Search results for: research approaches

Authors: Frances Bernard Kominkiewicz

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Demonstrating the ability to build social justice and peace is integral in undergraduate and graduate education. Many disciplines are involved in peace education and peace studies, and the collaboration of those disciplines are examined in this paper. To the author’s best knowledge, no content analysis research previously existed regarding peace studies and peace education from a multidisciplinarity, interdisciplinarity, and transdisciplinarity perspective. Peacebuilding is taught through these approaches, which adds to the depth, breadth, and richness of peace education and peace studies. This paper presents a content analysis of academic peace studies programs and course descriptions. Variables studied include contributions and foci of disciplines in peace studies programs and students’ engagement in community peacebuilding. The social work discipline, for example, focuses on social and economic justice as one of the nine competencies that undergraduate and graduate students must attain before earning a Bachelor of Social Work degree or a Master of Social Work degree and becoming social work practitioners. Demonstrating the ability to build social justice and peace is integral in social work education. Peacebuilding is taught through such social work courses as conflict resolution, and social work practice with communities and organizations, and these courses are examined in this research through multidisciplinarity, interdisciplinarity, and transdisciplinarity approach. Peace and social justice are linked terms in various fields, including social work. Social justice is of paramount importance in social work programs, and social workers are trained to advocate for human rights and social, economic, and environmental justice. Social workers use knowledge of oppression, globally as well as nationally, in the practice of peace education and peace studies. Social work is at the forefront in advocating for social justice as a discipline and joins with other educators in strengthening the peacebuilding opportunities for students. The content analysis, conducted through a random sample of peace studies and peace education university and college programs in the United States, found that although courses teach the concepts of peace education and peace studies, courses often are not given these titles in the social work discipline. Therefore, this analysis also includes a discussion of the multidisciplinarity, interdisciplinarity, and transdisciplinarity approach to peace education, peace studies, and peacebuilding and the importance of these approaches in educating students about peace. The content analysis further found great variability in the number of disciplines involved in peace studies programs, the focus of those disciplines in peace education, the placement of peace studies and peace education within the university or college, and the number of courses and concentrations available in peace studies and peace education. In conclusion, the research points toward very robust and diverse approaches to peace education with opportunities for further research and discussion.

Keywords: content analysis, interdisciplinarity, multidisciplinarity, peace education programs

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Authors: O. Starineca, I. Voronchuk

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Human Resources (HR) selection and training have various implementation possibilities depending on an organization’s abilities and peculiarities. We propose to base HR selection and training decisions about on a competence-based approach. HR selection and training of employees are topical as there is room for improvement in this field; therefore, the aim of the research is to propose rational decision-making approaches for an organization HR selection and training choice. Our proposals are based on the training development and competence-based selection approaches created within previous researches i.e. Analytic-Hierarchy Process (AHP) and Linear Programming. Literature review on non-formal education, competence-based selection, AHP form our theoretical background. Some educational service providers in Latvia offer employees training, e.g. motivation, computer skills, accounting, law, ethics, stress management, etc. that are topical for Public Administration. Competence-based approach is a rational base for rational decision-making in both HR selection and considering HR training.

Keywords: competence-based selection, human resource, training, decision-making

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Authors: Javiera Espinosa, Patricia López, Noelia Santos, Nadia Loro, Esther Moraleda

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In recent years, there has been a notable increase in the number of investigations that establish that Down Syndrome and Autism Spectrum Disorder are diagnoses that can coexist together. However, there are also many studies that consider that both diagnoses present neuropsychological, linguistic and adaptive characteristics with a totally different profile. The objective of this research is to question whether there really can be a profile that encompasses both disorders or if they can be incompatible with each other. To this end, a review of the scientific literature of recent years has been carried out. The results indicate that the two lines collect opposite approaches. On the one hand, there is research that supports the increase in comorbidity between Down Syndrome and Autism Spectrum Disorder, and on the other hand, many investigations show a totally different general development profile between the two. The discussion focuses on discussing both lines of work and on proposing future lines of research in this regard.

