Search results for: evolutionary cultural algorithm

Authors: Zicheng Zhang, Linli Zhang

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As China's biggest social media platform, Weibo has taken on essential health communication responsibilities during the pandemic. This research takes 105 posters in 15 health-related official Weibo accounts as the analysis objects to explore COVID19 health information communication and visualisation. First, the interaction between the audiences and Weibo, including forwarding, comments, and likes, is statistically analysed. The comments about the information design are extracted manually, and then the sentiment analysis is carried out to verdict audiences' views about the poster's design. The forwarding and comments are quantified as the attention index for a reference to the degree of likes. In addition, this study also designed an evaluation scale based on the standards of Health Literacy Resource by the Centers for Medicare& Medicaid Services (US). Then designers scored all selected posters one by one. Finally, combining the data of the two parts, concluded that: 1. To a certain extent, people think that the posters do not deliver substantive and practical information; 2. Non-knowledge posters(i.e., cartoon posters) gained more Forwarding and Likes, such as Go, Wuhan poster; 3. The analysis of COVID posters is still mainly picture-oriented, mainly about encouraging people to overcome difficulties; 4. Posters for pandemic prevention usually contain more text and fewer illustrations and do not clearly show cultural differences. In conclusion, health communication usually involves a lot of professional knowledge, so visualising that knowledge in an accessible way for the general public is challenging. The relevant posters still have the problems of lack of effective communication, superficial design, and insufficient content accessibility.

Keywords: weibo, visualisation, covid posters, poster design

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Nemanja Kajtez, Yue Zhan, Basel Halak

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The significant rise in the cost of manufacturing of nanoscale integrated circuits (IC) has led the majority of IC design companies to outsource the fabrication of their products to other companies, often located in different countries. This multinational nature of the hardware supply chain has led to a host of security threats, including IP piracy, IC overproduction, and Trojan insertion. To combat that, researchers have proposed logic locking techniques to protect the intellectual properties of the design and increase the difficulty of malicious modification of its functionality. However, the adoption of logic locking approaches is rather slow due to the lack of the integration with IC production process and the lack of efficacy of existing algorithms. This work automates the logic locking process by developing software using Python that performs the locking on a gate-level netlist and can be integrated with the existing digital synthesis tools. Analysis of the latest logic locking algorithms has demonstrated that the SFLL-HD algorithm is one of the most secure and versatile in trading-off levels of protection against different types of attacks and was thus selected for implementation. The presented tool can also be expanded to incorporate the latest locking mechanisms to keep up with the fast-paced development in this field. The paper also presents a case study to demonstrate the functionality of the tool and how it could be used to explore the design space and compare different locking solutions. The source code of this tool is available freely from (https://www.researchgate.net/publication/353195333_Source_Code_for_The_Lockit_Tool).

Keywords: design automation, hardware security, IP piracy, logic locking

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: Alireza Fard Kashani

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This study reports on the experiences and attitudes of six Iranian migrant families, from two groups of asylum seekers and skilled workers, with regard to their language, identity, and acculturation in Australia. The participants included first generation parents and 1.5-generation adolescents, who had lived in Australia for a minimum of three years. For this investigation, Mendoza’s (1984, 2016) acculturation model, as well as poststructuralist views of identity, were employed. The semi-structured interview results have highlighted that Iranian parents and adolescents face low degrees of intergenerational conflicts in most domains of their acculturation. However, the structural and lawful patterns in Australia have caused some internal conflicts for the parents, especially fathers (e.g., their power status within the family or their children’s freedom). Furthermore, while most participants reported ‘cultural eclecticism’ as their preferred acculturation orientation, female participants seemed to be more eclectic than their male counterparts who showed inclination towards keeping more aspects of their home culture. This finding, however, highlights a meaningful effort on the part of husbands that in order to make their married lives continue well in Australia they need to re-consider the traditional male-dominated customs they used to have in Iran. As for identity, not only the parents but also the adolescents proudly identified themselves as Persians. In addition, with respect to linguistic behaviour, almost all adolescents showed enthusiasm to retain the Persian language at home to be able to maintain contacts with their relatives and friends in Iran and to enjoy many other benefits the language may offer them in the future.

