Search results for: extracurricular English learning

Authors: Oloyede Akinniyi Ojo

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This study investigated the relationship between truancy and academic performance of Colleges of Education students in southwestern, Nigeria. It also examined the relationship between College Physical environment and truancy behavior among students. Furthermore, it examined the relationship between male and female students involvement in truancy behavior. Purposive sampling was used to select four colleges of education in south-western Nigeria and 120 students per college were selected from year 3 while stratified sampling was used to select schools and courses. A total of 480 students participated in the study. Three research instruments were used for this study namely: Lecturers Attendance Record, Students Statement of Result and ‘College Environment Questionnaires’ (CEQ). Four research questions guided the study. Data was analyzed using descriptive, Chi-square and T-Test. CEQ was validated by a team of experts in the field of educational evaluation. Test reliability was established at an r=0-74. The study concluded that truancy exist in colleges of education and that there was a significant relationship between truancy and academic performance of male and female truants, the study also revealed that physical environment has so much effect on the truancy behavior of the students, hence the study recommended that effort should be made to provide attractive college environment for effective learning.

Keywords: academic performance, colleges of education, students, truancy

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: K. Shaloom Mbambu, M. Pascal Tshimbalanga, K. Ruth Mutala, K. Roger Kabuya, N. Dieudonné Kabeya, Y. L. Kabeya Mukeba

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In this article, the authors examine the even more worrying situation of girls in sub-Saharan Africa. Two-girls on five are private of Global Education, which represents a real loss to the development of communities and countries. Cultural traditions, poverty, violence, early and forced marriages, early pregnancies, and many other gender inequalities were the causes of this cancer development. Namely, "it is no more efficient development tool that is educating girls." The non-schooling of girls and their lack of supervision by liberal professions have serious consequences for the life of each of them. To improve the conditions of their inferior status, girls to men introduce poverty and health risks. Raising awareness among parents and communities on the importance of girls' education, improving children's access to school, girl-boy equality with their rights, creating income, and generating activities for girls, girls, and girls learning of liberal trades to make them self-sufficient. Organizations such as the United Nations Organization can save the children. ASEAD and the AEDA group are predicting the impact of this cancer on the development of a nation's future generation must be preserved.

Keywords: young girl, Sub-Saharan Africa, higher and vocational education, development, society, environment

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Authors: Junali Deka

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“Pictures speak more than a thousand words”. It is the power of image which can have multiple meanings the way it is read by the viewers. This research article is an outcome of the extensive study of the phenomenon of‘selfie culture’ and dire need of self-constructed virtual identity among youths. In the recent times, there has been a revolutionary change in the concept of photography in terms of both techniques and applications. The popularity of ‘self-portraits’ mainly depend on the temporal space and time created on social networking sites like Facebook, Instagram. With reference to Stuart’s Hall encoding and decoding process, the article studies the behavior of the users who post photographs online. The photographic messages (Roland Barthes) are interpreted differently by different viewers. The notion of ‘self’, ‘self-love and practice of looking (Marita Sturken) and ways of seeing (John Berger) got new definition and dimensional together. After Oscars Night, show host Ellen DeGeneres’s selfie created the most buzz and hype in the social media. The term was judged the word of 2013, and has earned its place in the dictionary. “In November 2013, the word "selfie" was announced as being the "word of the year" by the Oxford English Dictionary. By the end of 2012, Time magazine considered selfie one of the "top 10 buzzwords" of that year; although selfies had existed long before, it was in 2012 that the term "really hit the big time an Australian origin. The present study was carried to understand the concept of ‘selfie-bug’ and the phenomenon it has created among youth (especially students) at large in developing a pseudo-image of its own. The topic was relevant and gave a platform to discuss about the cultural, psychological and sociological implications of selfie in the age of digital technology. At the first level, content analysis of the primary and secondary sources including newspapers articles and online resources was carried out followed by a small online survey conducted with the help of questionnaire to find out the student’s view on selfie and its social and psychological effects. The newspapers reports and online resources confirmed that selfie is a new trend in the digital media and it has redefined the notion of beauty and self-love. The Facebook and Instagram are the major platforms used to express one-self and creation of virtual identity. The findings clearly reflected the active participation of female students in comparison to male students. The study of the photographs of few selected respondents revealed the difference of attitude and image building among male and female users. The study underlines some basic questions about the desire of reconstruction of identity among young generation, such as - are they becoming culturally narcissist; responsible factors for cultural, social and moral changes in the society, psychological and technological effects caused by Smartphone as well, culminating into a big question mark whether the selfie is a social signifier of identity construction.