Keywords: disability, language, speech, down syndrome

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Authors: Anuj Kumar Vaksha

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The research paper examines the trends and approaches of the international investment arbitral tribunals to the issues of environment and the exercise of states' regulatory power for the preservation of environment vis-à-vis the rights of the affected foreign investors. The paper analyses arbitral awards, decisions and orders in the leading cases of international investment arbitrations involving issues of environment and finds that there has been strong trend among the arbitral tribunals to balance the imperatives of the environmental regulation and the interest of the foreign investors. The arbitral tribunals have reflected deference to States' competence for regulation of environment to the extent they were genuine, relevant and in proportion to the legitimate objective sought to be achieved. The arbitral tribunals have at times been innovative and non-conservative in promoting the cause of environment through the mechanism of investor-state arbitration.

Keywords: International Investment Arbitration, environmental regulations, bilateral investment treaties, ICSID, NAFTA, amicus curiae, pollution havens hypothesis, environmental race to the bottom hypothesis

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Rosidah Rosidah

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The paper aims to identify and examine the effectiveness of social marketing as an approach for conducting anti-corruption campaign. Social marketing has been widely used to promote social change for the benefit of individual and society; such as for promoting healthy foods consumption, encouraging breastfeeding, reducing smoking, solving alcohol problem and drunk driving. Therefore, it is believed that this approach can be promising to be used in anti-corruption campaign. It is because social marketing can be useful of prompting people to act in accordance to the existing norms that denounce corruption, or help to establish new norms that more averse to corruption. It has established into evidence and insight based approaches to social campaign that focus on changing people’s behavior. Qualitative approach will be used in this study, with the using of literature review and secondary data analysis as the research methods. This paper is still on preliminary stage, which its results is expected to provide fundamental basis for designing model of intervention (anti-corruption campaign) using social marketing approaches.

Keywords: anti-corruption campaign, behavioral change, social influence, social marketing

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Authors: Oli Sophie Meredith, Jacquelyn Osborne, Sarah Verdon, Jane Frawley

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PROJECT OVERVIEW AND BACKGROUND: Over one million Australians are affected by ADHD at an economic and social cost of over $20 billion per annum. Despite health outcomes being significantly worse compared with men, women have historically been overlooked in ADHD diagnosis and treatment. While research suggests physical activity and other non-prescription options can help with ADHD symptoms, the frontline response to ADHD remains expensive stimulant medications that can have adverse side effects. By interviewing women with ADHD, this research will examine women’s self-directed approaches to managing symptoms, including alternatives to prescription medications. It will investigate barriers and affordances to potentially helpful approaches and identify any concerning strategies pursued in lieu of diagnosis. SIGNIFICANCE AND INNOVATION: Despite the economic and societal impact of ADHD on women, research investigating how women manage their symptoms is scant. This project is significant because although women’s ADHD symptoms are markedly different to those of men, mainstream treatment has been based on the experiences of men. Further, it is thought that in developing nuanced coping strategies, women may have masked their symptoms. Thus, this project will highlight strategies which women deem effective in ‘thriving’ rather than just ‘hiding’. By investigating the health service use, self-care and physical activity of women with ADHD, this research aligns with a priority research areas as identified by the November 2023 senate ADHD inquiry report. APPROACH AND METHODS: Semi-structured interviews will be conducted with up to 20 women with ADHD. Interviews will be conducted in person and online to capture experience across rural and metropolitan Australia. Participants will be recruited in partnership with the peak representative body, ADHD Australia. The research will use an intersectional framework, and data will be analysed thematically. This project is led by an interdisciplinary and cross-institutional team of women with ADHD. Reflexive interviewing skills will be employed to help interviewees feel more comfortable disclosing their experiences, especially where they share common ground ENGAGEMENT, IMPACT AND BENEFIT: This research will benefit women with ADHD by increasing knowledge of strategies and alternative treatments to prescription medications, reducing the social and economic burden of ADHD on Australia and on individuals. It will also benefit women by identifying risks involved with some self-directed approaches in lieu of medical advice. The project has an accessible impact plan to directly benefit end-users, which includes the development of a podcast and a PDF resource translating findings. The resources will reach a wide audience through ADHD Australia’s extensive national networks. We will collaborate with Charles Sturt’s Accessibility and Inclusion Division of Safety, Security and Well-being to create a targeted resource for students with ADHD.