Keywords: acculturation, asylum seekers, identity, intergenerational conflicts, language, skilled workers, 1.5 generation

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Authors: Anita De Melo

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Today we live in a crucial time of ecological crisis, of environmental catastrophes worldwide, and this scenario is, arrogantly, overlooked by powerful economic forces and their politics. Thus, a critical pedagogy that leads to action and that fosters ecoliteracy, environment education, is now inevitable, and it must become an integral part of the school curriculum across the disciplines, including the social sciences and the humanities. One of the most important contemporary and emerging movement of today is ecopedagogy, a movement that blends theory and ethics towards a curriculum that focus on an environmental education that will promote ecological justice, respect, and care by educating students to become planetary citizens. This paper aims, first, to emphasize the need for discussions and investigations regarding ecoliteracy within our field of teaching foreign languages, which will consider, among others, the of role language in stimulating sustainability, and the role of second language proficiency in fostering positive transnational dialogues conducive to fighting our current planetary crisis. Second, this paper suggests and discusses some critical ecopedagogical practices -- in the form of project-based learning, service-learning and environmental-oriented study abroad programs – apropos to ecoliteracy. These interdisciplinary projects can and should bring students in contact with communities speaking the target language, and such encounter would facilitate cultural exchanges and promote positive language proficiency whilst it would also give students the opportunity to work with finding ideas/projects to fight our current ecological catastrophe.

Keywords: critical pedagogy, ecoliteracy, ecopedagogy, planetary crisis

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Authors: Itay Harlap

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Over the past decade, LGBT figures have become increasingly visible on Israeli television in its various channels and genres. In recent years, however, the representation of gays on Israeli television has undergone an interesting shift, whereby many television texts feature gay people as fathers. These texts, mostly news items and documentaries, usually present gay parenthood as a positive phenomenon. The question in paper is whether LGBT parenting (in reality and as representation) fated to be part of the homonormativity that characterizes the LGBT community in Israel, or can it be an alternative to the hegemonic discourse? This paper embraces a dialectical position and explores the tension between mainstream and radical, or homonormativity and queer politics in the specific Israeli Jewish context through a textual and discursive reading of a selection of television programs that revolve principally around gay parenting in Israel. The first part of this lecture addresses the cultural and social context that generated these representations, dealing with three key Israeli areas: The fertility cult, the evolution of the LGBT community, and the evolution of local television. The second part offers a queer reading of these ‘positive’ representations (mainly in special reports on the news and programs labeled as ‘documentaries’ by broadcasters) and highlight the possible price of the ‘bear hug’ given by Israeli media to gay parents. The last part focuses on a single case study, the TV serial drama Ima Veabaz, and suggests that this drama exposes the performative aspect of parenting and the connection between ethnicity and fertility, and offers an alternative to normative displays of gay parenting.

Keywords: fatherhood, heteronormativity, Israel, queer theory, television

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Authors: Ma Lanting, S. Eguilior, A. Hurtado, Juan F. Llamas Borrajo

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Horizontal hydraulic fracturing is a technology to increase natural gas flow and improve productivity in the low permeability formation. During this drilling operation tons of flowback and produced water which contains many organic compounds return to the surface with a potential risk of influencing the surrounding environment and human health. A mathematical model is urgently needed to represent organic compounds in water transportation process behavior and the concentration change with time throughout the hydraulic fracturing operation life cycle. A comprehensive model combined Organic Matter Transport Dynamic Model with Two-Compartment First-order Model Constant (TFRC) Model has been established to quantify the organic compounds concentration. This algorithm model is composed of two transportation parts based on time factor. For the fast part, the curve fitting technique is applied using flowback water data from the Marcellus shale gas site fracturing and the coefficients of determination (R2) from all analyzed compounds demonstrate a high experimental feasibility of this numerical model. Furthermore, along a decade of drilling the concentration ratio curves have been estimated by the slow part of this model. The result shows that the larger value of Koc in chemicals, the later maximum concentration in water will reach, as well as all the maximum concentrations percentage would reach up to 90% of initial concentration from shale formation within a long sufficient period.

