Search results for: Kinaesthetic learning style

Authors: Farouk A. N. Bouhadiba

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This work addresses the issue of the LMD(Licence, Master, Doctorat) in Algeria and the impact it has had on education quality in terms of educational affect and effect. It starts with a brief introduction to the financial means, the educational settings, and the social environment in place when the LMD was institutionalized in Algeria (2003-2004). Some factors for the success or failure of this top-down institutional endeavor are examined and analyzed. These include – among other factors - the teacher/student attitudes, apprehensions, and motivations on the one hand and the institutional euphoria for the LMD in Algeria on the other hand. Some issues at stake are discussed. More specifically, the professional versus the student affect on today’s attitudes, interests, and values is examined as a result of nearly two decades of LMD teaching and learning in Algerian universities. We shall then present some official curricula that, in terms of content, reflect the spirit, principles, and architectures of the LMD but which, in reality, are partially, if not fully, set aside when it comes to teaching practices, learning behaviors, motivation, and evaluation. The discussion on effect highlights attitudinal, developmental, and social markers that are indicative of the extent to which Education Quality in Algeria has been positively or negatively affected by the implementation of the LMD.

Keywords: LMD bachelor's masters doctorat, affects and effects, education quality, Algeria

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Authors: Yee Yan Crystal Kwong

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The essence of rape is the absence of consent to sexual intercourse. Yet, the definition of consent is not absolute and allows for subjectivity. In this case, the accuracy of oral interpretation becomes very important as the narratives of events and situation, as well as the register and style of speakers would influence the juror decision making. This paper first adopts a corpus-based approach to investigate how court interpreters in Hong Kong handle expressions that refer to sexual activities. The data of this study will be based on online corpus :From legislation to translation, from translation to interpretation: The narrative of sexual offences. The corpus comprises the transcription of five separate rape trials and all of these trials were heard with the presence of an interpreter. Since there are plenty of sex-related expressions used by witnesses and defendants in the five cases, emphasis will be put on those which have an impact on the definition of rape. With an in-depth analysis of the interpreted utterances, different interpreting approaches will be identified to observe how interpreters retain the intended meanings. Interviews with experienced court interpreters will also be conducted to revisit the validity of the traditional verbatim standard. At the end of this research, various interpreting approaches will be compared and evaluated. A redefinition of interpreters' institutional role, as well as recommendations for interpreting learners will be provided.

Keywords: court interpreting, interpreters, legal translation, slangs

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Authors: Nassrin Badrkhani

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Current paper was designed aiming at finding the impacts of play therapy on the development of mentally retarded students in elementary school. The sample included 191 elementary students from 5 classes. Sixty students were chosen from each class, and based on their learning capabilities, they were further assigned into similar control and treatment groups. Then, five groups received treatments with special types of games, instruments, and methods for two months. The teacher-made instruments in literature, math, and science were adopted after their content validity had been confirmed by experienced teachers. The findings were analyzed in both descriptive, including mean, median, and standard deviation, and interpretive levels, using covariance analysis in SPSS. The results were indicative of the fact that play therapy (individual and group games) was positively effective in mentally retarded students’ educational development. Moreover, regarding P ˂0/001, it was found that group games were more influential than individual ones. It was also clear that the students’ gender played no role in this kind of treatment. Therefore, it is highly recommended to implement play therapy as a part of the educational curriculum for mentally retarded pupils.

Keywords: development, education, learning, play therapy, student, teacher

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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Speaker recognition is a crucial task in the field of speech processing, aimed at identifying individuals based on their vocal characteristics. However, existing speaker recognition methods face numerous challenges. Traditional methods primarily rely on audio signals, which often suffer from limitations in noisy environments, variations in speaking style, and insufficient sample sizes. Additionally, relying solely on audio features can sometimes fail to capture the unique identity of the speaker comprehensively, impacting recognition accuracy. To address these issues, we propose a multi-modal network architecture that simultaneously processes both audio and text signals. By gradually integrating audio and text features, we leverage the strengths of both modalities to enhance the robustness and accuracy of speaker recognition. Our experiments demonstrate significant improvements with this multi-modal approach, particularly in complex environments, where recognition performance has been notably enhanced. Our research not only highlights the limitations of current speaker recognition methods but also showcases the effectiveness of multi-modal fusion techniques in overcoming these limitations, providing valuable insights for future research.