Keywords: ADHD, women's health, self-directed strategies, health service use, physical activity, public health

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Authors: Selvia Arokiya Mary

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Introduction: Worldwide, breast cancer comprises 10.4% of all cancer incidence among women. In 2004, breast cancer caused 519,000 deaths worldwide (7% of cancer deaths; almost 1% of all deaths). Many women who undergo breast surgery suffer from ill-defined pain syndromes. STATEMENT OF THE PROBLEM: A study to assess the effectiveness of twin therapeutic approaches on certain bio-physiological parameters in breast cancer patients after breast surgery at selected hospital, Chennai. Objectives: This study is to 1. assess the level of certain biophysiological parameters in women after mastectomy. 2. assess the effectiveness of twin therapeutic approaches on certain biophysiological parameters in women after mastectomy. 3. correlate the practice of twin therapeutic approaches with certain biophysiological parameters. 4. associate the selected demographic variables with certain biophysiological parameters in women after mastectomy Research Design and Method: Pre experimental research design was used. Fifty women were selected by using convenient sampling technique at government general hospital, Chennai. Results: The Level of pain shows, in the study group 49(98%) of them had moderate in the pre test and after the intervention all of them had mild pain in the post test. In relation to level of shoulder function before the intervention shows that in the study group 49(98%) of them had movement towards gravity and after intervention 24 (48%) of them had movement against gravity maximum resistance. There was a significant reduction in pain and shoulder stiffness level at a ‘P’ level of < 0.001. There was a negative correlation between the pranayama practice and the level of pain, there was a positive correlation between the arm exercise practice and the level of shoulder function. There was no significant association between demographic and clinical variables with the level of pain and shoulder function in the study. Hypothesis: There is a significant difference in level of pain and shoulder function among women following breast surgery who receive pranayama & arm exercise programme. The pranayama had effect in terms of reduction of pain, arm exercise programme had effect in prevention of arm stiffness among post operative women following breast surgery. Thus the stated hypothesis was accepted. Conclusion: On the basis of the findings of the present study there was Advancing age related to increasing risk of breast cancer, level of pain also the type of surgery was associated with level of pain and shoulder function, There fore it is to be concluded that the study participants may get benefited by practice of pranayama and arm exercise program.

Keywords: biophysiological parameters breast surgery, lumpectomy , mastectomy, radical mastectomy, twin therapeutic approach, pranayama, arm exercise

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Authors: William Ho, Agus Wicaksana