Keywords: model, shale gas, concentration, organic compounds

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Authors: Miguel Costa

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Despite the "time" element being an intrinsic characteristic of the work with the landscape, its execution and completion are also often dependent on external factors, i.e., the slow bureaucratic procedures required for the implementation of a project. In the urban areas of the city, these conditions are even more present — some landscape projects are articulated with the architectural/urban design, transporting itself long, expensive and inflexible processes related with the constant transformations of contemporary urban culture, where the needs and expectations could change before the project is finished. However, despite the renewed interest and growing concern for issues related to the landscapes (particularly since the European Landscape Convention, its scope and fields of action, extended to all the landscapes and not just the selected ones), still lacks the need for a greater inclusion of citizens in its protection and construction processes as well as a greater transparency and clarity of the consequences and results of their active participation. This article aims to reflect on the production processes of urban landscapes, on its completion runtime and its relationship with the citizens by introducing temporary projects as a fieldwork methodology, as well as using the contribution of different professional practices and knowledge for its monitoring, execution, and implementation. These strategies address a more interdisciplinary, transdisciplinary and performative approach, not only from the ephemeral experience of objects and actions but also from the processes and the dynamic events that are organized from these objects and actions over the landscape. The goal is to discuss the results of these approaches on its different dimensions: critical dimension; experimental and strategic dimension; pedagogical dimension; political dimension; cultural.

Keywords: landscape fieldwork, interdisciplinarity, public inclusion, public participation, temporary projects, transdisciplinarity

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Authors: Abdelkader Ababneh

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Heritage management planning is increasingly important throughout the international context, particularly in the developing countries. Jordan has important and unique heritage resources due to its natural topography and climate, but also to its history and old sites. A high number of these archaeological sites are in very good state of preservation. Most natural sites and resources are privately managed while archaeological heritage sites are publicly managed within national legal texts and with some referencing to international legal documents. This study examines the development of cultural heritage management in Jarash, and questions if this heritage has been managed in an appropriate manner. The purpose of this paper is to define and review the stakeholders in charge of the management of the archaeological site of Jarash, the legal texts, laws and documents adopted to apply the site management. Relations and coordination between stakeholders and the challenge of the planning process is also the focus of this paper. A review of pertinent academic, technical studies, reports and projects literature pertaining to the heritage management planning in general and related to the site of Jarash in particular coupled with field study of the site served as the background of the information base for the study. Current context of actors, legislative framework, planning policies and initiatives for the site of Jarash reveal important and continuous challenge for managing the site. Recommendations suggest reviewing and restructuring the entity responsible of the sites management. It is also recommended to review their applied policies and a redevelopment of the legislative frame work.

Keywords: heritage management, stakeholders, legal protection, Jarash

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Authors: Tatia Kekelia

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This paper is part of an ongoing research addressing gender discrimination in the Court of Georgia. The research suggests that gender stereotypes influence the processes at the Court in contemporary Georgia, which causes uneven fights for women and men, not to mention other gender identities. The sub-hypothesis proposes that the gender stereotypes derive from feudal representations, which persisted during the Soviet rule. It is precisely those stereotypes that feed gender-based discrimination today. However, this paper’s main focus is on the main hypothesis, describing the revealed stereotypes, and identifying the Court as a place where their presence is most hindering societal development. First of all, this happens by demotivating people, causing loss of trust in the Court, and therefore potentially encouraging crime. Secondly, it becomes harder to adequately mobilize human resources, since more than a half of the population is female, and under the influence of rigid or more subtle forms of discrimination, they lose not only equal rights, but also the motivation to work or fight for them. Consequently, this paper falls under democracy studies as well – considering that an unbiased Court is one of the most important criteria for assessing the democratic character of a state. As the research crosses the disciplines of sociology, law, and history, a complex of qualitative research methods is applied, among which this paper relies mainly on expert interviews, interviews with attorneys, and desk research. By showcasing and undermining the gender stereotypes that work at the Court of Georgia, this research might assist in rising trust towards it in the long-term. As for the broader relevance, the study of the Georgian case opens the possibility to conduct comparative analyses in the region and the continent, and, presumably, carve the lines of cultural influences.

