Search results for: online social learning

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: Phayong Thepaksorn

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The objective of this study was to assess whether living in proximity to a roofing fiber cement factory in southern Thailand was associated with physical, mental, social, and spiritual health domains measured in a self-reported health risk assessment (HRA) questionnaire. A cross-sectional study was conducted among community members divided into two groups: near population (living within 0-2 km of factory) and far population (living within 2-5 km of factory)(N=198). A greater proportion of those living far from the factory (65.34%) reported physical health problems than the near group (51.04 %)(p=0.032). This study has demonstrated that the near population group had higher proportion of participants with positive ratings on mental assessment (30.34%) and social health impacts (28.42%) than far population group (10.59% and 16.67 %, respectively) (p<0.001). The near population group (29.79%) had similar proportion of participants with positive ratings in spiritual health impacts compared with far population group (27.08%). Among females, but not males, this study demonstrated that a higher proportion of the near population had a positive summative score for the self-HRA, which included all four health domain, compared to the far population (p <0.001 for females; p=0.154 for males). In conclusion, this self-HRA of physical, mental, social, and spiritual health domains reflected the risk perceptions of populations living in the vicinity of the roofing fiber cement factory. This type of tool can bring attention to population concerns and complaints in the factory’s surrounding community. Our findings may contribute to future development of self-HRA for HIA development procedure in Thailand.

Keywords: cement dust, health impact assessment, risk assessment, walk-though survey

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Authors: Tran Tran

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Mental health issues are prevalent among Vietnamese undergraduate students, and they are greatly exacerbated during the COVID-19 pandemic for this population. While there is empirical evidence supporting the effectiveness and efficiency of therapy on mental health issues among college students, the rates of Vietnamese college students seeking professional mental health services were alarmingly low. Multiple factors can prevent those in need from finding support. The Internalized Stigma Model posits that public stigma directly affects intentions to seek psychological help via self-stigma and attitudes toward seeking help. However, little research has focused on what factors can predict public stigma toward seeking professional psychological support, especially among this population. A potential predictor is academic majors since academic majors can influence undergraduate students' perceptions, attitudes, and intentions. A study suggested that students who have completed two or more psychology courses have a more positive attitude toward seeking care for mental health issues and reduced stigma, which might be attributed to increased mental health literacy. In addition, research has shown that women are more likely to utilize mental health services and have lower stigma than men. Finally, studies have also suggested that experience of mental health services can increase endorsement of perceived need and lower stigma. Thus, it is expected that perceived helpfulness from past service uses can reduce stigma. This study aims to address this gap in the literature and investigate which factors can predict public stigma, specifically academic major, gender, and perceived helpfulness, potentially suggesting an avenue of prevention and ultimately improving the well-being of Vietnamese college students. The sample includes 408 undergraduate students (Mage = 20.44; 80.88% female) Hanoi city, Vietnam. Participants completed a pen-and-paper questionnaire. Students completed the Stigma Scale for Receiving Psychological Help, which yielded a mean public stigma score. Participants also completed a measurement assessing their perceived helpfulness of their university’s counseling center, which included eight subscales: future self-development, learning issues, career counseling, medical and health issues, mental health issues, conflicts between teachers and students, conflicts between parents and students, and interpersonal relationships. Items were summed to create a composite perceived helpfulness score. Finally, participants provided demographic information. This included gender, which was dichotomized between female and other. Additionally, it included academic major, which was also similarly dichotomized between psychology and other (e.g., natural science, social science, and pedagogy & social work). Linear relationships between public stigma and gender, academic major, and perceived helpfulness were analyzed individually with a regression model. Findings suggested that academic major, gender, and perceived counseling center's helpfulness predicted stigma against seeking professional psychological help. Specifically, being a psychology major predicted lower levels of public stigma (β = -.25, p < .001). Additionally, gender female predicted lower levels of public stigma (β = -.11, p < .05). Lastly, higher levels of perceived helpfulness of the counseling center also predicted lower levels of public stigma (β = -.16, p < .01). The study’s results offer potential intervention avenues to help reduce stigma and increase well-being for Vietnamese college students.