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Anecdotal evidence in the last decade shows that the occurrence of disruptive events and uncertainties in the supply chain is increasing. The coupling of these events with the nature of an increasingly complex and interdependent business environment leads to devastating impacts that quickly propagate within and across organizations. For example, the recent COVID-19 pandemic increased the global supply chain disruption frequency by at least 20% in 2020 and is projected to have an accumulative cost of $13.8 trillion by 2024. This crisis raises attention to organizational resilience to weather business uncertainty. However, the concept has been criticized for being vague and lacking a consistent definition, thus reducing the significance of the concept for practice and research. This study is intended to solve that issue by providing a comprehensive review of the conceptualization, measurement, and antecedents of operational resilience that have been discussed in the supply chain risk management literature (SCRM). We performed a Scholarly Network Analysis, combining citation-based and text-based approaches, on 252 articles published from 2000 to 2021 in top-tier journals based on three parameters: AJG ranking and ABS ranking, UT Dallas and FT50 list, and editorial board review. We utilized a hybrid scholarly network analysis by combining citation-based and text-based approaches to understand the conceptualization, measurement, and antecedents of operational resilience in the SCRM literature. Specifically, we employed a Bibliographic Coupling Analysis in the research cluster formation stage and a Co-words Analysis in the research cluster interpretation and analysis stage. Our analysis reveals three major research clusters of resilience research in the SCRM literature, namely (1) supply chain network design and optimization, (2) organizational capabilities, and (3) digital technologies. We portray the research process in the last two decades in terms of the exemplar studies, problems studied, commonly used approaches and theories, and solutions provided in each cluster. We then provide a conceptual framework on the conceptualization and antecedents of resilience based on studies in these clusters and highlight potential areas that need to be studied further. Finally, we leverage the concept of abnormal operating performance to propose a new measurement strategy for resilience. This measurement overcomes the limitation of most current measurements that are event-dependent and focus on the resistance or recovery stage - without capturing the growth stage. In conclusion, this study provides a robust literature review through a scholarly network analysis that increases the completeness and accuracy of research cluster identification and analysis to understand conceptualization, antecedents, and measurement of resilience. It also enables us to perform a comprehensive review of resilience research in SCRM literature by including research articles published during the pandemic and connects this development with a plethora of articles published in the last two decades. From the managerial perspective, this study provides practitioners with clarity on the conceptualization and critical success factors of firm resilience from the SCRM perspective.

Keywords: supply chain risk management, organizational resilience, scholarly network analysis, systematic literature review

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Authors: M. A. Fodha, H. Benfradj, A. Ghazel

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This paper is a survey of recent works that proposes a baseband processor architecture for software defined radio. A classification of different approaches is proposed. The performance of each architecture is also discussed in order to clarify the suitable approaches that meet software-defined radio constraints.

Keywords: multi-core architectures, reconfigurable architectures, software defined radio, baseband processor

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Authors: Abdel-Aziz M. Mohamed

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This paper presents a state-of-the-art survey of the operations research models developed for internal audit planning. Two alternative approaches have been followed in the literature for audit planning: (1) identifying the optimal audit frequency; and (2) determining the optimal audit resource allocation. The first approach identifies the elapsed time between two successive audits, which can be presented as the optimal number of audits in a given planning horizon, or the optimal number of transactions after which an audit should be performed. It also includes the optimal audit schedule. The second approach determines the optimal allocation of audit frequency among all auditable units in the firm. In our review, we discuss both the deterministic and probabilistic models developed for audit planning. In addition, game theory models are reviewed to find the optimal auditing strategy based on the interactions between the auditors and the clients.

Keywords: operations research applications, audit frequency, audit-staff scheduling, audit planning

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Authors: Muhammad Akhtaruzzaman

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The impact of corporate environmental social and governance (ESG) on financial performance is often difficult to quantify despite the ESG related theories predict that ESG performance improves financial performance of a company. This research examines the link between corporate ESG performance and the financial performance of the NZX (New Zealand Stock Exchange) listed companies. For this purpose, this research utilizes mixed methods approaches to examine and understand this link. While quantitative results found no robust evidence of such a link, however, the qualitative analysis of content data suggests a strong cooccurrence exists between ESG performance and financial performance. The findings of this research have important implications for policymakers to support higher ESG-performing companies and for management practitioners to develop ESG-related strategies.

Keywords: ESG, financial performance, New Zealand firms, thematic analysis, mixed methods