Keywords: Culture, Narcissist, Photographs, Selfie

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Authors: Beverly Komen

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Online crimes have been on the rise in the recent days, especially with the hit of the covid-19 pandemic. The coronavirus pandemic has led to an unprecedented rise in screen time, this means more families are relying on technology and digital solutions to keep children learning, spending more time on the virtual platforms can leave children vulnerable to online abuse and exploitation. With ease access of affordable phones, internet, and increased online activities, all children are at risk of being abused online hence making the digital space unsafe for children. With these increased use of technology and its accessibility, children are at risk of facing challenges such as access to inappropriate content, online grooming, identity theft, cyber bullying, among other risks. The big question is; as we enjoy the benefits brought in by technology, how do we ensure that our children are save in this digital space? With the analysis of the current trends, there is a gap in knowledge on people’s understanding on child online protection and safety measures when using the digital space. A survey conducted among 50 parents in Nairobi in Kenya indicated that there is a gap in knowledge on online protection of children and over 50 % of the participants shared that for sure they have no idea on how to protect children online. This paper seeks to address the concept of child protection in the digital space and come up with viable solutions in protecting children from online vices.

Keywords: child protection, digital space, online risks, online grooming, cyber bulying, online child sexual exploitation, and abuse

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Authors: Anita Burgund Isakov, Cristina Nunes, Nevenka Zegarac, Ana Antunes

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Contemporary societies are facing a noticeable shift in family realities, urging to need for the development of new policies, service, and practice orientation that has application across different sectors who serves families with children across the world. A challenge for the field of family support is diversity in conceptual assumptions and epistemological frameworks. Since many disciplines and professionals are working in the family support field, there is a need to map and gain a deeper insight into the skills for the workforce in this field. Under the umbrella of the COST action 'The Pan-European Family Support Research Network: A bottom-up, evidence-based and multidisciplinary approach', a review of the current state of knowledge published from the European studies on family support workforce skills standards is performed. Contributing to the aim of mapping and catalogization of skills standards, key stages of literature review were identified in order to extract and systematize the data. We have considered inclusion and exclusion criteria for this literature review. Inclusion criteria were: a) families living with their children and families using family support services; different methodological approaches were included: qualitative, quantitative, mix method, literature review and theoretical reflections various topic appeared in journals like working with families that are facing difficulties or culturally sensitive practice and relationship-based approaches; b) the dates ranged from 1995 to February 2020. Articles published prior to 1995 were excluded due to modernization of family support services across world; c) the sources and languages included peer-reviewed articles published in scientific journals in English. Six databases were searched and once we have extracted all the relevant papers (n=29), we searched the list of reference in each and we found 11 additional papers. In total 40 papers have been extracted from six data basis. Findings could be summarized in: 1) only five countries emerged with production in the specific topic, that is, workforce skills to family support (UK, USA, Canada, Australia, and Spain), 2) studies revealed that diverse skills support family topics were investigated, namely the professional support skills to help families of neglected/abused children or in care; the professional support skills to help families with children who suffer from behavioral problems and families with children with disabilities; and the professional support skills to help minority ethnic parents, 3) social workers were the main targeted professionals' studies albeit other child protection workers were studied too, 4) the workforce skills to family support were grouped in three topics: the qualities of the professionals (attitudes and attributes); technical skills, and specific knowledge. The framework of analyses, literature strategy and findings with study limitations will be further discussed. As an implication, this study contributes and advocates for the structuring of a common base for cross-sectoral and interdisciplinary qualification standards for the family support workforce.