Keywords: stigma, vietnamese college students, counseling services, help-seeking

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Authors: Nasrin Badrkhani, Hosein Dehghani

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Teaching is an interaction between the teacher, student, and the concept in the classroom. As society needs thoughtful and creative people, there is a necessity to change the teaching methods and use modern and active methods of teaching. Teaching has to involve the student in thinking activities. Problem-solving, creativity, cooperation, and scientific thinking skills. Among the prominent characteristics of the modern methods, paying attention to the student struggle and the gradual and continuous learning (process-centered), emphasizing evaluating the students’ entire abilities and talents, and evaluating the students’ maximum ability can be mentioned. And student-centered teaching has to replace teacher-centered teaching. Among the modern methods, group work, role-playing, group discussion, cooperation, and engagement in judgments concerning societal values can be mentioned. This research uses a survey and a questionnaire with 38 questions on the Likert scale to examine the teacher’s ideas about the impact of modern methods of teaching on the quality of teaching. And also studies the relation between this factor and sex, major, and the teaching experience. The statistical population of this research is the teachers of Shiraz-Iran high schools. Morgan table is used for sampling; discriminant analysis is used for the mental of the questions. For the final examination of the questionnaire, Cronbach’s Alpha test and for the statistical analysis of SPSS Software are used. And in the inferential statistic level, T test and one-way variance are used. The results of this research showed that the teachers of this city have positive viewpoints about the use of modern teaching methods except engage in judgments concerning societal values. Both male and female teachers have the same viewpoints, and there isn’t any significant difference between the education degree and the use of modern methods. Also, this research confirms the results of similar research which were done in and out of Iran.

Keywords: learning, teaching, student, teacher, modern methods

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Authors: Deena Moustafa

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The purpose of this paper is to describe the sources of parenting stress in mothers of Dual Diagnosis children (n =60) and examine the relationship between parenting stress and maternal psychological status (depression and well-being), also examine if there is any difference between the previous variables in different disabilities associated with Autism. A descriptive correlational design was used. Data were collected via online questionnaires. The study finds that there was no significant relationship between Autism Parenting Stress Index (APSI) scores and types of disability which associated with Autism, although Mothers with deaf autistic reported more parenting stress, Similar findings were found regarding Depressive Symptoms, as there was no significant relationship between (CESD-R) scores and types of disability which associated with Autism, also study finds that there was a significant correlation of the (APSI) with the (CESD-R) Mothers with higher overall parenting stress reported more depressive symptoms. Likewise, there was also a significant correlation between the (APSI) and the (RPWB) Mothers reporting more parenting stress also reported lower levels of well-being.

Keywords: parenting stress, maternal psychological statues, mothers of dual diagnosis, autism

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Authors: Lynn Mcquarrie, Charlotte Enns

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The goal of this project was to develop a visually-based, signed language phonological awareness training program and to pilot the intervention with signing deaf children (ages 6 -10 years/ grades 1 - 4) who were beginning readers to assess the effects of systematic explicit American Sign Language (ASL) phonological instruction on both ASL vocabulary and English print vocabulary learning. Growing evidence that signing learners utilize visually-based signed language phonological knowledge (homologous to the sound-based phonological level of spoken language processing) when reading underscore the critical need for further research on the innovation of reading instructional practices for visual language learners. Multiple single-case studies using a multiple probe design across content (i.e., sign and print targets incorporating specific ASL phonological parameters – handshapes) was implemented to examine if a functional relationship existed between instruction and acquisition of these skills. The results indicated that for all cases, representing a variety of language abilities, the visually-based phonological teaching approach was exceptionally powerful in helping children to build their sign and print vocabularies. Although intervention/teaching studies have been essential in testing hypotheses about spoken language phonological processes supporting non-deaf children’s reading development, there are no parallel intervention/teaching studies exploring hypotheses about signed language phonological processes in supporting deaf children’s reading development. This study begins to provide the needed evidence to pursue innovative teaching strategies that incorporate the strengths of visual learners.