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Authors: Victor Abu

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Background: Social justice ideals are considered as the foundation of nursing practice. These ideals are not always clearly integrated into nursing professional standards or curricula. This hinders concerted global nursing agendas for becoming aware of social injustice or engaging in action for social justice to improve the health of individuals and groups. Aim and objectives: The aim was to create an educational framework for empowering nursing students for social justice awareness and action. This purpose was attained by understanding the meaning of social justice, the effect of social injustice, the visibility of social justice learning, and ways of integrating social justice in nursing education and practice. Methods: Critical interpretive methodologies and constructivist grounded theory research designs guided the processes of recruiting nursing students (n = 11) and nurse educators (n = 11) at a London nursing university to participate in interviews and focus groups, which were analysed by coding systems. Findings: Firstly, social justice was described as ethical practices that enable individuals and groups to have good access to health resources. Secondly, social injustice was understood as unfair practices that caused minimal access to resources, social deprivation, and poor health. Thirdly, social justice learning was considered to be invisible in nursing education due to a lack of explicit modules, educator knowledge, and organisational support. Lastly, explicit modules, educating educators, and attracting leaders’ support were suggested as approaches for the visible integration of social justice in nursing education and practice. Discussion: This research proposes approaches for nursing awareness and action for the development of critical active nurse-learner, critical conscious nurse-educator, and servant nurse leader. The framework on Awareness for Social Justice Action (ASJA) created in this research is an approach for empowering nursing students for social justice practices. Conclusion: This research contributes to and advocates for greater nursing scholarship to raise the spotlight on social justice in the profession.

Keywords: social justice, nursing practice, nursing education, nursing curriculum, social justice awareness, social justice action, constructivist grounded theory

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Authors: A. Felimban, A. Prieto, U. Knaack, T. Klein

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This study aims to present an overview of recent research in building energy-retrofitting strategy applications and analyzing them within the context of hot arid climate regions which is in this case study represented by the Kingdom of Saudi Arabia. The main goal of this research is to do an analytical study of recent research approaches to show where the primary gap in knowledge exists and outline which possible strategies are available that can be applied in future research. Also, the paper focuses on energy retrofitting strategies at a building envelop level. The study is limited to specific measures within the hot arid climate region. Scientific articles were carefully chosen as they met the expression criteria, such as retrofitting, energy-retrofitting, hot-arid, energy efficiency, residential buildings, which helped narrow the research scope. Then the papers were explored through descriptive analysis and justified results within the Saudi context in order to draw an overview of future opportunities from the field of study for the last two decades. The conclusions of the analysis of the recent research confirmed that the field of study had a research shortage on investigating actual applications and testing of newly introduced energy efficiency applications, lack of energy cost feasibility studies and there was also a lack of public awareness. In terms of research methods, it was found that simulation software was a major instrument used in energy retrofitting application research. The main knowledge gaps that were identified included the need for certain research regarding actual application testing; energy retrofitting strategies application feasibility; the lack of research on the importance of how strategies apply first followed by the user acceptance of developed scenarios.

Keywords: energy efficiency, energy retrofitting, hot arid, Saudi Arabia

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Authors: Maria Angela Bedini, Fabio Bronzini

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Most of the Italian territory is at seismic risk. Many earthquakes have hit Italy, and devastating effects have been generated. The specific objective of the research is to distinguish the negative approaches that have generated unacceptable social situations of marginalization, abandonment, and economic regression, from positive methodological approaches. On the basis of the different situations examined, the study proposes strategies and guidelines to obtain the best possible results, in Italy or abroad, in the event of new earthquakes. At national and international level, many theoretical studies address the aspects of prevention, while the comparisons, carried out in this study, between the techniques and the operative procedures applied and the results obtained are rare. The adopted methodology compares the different pre-earthquake urban-planning approaches, for the emergency (temporary urban planning), and for the post-earthquake (socio-economic-territorial processes) in Italy. Attention is placed on the current consolidated planning and programming acquisitions, pre and post-earthquake. The main results of the study concern the prospects in Italy of protection from seismic risks in the next decades. An integrated settlement system for a new economic and social model, aimed at the rebirth of territories in crisis, is proposed. Finally, the conclusions describe the disciplinary positions, procedures and the fundamental points generally shared by the scientific community for each approach, in order to identify the strategic choices and the disciplinary and management paths that will be followed in the coming decades.

