Search results for: scholarly search

Authors: Ana Nascimento

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For several reasons and in different countries worldwide, there is an increasing difficulty of the States to finance higher education. However, most societies consider education as a public good, so it should be a State obligation to provide this service to citizens. In Portugal, over the last decades, state has diminished its contribution to public higher education and the public higher education institutions started to look for alternative incoming sources, namely charging student’s taxes and fees, provision of services to companies, production of applied research, search for sponsors, configuring new forms of fundraising. This financial policy can raise some concerns to the scientific and pedagogical autonomy of these institutions as well as concerns in access and equity in higher education. For these reasons and in the scope of a PhD research in the area of Economy of Education, a survey is taking place in all public higher education institutions in the Great Lisbon area that intends to analyze and discuss the policy measures in each institution in the search for external financing. The research aims to understand what these measures are and what implications they might have in the institution’s autonomy as well as in higher education access by students from less favored backgrounds. The research uses a qualitative approach, namely through semi-structured interviews to presidents, directors and rectors of each institution, totalizing 50 interviews. In this paper are discussed some of the results from the interviews made so far that present the subjects opinion about higher education finance, the right to education, the search for fundraising and the possible consequences to the institution’s autonomy as well as some literature on the state of the art.

Keywords: autonomy, finance, higher education, public goods

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Authors: Saeed Kamarian, Mahmoud Shakeri

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Sandwich structures are used in a variety of engineering applications including aircraft, construction and transportation where strong, stiff and light structures are required. In this paper, frequency maximization of Functionally Graded Sandwich (FGS) beams resting on Pasternak foundations is investigated. A generalized power-law distribution with four parameters is considered for material distribution through the thicknesses of face layers. Since the search space is large, the optimization processes becomes so complicated and too much time consuming. Thus a novel meta–heuristic called Imperialist Competitive Algorithm (ICA) which is a socio-politically motivated global search strategy is implemented to improve the speed of optimization process. Results show the success of applying ICA for engineering problems especially for design optimization of FGM sandwich beams.

Keywords: sandwich beam, functionally graded materials, optimization, imperialist competitive algorithm

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Authors: Ghada Badr, Manar Hosny, Nuha Bintayyash, Eman Albilali, Souad Larabi Marie-Sainte

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The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms.

Keywords: median problem, phylogenetic tree, permutation, genetic algorithm, beam search, genome rearrangement distance

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Authors: Mohamed Abolgasem Arteimi, Ahlam Al-Tajori

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This paper describes an ongoing project at the Libyan Academy. The project aims to build digital library for thesis and dissertations (ETD). The researchers developed a system based on Greenstone open source systems for building ETD digital library. A metadata for theses and dissertations was developed. The paper addresses issues related to project design, development and user satisfaction. Conclusions highlighted some important lessons learned to date.

Keywords: digital library, electronic theses and dissertations, open access, ETD, metadata

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Authors: Benguerine Zohra, Merzak Siham, Bouziane Cheimaa, Si Tayeb Fatima, Jou Siham, Belkessam

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Introduction: Antibiotics, widely produced and consumed in large quantities, have proven problematic due to various types of side effects. The development of bacterial resistance to currently available antibiotics has made the search for new antibacterial agents necessary. One alternative strategy to combat antibiotic-resistant bacteria is the use of natural antimicrobial substances such as plant extracts. The objective of this study is to provide an overview of the antibacterial effects of a plant native to the Middle East and Mediterranean regions, Salvia officinalis (sage). Materials and Methods: This review article was conducted by searching studies in the PubMed, Scopus, JSTOR, and SpringerLink databases. The search terms were "Salvia officinalis L." and "antibacterial effects." Only studies that met our inclusion criteria (in English, antibacterial effects of Salvia officinalis L., and primarily dating from 2012 to 2023) were accepted for further review. Results and Discussion: The initial search strategy identified approximately 78 references, with only 13 articles included in this review. The synthesis of the articles revealed that several data sources confirm the antimicrobial effects of S. officinalis. Its essential oil and alcoholic extract exhibit strong bactericidal and bacteriostatic effects against both Gram-positive and Gram-negative bacteria. Conclusion: The significant value of the extract, oil, and leaves of S. officinalis calls for further studies on the other useful and unknown properties of this multi-purpose plant.