Keywords: American sign language phonological awareness, dual language strategies, vocabulary learning, word reading

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Authors: Mallikarjun Vaddenkeri, Suresh Jange

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This research study reports results of information behaviour by members of faculty and research scholars of various departments of social sciences working at universities with a sample of 300 and Members of Legislative Assembly and Council with 216 samples in Karnataka State, India. The results reveal that 29.3% and 20.3% of Social Scientists indicated medium and high level of awareness of primary sources - Primary Journals are found to be at scale level 5 and 9. The usage of primary journals by social scientists is found to be 28% at level 4, 24% of the respondent’s opined use of primary Conference Proceedings at level 5 as medium level of use. Similarly, the use of Secondary Information Sources at scale 8 and 9 particularly in case of Dictionaries (31.0% and 5.0%), Encyclopaedias (22.3% and 6.3%), Indexing Periodicals (7.0% and 15.3%) and Abstracting Periodicals (5.7% and 20.7%). For searching information from Journals Literature available in CD-ROM version, Keywords (43.7%) followed by Keywords with logical operators (39.7%) have been used for finding the required information. Statistical inference reveals rejection of null hypothesis `there is no association between designation of the respondents and awareness of primary information resources’. On the other hand, educational qualification possessed by Legislative members, more than half of them possess graduate degree as their academic qualification (57.4%) and just 16.7% of the respondents possess graduate degree while only 26.8% of the respondents possess degree in law and just 1.8% possess post-graduate degree in law. About 42.6% indicated the importance of information required to discharge their duties and responsibilities as a Policy Maker in the scale 8, as a Scholar (27.8%) on a scale 6, as a politician (64.8%) on a scale 10 and as a Councillor (51.9%) on a scale 8. The most preferred information agencies/sources very often contacted for obtaining useful information are by means of contacting the people of Karnataka State Legislative Library, listening Radio programmes, viewing Television programmes and reading the newspapers. The methods adopted for obtaining needed information quite often by means of sending their assistants to libraries to gather information (35.2%) and personally visiting the information source (64.8%). The null hypotheses `There is no association between Members of Legislature and Opinion on the usefulness of the resources of the Karnataka State Legislature Library’ is accepted using F ANOVA test. The studies conclude with a note revamp the existing library system in its structure and adopt latest technologies and educate and train social scientists and Legislators in using these resources in the interest of academic, government policies and decision making of the country.

Keywords: information use behaviour, government information, searching behaviour, policy makers

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Authors: M. Velasco, D. While, P. Raju, J. Krasniewicz, A. Amini, L. Hernandez-Munoz

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Web service adaptation involves the creation of adapters that solve Web services incompatibilities known as mismatches. Since the importance of Web services adaptation is increasing because of the frequent implementation and use of online Web services, this paper presents a literature review of web services to investigate the main methods of adaptation, their theoretical underpinnings and the metrics used to measure adapters performance. Eighteen publications were reviewed independently by two researchers. We found that adaptation techniques are needed to solve different types of problems that may arise due to incompatibilities in Web service interfaces, including protocols, messages, data and semantics that affect the interoperability of the services. Although adapters are non-invasive methods that can improve Web services interoperability and there are current approaches for service adaptation; there is, however, not yet one solution that fits all types of mismatches. Our results also show that only a few research projects incorporate theoretical frameworks and that metrics to measure adapters’ performance are very limited. We conclude that further research on software adaptation should improve current adaptation methods in different layers of the service interoperability and that an adaptation theoretical framework that incorporates a theoretical underpinning and measures of qualitative and quantitative performance needs to be created.

Keywords: Web Services Adapters, software adaptation, web services mismatches, web services interoperability

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Authors: Rozan El-Khateeb

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This literature review examines the effectiveness of therapy programs that utilize play as an intervention for reducing symptoms associated with Autism Spectrum Disorder (ASD). Play-based therapy approaches provide a child-centered and developmentally appropriate framework to address the core symptoms of ASD, including social communication deficits, restricted and repetitive behaviors, and sensory sensitivities. The review explores various play-based therapy strategies and their impact on improving social skills, communication abilities, adaptive behaviors, and overall functioning in individuals with ASD. The findings suggest that play-based therapy programs hold promise as effective interventions for reducing symptoms and enhancing the quality of life for individuals with ASD. However, further research is necessary to establish standardized protocols, identify optimal dosage and duration, and evaluate long-term outcomes.