Keywords: post-earthquake, seismic emergency, seismic prevention, urban planning interventions in Italy

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Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

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In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Ibraheem Husain, Abul Kalam Najmi, Karishma Chester

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First-in-human (FIH) studies are a critical step in clinical development of any molecule that has shown therapeutic promise in preclinical evaluations, since preclinical research and safety studies into clinical development is a crucial step for successful development of monoclonal antibodies for guidance in pharmaceutical industry for the treatment of human diseases. Therefore, comparison between USFDA and nine pharmacologically guided approaches (PGA) (simple allometry, maximum life span potential, brain weight, rule of exponent (ROE), two species methods and one species methods) were made to determine maximum recommended starting dose (MRSD) for first in human clinical trials using four drugs namely Denosumab, Bevacizumab, Anakinra and Omalizumab. In our study, the predicted pharmacokinetic (pk) parameters and the estimated first-in-human dose of antibodies were compared with the observed human values. The study indicated that the clearance and volume of distribution of antibodies can be predicted with reasonable accuracy in human and a good estimate of first human dose can be obtained from the predicted human clearance and volume of distribution. A pictorial method evaluation chart was also developed based on fold errors for simultaneous evaluation of various methods.

Keywords: clinical pharmacology (CPH), clinical research (CRE), clinical trials (CTR), maximum recommended starting dose (MRSD), clearance and volume of distribution

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Rene Hellmuth, Jorg Frohnmayer

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The requirements of the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Even today, the methods and process models used in factory planning are predominantly based on the classical planning principles of Schmigalla, Aggteleky and Kettner, which, however, are not specifically designed for reorganization. In addition, they are designed for a largely static environmental situation and a manageable planning complexity as well as for medium to long-term planning cycles with a low variability of the factory. Existing approaches already regard factory planning as a continuous process that makes it possible to react quickly to adaptation requirements. However, digital factory models are not yet used as a source of information for building data. Approaches which consider building information modeling (BIM) or digital factory models in general either do not refer to factory conversions or do not yet go beyond a concept. This deficit can be further substantiated. A method for factory conversion planning using a current digital building model is lacking. A corresponding approach must take into account both the existing approaches to factory planning and the use of digital factory models in practice. A literature review will be conducted first. In it, approaches to classic factory planning and approaches to conversion planning are examined. In addition, it will be investigated which approaches already contain digital factory models. In the second step, an approach is presented how digital factory models based on building information modeling can be used as a basis for augmented reality tablet applications. This application is suitable for construction sites and provides information on the costs and time required for conversion variants. Thus a fast decision making is supported. In summary, the paper provides an overview of existing factory planning approaches and critically examines the use of digital tools. Based on this preliminary work, an approach is presented, which suggests the sensible use of digital factory models for decision support in the case of conversion variants of the factory building. The augmented reality application is designed to summarize the most important information for decision-makers during a reconstruction process.

Keywords: augmented reality, digital factory model, factory planning, restructuring

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Authors: Ghorbanali Mohammadi

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New approaches to sequencing mixed-model manufacturing systems are present. These approaches have attracted considerable attention due to their potential to deal with difficult optimization problems. This paper presents Multi-Objective Simulated Annealing Algorithms (MOSAA) approaches to the Just-In-Time (JIT) sequencing problem where workload-smoothing (WL) and the number of set-ups (St) are to be optimized simultaneously. Mixed-model assembly lines are types of production lines where varieties of product models similar in product characteristics are assembled. Moreover, this type of problem is NP-hard. Two annealing methods are proposed to solve the multi-objective problem and find an efficient frontier of all design configurations. The performances of the two methods are tested on several problems from the literature. Experimentation demonstrates the relative desirable performance of the presented methodology.

Keywords: scheduling, just-in-time, mixed-model assembly line, sequencing, simulated annealing

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Authors: Eric Ho

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Pedagogical approaches in Asia nowadays are imported from the West. In Confucian Heritage Culture (CHC), however, there is a dichotomy between the perceived benefits of Western pedagogies and the real classroom practices in Chinese societies. The success of Hong Kong students in large-scale international assessments has proved that both the strengths of both Western pedagogies and CHC educational approaches should be integrated for the sake of the students. University students aim to equip themselves with employability skills upon graduation. Formative assessments allow students to receive detailed, positive, and timely feedback and they can identify their strengths and weaknesses before they start working. However, there remains a question of whether university year 1 students who come from an examination-driven secondary education background are ready to respond to more formative assessments. The findings show that year 1 students are less concerned about competition in the university and more open to new teaching approaches that will allow them to improve as professionals in their major study areas.