Keywords: gender, stereotypes, bias, democratization, judiciary

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Authors: Jitendra Aswani

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In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that.

Keywords: global financial crisis, Asian stock markets, network science, Kruskal algorithm

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Authors: Anju Batta Sehgal

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Climate change is a major challenge in terms of agriculture, food security and rural livelihood for thousands of people especially the poor in Himachal, which falls in North-Western Himalayas. Agriculture contributes over 45 per cent to net state domestic product. It is the main source of income and employment. Over 93 per cent of population is dependent on agriculture which provides direct employment to 71 percent of its people. Area of operation holding is about 9,79 lakh hectares owned by 9.14 lakh farmers. About 80 per cent area is rain-fed and farmers depend on weather gods for rains. Region is a home of diverse ethnic communities having enormous socio-economic and cultural diversities, gifted with range of farming systems and rich resource wealth, including biodiversity, hot spots and ecosystems sustaining millions of people living in the region. But growing demands of ecosystem goods and services are posing threats to natural resources. Climate change is already making adverse impact on the indigenous people. The rural populace is directly dependent for all its food, shelter and other needs on the climate. Our aim should be to shift the focus to indigenous people as primary actors in terms of global climate change monitoring, adaptations and innovations. Objective of this paper is to identify the climate change related threats and vulnerabilities associated with agriculture as a sector and agriculture as people’s livelihood. Broadly it analyses the connections between the nature and rural consumers the ethnic groups.

Keywords: climate change, agriculture, indigenous people, Himachal Pradesh

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Authors: Mas Rahmah

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Indonesia is the most populous Southeast Asian nations, as Indonesia`s population is constantly growing, food security has become a crucial trending issue. Although Indonesia has more than enough natural resources and agricultural products to ensure food security for all, Indonesia is still facing the problem of food security because of adverse weather conditions, increasing population, political instability, economic factors (unemployment, rising food prices), and the dependent system of agriculture. This paper will analyze that Geographical Indication (GI) can aid in transforming Indonesian agricultural-dependent system by tapping the unique product attributes of their quality products since Indonesia has a lot of agricultural products with unique quality and special characteristic associated with geographical factors such as Toraja Coffee, Alor Vanili, Banda Nutmeg, Java Tea, Deli Tobacco, Cianjur Rise etc. This paper argues that the reputation and agricultural products and their intrinsic quality should be protected under GI because GI will provide benefit supporting the food security program. Therefore, this paper will expose the benefit of GI protection such as increasing productivity, improving the exports of GI products, creating employment, adding economic value to products, and increasing the diversity of supply of natural and unique quality products, etc. that can contribute to food security. The analysis will finally conclude that the scenario of promoting GI may indirectly contribute to food security through adding value by incorporating territory specific cultural, environmental and social qualities into production, processing and developing of unique local, niche and special agricultural products.

Keywords: geographical indication, food security, agricultural product, Indonesia

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Authors: S. Cobos-Guzman

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This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.