Keywords: autism, ABA, play, NET, systematic review

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Authors: A. R. Shokoohi, E. A. M. Bulder, C. Th. van Alphen, D. F. den Hertog, E. J. Hin

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The Northern region of the Netherlands has beautiful landscapes, a nice diversity of green and blue areas, and dispersed settlements. However, some recent population changes can become threats to health and wellbeing in these areas. The rural areas in the three northern provinces -Groningen, Friesland, and Drenthe, see youngsters leave the region for which reason they are aging faster than other regions in the Netherlands. As a result, some villages have faced major population decline that is leading to loss of facilities/amenities and a decrease in accessibility and social cohesion. Those who still live in these villages are relatively old, low educated and have low-income. To develop a deeper understanding of the health status of the people living in these areas, and help them to improve their living environment, the GO!-Method is being applied in this study. This method has been developed by the National Institute for Public Health and the Environment (RIVM) of the Netherlands and is inspired by the broad definition of health by Machteld Huber: the ability to adapt and direct control, in terms of the physical, emotional and social challenges of life, while paying extra attention to vulnerable groups. A healthy living environment is defined as an environment that residents find it pleasant and encourages and supports healthy behavior. The GO!-method integrates six domains that constitute a healthy living environment: health and lifestyle, facilities and development, safety and hygiene, social cohesion and active citizens, green areas, and air and noise pollution. First of all, this method will identify opportunities for a healthier living environment using existing information and perceptions of residents and other local stakeholders in order to strengthen social participation and quality of life in these rural areas. Second, this approach will connect identified opportunities with available and effective evidence-based interventions in order to develop an action plan from the residents and local authorities perspective which will help them to design their municipalities healthier and more resilient. This method is being used for the first time in rural areas to our best knowledge, in close collaboration with the residents and local authorities of the three provinces to create a sustainable process and stimulate social participation. Our paper will present the outcomes of the first phase of this project in collaboration with the municipality of Westerkwartier, located in the northwest of the province of Groningen. And will describe the current situation, and identify local assets, opportunities, and policies relating to healthier environment; as well as needs and challenges to achieve goals. The preliminary results show that rural demographic changes in the northern Netherlands have negative impacts on service provisions and social cohesion, and there is a need to understand this complicated situation and improve the quality of life in those areas.

Keywords: population decline, rural areas, healthy environment, Netherlands

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Authors: Donald Wright

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The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

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Authors: Animish Jain

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This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

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Authors: Hozaifa Zaki, Ghada Soliman

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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

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Authors: A. Deswal, N. S. Deora, H. N. Mishra

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The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyse spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), discriminant factorial analysis (DFA) and soft independent modelling by class analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable counts showed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20 hours and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.

Keywords: electronic-nose, bacteriological, shelf-life, classification

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Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: Raghav Srivastava, Namrata Ramachandran

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Strong sustainability has been, by consensus, imagined as comprising economic and extra-economic variables and cannot be viewed merely in terms of a trade-off between the economic needs of today and the potential left for tomorrow. Specifically, the cultural as well the ecological impacts of development projects on the affected communities should be evaluated, in addition to the economic. In developing and densely populated economies such as India, energy intensive development is seen as a sine qua non – a necessary trade off with ecological conservation. Although social impact assessment has been included as an inalienable part of the Environmental Impact Assessment required to be conducted under Indian law, it seems that the same is unable to meet the ends it seeks to achieve. The dissociation between those bearing the costs of development, and those reaping its benefits, lies at the heart of this failure. This paper attempts to study the various cost–benefit relationships for these minority stakeholders using the proposed Nyamjang Chhu hydroelectric power plant in Tawang District of Arunachal Pradesh (in North-east India) as the chief object of study, and discusses whether the current model of sustainable development is truly sustainable, given the level of social dissociation and disintegration that occurs between affected communities and their environment. The economic allure of hydroelectric projects in the hilly regions of India very rarely results in a proper assessment of their ecological and social externalities. Examining the various issues that have been agitated in the course of litigation over the Nyamjang Chhu hydroelectric project, the authors argue that there is a pressing need to re-evaluate the current Indian model of sustainable development going forward.