Keywords: salvia officinalis, literature review, antibacterial, effects

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Authors: Mohammad Arifur Rahman

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The research study aims to bring to light the contribution of sir Sayeed Ahmed in the realm of education and literature. Sir Sayeed Ahmed Khan (1817 –1898), commonly known as Sir Sayeed, was an Indian Muslim leader, Islamic modernist, philosopher and social reformer of the nineteenth century. He earned a reputation as a distinguished scholar while working as a jurist for British India. During the Indian Rebellion of 1857, he remained loyal to the British Empire and was noted for his actions in saving European lives. Believing that the future of Muslims was threatened by the rigidity of their orthodox outlook, Sir Sayeed began promoting Western–style scientific education by founding modern schools and journals and organizing Muslim entrepreneurs. He was one of the founders of the Aligarh Movement and Aligarh Muslim University. He began focusing on writing, from his early life, on various subjects, mainly educational issues. He launched his attempts to revive the spirit of progress within the Muslim community of India. Therefore, modern education became the pivot of his movement for the regeneration of the Indian Muslims. Sayeed Ahmed Khan found time for literary and scholarly pursuits. The range of his literary and scholarly interests was very wide, comprising all the major areas: education, law, philosophy, history, politics, archeology, journalism, Muslim modernism, literature, science and culture, mainly based on his comprehensive religious ideas should be well measured in view to making out him and his contribution to the context. The books written by himself and the books composed by him by some of the great writers like Altaf Hussein Hali, Hafee z Malick, Nasim Rashid, and Christian W. Troll were studied to understand him and his contribution. The readers of this paper would benefit from dispelling the hazy ideas about this great man of India who made an immense contribution. Further research should be undertaken to know more about the different sides of his thought and personality. The qualitative and the historical methods are adopted for the accomplishment of the work.

Keywords: thinker, reformer, educator and Philosopher, modernist

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Authors: Alper Akin, Ibrahim Aydogdu

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This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teaching-learning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame

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Authors: F. Debbat, F. T. Bendimerad

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The efficient frequency assignment for radio communications becomes more and more crucial when developing new information technologies and their applications. It is consists in defining an assignment of frequencies to radio links, to be established between base stations and mobile transmitters. Separation of the frequencies assigned is necessary to avoid interference. However, unnecessary separation causes an excess requirement for spectrum, the cost of which may be very high. This problem is NP-hard problem which cannot be solved by conventional optimization algorithms. It is therefore necessary to use metaheuristic methods to solve it. This paper proposes Hybrid approach based on simulated annealing (SA) and Tabu Search (TS) methods to solve this problem. Computational results, obtained on a number of standard problem instances, testify the effectiveness of the proposed approach.

Keywords: cellular mobile communication, frequency assignment problem, optimization, tabu search, simulated annealing

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Authors: Ani Hambardzumyan

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The influence of Greek culture and Greek mythology on the fashion industry is enormous. The first reason behind this is that Greek culture is one of the core elements to form the clothing tradition in Europe. French fashion houses have always been considered one of the leading cloth representatives in the world. As we could perceive in the first chapter, they are among the first ones to get inspired from Greek cultural heritage and apply it while creating their garments. The French fashion industry has kept traditional classical elements in clothes for decades. However, from the second half of the 20th century, this idea started to alter step by step. Society was transforming its vision with the influence of avant-garde movements. Hence, the fashion industry needed to transform its conception as well. However, it should be mentioned that fashion brands never stopped looking at the past when creating a new perspective or vision. Paradoxically, Greek mythology and clothing tradition continued to be applied even in the search of new ideas or new interpretations. In 1997 Alexander McQueen presents his first Haute Couture collection for French fashion house Givenchy, inspired by Greek mythology and titled ‘‘Search for The Golden Fleece.’’ Perhaps, this was one of the most controversial Haute Couture shows that French audience could expect to see and French media could capture and write about. The paper discuss Spring/Summer 1997 collection ‘‘The Search of Golden Fleece’’ by Alexander McQueen. It should be mentioned that there has not been yet conducted researches to analyze the mythological and archetypal nature of the collection, as well as general observations that go beyond traditional historical reviews are few in number. Here we will observe designer’s transformative new approach regarding Greek heritage and the media’s perception of it while collection was presented. On top of that, we will observe Alexander McQueen life in the parallel line with the fashion show since the collection is nothing else but the sublimation of his personal journey and drama.