Keywords: family support, skill standards, systemic review, workforce

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Authors: Bâlc Denisa-Maria

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This paper aims to present some ways of preserving a language heritage in the global era. Teaching a second language to foreign students does not imply only teaching the grammar and the vocabulary in order to reach the 4 skills, but it means constant work on developing strategies to make the students aware of the heritage that the language they learn has. Teachers and professors need to be aware of the fact that language is in constant change, they need to adjust their techniques to the digital era, but they also have to be aware of the changes, the good and the bad parts of globalizations. How is it possible to preserve the patrimony of a certain language in a globalized era? What transformations does a language face in time? What does it mean to preserve the heritage of a language through L2 teaching? What makes a language special? What impact does it have on the foreign students? How can we, as teachers, preserve the heritage of our language? Would it be everything about books, films, music, cultural events or what else? How is it possible to include digital programs in your teaching and preserving the patrimony of a language at the same time? How does computational linguistics help us in teaching a certain language? All these questions will be tackled during the essay, with special accent on the definition of a language heritage, the new perspectives for teachers/ professors, everything in a multimodal and complex way of presenting the context. The objectives of this research are: - to present some ways of preserving the heritage of a certain language against globalization - to illustrate what preservation means for L2 teaching - to encourage teachers to be aware of their language patrimony The main contributions of my research are on moving the discussion of preserving a certain language patrimony in the context of L2 teaching.

Keywords: preservation, globalization, language heritage, L2 teaching

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Authors: Hasan Husain Ali Abdulnabi

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Formative assessment feedback is increasingly practiced in higher education. Instructors allocate great time and effort to provide assessment feedback. However, educators are not sure about students’ perceptions, understanding and respond to the feedback given, as very limited research have been done about what students do with feedback and whether if they understand it. This study aims to explore students’ conceptions and perceptions of formative assessment feedback through questionnaire and focus group interviews. One hundred eighty undergraduate students doing different courses filled the questionnaire, and ten focus group discussions were conducted. Basic descriptive and content analyses were used to analyze students’ responses to the questionnaire, while grounded theory with open coding was used to analyze the focus group interviews. The study revealed that most students believe assessment feedback is helpful to improve their academic performance, and they take time to read, think and discuss their feedback. Also, the study shows most students understand the feedback given. However, students expressed that most of the written feedback given are too general, and they prefer individual oral feedback as it can lead to better understanding on how what and where to improve. The study concluded that students believe formative assessment feedback is valuable, students have reasonable understanding and respond to the feedback provided. However, this practice could be improved by requesting lecturers to make more specific feedback and communicate with students on the way of interpreting and using assessment feedback as a part of the learning and teaching process.

Keywords: assessment, feedback, formative, undergraduate, higher education

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Authors: Samal Abzhanova, Saule Mussabekova

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Today, a new system of education is being created in Kazakhstan in order to develop the system of education and to satisfy the world class standards. For this purpose, there have been established new requirements and responsibilities to the instructors. Students should not be limited with providing only theoretical knowledge. Also, they should be encouraged to be competitive, to think creatively and critically. Moreover, students should be able to implement these skills into practice. These issues could be resolved through the permanent improvement of teaching methods. Therefore, a specialist who teaches the languages should use up-to-date methods and introduce new technologies. The result of the investigation suggests that an interactive teaching method is one of the new technologies in this field. This paper aims to provide information about implementing new technologies in the process of teaching language. The paper will discuss about necessity of introducing innovative technologies and the techniques of organizing interactive lessons. At the same time, the structure of the interactive lesson, conditions, principles, discussions, small group works and role-playing games will be considered. Interactive methods are carried out with the help of several types of activities, such as working in a team (with two or more group of people), playing situational or role-playing games, working with different sources of information, discussions, presentations, creative works and learning through solving situational tasks and etc.