Keywords: feature fusion, memory network, multimodal input, speaker recognition

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Authors: Tamas Madl

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Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

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Authors: Muna Shafiq

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Growth in international immigration is a reflection of increased migration patterns in Canada and in other parts of the world. Canada continues to promote itself as a bilingual country, yet the bilingual French and English population numbers do not reflect this platform. Each province’s integration policies focus only on second language learning of either English or French. Moreover, since English Canadians outnumber French Canadians, maintaining, much less increasing, English-French bilingualism appears unrealistic. One solution to increasing Canadian bilingualism requires creating intercultural communication initiatives between youth in Quebec and the rest of Canada. Specifically, the focus is on active, experiential learning, where intercultural competencies develop outside traditional classroom settings. The target groups are Generation Y Millennials and Generation Z Linksters, the next generations in the career and parenthood lines. Today, Canada’s education system, like many others, must continually renegotiate lines between programs it offers its immigrant and native communities. While some purists or right-wing nationalists would disagree, the survival of bilingualism in Canada has little to do with reducing immigration. Children and youth immigrants play a valuable role in increasing Canada’s French and English speaking communities. For instance, a focus on more immersion, over core French education programs for immigrant children and youth would not only increase bilingual rates; it would develop meaningful intercultural attachments between Canadians. Moreover, a vigilant increase of funding in French immersion programs is critical, as are new initiatives that focus on experiential language learning for students in French and English language programs. A favorable argument supports the premise that other than French-speaking students in Québec and elsewhere in Canada, second and third generation immigrant students are excellent ambassadors to promote bilingualism in Canada. Most already speak another language at home and understand the value of speaking more than one language in their adopted communities. Their dialogue and participation in experiential language exchange workshops are necessary. If the proposed exchanges take place inter-provincially, the momentum to increase collective regional voices increases. This regional collectivity can unite Canadians differently than nation-targeted initiatives. The results from an experiential youth exchange organized in 2017 between students at the crossroads of Generation Y and Generation Z in Vancouver and Quebec City respectively offer a promising starting point in assessing the strength of bringing together different regional voices to promote bilingualism. Code-switching between standard, international French Vancouver students, learn in the classroom versus more regional forms of Quebec French spoken locally created regional connectivity between students. The exchange was equally rewarding for both groups. Increasing their appreciation for each other’s regional differences allowed them to contribute actively to their social and emotional development. Within a sociolinguistic frame, this proposed model of experiential learning does not focus on hands-on work experience. However, the benefits of such exchanges are as valuable as work experience initiatives developed in experiential education. Students who actively code switch between French and English in real, not simulated contexts appreciate bilingualism more meaningfully and experience its value in concrete terms.

Keywords: experiential learning, intercultural communication, social and emotional learning, sociolinguistic code-switching

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Authors: Ricky Leung

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Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve the health and well-being of individuals and communities. One way AI can be used to enhance social media in health organizations is through sentiment analysis. This involves analyzing the emotions expressed in social media posts to better understand public opinion and respond accordingly. This can help organizations gauge the impact of their campaigns, track the spread of misinformation, and improve communication with the public. While social media is a useful tool, researchers and practitioners have expressed fear that it will be used for the spread of misinformation, which can have serious consequences for public health. Health organizations must work to ensure that AI systems are transparent, trustworthy, and unbiased so they can help minimize the spread of misinformation. In conclusion, AI and ML have the potential to greatly enhance the use of social media in health organizations. These technologies can help organizations effectively manage large amounts of data and understand stakeholders' sentiments. However, it is important to carefully consider the potential consequences and ensure that these systems are carefully designed to minimize the spread of misinformation.