Keywords: mythology, mcqueen, the argonaut, french fashion, golden fleece, givenchy

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Authors: Mwenya Mubanga, Sula Mazimba

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Background: In Zambia, much of the focus on nutrition and health has been on reducing micronutrient deficiencies, wasting and underweight malnutrition and not on the rising global projections of trends in obesity and type 2 diabetes. The aim of this review was to identify and collate studies on the prevalence of obesity, diabetes and diabetes-related cardiovascular disease conducted in Zambia, to summarize their findings and to identify areas that need further research. Methods: The Medical Literature Analysis and Retrieval System (MEDLINE) database was searched for peer-reviewed articles on the prevalence of, and factors associated with obesity, type 2 diabetes, and diabetes-related cardiovascular disease amongst Zambian residents using a combination of search terms. The period of search was from 1 January 2000 to 31 December 2016. We expanded the search terms to include all possible synonyms and spellings obtained in the search strategy. Additionally, we performed a manual search for other articles and references of peer-reviewed articles. Results: In Zambia, the current prevalence of Obesity and Type 2 diabetes is estimated at 13%-16% and 2.0 – 3.0% respectively. Risk factors such as the adoption of western dietary habits, the social stigmatization associated with rapid weight loss due to Tuberculosis and/ or the human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and rapid urbanization have all been blamed for fueling the increased risk of obesity and type 2 diabetes. However, unlike traditional Western populations, those with no formal education were less likely to be obese than those who attained secondary or tertiary level education. Approximately 30% of those surveyed were unaware of their diabetes diagnosis and more than 60% were not on treatment despite a known diabetic status. Socio-demographic factors such as older age, female sex, urban dwelling, lack of tobacco use and marital status were associated with an increased risk of obesity, impaired glucose tolerance and type 2 diabetes. We were unable to identify studies that specifically looked at diabetes-related cardiovascular disease. Conclusion: Although the prevalence of Obesity and Type 2 diabetes in Zambia appears low, more representative studies focusing on parts of the country outside of the main industrial zone need to be conducted. There also needs to be research on diabetes-related cardiovascular disease. National surveillance, monitoring and evaluation on all non-communicable diseases need to be prioritized and policies that address underweight, obesity and type 2 diabetes developed.

Keywords: type 2 diabetes, Zambia, obesity, cardiovascular disease

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Authors: B. J. Sandesh, Saurabha Jirgi, S. Vidya, Prakash Eljer, Gowri Srinivasa

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In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.

Keywords: video indexing and retrieval, lecture videos, content based video search, multimodal indexing

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Authors: Kofi Nkonkonya Mpuangnan, Samantha Govender, Hlengiwe Romualda Mhlongo

