant contribution of these international students to the cultural and academic diversity of the UK universities’ doctoral programmes is widely acknowledged. The substantial fees these students bring to British Higher Education institutions is also much appreciated. The rationale for undertaking this study grew from personal experience of studying in the UK. Through membership in different groups both online and, when regulations permitted it, face to face social groups, it quickly became apparent that among all students, there were both shared and individual experiences of struggles and triumphs. This insight led to the decision to investigate these matters in greater detail. This in-depth qualitative interpretative study, inspired by a phenomenological approach, offers fresh insights into academic, social and cultural experiences of international PhD students in the UK. Data collection was carried out in the UK over a period of three months, deploying focus groups, individual semi-structured interviews, and images selected by participants that represent their feelings towards their experiences. The ten participants are attending different UK universities, studying a range of disciplines and have diverse backgrounds. Interviews and discussions took place in the participants' preferred languages; Arabic, English and French. The analysis shows that the participants had experienced two types of shock: negative and positive. Negative shocks, which have seen considerable attention in the field of international students’ experiences, relate to unexpected incidents that happened to the participants in relation to their interactions with others: people from different backgrounds and people from the same background. This impacted their experience negatively through experiencing feelings of anxiety, stress, low self-esteem and xenophobia, all these hindering factors contribute to make international students struggle to adapt to the new environment. Positive shocks, which have remained largely under-researched in the field of international students’ experiences, refer to all the positive occurrences that participants experienced. For instance, a shop assistant saying: “do you need any help, honey?” which brought a sense of belonging, feeling home, safety, and satisfaction to the respondents, and made their experiences less challenging. This investigation will offer insights into the PhD international students’ experiences and shed new light on the shocks that can work as facilitators, rather than as inhibitors.

Keywords: international students, PhD journey, phenomenological approach, positive shock

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Authors: Diego Aguirre, Olac Fuentes

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In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

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Authors: Chen Xi, LIU Xuebin, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Lao Xuerui

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature have led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using Yolov5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network, machine vision

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Authors: Omojokun Gabriel Aju

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Communication network is a process of exchanging data between two or more devices via some forms of transmission medium using communication protocols. The data could be in form of text, images, audio, video or numbers which can be grouped into FTP, Email, HTTP, VOIP or Video applications. The effectiveness of such data exchange will be proved if they are accurately delivered within specified time. While some senders will not really mind when the data is actually received by the receiving device, inasmuch as it is acknowledged to have been received by the receiver. The time a data takes to get to a receiver could be very important to another sender, as any delay could cause serious problem or even in some cases rendered the data useless. The validity or invalidity of a data after delay will therefore definitely depend on the type of data (information). It is therefore imperative for the network device (such as router) to be able to differentiate among the packets which are time sensitive and those that are not, when they are passing through the same network. So, here is where the queuing disciplines comes to play, to handle network resources when such network is designed to service widely varying types of traffics and manage the available resources according to the configured policies. Therefore, as part of the resources allocation mechanisms, a router within the network must implement some queuing discipline that governs how packets (data) are buffered while waiting to be transmitted. The implementation of the queuing discipline will regulate how the packets are buffered while waiting to be transmitted. In achieving this, various queuing disciplines are being used to control the transmission of these packets, by determining which of the packets get the highest priority, less priority and which packets are dropped. The queuing discipline will therefore control the packets latency by determining how long a packet can wait to be transmitted or dropped. The common queuing disciplines are first-in-first-out queuing, Priority queuing and Weighted-fair queuing (FIFO, PQ and WFQ). This paper critically evaluates and analyse through the use of Optimized Network Evaluation Tool (OPNET) Modeller, Version 14.5 the effects of three queuing disciplines (FIFO, PQ and WFQ) on the performance of 5 different applications (FTP, HTTP, E-Mail, Voice and Video) within specified parameters using packets sent, packets received and transmission delay as performance metrics. The paper finally suggests some ways in which networks can be designed to provide better transmission performance while using these queuing disciplines.