Keywords: hydroelectric power, socio-cultural dissociation, sustainable development, trade offs

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Authors: Richa Grover, Rahul Grover, V. Balaji Rao, Kavish Kejriwal

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Selection of suppliers is a crucial problem in the supply chain management. On top of that, sustainable supplier selection is the biggest challenge for the organizations. Environment protection and social problems have been of concern to society in recent years, and the traditional supplier selection does not consider about this factor; therefore, this research work focuses on introducing sustainable criteria into the structure of supplier selection criteria. Sustainable Supply Chain Management (SSCM) is the management and administration of material, information, and money flows, as well as coordination among business along the supply chain. All three dimensions - economic, environmental, and social - of sustainable development needs to be taken care of. Purpose of this research is to maximize supply chain profitability, maximize social wellbeing of supply chain and minimize environmental impacts. Problem statement is selection of suppliers in a sustainable supply chain network by ranking the suppliers against sustainable criteria identified. The aim of this research is twofold: To find out what are the sustainable parameters that can be applied to the supply chain, and to determine how these parameters can effectively be used in supplier selection. Multicriteria decision making tools will be used to rank both criteria and suppliers. AHP Analysis will be used to find out ratings for the criteria identified. It is a technique used for efficient decision making. TOPSIS will be used to find out rating for suppliers and then ranking them. TOPSIS is a MCDM problem solving method which is based on the principle that the chosen option should have the maximum distance from the negative ideal solution (NIS) and the minimum distance from the ideal solution.

Keywords: sustainable supply chain management, sustainable criteria, MCDM tools, AHP analysis, TOPSIS method

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Authors: Marija Lončar, Zorana Šuljug Vučica, Magdalena Nigoević

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Diverse social, cultural and economic trends and changes in contemporary societies influence the ways masculinity is represented in a variety of media. Masculinity is constructed within media images as a dynamic process that changes slowly over time and is shaped by various social factors. In many societies, dominant masculinity is still associated with authority, heterosexuality, marriage, professional and financial success, ethnic dominance and physical strength. But contemporary media depict men in ways that suggest a change in the approach to media images. The number of media images of men, which promote men’s identity through their body, have increased. With the male body more scrutinized and commodified, it is necessary to highlight how the body is represented and which visual elements are crucial since the body has an important role in the construction of masculinities. The study includes content analysis of male body images in the advertisements of different men’s and women’s lifestyle magazines available in Croatia. The main aim was to explore how masculinities are currently being portrayed through body regarding age, physical appearance, fashion, touch and gaze. The findings are also discussed in relation to female images since women are central in many of the processes constructing masculinities and according to the recent conceptualization of masculinity. Although the construction of male images varies through body features, almost all of them convey the message that men’s identity could be managed through manipulation and by enhancing the appearance. Furthermore, they suggest that men should engage in “bodywork” through advertised products, activities and/or practices, in order to achieve their preferred social image.

Keywords: body images, content analysis, lifestyle magazines, masculinity

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Authors: Shayem Saleh ALresheedi, Lu Song Feng, Abdulaziz Abdulwahab M. Fatani

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Cloud computing is an emerging concept in the technological sphere. Its development enables many applications to avail information online and on demand. It is becoming an essential element for businesses due to its ability to diminish the costs of IT infrastructure and is being adopted in Saudi Arabia. However, there exist many factors that affect its adoption. Several researchers in the field have ignored the study of the TAM model for identifying the relevant factors and their impact for adopting of cloud computing. This study focuses on evaluating the acceptability of cloud computing and analyzing its impacting factors using Technology Acceptance Model (TAM) of technology adoption in Saudi Arabia. It suggests a model to examine the influential factors of the TAM model along with external factors of technical support in adapting the cloud computing. The proposed model has been tested through the use of multiple hypotheses based on calculation tools and collected data from customers through questionnaires. The findings of the study prove that the TAM model along with external factors can be applied in measuring the expected adoption of cloud computing. The study presents an investigation of influential factors and further recommendation in adopting cloud computing in Saudi Arabia.