Keywords: formative assessment, higher education, learning styles, Confucian heritage cultures

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Authors: Xinrui Gao

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This research aims to explore the potential of shifting urban villages to public housing in China. In common practice, the central and local governments established two divided systems of urban redevelopment and public housing, including aims, design ideas, policy, headquarters, and branch offices. In most cases, the urban regeneration and public housing projects satisfy only the selected part of the society who can afford it (urban regeneration) or meet the requirements (public housing), which fail to cover the housing demand. However, there are many similarities between these two types of housing under the background of a shared economy, especially in target groups, affordable prices, and efficient use of spaces. Shenzhen always takes the lead in China’s urban regeneration and housing reformation. There are some top-down approaches to transforming housing in the urban village into public housing at present. These new approaches will provide a good chance to evaluate existing practices and explore the future development path of urban villages; while at the same time it could positively influence the housing problem in China.

Keywords: urban village, public housing, sharing economy, urban redevelopment

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Authors: Elena Jiménez Lidueña, Noelia Santos Muriel, Patricia López Resa, Noelia Pulido García, Esther Moraleda Sepúlveda

Abstract:

In recent years, there has been a notable increase in the number of investigations that establish that Down Syndrome and Autism Spectrum Disorder are diagnoses that can coexist together. However, there are also many studies that consider that both diagnoses present neuropsychological, linguistic and adaptive characteristics with a totally different profiles. The objective of this research is to question whether there really can be a profile that encompasses both disorders or if they can be incompatible with each other. To this end, a review of the scientific literature of recent years has been carried out. The results indicate that the two lines collect opposite approaches. On the one hand, there is research that supports the increase in comorbidity between Down Syndrome and Autism Spectrum Disorder and, on the other hand, shows a totally different general development profile between the two. The discussion focuses on discussing both lines of work and on proposing future lines of research in this regard.

Keywords: Down Syndrome, Autism, comorbidity, linguistic

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: Suzan Duygu Bedir Erişti

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The present study tried to make a general evaluation of the dissertations conducted in the last decade in the field of art education in the Department of Fine Arts Education in the Institutes of Education Sciences in Turkey. In the study, most of the universities which involved an Institute of Education Sciences within their bodies in Turkey were reached. As a result, a total of a hundred dissertations conducted in the departments of Fine Arts Education at several universities (Anadolu, Gazi, Ankara, Marmara, Dokuz Eylul, Ondokuz Mayıs, Selcuk and Necmettin Erbakan) were determined via the open access systems of universities as well as via the Thesis Search System of Higher Education Council. Most of the dissertations were reached via the latter system, and in cases of failure, the dissertations were reached via the former system. Consequently, most of the dissertations which did not have any access restriction and which had appropriate content were reached. The dissertations reached were examined based on document analysis in terms of their research topics, research paradigms, contents, purposes, methodologies, data collection tools, and analysis techniques. The dissertations conducted in institutes of Education Sciences could be said to have demonstrated a development, especially in recent years with respect to their qualities. It was also found that a great majority of the dissertations were carried out at Gazi University and Marmara University and that a similar number of dissertations were conducted in other universities. When all the dissertations were taken into account, in general, they were found to differ a lot in their subject areas. In most of the dissertations, the quantitative paradigm was adopted, while especially in recent years, more importance has been given to methods based on the qualitative paradigm. In addition, most of the dissertations conducted with quantitative paradigm were structured based on the general survey model and experimental research model. In terms of statistical techniques, university-focused approaches were used. In some universities, advanced statistical techniques were applied, while in some other universities, there was a moderate use of statistical techniques. Most of the studies produced results generalizable to the levels of postgraduate education and elementary school education. The studies were generally structured in face-to-face teaching processes, while some of them were designed in environments which did not include results generalizable to the face-to-face education system. In the present study, it was seen that the dissertations conducted in the departments of Fine Arts Education at the Institutes of Education Sciences in Turkey did not involve application-based approaches which included art-based or visual research in terms of either research topic or methodology.