Keywords: applications, first-in-first-out queuing (FIFO), optimised network evaluation tool (OPNET), packets, priority queuing (PQ), queuing discipline, weighted-fair queuing (WFQ)

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

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Authors: Mehmet Hakan Karaata

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In this paper, we first coin a new graph theocratic problem with numerous applications. Second, we provide two algorithms for the problem. The first solution is using a brute-force techniques, whereas the second solution is based on an initial identification of the cycles in the given graph. We then provide a correctness proof of the algorithm. The applications of the problem include graph analysis, graph drawing and network structuring.

Keywords: algorithm, cycle, graph algorithm, graph theory, network structuring

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Authors: Ioanna H. Lioliou, Despoina D. Zavraka

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The radical reformation that Greek urban space, has undergone over the last century, due to the socio-historical developments, technological development and political–geographic factors, has left its imprint on the urban landscape. While the big cities struggle to regain urban landscape balance, small towns are considered to offer high quality lifescapes, ensuring sustainable development potential. However, their unplanned urbanization process led to the loss of significant areas of nature, lack of essential infrastructure, chaotic built environment, incompatible land uses and urban cohesiveness. Natural environment reference points, such as springs, streams, rivers, forests, suburban greenbelts, and etc.; seems to be detached from urban space, while the public, open and green spaces, unequally distributed in the built environment, they are no longer able to offer a complete experience of nature in the city. This study focuses on Greek mainland, a small town Elassona, and aims to restore spatial coherence between the city’s homonymous river and its urban space surroundings. The existence of a linear aquatic ecosystem, is considered a precious greenway, also referred as blueway, able to initiate natural penetrations and ecosystems empowering. The integration of disconnected natural ecosystems forms the basis of a strategic intervention scheme, where the river becomes the urban integration tool / feature, constituting the main urban corridor and an indispensible part of a wider green network that connects open and green spaces, ensuring the function of all the established networks (transportation, commercial, social) of the town. The proposed intervention, introduces a green network highlighting the old stone bridge at the ‘entrance’ of the river in the town and expanding throughout the town with strategic uses and activities, providing accessibility for all the users. The methodology used, is based on the collection of design tools used in related urban river-design interventions around the world. The reinstallation/reactivation of the balance between natural and urban landscape, besides the environmental benefits, contributes decisively to the illustration/projection of urban green identity and re-enhancement of the quality of lifescape qualities and social interaction.

Keywords: green network, rehabilitation scheme, urban landscape, urban streams

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Authors: Omar Alshehri, Vic Lally

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This paper examined the attitudes of using social media tools to support learning at a university in Saudi Arabia. Moreover, it investigated the students’ current usage of these tools and examined the barriers they could face during the use of social media tools in the education process. Participants in this study were 42 university students. A web-based survey was used to collect data for this study. The results indicate that all of the students were familiar with social media and had used at least one type of social media for learning. It was found out that all students had very positive attitudes towards the use of social media and welcomed using these tools as a supplementary to the curriculum. However, the results indicated that the major barriers to using these tools in learning were distraction, opposing Islamic religious teachings, privacy issues, and cyberbullying. The study recommended that this study could be replicated at other Saudi universities to investigate factors and barriers that might affect Saudi students’ attitudes toward using social media to support learning.

Keywords: barriers to social media use, benefits of social media use, higher education, Saudi Arabia, social media

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: Adewusi Adeoluwawale, Oronti Iyabosola Busola, Akinola Iretiayo, Komolafe Olusola Aderibigbe

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The complex and radial structure of the low voltage distribution network (415V) makes it vulnerable to faults which are due to system and the environmental related factors. Besides these, the protective scheme employed on the low voltage network which is the fuse cannot be monitored remotely such that in the event of sustained fault, the utility will have to rely solely on the complaint brought by customers for loss of supply and this tends to increase the length of outages. A microcontroller based fault detection scheme is hereby developed to detect low voltage and high voltage fault conditions which are common faults on this network. Voltages below 198V and above 242V on the distribution feeders are classified and detected as low voltage and high voltages respectively. Results shows that the developed scheme produced a good response time in the detection of these faults.