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In recent years, a noticeable and worrisome pattern has emerged in numerous developing nations which is a steady and persistent rise in unemployment rates. This escalation of economic struggles has become a cause of great concern for parents who, having invested significant resources in their children's education, harboured hopes of achieving economic prosperity and stability for their families through secure employment. To effectively tackle this pressing unemployment issue, it is imperative to adopt a holistic approach, and a pivotal aspect of this approach involves incorporating entrepreneurial education seamlessly into the entire educational system. In this light, the authors explored approaches to integrating entrepreneurial education into school curriculum focusing on the following questions. How can an entrepreneurial mindset among learners be promoted in school? And how far have pedagogical approaches improved entrepreneurship in schools? To find answers to these questions, a systematic literature review underpinned by Human Capital Theory was adopted. This method was supported by the three stages of guidelines like planning, conducting, and reporting. The data were specifically sought from publishers with expansive coverage of scholarly literature like Sage, Taylor & Francis, Emirate, and Springer, covering publications from 1965 to 2023. The search was supported by two broad terms such as promoting entrepreneurial mindset in learners and pedagogical strategies for enhancing entrepreneurship. It was found that acquiring an entrepreneurial mindset through an innovative classroom environment, resilience, and guest speakers and industry experts. Also, teachers can promote entrepreneurial education through the adoption of pedagogical approaches such as hands-on learning and experiential activities, role-playing, business simulation games and creative and innovative teaching. It was recommended that the Ministry of Education should develop tailored training programs and workshops aimed at empowering educators with the essential competencies and insights to deliver impactful entrepreneurial education.

Keywords: education, entrepreneurship, school curriculum, pedagogical approaches, integration

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Authors: Ghadeer Aly, Yasmeen Hanafy

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The way we research travel options and decide where to go has substantially changed in the digital age. Atypical search engines like social networking sites like TikTok have evolved, influencing the preferences of various generations. The influence of TikTok use as a search engine for choosing travel locations and its effect on a country's destination branding are both examined in this study. The study specifically focuses on the comparative preferences and actions of Generations Y and Z within the Egyptian community, shedding light on how these generations interact with travel related TikTok content and how it influences their perceptions of various destinations. It also investigates how TikTok Accounts use tourism branding techniques to promote a country's tourist destination. The investigation of how social media platforms are changing as unconventional search engines has theoretical relevance. This study can advance our knowledge of how digital platforms alter information-seeking behaviors and affect the way people make decisions. Furthermore, investigating the relationship between TikTok video and destination branding might shed light on the intricate interplay between social media, perceptions of locations, and travel preferences, enhancing theories about consumer behavior and communication in the digital age. Regarding the methodology of the research, the study is conducted in two stages: first, both generations are polled, and from the results, the top three destinations are chosen to be subjected to content analysis. As for the research's theoretical framework, it incorporates the tourism destination branding model as well as the conceptual model of nation branding. Through the use of the survey as a quantitative approach and the qualitative content analysis, the research will rely on both quantitative and qualitative methods. When it comes to the theoretical framework, both the Nation Branding Model and the Tourism Branding Model can offer useful frameworks for analyzing and comprehending the dynamics of using TikTok as a search engine to choose travel destinations, especially in the context of Generation Y and Generation Z in the Egyptian community. Additionally, the sample will be drawn specifically from both Gen-Y and Gen-Z. 100 members of Gen Z and 100 members of Gen Y will be chosen from TikTok users and followers of travel-related accounts, and the sample for the content analysis will be chosen based on the survey's results.

Keywords: tiktok, nation image, egyptian community, tourism branding

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Authors: Meziane Rachid, Boufala Seddik, Hamzi Amar, Amara Mohamed

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Today’s energy industry seeks maximum benefit with maximum reliability. In order to achieve this goal, design engineers depend on reliability optimization techniques. This work uses a harmony search algorithm (HS) meta-heuristic optimization method to solve the problem of wind-Solar-Gas power systems design optimization. We consider the case where redundant electrical components are chosen to achieve a desirable level of reliability. The electrical power components of the system are characterized by their cost, capacity and reliability. The reliability is considered in this work as the ability to satisfy the consumer demand which is represented as a piecewise cumulative load curve. This definition of the reliability index is widely used for power systems. The proposed meta-heuristic seeks for the optimal design of series-parallel power systems in which a multiple choice of wind generators, transformers and lines are allowed from a list of product available in the market. Our approach has the advantage to allow electrical power components with different parameters to be allocated in electrical power systems. To allow fast reliability estimation, a universal moment generating function (UMGF) method is applied. A computer program has been developed to implement the UMGF and the HS algorithm. An illustrative example is presented.