Keywords: AI, ML, social media, health organizations

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Authors: Chi-Ying Yu

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Fashion design is, in fact, an aesthetic inquiry of fabric, style and human body. In recent years, close cooperation between the artistic circles and the fashion world has even brought fashion into the arena of contemporary art. This study offers a case study on the avant-garde fashion designer Alexander McQueen, investigating how he and his brand translate fashion into contemporary art at various levels. Firstly, in terms of his designs themselves, McQueen demonstrates through fashions his declarations on political and gender issues, demonstrating his unique barbarian aesthetics and creating an enchanting sublimity. Secondly, McQueen extends his fashion aesthetics into a cross-disciplinary performing method, and raises catwalk shows to the level of complete artistic experience. Finally, and also most importantly, the brand has been producing fashion movies for its seasonal design series. By means of an abstract, non-narrative visual language, these films essentially transform people’s experience of clothing – from the senses to the pure visual. This is not simply a cross-media artistic practice, but much more fundamentally a discourse on contemporary perceptual experience. From the case of Alexander McQueen, it can be argued that avant-garde fashion has broken through the boundary between design and art, issuing its own art manifesto through the field of art or non-art.

Keywords: Alexander McQueen, avant-garde fashion, contemporary art, fashion film

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Authors: Yasàlu Haruna

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In every transaction, the use of language is central regardless of form or complexity if any meaning is expected to be harvested therefrom. Students constituting a population group in the learning landscape of Nigeria occupy a central position with a propensity to excel or otherwise in the context of communication, especially in the learning process and social interaction. The nature or quantum of anxiety or confidence in speaking a second language is not only peculiar to societies where the second language is not an official language but to a degree, the linguistic gap created by adoption and adaptation syndrome manifests in created anxiety or lack of confidence especially where mastery of a spoken language becomes a major challenge. This paper explores the manner in which linguistic complexity and cultural barriers combine to widen the adaptation and adoption gap. In much the same way, typical issues of pronouncement, intonation and accent difficulties are vital variables that explain the root cause of anxiety. Using a combination of primary and secondary sources of data expressed in questionnaires, key informant interviews and other available data, the paper concludes that the non-integration of anxiety possibility into the education delivery framework has left a lot to be needed in cultivating second language speakers among students of Nigerian Colleges of Education. In addition, cultural barriers and the absence of integration interfaces in the course of learning within and outside the classroom contribute to further widening the gap. Again, colleagues/mates/conversation partners' mastery of a second language remains a contributory factor largely due to the quality of the preparatory school system in many parts of the country. The paper recommends that national policies and frameworks must be reviewed to consider integration windows where culture and conversation partner deficiencies can be remedied through educational events such as debates, quizzes and symposia; improvements can be attained while commercial advertisements are tailored towards seeking for adoption of second language in commerce and major cultural activities.

Keywords: cultural barriers, integration, college of education and adaptation, second language

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Authors: Afolakemi Helen Olaleye, Ogunjobi A. O

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Since coronavirus disease 2019 (COVID-19) was first reported in Nigeria, the virus has spread to virtually all sub-Saharan Africa (SSA) countries. In Nigeria, government agencies came together to create a goal-driven taskforce in improving our response against the virus. As COVID-19 international spread has been curtailed, community spread became rampant locally, leading to many health authorities raising concerns over the scarcity of medical consumables and supplies. Here at Lagos university teaching Hospital (LUTH), we present data analysis of COVID-19 infections offered at our Hospital (LUTH) and the surrounding communities. In addition, the adopted innovative solution to control the spread of infection, methods used in filling shortages of consumables, personal protective equipment (PPE), and use of mobile video technology in patient’s consultation. The management style and strategy adopted has led to a decline in infection rates in our community and among our front line staff. The current COVID -19 crisis has created an opportunity to test and demonstrate our pandemic response and control of infectious disease along with the revealed unknown potential in our community.

Keywords: COVID-19, preparedness, response, Lagos university teaching hospital

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Valery Yakubovich, Shuping wu

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Organization theorists have long claimed that organizational innovations are nontechnological, in part because they are unpatentable. The claim rests on the assumption that organizational innovations are abstract ideas embodied in persons and contexts rather than in context-free practical tools. However, over the last three decades, organizational knowledge has been increasingly embodied in digital tools which, in principle, can be patented. To provide the first empirical evidence regarding the patentability of organizational innovations, we trained two machine learning algorithms to identify a population of 205,434 patent applications for organizational technologies (OrgTech) and, among them, 141,285 applications that use organizational innovations accumulated over the 20th century. Our event history analysis of the probability of patenting an OrgTech invention shows that ideas from organizational innovations decrease the probability of patent allowance unless they describe a practical tool. We conclude that the present-day digital transformation places organizational innovations in the realm of high tech and turns the debate about organizational technologies into the challenge of designing practical organizational tools that embody big ideas about organizing. We outline an agenda for patent-based research on OrgTech as an emerging phenomenon.