Keywords: fault detection, low voltage distribution feeders, outage times, sustained faults

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Authors: Jean Patrick Mve

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The increasing quest for efficiency, accountability, and transparency has led to the implementation of massive governance reforms among higher education systems worldwide. This is causing many changes in the governance of higher education institutions. Governments over the world are trying to adopt business-like organizational strategies to enhance the performance of higher education institutions. This study explores the changes that have taken place in the Cameroonian higher education sector. It also attempts to draw a picture of the likely future of higher education governance and the actions to be taken for the promotion of institutional effectiveness among higher education institutions. The “governance equalizer” is used as an analytical tool to this end. It covers the five dimensions of the New Public Management (NPM), namely: state regulation, stakeholder guidance, academic self-governance, managerial self-governance, and competition. Qualitative data are used, including semi-structured interviews with key informants at the organizational level and other academic stakeholders, documents and archival data from the university and from the ministry of higher education. It has been found that state regulation among higher education institutions in Cameroon is excessively high, causing the institutional autonomy to be very low, especially at the level of financial management, staffing and promotion, and other internal administrative affairs; at the level of stakeholder guidance there is a higher degree of stakeholders consideration in the academic and research activities among universities, though the government’s interest to keep its hands in most management activities is still high; academic self-governance is also very weak as the assignment of academics is done more on the basis of political considerations than competence; there is no real managerial self-governance among higher education institutions due to the lack of institutional capacity and insufficient autonomy at the level of decision making; there is a plan to promote competition among universities but a real competitive environment is not yet put into place. The study concludes that the government’s policy should make state control more relaxed and concentrate on steering and supervision. As well, real institutional autonomy, professional competence building for top management and stakeholder participation should be considered to guarantee competition and institutional effectiveness.

Keywords: Cameroon higher education, effective institutional governance, governance equalizer, institutional autonomy, institutional effectiveness

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Authors: Shuaili Ji

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The correct use of verbs is an important element of high-quality research articles, and thus for Chinese EFL learners, it is significant to master characteristics of verbs and to precisely use verbs. However, some researches have shown that there are differences in using verbs between learners and native speakers and learners have difficulty in using English verbs. This corpus-based quantitative research can enhance learners’ knowledge of English verbs and promote the quality of research article abstracts even of the whole academic writing. The aim of this study is to find the differences between learners’ and native speakers’ use of verbs and to study the factors that contribute to those differences. To this end, the research question is as follows: What are the differences between most frequently used verbs by learners and those by native speakers? The research question is answered through a study that uses corpus-based data-driven approach to analyze the verbs used by learners in their abstract writings in terms of collocation, colligation and semantic prosody. The results show that: (1) EFL learners obviously overused ‘be, can, find, make’ and underused ‘investigate, examine, may’. As to modal verbs, learners obviously overused ‘can’ while underused ‘may’. (2) Learners obviously overused ‘we find + object clauses’ while underused ‘nouns (results, findings, data) + suggest/indicate/reveal + object clauses’ when expressing research results. (3) Learners tended to transfer the collocation, colligation and semantic prosody of shǐ and zuò to make. (4) Learners obviously overused ‘BE+V-ed’ and used BE as the main verb. They also obviously overused the basic forms of BE such as be, is, are, while obviously underused its inflections (was, were). These results manifested learners’ lack of accuracy and idiomatic property in verb usage. Due to the influence of the concept transfer of Chinese, the verbs in learners’ abstracts showed obvious transfer of mother language. In addition, learners have not fully mastered the use of verbs, avoiding using complex colligations to prevent errors. Based on these findings, the present study has implications for English teaching, seeking to have implications for English academic abstract writing in China. Further research could be undertaken to study the use of verbs in the whole dissertation to find out whether the characteristic of the verbs in abstracts can apply in the whole dissertation or not.