Keywords: reliability optimization, harmony search optimization (HSA), universal generating function (UMGF)

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Authors: Shuk Ting Kinnia Yau

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As China has become more and more influential in the global and geo-political arena, mutual understanding between Japan and China has also become a topic of paramount importance. There have always been tensions between the two countries, but unfortunately, each country tends to blame the other for fanning emotions. This research will investigate portrayals of China and the Chinese people in Japanese media such as newspapers, TV news, TV drama, and cinema over this period, focusing on media sources that have particularly wide viewership or readership. By doing so, it attempts to detect any general trends in the positive or negative character of such portrayals and to see if they correlate with the results of surveys of attitudes among the general population. To the degree that correlations may be found, the question arises as to whether the media portrayals are a reflection of societal attitudes towards the Chinese, on one hand, or may be playing a role in promoting such attitudes, on the other. The relationship here is, without doubt, more complex than a simple one-way relationship of cause and effect, but indications of some direction of causality may be suggested by trends in one occurring before or after the other. Evidence will also be sought of possible longer-term trends in media portrayals of China and the Chinese people in Japan during the post-2012 period, i.e., Abe Shinzo’s second term as prime minister, in comparison to earlier periods. Perceptions of Japan’s view of China and the Chinese, both inside and outside the scholarly world, tend to be oversimplified and are often incomprehensive. This research calls attention to the role played by the media in promoting or de-promoting Sino-Japanese relations. By analyzing the nature and background of images of China and the Chinese people presented in the Japanese media, especially under the new Abe Regime, this research seeks to promote a more balanced and comprehensive understanding of attitudes in Japanese society towards its gigantic neighbor. Scholars have seen the increasingly fragile Sino-Japanese relationship as inseparable from the real-world political conflicts that have become more frequent in recent years and have sought to draw a correlation between the two. The influence of the media, however, remains a mostly under-explored domain in the academic world. Against this background, this research aims to provide an enriched scholarly understanding of Japan’s perception of China by investigating to what extent such perception can be seen to be affected by subjective or selective forms of presentation of China found in the Japanese media, or vice versa.

Keywords: Abe Shinzo, China, Japan, media

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Authors: Murat Sarı, Emin Gundogar, Mumtaz Ipek

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Nowadays, in a furniture sector, competition of market share (portion) and production variety and changeability enforce the firm to reengineer operations on manufacturing line to increase the productivity. In this study, spring mattress manufacturing line of the furniture manufacturing firm is analyzed analytically. It’s intended to search and find the bottlenecks of production to balance the semi-finished material flow. There are four base points required to investigate in bottleneck elimination process. These are bottlenecks of Method, Material, Machine and Man (work force) resources, respectively. Mentioned bottlenecks are investigated and varied scenarios are created for recruitment of manufacturing system. Probable near optimal alternatives are determined by system models built in Arena simulation software.

Keywords: bottleneck search, buffer stock, furniture sector, simulation

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Authors: Muhammedamin Hussen Saad, Geoffrey Haagler, Onno Omta, Gerben Van Der Velde

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Unfolding chaos and persistent disruptions pose threats to companies’ performance especially in vulnerable settings of SME’s particularly in developing countries. Attention for resilience research in the academic world has increased considerably during the last decade looking at the number of papers published. As we are interested in adding to the understanding of the foundation and development of the concept of resilience, we focus especially on structuring the literature of business resilience in those vulnerable settings. A well-structured systematic search & review procedure was deployed. First, we defined key search terms and applied these to multiple databases (Scopus, Web of Science, Google Scholar, Emerald, and Science Direct). To make our literature search more encompassing, we augmented with co-citation, reference checking including hand searching techniques. The paper offers (1) an overview of SMEs resilience literature from 2000 up to March 2017 comprising 88 articles, and (2) special attention, within that overview, to developing countries. This review concludes that resilience literature is very much diverse in definitions and its measurements, and is inconclusive about its influencing factors. Furthermore, resilience literature is based predominantly on research in the developed world. On the bases of how the concept resilience emerges from the literature we describe distinct features of resilience, give options to extend the theoretical bases of research into resilience and describe concrete ideas for further research.