Keywords: organizational innovation, organizational technology, high tech, patents, machine learning

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Authors: Jan Schmitt, Sophie Fischer

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After the Corona pandemic, climate change is a further, long-lasting challenge the society must deal with. An ongoing climate change need to be prevented. Nevertheless, the adoption tothe already changed climate conditionshas to be focused in many sectors. Recently, the decisive role of the economic sector with high value added can be seen in the Corona crisis. Hence, manufacturing industry as such a sector, needs to be prepared for climate change and adaption. Several examples from the manufacturing industry show the importance of a strategic effort in this field: The outsourcing of a major parts of the value chain to suppliers in other countries and optimizing procurement logistics in a time-, storage- and cost-efficient manner within a network of global value creation, can lead vulnerable impacts due to climate-related disruptions. E.g. the total damage costs after the 2011 flood disaster in Thailand, including costs for delivery failures, were estimated at 45 billion US dollars worldwide. German car manufacturers were also affected by supply bottlenecks andhave close its plant in Thailand for a short time. Another OEM must reduce the production output. In this contribution, a game-based learning approach is presented, which should enable manufacturing companies to derive their own strategies for climate adaption out of a mix of different actions. Based on data from a regional study of small, medium and large manufacturing companies in Mainfranken, a strongly industrialized region of northern Bavaria (Germany) the game-based learning approach is designed. Out of this, the actual state of efforts due to climate adaption is evaluated. First, the results are used to collect single actions for manufacturing companies and second, further actions can be identified. Then, a variety of climate adaption activities can be clustered according to the scope of activity of the company. The combination of different actions e.g. the renewal of the building envelope with regard to thermal insulation, its benefits and drawbacks leads to a specific strategy for climate adaption for each company. Within the game-based approach, the players take on different roles in a fictionalcompany and discuss the order and the characteristics of each action taken into their climate adaption strategy. Different indicators such as economic, ecologic and stakeholder satisfaction compare the success of the respective measures in a competitive format with other virtual companies deriving their own strategy. A "play through" climate change scenarios with targeted adaptation actions illustrate the impact of different actions and their combination onthefictional company.

Keywords: business strategy, climate change, climate adaption, game-based learning

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Authors: Yael Leibovitch

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Teaching academic writing is a source of concern for secondary schools. Many students struggle to meet the basic standards of literacy while teacher confidence in this arena remains low. These issues are compounded by the conventionally prescriptive character of writing instruction, which fails to engage student writers. At the same time, a growing body of research on dialogic teaching has highlighted the powerful role of talk in student learning. With the intent of enhancing pedagogical capability, this paper shares finding from a co-inquiry case study that investigated how teachers think about and negotiate classroom discourse to position students as effective academic writers and thinkers. Using a range of qualitative methods, this project closely documents the iterative collaboration of educators as they sought to create more opportunities for dialogic engagement. More specifically, it triangulates both teacher and student data regarding the efficacy of interdependent thinking and collaborative reasoning as organizing principals for literacy learning. Findings indicate that a dialogic teaching repertoire helps to develop the cognitive and metacognitive skills of adolescent writers. In addition, they underscore the importance of sustained professional collaboration to the uptake of new writing pedagogies.

Keywords: dialogic teaching, writing, teacher professional development, student literacy

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Authors: Evrim Genc Kumtepe, Elif Toprak, Aylin Ozturk, Gamze Tuna, Hakan Kilinc, Irem Aydin Menderis