Keywords: academic writing abstracts, Chinese EFL learners, corpus-based, data-driven, verbs

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Authors: Shalini Misra

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The means and methods of education have been changing fast since the invention of internet. Both, ancient and modern education emphasized on the holistic development of students. But, a significant change has been observed in the 21st century learners. Online classes, intercultural and interdisciplinary education which were exceptions in the past, are setting new trends in the field of education. In the modern era, intercultural and interpersonal skills are of immense importance, not only for students but for everyone. It sets a platform for better understanding and deeper learning by ensuring the active participation and involvement of students belonging to different social and cultural backgrounds in various academic and non-academic pursuits. On October 31, 2015, on the occasion of 140th birth anniversary of Sardar Vallabhbhai Patel, Hon’ble Prime Minister of India, Narendra Modi announced a wonderful initiative, ‘Ek Bharat Shreshtha Bharat’ i.e. ‘One India Best India’ commonly known as ‘EBSB’. The program highlighted India’s rich culture and traditions. The objective of the program was to foster a better understanding and healthy relationship among Indian States. Under this program, a variety of subjects were covered like ‘Arts, Culture and Language’ .It was claimed to be a successful cultural exchange where students from diverse communities shared their thoughts and experiences with one another. Under this online cultural exchange program, the state of Uttarakhand was paired with the state of Karnataka in the year 2022. The present paper proposes to undertake a survey of a total of thirty secondary level students of Uttarakhand and the partner state Karnataka, who participated in this program with a purpose of learning and embracing new ideas and culture thus promoting intercultural education. It aims to study and examine the role of intercultural education in shifting and establishing new paradigms of education.

Keywords: education, intercultural, interpersonal, traditions, understanding

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Authors: Gintaras Mitrulevičius

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This text, which is based on the conference report, seeks to briefly examine the relationship between the concepts of social democracy and democratic socialism, drawing attention to the essential aspects of its development and, in particular, discussing the contradictions in the relationship between these concepts in the modern period. In the preparation of this text, such research methods as historical, historical-comparative methods were used, as well as methods of analyzing, synthesizing, and generalizing texts. The history of the use of terms in social democracy and democratic socialism shows that these terms were used alternately and almost synonymously. At the end of the 20th century, traditional social democracy was transformed into the so-called "new social democracy." Many of the new social democrats do not consider themselves democratic socialists and avoid the historically characteristic identification of social democracy with democratic socialism. It has become quite popular to believe that social democracy is a separate ideology from democratic socialism. Or that it has become a variant of the ideology of liberalism. This is a testimony to the crisis of ideological self-awareness of social democracy. Since the beginning of the 21st century, social democracy has also experienced a growing crisis of electoral support. This, among other things, led to her slight shift to the left. In this context, some social democrats are once again talking about democratic socialism. The rise of the ideas of democratic socialism in the United States was catalyzed by Bernie Sanders. But the proponents of democratic socialism in the United States have different concepts of democratic socialism. In modern Europe, democratic socialism is also spoken of by leftists of non-social democratic origin, whose understanding is different from that of democratic socialism inherent in classical social democracy. Some political scientists also single out the concepts in question. Analysis of the problem shows that there are currently several concepts of democratic socialism on the spectrum of the political left, both social-democratic and non-social-democratic.

Keywords: democratic socializm, socializm, social democracy, new social democracy, political ideologies

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Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

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In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Abigail Qian Zhou

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In today's China, the well-educated middle class, with stable jobs and above-average income, are the driving force behind its Internet society. Through the analysis of data from the 2015 Chinese General Social Survey and 50 interviewees, this study investigates the current situation of this group’s specific internet usage. The findings of this study demonstrate that daily life among the members of this socioeconomic group is closely tied to the Internet. For Chinese middle class, the Internet is used to socialize and entertain self and others. It is also used to search for and share information as well as to build their identities. The empirical results of this study will provide a reference, supported by factual data, for enterprises seeking to target the Chinese middle class through online marketing efforts.