Keywords: business resilience, systematic review, SMEs, developing countries

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

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Authors: Nasa'i Muhammad Gwadabe

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This study seeks to find the extent to which the old Islamophobic prejudice was tilted towards a more negative direction in the United States following the 9/11 terrorist attacks. It is hypothesized that, the 9/11 attacks in the United States reshaped the old Islamophobic prejudice through the reinforcement of a strong social identity construction of Muslims as “out-group”. The “social identity” and “discourse representation” theories are used as framework for analysis. To test the hypothesis, two categories were created: the prejudice (out-group) and the tolerance (in-group) categories. The Prejudice (out-group) against Muslims category was coded to include six attributes: (Terrorist, Threat, Women's Rights violation, Undemocratic, Backward and Intolerant); while the tolerance (In-group) for Muslims category was also coded to include six attributes: (Peaceful, civilized, educated, partners trustworthy and honest). Data are generated from the archives of three American newspapers: The Los Angeles Times, New York Times and USA Today using specific search terms and specific date range; from 9/11/1996 to 9/11/2006, that is five years before and five years after the 9/11. An aggregate of 20595 articles were generated from the search of the three newspapers throughout the search periods. Conclusively, for both pre and post 9/11 periods, the articles generated under the category of prejudice (out-group) against Muslims revealed a higher frequency, against that of tolerance (in-group) for them, which is lesser. Finally, The comparison between the pre and post 9/11 periods showed that, the increased Prejudice (out-group) against Muslims was most influenced through libeling them as terrorist, which signaled a skyrocketed increase from pre to post 9/11.

Keywords: in-group, Islam, Islamophobia, Muslims, out-group, prejudice, terrorism, the 9/11 and tolerance

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Authors: Seongsoo Lee

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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

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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: Ferdi Sönmez, Başak Buluz

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Agility in Knowledge Management (AKM) tries to capture agility requirements and their respective answers within the framework of knowledge and learning for organizations. Since it is rather a new construct, it is difficult to claim that it has been sufficiently discussed and analyzed in practical and theoretical realms. Like the term ‘agile learning’, it is also commonly addressed in the software development and information technology fields and across the related areas where those technologies can be applied. The organizational perspective towards AKM, seems to need some more time to become scholarly mature. Nevertheless, in the literature one can come across some implicit usages of this term occasionally. This research is aimed to explore the conceptual background of agility in KM, re-conceptualize it and extend it to business applications with a special focus on e-business.

Keywords: knowledge management, agility requirements, agility, knowledge

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Badr M. Alshammari, T. Guesmi

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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

Abstract:

In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Mahdi Taheri Asl

Abstract:

Using a variety of strategies to read text plays an important role to make students strategic independent, strategic, and metacognitive readers. Given the importance of comprehension instruction (CI), it is essential to support the fostering comprehension skills at elementary age students, particularly those who struggle with or dislike reading. One of the main components of CI is activating metacognitive skills, which double function of elementary students. Thus, it’s important to evaluate the implemented comprehension interventions to inform reading specialist and teachers. There has been limited review research in the area of CI, so the conduction review research is required. The purpose of this review is to examine the effectiveness of metacognitive reading strategies in a regular classroom environment with elementary aged students. We develop five inclusion criteria to identify researches relevant to our research. First, the article had to be published in a peer-reviewed journal from 2000 to 2023. second, the study had to include participants in elementary school it could include of special education students. Third, the intervention needed to be involved with metacognitive strategies. Fourth, the articles had to use experimental or quasi experimental design. The last one needed to include measurement of reading performance in pre and post intervention. We used computer data-based site like Eric, PsychoINFO, and google scholar to search for articles that met these criteria. we used the following search terms: comprehension instruction, meta cognitive strategies, and elementary school. The next step was to do an ancestral search that get in reviewing the relevant studies cited in the articles that were found in the database search. We identified 30studies in the initial searches. After coding agreement, we synthesized 13 with respect to the participant, setting, research design, dependent variables, measures, the intervention used by instructors, and general outcomes. The finding show metacognitive strategies were effective to empower student’s comprehension skills. It also showed that linguistic instruction will be effective if got mixed with metacognitive strategies. The research provides a useful view into reading intervention. Despite the positive effect of metacognitive instruction on students’ comprehension skills, it is not widely used in classroom.