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Support services are very significant elements for all educational institutions in general; however, for distance learners, these services are more essential than traditional (face-to-face) counterparts. One of the most important reasons for this is that learners and instructors do not share the same physical environment and that distance learning settings generally require intrapersonal interactions rather than interpersonal ones. Some learners in distance learning programs feel isolated. Furthermore, some fail to feel a sense of belonging to the institution because of lack of self-management skills, lack of motivation levels, and the need of being socialized, so that they are more likely to fail or drop out of an online class. In order to overcome all these problems, support services have emerged as a critical element for an effective and sustainable distance education system. Within the context of distance education support services, it is natural to include technology-based and web-based services and also the related materials. Moreover, institutions in education sector are expected to use information and communication technologies effectively in order to be successful in educational activities and programs. In terms of the sustainability of the system, an institution should provide distance education services through ICT enabled processes to support all stakeholders in the system, particularly distance learners. In this study, it is envisaged to develop a model based on the current support services literature in the field of open and distance learning and the applications of the distance higher education institutions. Specifically, content analysis technique is used to evaluate the existing literature in the distance education support services, the information published on websites, and applications of distance higher education institutions across the world. A total of 60 institutions met the inclusion criteria which are language option (English) and availability of materials in the websites. The six field experts contributed to brainstorming process to develop and extract codes for the coding scheme. During the coding process, these preset and emergent codes are used to conduct analyses. Two coders independently reviewed and coded each assigned website to ensure that all coders are interpreting the data the same way and to establish inter-coder reliability. Once each web page is included in descriptive and relational analysis, a model of support services is developed by examining the generated codes and themes. It is believed that such a model would serve as a quality guide for future institutions, as well as the current ones.

Keywords: support services, open education, distance learning, support model

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Authors: Belayneh Matebie, Michael Melese

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The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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Authors: Halima Akhtar, Abhijeet Chandra

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The paper attempts to analyze the factors that influence the Consumer Behavior to purchase apparel through the internet. The intentions to buy apparels online were based on in terms of user style, orientation, size and reputation of the merchant, social influence, perceived information utility, perceived ease of use, perceived pleasure and attractiveness and perceived trust and risk. The basic framework used was Technology acceptance model to explain apparels acceptance. A survey was conducted to gather the data from 200 people. The measures and hypotheses were analyzed using Correlation testing and would be further validated by the Structural Equation Modelling. The implications of the findings for theory and practice could be used by marketers of online apparel websites. Based on the values obtained, we can conclude that the factors such as social influence, Perceived information utility, attractiveness and trust influence the decision for a user to buy apparels online. The major factors which are found to influence an online apparel buying decision are ease of use, attractiveness that a website can offer and the trust factor which a user shares with the website.

Keywords: E-tailers, consumer behaviour, technology acceptance model, structural modelling

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Authors: Osuagwu Justine Ugochukwu

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Investigating the effects of transformational and transactional leadership styles on the performance of healthcare employees at the University Teaching Hospital (UNTH) in Enugu, Nigeria, was the goal of the research. The respondents were asked to fill out a structured questionnaire. The respondents were chosen using a straightforward random sampling technique and consisted of 370 health workers at the hospital. The result of the analysis revealed that transactional and transformational leadership style has a positive while ambidextrous leadership has a negative effect on healthcare workers' performance in UNTH, Enugu. Therefore, the management of public hospitals that have the capacity to change their top management approach to leadership styles will gain substantial support from their employees’ thereby increasing organizational commitment and performance among health workers. This will have remarkable social implications, one of which is a change in the work culture and attitude of medical personnel from the seemingly anti-community of patients to friendly engagement and treatment of patients leading to a harmonious coexistence among these individuals in society. Investigating ambidextrous leadership and the use of nonparametric analysis is unique and has brought brand-new knowledge to leadership literature.

Keywords: workers performance, transformational leadership, transactional leadership, governance quality, ambidextrous leadership

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Ricardo Pinto Mario Covele, Patricio V. Langa, Patrick Swanzy