Keywords: fine arts education, dissertations, evaluation of dissertations, research trends in fine arts education

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: Jagbir Singh Kadyan

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This research paper critically analyse the performance of those Indian Automobile Companies which are listed and traded on the National Stock Exchange (NSE) of India and which are also included in the NSE nifty auto Index. In India, CSR–Corporate Social Responsibility is mandatory for certain qualifying companies under the Indian Companies Act 2013, which replaces the erstwhile Companies Act 1956. There has been a significant shift in the focus and approaches of the Indian Corporates towards their CSR obligations with the insertion of section 135, revision of section 198 and introduction of schedule VII of the Indian Companies Act 2013. Every such qualifying companies are required to mandatorily spend at least 2% of their annual average net profit of the immediately preceding three financial years on such CSR activities as specified under schedule VII of the Companies act 2013. This research paper analyzes the CSR performance of such Indian companies. This research work is originally based on the secondary data. The annual reports of the selected Indian automobile companies have been extensively used and considered for this research work.

Keywords: board of directors, corporate social responsibility, CSR committees, Indian automobile companies, Indian companies act 2013, national stock exchange

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Authors: Eman Nagi Gowid Selim

Abstract:

Nowadays, the relevance of places to people has been questioned from different perspectives. This is attributed to the fact that many international concrete blocks were used to create multi-use public spaces in neighborhoods based on the techniques of mass-productions concepts that became one of the most effective ways in building construction, replacing the local and traditional built environment. During the last decades, the world has become increasingly globalized and citizen more mobilized, and thus, ignoring the social and environmental dimensions of the local identity. The main enquiries of the research are “How did building technologies affect urban settlement’s identity?” and “What are the impacts of technologies and globalization on local identities in urban spaces? “From this perspective, the research presents firstly, a historical review that shows how old civilizations enhance their local identities using the newly discovered building materials in each era in different urban settlement and fabrics without losing the identity. The second part of the research highlights the different approaches of building technologies and urban design to present a clear understanding of ways of applying and merging between different methodologies to achieve the most efficient urban space design. The third part aims at analyzing some international and national case studies where the form and structure of particular spaces are vital to identifying the morphological elements of urban settlements and the links existing between them. In addition, it determines how the building materials are used to enrich the vocabulary of the local identity. This part ends with the deduction of the guidelines for the integration of the environmental and social dimensions within the building technologies` approaches to enhance the sustainability of local identities and thus, ending up with redefining "Urban Identity" to guide future research in such cultural areas. Finally, the research uses the comparative methodology for applying the deduced guidelines on a national case study namely “Othman`s Towers” in corniche El Maadi, and then ends up by some results in the form of strategies for future researcher, that identifies how to ensure local identity in urban settlements using new building materials and technologies to achieve social and environmental comfort within the cultural areas.

Keywords: building technologies, cultural context, environmental approach, participatory design, social dimension, urban spaces

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Authors: Mohammad Sadeghi, Mahdieh Saniee

Abstract:

Nowadays, development laws have become a major branch of engineering science, laws help humankind achieve his/her basic needs, and it is attracted to the attention of the nations. Therefore, lawyers have been invited to contemplate legislator's approaches respecting legislating countries' economic, social and cultural development plans and to observe the reliance of approaches on two elements of distributive justice and transitional justice in light of legal rationality. Legal rationality in development planning has encountered us with this question that whether a rational approach and existing models in the Iran development planning system approximate us to the goal of development laws respecting the rationalist approach and also regarding wisely decision-making model. The present study will investigate processes, approaches, and damages of development planning in the legislation of country development plans to answer this question.

Keywords: rationality, decision-making process, policymaking, development

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