Keywords: autonomous, indoor robot, mechatronic, omnidirectional robot

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Authors: Jerzy Banski

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The basic aim of this study is to discuss and assess different classifications and research approaches to small towns that take their social and economic functions into account, as well as relations with surrounding areas. The subject literature typically includes three types of approaches to the classification of small towns: 1) the structural, 2) the location-related, and 3) the mixed. The structural approach allows for the grouping of towns from the point of view of the social, cultural and economic functions they discharge. The location-related approach draws on the idea of there being a continuum between the center and the periphery. A mixed classification making simultaneous use of the different approaches to research brings the most information to bear in regard to categories of the urban locality. Bearing in mind the approaches to classification, it is possible to propose a synthetic method for classifying small towns that takes account of economic structure, location and the relationship between the towns and their surroundings. In the case of economic structure, the small centers may be divided into two basic groups – those featuring a multi-branch structure and those that are specialized economically. A second element of the classification reflects the locations of urban centers. Two basic types can be identified – the small town within the range of impact of a large agglomeration, or else the town outside such areas, which is to say located peripherally. The third component of the classification arises out of small towns’ relations with their surroundings. In consequence, it is possible to indicate 8 types of small-town: from local centers enjoying good accessibility and a multi-branch economic structure to peripheral supra-local centers characterised by a specialized economic structure.

Keywords: small towns, classification, functional structure, localization

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Authors: Jui-Chien Hsieh

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Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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Authors: Surichai Butcha, Dararat Khampusaen

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As the Internet is recognized as a high potential and powerful educational tool to access sources of knowledge, plagiarism is an increasing unethical issue found in students’ writing. This paper is deriving from the 1st phase of an on-going study investigating the effects of the supplementary on citing sources on undergraduate students’ writing. The 40 participants were divided into 1 experimental group and 1 control group. Both groups were administered with a questionnaire on knowledge and an interview on attitude related to using sources in writing. Only the experimental group undertook the 4 lessons focusing on using outside sources and citing the original work (quoting, synthesizing, summarizing and paraphrasing) were delivered to them via e-learning tools throughout a semester. Participants were required to produce 4 writing tasks after each lesson. The results were concerned with types and factors on using outside sources in writing of Thai undergraduate EFL students from the survey. The interview results supported and clarified the survey result. In addition, the writing rubrics confirmed the types of plagiarism frequently occurred in students’ writing. The results revealed the types and factors on plagiarism including their perceptions on using the outside sources in their writing from the interview. The discussion shed the lights on cultural dimensions of plagiarism in student writing, roles of teachers, library, and university policy on the rate of plagiarism. Also, the findings promoted the awareness on ethics in writing and prevented the rate of potential unintentional plagiarism. Additionally, the results of this phase of study could lead to the appropriate contents to be considered for inclusion in the supplementary on using sources for writing for future research.

Keywords: citing source, EFL writing, e-learning, Internet, plagiarism

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Authors: Lucia Perez, Maria Gaton y Santa Palella

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Starting from the etymology of the word culture, the Latin term ‘colere’, whose meaning is to cultivate, we understand that the society that cultivates its knowledge is laying the foundations for new possibilities. In this sense, art and fashion contain the same attributes: concept, aesthetic principles, and refined techniques. Both play a crucial role, communication, and this implies a sense of community, relationship with tradition, and innovation. This is the mirror in which to contemplate, but also the space that helps to grow. This is the framework where our object of study opens up: the anthropological management or the mission management model applied to fashion exhibitions in museums and cultural institutions. For this purpose, a bibliographic review has been carried out with its subsequent analysis, a case study of three successful exhibitions: ‘Christian Dior: designer of dreams’, ‘Balenciaga and the Spanish painting’, and ‘China: Through the Looking Glass’. The methodology has been completed with interviews focused on the curators. Amongst the results obtained, it is worth highlighting the fundamental role of transcendent leadership, which, in addition to being results-oriented, must align the motivations of the collaborators with the mission. The anthropological management model conceives management as a service, and it is oriented to the interests of the staff and the public, in short, of the person; this is what enables the objectives of effectiveness, efficiency, and social value to be achieved; dimensions, all necessary for the proper development of the mission of the exhibitions. Fashion, understood as art, is at the service of culture, and therefore of the human being, which defines a transcendent mission. We conclude that the profile of an anthropological management model applied to fashion exhibitions in museums is the ideal one to achieve the purpose of these institutions.