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The English language has been recognized as a universal medium of instruction in academia, especially in Higher Education Institutions (HEIs) hence exerting enormous influence within the context of research and publication. By extension, the English Language has been embraced by scholars from non-English speaking countries. The purpose of this review was to synthesize the discussions using four databases. Discussion in the English language in the career development of academics, particularly in non-English speaking universities, is largely less visible. This paper seeks to fill this gap and to improve the visibility of the English language in the career development of academics focusing on non-English language speaking universities by undertaking a systematic literature review. More specifically, the paper addresses the language policy, English language learning model as a second language, sociolinguistic field and career development, methods, as well as its main findings. This review analyzed 75 relevant resources sourced from Western Cape’s Library, Scopus, Google scholar, and web of science databases from November 2020 to July 2021 using the PQRS framework as an analytical lens. The paper’s findings demonstrate that, while higher education continues to be under-challenges of English language usage, literature targeting non-English speaking universities remains less discussed than it is often described. The findings also demonstrate the dominance of English language policy, both for knowledge production and dissemination of literature challenging emerging scholars from non-English speaking HEIs. Hence, the paper argues for the need to reconsider the context of non-English language speakers in the English language in the career development of academics’ research, both as empirical fields and as emerging knowledge producers. More importantly, the study reveals two bodies of literature: (1) the instrumentalist approach to English Language learning and (2) Intercultural approach to the English Language for career opportunities, classified as the appropriate to explain the English language learning process and how is it perceived towards scholars’ academic careers in HEIs.

Keywords: English language, public and private universities, language policy, career development, non-English speaking countries

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Authors: Şakir Bingöl, Abdullah Emre Aydemir, Abdullah Saado, Ahmet Akıl, Elif Canbaz, Feyza Nur Bulgurcu, Gizem Uzun, Günsu Bilge Dal, Muhammedcan Pirinççi

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Smart contracts, which can be applied in many different areas, from financial applications to the internet of things, come to the fore with their security, low cost, and self-executing features. In this paper, it is focused on peer-to-peer (P2P) energy trading and the implementation of the smart contract on the Ethereum blockchain. It is assumed a microgrid consists of consumers and prosumers that can produce solar and wind energy. The proposed architecture is a system where the prosumer makes the purchase or sale request in the smart contract and the maximum price obtained through the distribution system operator (DSO) by forecasting. It is aimed to forecast the hourly maximum unit price of energy by using deep learning instead of a fixed pricing. In this way, it will make the system more reliable as there will be more dynamic and accurate pricing. For this purpose, Istanbul's energy generation, energy consumption and market clearing price data were used. The consistency of the available data and forecasting results is observed and discussed with graphs.

Keywords: energy trading smart contract, deep learning, microgrid, forecasting, Ethereum, peer to peer

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Authors: Sarah Mhae Diaz, Erika Anna De Leon, Jacklin Alwil Cartagena, Geordan Caruncong, Micah Riezl Gonzales

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This study examined the intervention of threat and surveillance on the obedience of 100 preschool children through a task variable experiment replicated from the previous studies of Higbee (1979), and Chua, J., Chua, M., & Pico (1983). Nowadays, obedience among Filipino children to authority is disregarded since they are more outspoken and rebel due to social influences. With this, aside from corporal punishment, threat and surveillance became a mean of inducing obedience. Threat, according to the Dissonance Theory, can give attitudinal change. On the other hand, surveillance, according to the Theory of Social Facilitation, can either contribute to the completion or failure to do a task. Through a 2x2 factorial design, results show; (1) threat (F(1,96) = 12.487, p < 0.05) and (2) surveillance (F(1,96)=9.942, p<.05) had a significant main effect on obedience, suggesting that the Dissonance Theory and Theory of Social Facilitation is respectively true in the study. On the other hand, (3) no interaction (F(1,96)=1.303, p > .05) was seen since threat and surveillance both have a main effect that could be positive or negative, or could be because of their complementary property as supported by the post-hoc results. Also, (4) most effective commanding style is threat and surveillance setting (M = 30.04, SD = 7.971) due to the significant main effect of the two variables. With this, in the Filipino Setting, threat and surveillance has proven to be a very effective strategy to discipline and induce obedience from a child.