Keywords: interactive education, interactive methods, system of education, teaching a language

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Authors: Nkosingiphile Mbusozayo Zungu

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The purpose of the current study is to adopt informetrics methods to analyse the research on phishing from 2012 to 2021 in three selected databases in order to contribute to global cybersecurity through impactful research. The study follows a quantitative research methodology. We opted for the positivist epistemology and objectivist ontology. The analysis focuses on: (i) the productivity of individual authors, institutions, and countries; (ii) the research contributions, using co-authorship as a measure of collaboration; (iii) the altmetrics of selected research contributions; (iv) the citation patterns and research impact of research on phishing; and (v) research contributions by keywords, to discover the concepts that are related to phishing. The preliminary findings favour developed countries in terms of quantity and quality of research in the domain. There are unique research trends and patterns in the developing countries, including those in Africa, that provide opportunities for research development in the domain in the region. This study explores an important research domain by using unexplored method in the region. The study supports the SDG Agenda 2030, such as ending abuse, exploitation, trafficking, and all other forms of violence and torture of children through the use of cyberspace (SDG 16). Further, the results from this study can inform research, teaching, and learning largely in Africa. Invariably, the study contributes to cybersecurity awareness that will mitigate cybersecurity threats against vulnerable communities.

Keywords: phishing, cybersecurity, informetrics, information security

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Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

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Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

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Authors: Laura Gleason, Sahithi Talasila, Lauren Banner, Ladan Afifi, Neda Nikbakht

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Primary cutaneous anaplastic large cell lymphoma (pcALCL) accounts for 9% of all cutaneous T-cell lymphomas. pcALCL is classically characterized as a solitary papulonodule that often enlarges, ulcerates, and can be locally destructive, but overall exhibits an indolent course with overall 5-year survival estimated to be 90%. Distinguishing pcALCL from systemic ALCL (sALCL) is essential as sALCL confers a poorer prognosis with average 5-year survival being 40-50%. Although extremely rare, there have been several cases of ALK-positive ALCL diagnosed on skin biopsy without evidence of systemic involvement, which poses several challenges in the classification, prognostication, treatment, and follow-up of these patients. Objectives: We present a case of cutaneous ALK-positive ALCL without evidence of systemic involvement, and a narrative review of the literature to further characterize that ALK-positive ALCL limited to the skin is a distinct variant with a unique presentation, history, and prognosis. A 30-year-old woman presented for evaluation of an erythematous-violaceous papule present on her right chest for two months. With the development of multifocal disease and persistent lymphadenopathy, a bone marrow biopsy and lymph node excisional biopsy were performed to assess for systemic disease. Both biopsies were unrevealing. The patient was counseled on pursuing systemic therapy consisting of Brentuximab, Cyclophosphamide, Doxorubicin, and Prednisone given the concern for sALCL. Apropos of the patient we searched for clinically evident, cutaneous ALK-positive ALCL cases, with and without systemic involvement, in the English literature. Risk factors, such as tumor location, number, size, ALK localization, ALK translocations, and recurrence, were evaluated in cases of cutaneous ALK-positive ALCL. The majority of patients with cutaneous ALK-positive ALCL did not progress to systemic disease. The majority of cases that progressed to systemic disease in adults had recurring skin lesions and cytoplasmic localization of ALK. ALK translocations did not influence disease progression. Mean time to disease progression was 16.7 months, and significant mortality (50%) was observed in those cases that progressed to systemic disease. Pediatric cases did not exhibit a trend similar to adult cases. In both the adult and pediatric cases, a subset of cutaneous-limited ALK-positive ALCL were treated with chemotherapy. All cases treated with chemotherapy did not progress to systemic disease. Apropos of an ALK-positive ALCL patient with clinical cutaneous limited disease in the histologic presence of systemic markers, we discussed the literature data, highlighting the crucial issues related to developing a clinical strategy to approach this rare subtype of ALCL. Physicians need to be aware of the overall spectrum of ALCL, including cutaneous limited disease, systemic disease, disease with NPM-ALK translocation, disease with ALK and EMA positivity, and disease with skin recurrence.