Keywords: middle class, Internet use, network behaviour, online marketing, China

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Authors: Tracey Woods

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In the ever-evolving landscape of academia, the traditional role of the librarian has undergone a remarkable transformation. Once considered as custodians of books and gatekeepers of information, librarians have the potential to take on the vital role of facilitators of cross and inter-disciplinary projects. This shift is driven by the growing recognition of the value of interdisciplinary collaboration in addressing complex research questions in pursuit of novel solutions to real-world problems. This paper shall explore the potential of the academic librarian’s role in facilitating innovative, multi-disciplinary projects, both recognising and validating the vital role that the librarian plays in a somewhat underplayed profession. Academic libraries support teaching, the strengthening of knowledge discourse, and, potentially, the development of innovative practices. As the role of the library gradually morphs from a quiet repository of books to a community-based information hub, a potential opportunity arises. The academic librarian’s role is to build knowledge across a wide span of topics, from the advancement of AI to subject-specific information, and, whilst librarians are generally not offered the research opportunities and funding that the traditional academic disciplines enjoy, they are often invited to help build research in support of the academic. This identifies that one of the primary skills of any 21st-century librarian must be the ability to collaborate and facilitate multi-disciplinary projects. In universities seeking to develop research diversity and academic performance, there is an increasing awareness of the need for collaboration between faculties to enable novel directions and advancements. This idea has been documented and discussed by several researchers; however, there is not a great deal of literature available from recent studies. Having a team based in the library that is adept at creating effective collaborative partnerships is valuable for any academic institution. This paper outlines the development of such a project, initiated within and around an identified library-specific need: the replication of fragile special collections for object-based learning. The research was developed as a multi-disciplinary project involving the faculties of engineering (digital twins lab), architecture, design, and education. Centred around methods for developing a fragile archive into a series of tactile objects furthers knowledge and understanding in both the role of the library as a facilitator of projects, chairing and supporting, alongside contributing to the research process and innovating ideas through the bank of knowledge found amongst the staff and their liaising capabilities. This paper shall present the method of project development from the initiation of ideas to the development of prototypes and dissemination of the objects to teaching departments for analysis. The exact replication of artefacts is also balanced with the adaptation and evolutionary speculations initiated by the design team when adapted as a teaching studio method. The dynamic response required from the library to generate and facilitate these multi-disciplinary projects highlights the information expertise and liaison skills that the librarian possesses. As academia embraces this evolution, the potential for groundbreaking discoveries and innovative solutions across disciplines becomes increasingly attainable.

Keywords: Liaison librarian, multi-disciplinary collaborations, library innovations, librarian stakeholders

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Muhammad Abubakar Alhassan, Diane Pennington

Abstract:

Social networking sites have become a space for people to discuss public health issues such as non-suicidal self-injury (NSSI). There are thousands of tweets containing self-harm and self-injury hashtags on Twitter. It is difficult to distinguish between different users who participate in self-injury discussions on Twitter and how their opinions change over time. Also, it is challenging to understand the topics surrounding NSSI discussions on Twitter. We retrieved tweets using #selfham and #selfinjury hashtags and investigated those from the United kingdom. We applied inductive coding and grouped tweeters into different categories. This study used the Latent Dirichlet Allocation (LDA) algorithm to infer the optimum number of topics that describes our corpus. Our findings revealed that many of those participating in NSSI discussions are non-professional users as opposed to medical experts and academics. Support organisations, medical teams, and academics were campaigning positively on rais-ing self-injury awareness and recovery. Using LDAvis visualisation technique, we selected the top 20 most relevant terms from each topic and interpreted the topics as; children and youth well-being, self-harm misjudgement, mental health awareness, school and mental health support and, suicide and mental-health issues. More than 50% of these topics were discussed in England compared to Scotland, Wales, Ireland and Northern Ireland. Our findings highlight the advantages of using the Twitter social network in tackling the problem of self-injury through awareness. There is a need to study the potential risks associated with the use of social networks among self-injurers.