Keywords: experimental study, obedience, preschool children, surveillance, threat

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Authors: Chananart Meenanan

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The composition Isan Symphonic Variations for Chorus and Orchestra is a musical composition inspired by Isan Folk music tunes. The composer has created the well crafted melodic variations and cultural sound character of the piece based on the Klon Lum Tang Isan Keaw (Green Isan’s short poems). Meanwhile, the poetic lyric has been motivatedly recreated to bring the abundance of Northeastern Thailand region’s sentiment back to life. Moreover, the sound of xylophone (Ponglang), the instruments of the orchestra and the chorus were blended in order to present Isan folk music’s character via the Western musical idiom. The 3 movement of this composition is divided as following: In Movement I (Allegro), the introduction has been represented the uniqueness in Isan folk music’s liveliness by expressing it through the sound of chorus and orchestra. The composer also added the melodious sound flavor by utilizing the variety of the muting sound style on trumpets and horns. In Movement II (Moderato), the aspect of the heterophonic approach music has been implied to the main idea of the entire movement whereby its formatted transformation worked effectively through chorus and the orchestra. In Movement III (Allegretto) the harmonic chromaticism was modified and applied as the symbolic icon of the entire movement. The transparence of Isan cultural sound was perfectly designed to be the highlight of this spectacular episode.

Keywords: Isan, symphonic variations, chorus, orchestra

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Gizem Barreto Martins

Abstract:

This paper explores the subversive potential inherent in the theatrical language employed within Arthur Miller's The Crucible. The research argues that this play intricately weaves ideological connections with its audience and the historical epoch it represents, effectively serving as a channel for ideological and cultural interaction potentially exerting subversive influences on social and political realms. Using a historical-materialist methodology that situates the play within its historical and political context, all while examining its connections with theater and literary theories, the paper raises a fundamental query: How does this dramatic work embody subversion, presenting a style unburdened by the performative conventions of daily life and prevailing codes and systems of representation? In response to this inquiry, the study asserts that theatrical language has the capacity to function as a subversive catalyst against prevailing ideologies, actively contributing to the process of social transformation. To substantiate this claim, the research conducts a detailed analysis of the selected play, employing the semiotic framework pioneered by Gilles Deleuze and Felix Guattari.

Keywords: arthur miller, The crucible, gilles deleuze, felix guattari, theater and literary theories

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Authors: Aslihan Cetinbas Genc, Meral Unal

Abstract:

This study presents the structural and cytochemical alterations of stigma at the stages of pre-anthesis, anthesis and post-anthesis in Vibirnum tinus. Capitate stigma continues with a closed style. The receptive surface of stigma is composed of unicellular papillae which are short and flattened at pre-anthesis stage. The papillae in this stage have dense cytoplasm with small vacuoles and a centrally located nucleus. With the start of anthesis, the stigma widens, papillae lengthen and become cylindrical. At anthesis stage, vacuoles enlarge, and nucleus moves to the base of the cell. At post-anthesis stage, the boundaries of the papillae become less noticeable. As proved by Periodic Acid Schiff procedure, the cytoplasm of papillae is rich in insoluble polysaccharides at all stages of development but it becomes remarkable at post-anthesis, particularly at the sub-papillar area. Although there is no significant difference in the content of protein in all stages of the development, it is more abundant at post-anthesis stage, as in Coomassie Brillant Blue stained sections. The surface of papillae is covered by a cuticle which becomes thicker at post-anthesis, and it gives positive reaction with Sudan Black B and Auramine O. The cuticle is covered by a pellicle stained by Coomassie Brillant Blue, indicating dry type of stigma.

Keywords: develeopmental features, histochemistry, stigma, Vibirnum tinus

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Authors: Rajender Dahiya

Abstract:

Investigation outcomes of major process incidents have been consistent for decades and validate that the causes and consequences are often identical. The debate remains as we continue to experience similar process incidents even with enormous development of new tools, technologies, industry standards, codes, regulations, and learning processes? The objective of this paper is to investigate the most common causes of major industrial incidents and reveal industry challenges and best practices to prevent such incidents. The author, in his current role, performs audits and inspections of a variety of high-hazard industries in North America, including petroleum refineries, chemicals, petrochemicals, manufacturing, etc. In this paper, he shares real life scenarios, examples, and case studies from high hazards operating facilities including key challenges and best practices. This case study will provide a clear understanding of the importance of near miss incident investigation. The incident was a Safe operating limit excursion. The case describes the deficiencies in management programs, the competency of employees, and the culture of the corporation that includes hazard identification and risk assessment, maintaining the integrity of safety-critical equipment, operating discipline, learning from process safety near misses, process safety competency, process safety culture, audits, and performance measurement. Failure to identify the hazards and manage the risks of highly hazardous materials and processes is one of the primary root-causes of an incident, and failure to learn from past incidents is the leading cause of the recurrence of incidents. Several investigations of major incidents discovered that each showed several warning signs before occurring, and most importantly, all were preventable. The author will discuss why preventable incidents were not prevented and review the mutual causes of learning failures from past major incidents. The leading causes of past incidents are summarized below. Management failure to identify the hazard and/or mitigate the risk of hazardous processes or materials. This process starts early in the project stage and continues throughout the life cycle of the facility. For example, a poorly done hazard study such as HAZID, PHA, or LOPA is one of the leading causes of the failure. If this step is performed correctly, then the next potential cause is. Management failure to maintain the integrity of safety critical systems and equipment. In most of the incidents, mechanical integrity of the critical equipment was not maintained, safety barriers were either bypassed, disabled, or not maintained. The third major cause is Management failure to learn and/or apply learning from the past incidents. There were several precursors before those incidents. These precursors were either ignored altogether or not taken seriously. This paper will conclude by sharing how a well-implemented operating management system, good process safety culture, and competent leaders and staff contributed to managing the risks to prevent major incidents.

Keywords: incident investigation, risk management, loss prevention, process safety, accident prevention

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Authors: Saule Shazhanbayeva, Denise van der Merwe

Abstract:

Study hypothesis: Nazarbayev Intellectual School of Kyzylorda’s Biology teachers can use STEM-integrated learning to improve students' problem-solving ability and responsibility as global citizens. The significance of this study is to indicate how the use of STEM integrative learning during Biology lessons could contribute to forming globally-minded students who are responsible community members. For the purposes of this study, worldview is defined as a view that is broader than the country of Kazakhstan, allowing students to see the significance of their scientific contributions to the world as global citizens. The context of worldview specifically indicates that most students have never traveled outside of their city or region within Kazakhstan. In order to broaden student understanding, it is imperative that students are exposed to different world views and contrasting ideas within the educational setting of Biology as the science being used for the research. This exposure promulgates students understanding of the significance they have as global citizens alongside the obligations which would rest on them as scientifically minded global citizens. Integrative learning should be Biological Science - with Technology and engineering in the form of problem-solving, and Mathematics to allow improved problem-solving skills to develop within the students of Nazarbayev Intellectual School (NIS) of Kyzylorda. The school's vision is to allow students to realise their role as global citizens and become responsible community members. STEM allows integrations by combining four subject skills to solve topical problems designed by educators. The methods used are based on qualitative analysis: for students’ performance during a problem-solution scenario; and Biology teacher interviews to ascertain their understanding of STEM implementation and willingness to integrate it into current lessons. The research indicated that NIS is ready for a shift into STEM lessons to promote globally responsible students. The only additional need is for proper STEM integrative lesson method training for teachers.

Keywords: global citizen, STEM, Biology, high-school

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Authors: N. M. Zukani, E. O. Adu

Abstract:

Homeschooling has been a primary method for parents to educate their children. It has become a growing educational phenomenon across the globe. However, homeschooling is, therefore, an alternative form of education in which children are instructed at home rather than in mainstream schools. This study evaluated the effectiveness of homeschooling in East London Education District, looking at the stakeholder’s perceptions, reviewing issues that impact on this as reflected in literature. This is a qualitative study done in selected homeschools. Semi structured interviews were used as a form of collecting data. Data was scrutinized and grouped into themes. The study revealed the importance of differentiation of instruction, and the need for flexibility in the process of homeschooling for children who faced difficulties, special needs in learning in mainstream schooling. It is therefore concluded that the participants in the study clearly showed that homeschooling is an educational choice for parents who have concerns about the quality of education of their children. Furthermore, homeschooling has the potential to be the most learner centered, nurturing educational approach. It was recommended that an effective homeschooling practice mainly, the practice should consider attention to children-parent’s goals and learning structure. Although homeschooling looks at how to overcome the drawbacks of mainstream schooling, there are also cases that reflected, the incompetency of parents or tutors conducting the homeschooling and also a need for the support material and other educational supports from the government.

Keywords: homeschooling, effectiveness, stakeholders, parents, perception

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

Abstract:

Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 331