Keywords: anaplastic large cell lymphoma, systemic, cutaneous, anaplastic lymphoma kinase, ALK, ALCL, sALCL, pcALCL, cALCL

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Authors: Sarah Rietze, Hannes Zacher

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Daily stand-up meetings are the most commonly used method in agile teams. In daily stand-ups, team members gather to coordinate and align their efforts, typically for a predefined period of no more than 15 minutes. The primary purpose is to ask and answer the following three questions: What was accomplished yesterday? What will be done today? What obstacles are impeding my progress? Daily stand-ups aim to enhance communication, mutual understanding, and support within the team, as well as promote collective learning from mistakes through daily synchronization and transparency. The use of daily stand-ups is intended to positively influence psychological safety within teams, which is the belief that it is safe to show oneself and take personal risks. Two studies will be presented, which explore the relationships between daily stand-ups, psychological safety, and psychological well-being. In a first study, based on survey results (n = 318), we demonstrated that daily stand-ups have a positive indirect effect on job satisfaction and a negative indirect effect on turnover intention through their impact on psychological safety. In a second study, we investigate, using an experimental design, how the use of daily stand-ups in teams enhances psychological safety and well-being compared to a control group that does not use daily stand-ups. Psychological safety is considered one of the most crucial cultural factors for a sustainable, agile organization. Agile approaches, such as daily stand-ups, are a critical part of the evolving work environment and offer a proactive means to shape and foster psychological safety within teams.

Keywords: occupational wellbeing, agile work practices, psychological safety, daily stand-ups

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Kwame Amoah

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Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

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Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

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Authors: Antonia Tsaknaki

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There are many and divergent views on how the science of translation should be taught in academic institutions or colleges, meaning as an independent study area or as part of Linguistics, Literature or Foreign Languages Departments. A much more debated issue refers to the question of whether translation theory should be included in syllabuses and study programs or the focus should be solely on practicing the profession, that is translating texts. This dissertation examines prevailing views on the significance of translation theory in translation studies in order to design an open course on moodle. Taking into account that there is a remarkable percentage of translation professionals who are self-taught without having any specific studies, the course aims at helping either translation students or professional translators familiarize with concepts, methods and problem-solving strategies that are considered necessary during the process. It is organized in four modules where the learner is guided through a series of topics (register, equivalence, decision-making, level of naturalness, Skopos theory etc); after completing these topics, they are given assignments (further reading) and texts to work on in order to practice the skills obtained. The course does not focus on a specific language pair and therefore is suitable for every individual who needs a theoretical background to boost their performance or for institutions seeking to save classroom time but not at the expense of learners’ skills.

Keywords: MOOCs, moodle, online learning, open courses, translation, translation theory

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Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

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Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

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Authors: Pranjali Avinash Yadav-Deshmukh

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Remarkable development of the Internet along with the new technological innovation, such as high-speed systems and affordable large storage space have led to a tremendous increase in the amount and accessibility to digital records. For any person, studying of all these data is tremendously time intensive, so there is a great need to access effective multi-document summarization (MDS) systems, which can successfully reduce details found in several records into a short, understandable summary or conclusion. For semantic representation of textual details in ontology area, as a theoretical design, our system provides a significant structure. The stability of using the ontology in fixing multi-document summarization problems in the sector of catastrophe control is finding its recommended design. Saliency ranking is usually allocated to each phrase and phrases are rated according to the ranking, then the top rated phrases are chosen as the conclusion. With regards to the conclusion quality, wide tests on a selection of media announcements are appropriate for “Jammu Kashmir Overflow in 2014” records. Ontology centered multi-document summarization methods using “NLP centered extraction” outshine other baselines. Our participation in recommended component is to implement the details removal methods (NLP) to enhance the results.