Keywords: self-harm, non-suicidal self-injury, Twitter, social networks

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Authors: Cheyne Kirkpatrick

Abstract:

In an attempt to make the university intensive English program more worthwhile for students, many English language programs are redesigning curriculum to offer for-credit English for Academic Purposes classes, sometimes marketed as “bridge” courses. These programs are designed to be accredited to national language standards, provide communicative language learning, and give students the opportunity to simultaneously earn university language credit while becoming proficient in academic English. This presentation will discuss the curriculum design of one such program in the United States at a large private university that created its own for-credit “bridge” program. The planning, development, piloting, teaching, and challenges of designing this type of curriculum will be presented along with the aspects of accreditation, communicative language learning, and integration within various university programs. Attendees will learn about how such programs are created and what types of objectives and outcomes are included in American EAP classes.

Keywords: IEP, AEP, Curriculum, CEFR, University Credit, Bridge

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Authors: Ge Zheng, Jun Peng

Abstract:

Unbalanced power output from individual cells of Proton Exchange Membrane Fuel Cell (PEMFC) has direct effects on PEMFC stack performance, in particular under transient operation. In the paper, a multi-layer ANN (Artificial Neural Network) model Radial Basis Functions (RBF) has been developed for predicting cells' output profiles by applying gas supply parameters, cooling conditions, temperature measurement of individual cells, etc. The feed-forward ANN model was validated with experimental data. Influence of relevant parameters of RBF on the network accuracy was investigated. After adequate model training, the modelling results show good correspondence between actual measurements and reconstructed output profiles. Finally, after the model was used to optimize the stack output performance under steady-state and transient operating conditions, it suggested that the developed ANN control model can help PEMFC stack to have obvious improvement on power output under fast acceleration process.

Keywords: proton exchange membrane fuel cell, PEMFC, artificial neural network, ANN, cell output profile, transient

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Authors: Pekka Makkonen, Georgios Lampropoulos, Kerstin Siakas

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This paper examines the impact of social media on knowledge work. It discloses and highlights which specific aspects, areas and tasks of knowledge work can be improved by the use of social media. Moreover, the study includes a survey about higher education students’ viewpoints in regard to the use of social media as a means to enhance knowledge work and knowledge sharing. The analysis has been conducted based both on empirical data and on discussions about the sources dealing with knowledge work and how it can be enhanced by using social media. The results show that social media can improve knowledge work, knowledge building and maintenance tasks in which communication, information sharing and collaboration play a vital role. Additionally, by using social media, personal, collaborative and supplementary work activities can be enhanced. Based on the results of the study, we suggest how knowledge work can be enhanced when using the contemporary information and communications technologies (ICTs) of the 21^st century and recommend future directions towards improving knowledge work.

Keywords: knowledge work, social media, social media services, improving work performance

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Authors: Mohd Adib Abd Muin, Shuhairimi Abdullah, Azizan Bahari

Abstract:

Problem: The research problem is lacking of model on social entrepreneurship that focus on Islamic perspective. Objective: The objective of this paper is to analyse the existing model on social entrepreneurship and to identify the research gap on Islamic perspective from existing models. Research Methodology: The research method used in this study is literature review and comparative analysis from 6 existing models of social entrepreneurship. Finding: The research finding shows that 6 existing models on social entrepreneurship has been analysed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: social entrepreneurship, Islamic perspective, research gap, business management

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Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

Abstract:

The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

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Authors: Marjan Golmaryami, Marzieh Behzadi

Abstract:

Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

Procedia PDF Downloads 530