Keywords: art, culture, fashion, anthropological model, fashion exhibitions

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Authors: Ying Han, Weirong Chen, Qi Li

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An energy management method based on equivalent hydrogen consumption minimum strategy is proposed in this paper aiming at the direct-current (DC) microgrid consisting of photovoltaic cells, fuel cells, energy storage devices, converters and DC loads. The rational allocation of fuel cells and battery devices is achieved by adopting equivalent minimum hydrogen consumption strategy with the full use of power generated by photovoltaic cells. Considering the balance of the battery’s state of charge (SOC), the optimal power of the battery under different SOC conditions is obtained and the reference output power of the fuel cell is calculated. And then a droop control method based on time-varying droop coefficient is proposed to realize the automatic charge and discharge control of the battery, balance the system power and maintain the bus voltage. The proposed control strategy is verified by RT-LAB hardware-in-the-loop simulation platform. The simulation results show that the designed control algorithm can realize the rational allocation of DC micro-grid energy and improve the stability of system.

Keywords: DC microgrid, equivalent minimum hydrogen consumption strategy, energy management, time-varying droop coefficient, droop control

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Bo Yan, Amy Y. M. Chow

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Bereavement is recognized as a universal challenging experience. It is important to gather research evidence on protective factors in bereavement. Hope is considered as one of the protective factors in previous coping studies. The present study aims to add knowledge by investigating hope at the first month after death to predict psychological symptoms altogether including complicated grief (CG), anxiety, and depressive symptoms at the seventh month. The data were collected via one-on-one interview survey in a longitudinal project with Hong Kong hospice users (sample size 105). Most participants were at their middle age (49-year-old on average), female (72%), with no religious affiliation (58%). Bayesian Structural Equation Modeling (BSEM) analysis was conducted on the longitudinal dataset. The BSEM findings show that hope at the first month of bereavement negatively predicts both CG and anxiety symptoms at the seventh month but not for depressive symptoms. Age and gender are controlled in the model. The overall model fit is good. The current study findings suggest assessing hope at the first month of bereavement. Hope at the first month after the loss is identified as an excellent predictor for complicated grief and anxiety symptoms at the seventh month. The result from this sample is clear, so it encourages cross-cultural research on replicated modeling and development of further clinical application. Particularly, practical consideration for early intervention to increase the level of hope has the potential to reduce the psychological symptoms and thus to improve the bereaved persons’ wellbeing in the long run.

Keywords: anxiety, complicated grief, depressive symptoms, hope, structural equational modeling

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Authors: Loai AbdAllah, Mahmoud Kaiyal

Abstract:

Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

Abstract:

Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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Authors: Panupong Makvichian

Abstract:

Global Navigation Satellite System (GNSS) is nowadays a common technology that improves navigation functions in our life. Additionally, GNSS is also being employed on behalf of an accurate atmospheric sensor these times. Meteorology is a practical application of GNSS, which is unnoticeable in the background of people’s life. GNSS Precise Point Positioning (PPP) is a positioning method that requires data from a single dual-frequency receiver and precise information about satellite positions and satellite clocks. In addition, careful attention to mitigate various error sources is required. All the above data are combined in a sophisticated mathematical algorithm. At this point, the research is going to demonstrate how GNSS and PPP method is capable to provide high-precision estimates, such as 3D positions or Zenith tropospheric delays (ZTDs). ZTDs combined with pressure and temperature information allows us to estimate the water vapor in the atmosphere as precipitable water vapor (PWV). If the process is replicated for a network of GNSS sensors, we can create thematic maps that allow extract water content information in any location within the network area. All of the above are possible thanks to the advances in GNSS data processing. Therefore, we are able to use GNSS data for climatic trend analysis and acquisition of the further knowledge about the atmospheric water content.