Keywords: comprehension instruction, metacogntion, metacognitive skills, reading intervention

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Authors: Hazim Abdulsada

Abstract:

The inspection of underneath vehicle system has been given significant attention by governments after the threat of terrorism become more prevalent. New technologies such as mobile robots and computer vision are led to have more secure environment. This paper proposed that a mobile robot like Aria robot can be used to search and inspect the bombs under parking a lot vehicle. This robot is using fuzzy logic and subsumption algorithms to control the robot that movies underneath the vehicle. An OpenCV library and laser Hokuyo are added to Aria robot to complete the experiment for under vehicle inspection. This experiment was conducted at the indoor environment to demonstrate the efficiency of our methods to search objects and control the robot movements under vehicle. We got excellent results not only by controlling the robot movement but also inspecting object by the robot camera at same time. This success allowed us to know the requirement to construct a new cost effective robot with more functionality.

Keywords: fuzzy logic, mobile robots, Opencv, subsumption, under vehicle inspection

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Authors: Ladislav Kristoufek, Helen Susannah Moat, Tobias Preis

Abstract:

Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms “depression” and “suicide” relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term “depression” is related to fewer suicides, whereas a greater number of searches for the term “suicide” is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.

Keywords: nowcasting, search data, Google Trends, official statistics

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Authors: Dalia Hanna, Alexander Ferworn

Abstract:

This research provides detailed proposed training modules for the public safety teams and, specifically, SAR teams responsible for search and rescue operations related to finding lost persons with dementia. Finding a lost person alive is the goal of this training. Time matters if a lost person is to be found alive. Finding lost people living with dementia is quite challenging, as they are unaware they are lost and will not seek help. Even a small contribution to SAR operations could contribute to saving a life. SAR operations will always require expert professional and human volunteers. However, we can reduce their time, save lives, and reduce costs by providing practical training that is based on real-life scenarios. The content for the proposed training is based on the research work done by the researcher in this area. This research has demonstrated that, based on utilizing drones, the algorithmic approach could support a successful search outcome. Understanding the behavior of the lost person, learning where they may be found, predicting their survivability, and automating the search are all contributions of this work, founded in theory and demonstrated in practice. In crisis management, human behavior constitutes a vital aspect in responding to the crisis; the speed and efficiency of the response often get affected by the difficulty of the context of the operation. Therefore, training in this area plays a significant role in preparing the crisis manager to manage the emotional aspects that lead to decision-making in these critical situations. Since it is crucial to gain high-level strategic choices and the ability to apply crisis management procedures, simulation exercises become central in training crisis managers to gain the needed skills to respond critically to these events. The training will enhance the responders’ ability to make decisions and anticipate possible consequences of their actions through flexible and revolutionary reasoning in responding to the crisis efficiently and quickly. As adult learners, search and rescue teams will be approaching training and learning by taking responsibility of the learning process, appreciate flexible learning and as contributors to the teaching and learning happening during that training. These are all characteristics of adult learning theories. The learner self-reflects, gathers information, collaborates with others and is self-directed. One of the learning strategies associated with adult learning is effective elaboration. It helps learners to remember information in the long term and use it in situations where it might be appropriate. It is also a strategy that can be taught easily and used with learners of different ages. Designers must design reflective activities to improve the student’s intrapersonal awareness.

Keywords: training, OER, dementia, drones, search and rescue, adult learning, UDL, instructional design

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