Keywords: disaster management, extraction technique, k-means, multi-document summarization, NLP, ontology, sentence extraction

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Authors: Araba A. Z. Osei-Tutu, Ebenezer Odame, Joseph Bawa, Samuel Amponsah

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Education is recognized as a fundamental human right and a catalyst for development. Despite progress in the provision of higher education on the African continent, there persist challenges with the tripartite areas of access, equity and quality. Therefore, this systematic review aimed at providing a comprehensive overview of conversations and voices of scholars on these three concepts in HE in Africa. The systematic review employed a thematic analysis approach, synthesizing findings from 38 selected sources. After a critical analysis of the sources included in the systematic review, deficits in access, quality, and equity were outlined, focusing on infrastructure, regional disparities, and privatization challenges. The review also revealed the weak enforcement of quality assurance measures. Strategies for improvement, proffered by the study, include expanding public sector HE, deregulating the educational sector, promoting open and distance learning, implementing preferential admission policies, and enhancing financial aid. This research contributes valuable insights for policymakers, educators, and stakeholders, fostering a collaborative approach to address challenges and promote holistic development in African higher education.

Keywords: access, equity, quality, higher education, Africa, systematic review, strategies

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Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

Abstract:

Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

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Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

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Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

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The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching, including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders, including Ghana Football Association (GFA), to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

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Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders including Ghana Football Association (GFA) to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 49

Authors: Catherine Constantinidis (Nee Tsacalos)

Abstract:

This paper presents one aspect of the larger Masters qualitative study exploring the roles of married Greek Orthodox clergy, the Priest and Presbytera, under the wing of the Greek Orthodox Archdiocese of Australia. This ground breaking research necessitated the creation of primary data within a phenomenological paradigm drawing from lived experiences of the Priests and Presbyteres in contemporary society. As a Social Worker, a bilingual (Greek/English) Mental Health practitioner and a Presbytera, the questions constantly raised and pondered are: Who do the Priest and Presbytera turn to when they experience difficulties or problems? Where do they go for support? What is in place for their emotional and psychological health and well-being? Who cares for the spiritual carer? Who is there to catch our falling clergy and their wives? What is their 'safety net'? Identified phenomena of angst, stress, frustration and confusion experienced by the Priest and (by extension) the Presbytera, within their position, coupled with basic assumptions, perceptions and expectations about their roles, the role of the organisation (the Church), and their role as spouse often caused confusion and in some cases conflict. Unpacking this complex and multi-dimensional relationship highlighted not only the roller coaster of emotions, potentially affecting their physical and mental health, but also the impact on the interwoven relationships of marriage and ministry. The author considers these phenomena in the light of bilingual cultural and religious organisational practice frameworks, specifically the Greek Orthodox Church, whilst filtering these findings through a mental health lens. One could argue that it is an expectation that clergy (and by default their wives) take on the responsibility to be kind, nurturing and supportive to others. However, when it comes to taking care of self, they are not nearly as kind. This research looks at a recurrent theme throughout the interviews where all participants talked about limited support systems and poor self care strategies and the impact this has on their ministry, mental, emotional, and physical health and ultimately on their relationships with self and others. The struggle all participants encountered at some point in their ministry was physical, spiritual and psychological burn out. The overall aim of the researcher is to provide a voice for the Priest and the Presbytera painting a clearer picture of these roles and facilitating an awareness of struggles and dilemmas faced in their ministry. It is hoped these identified gaps in self care strategies and support systems will provide solid foundations for building a culturally sensitive, empathetic and effective support system framework, incorporating the spiritual and psychological well-being of the Priest and Presbytera, a ‘safety net’. A supplementary aim is to inform and guide ministry practice frameworks for clergy, spouses, the church hierarchy and religious organisations on a local and global platform incorporating some sort of self-care system.

Keywords: care for the carer, mental health, Priest, Presbytera, religion, support system

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

Abstract:

The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

Procedia PDF Downloads 119