Keywords: GNSS, precise point positioning, Zenith tropospheric delays, precipitable water vapor

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Authors: Juhee Lee, Yongjun Lee

Abstract:

In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: finite volume method, fluid flow, laminar flow, unstructured grid

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Authors: Michelle Odudu

Abstract:

Ghana and Nigeria are known for their high levels of Occupational Fraud in public offices. The governments of both countries have emphasised their commitment to reducing the losses caused to the state by pledging their allegiance to the counter-fraud agencies to help tackle Occupational Fraud. Yet it seems that the prosecution of such cases is ineffective as high-profile fraudsters can operate with immunity and their cases remain unprosecuted. This research project was based on in-depth examinations of 50 occupational fraud cases involving high-profile individuals in both countries. In doing so, it established the characteristics of those who were prosecuted; the extent to which prosecutions were effectively managed; the barriers to effective prosecutions; and the similarities or differences between the occurrences in both countries. The aim of the project is to examine the practice of and barriers to prosecution of large-scale occupational fraud of those in senior public positions in Ghana and Nigeria. The study drew on the experiences of stakeholders such as defence and prosecution barristers, academics, and fraud analysts via semi-structured interviews and questionnaires. 13 interviews were conducted in Ghana and in Nigeria, where respondents were recruited using a snowball approach. Questionnaires were physically distributed: 20 of the staff at EOCO and 10 to NGO staff in Ghana; 6 and 5 came back, respectively. The empirical data collected suggests that there is no lack of will on the agencies’ part to at least commence proceedings. However, various impediments hamper a successful completion of prosecution. Challenges were more evident in Nigeria, where agencies are less effective at retrieving stolen assets and changing social norms. This is further compounded by several cultural and political factors, which create limitations leaving many cases ‘still pending’.

Keywords: comparative, prosecution, punishment, international, whitecollar, fraud

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Authors: Shayma Munqith Al-Baker, Fadhl Ahmed Saeed Al-Gasha’a, Samira Hamid Hanash, Ahmed Ali Al-Hazmi

Abstract:

A total of 200 samples (180 fecal materials and 20 organ samples) were collected from (5 different poultry farms, 10 local poultry shops, 5 houses poultry, 5 Eggs stores shops and 5 hand slaughters centers) in Ibb city, Yemen, 2014. According to morphological, cultural, as well as biochemical characterization and serological tests, 59 29.5% isolates were identified as Salmonella spp. and all Salmonella isolates were categorized by serotype, which comprised of, 37 62.71% Salmonella Typhimurium serovar, 21 35.59%. Salmonella Enteritidis serovar and 11.69% Salmonella Heidelberg serovar. Antibiotic sensitivity test was done for bacterial isolates and the results showed there were clear differences in antibiotic resistant. Antimicrobial susceptibility of the isolates varies as follows: Ofloxacin 79.66%, Ciprofloxacin 67.80%, Colistin 59.32% and Gentamycin 52.54%. All of isolates were resistant to Erythromycin, Penicillin and Lincomycin. Antibacterial activity was done for both aqueous and ethanol extracts of Dodonaea viscosa plant by using well and disc diffusion assay. The results indicated that well diffusion assay had best results than disc diffusion assay, the highest inhibition zone was 22 mm for well diffusion and 15 mm for disc diffusion assay, the results observed that ethanol extract had best antibacterial effect than aqueous extract which the percentage of bacterial isolates affected with ethanol extract was 71.19% comparing with aqueous extract 28.81% by using disc diffusion assay, while the percentage of bacterial isolates affected with ethanol extract was 88.13% comparing with aqueous extract 52.54% by using will diffusion assay.

Keywords: Salmonella spp, Dodonaea viscosa, antimicrobial and salmonellosis

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Authors: Hao Wang, Shengchun Wang, Weidong Wang

Abstract:

On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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