Keywords: cloud computing, acceptability, adoption, determinants

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Authors: Sarah Amodeo

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Drawing on the author’s research about the experiences of female immigrant students in academic Adult Education, in Montreal, Quebec, this paper deconstructs the benefits of autoethnography as a methodology for educators in Adult Education. Autoethnography is an advantageous methodology for teachers in Adult Education as it allows for deep engagement, allowing for educators to reflect on student experiences and their day-to-day realities, and in turn, allowing for professional development, improved andragogy, and changes to classroom practices. Autoethnography is a qualitative research methodology that cultivates strategies for improving adult learning. The paper begins by outlining the context that inspired autoethnography for the author’s work, highlighting the emergence of autoethnography as a method, while examining how it is evolving and drawing on foundational work that continues to inspire research. The basic autoethnographic methodologies that are explored in this paper include the use of memory work in episode formation, the use of personal photographs, and textual readings of artworks. Memory work allows for the researcher to use their professional experience and the lived/shared experiences of their students in their research, drawing on episodes from their past. Personal photographs and descriptions of artwork allow researchers to explore images of learning environments/realities in ways that compliment student experiences. Major findings of the text are examined through the analysis of categories of autoethnography. Specific categories include realism, impressionism, and conceptualism which aid in orientating the analysis and emergent themes that develop through self-study. Finally, the text presents a discussion surrounding the limitations of autoethnography, with attention to the trustworthiness and ethical issues. The paper concludes with a consideration of the implications of autoethnography for adult educators in juxtaposition with youth sector work.

Keywords: artwork, autoethnography, conceptualism, episode formation, impressionism, memory work, personal photographs, and realism, realism

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Authors: Yumi Okano

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The low level of English proficiency among Japanese people has been a problem for a long time. Japanese non-native English language teachers, under social or ideological constraints, feel a gap between government policy and their language proficiency and cannot maintain high self-esteem. This paper focuses on current Japanese policies and the social context in which teachers are placed and examines the measures necessary for their positive identity formation from a macro-meso-micro perspective. Some suggestions for achieving this are: 1) Teachers should free themselves from the idea of native speakers and embrace local needs and accents, 2) Teachers should be involved in student discussions as facilitators and individuals so that they can be good role models for their students, and 3) Teachers should invest in their classrooms. 4) Guidelines and training should be provided to help teachers gain confidence. In addition to reducing the workload to make more time available, 5) expanding opportunities for investment outside the classroom into the real world is necessary.

Keywords: language teacher identity, native speakers, government policy, critical pedagogy, investment

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Authors: Ebim Matthew Abua

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In Chinua Achebe’s Things Fall Apart (henceforth, TFA), the character Unoka is portrayed as a weakling and indolent person even when he was a creative artist, a talented musician, and a mathematician. His lack of achievement becomes the barometer for measuring his success. Right from time, music is considered to be of great significance because of its capacity to recreate and retell social events. To this end, music is both a social act and a creative art. As a social act, music is a discursive medium that exploits the dynamics of art in its evaluation of society. Music is so much a part of human existence that its presence in literature can help readers relate to fictional situations and characters. In this paper, the character Unoka is examined against the backdrop of his musical proclivities and his contributions to the overall development of TFA. Unfortunately, Achebe’s Things Fall Apart, a product of artistic creativity, portrays the personality of Unoka as lazy and uninspiring because he (Unoka) is a musician who is busy playing his flute and hardly doing anything productive. This paper is significant because it examines the literary and or linguistic depiction of Unoka and the aftermath of that depiction on the entire novel and, by extension, the larger society. Methodologically, this paper adopted the qualitative approach from the ethnography of communication (EOC), which is the analysis of communication within the wider context of the social and cultural practices and beliefs of the members of a particular culture or speech community. The aim of this qualitative research method includes the ability to discern which communication acts and/or codes are important to different groups, what types of meanings groups apply to different communication events, and how group members learn these codes to provide insight into particular communities. The study reveals that the people of Umuofia were mono-directional in their economy, and there was no room for diversification. One was either a farmer, or such a person was relegated to the background. Unoka, taking up a new challenge of diversifying the economy from the perspective of entertainment, was viewed as a misnomer. This study opens the door to other areas of studying Achebe’s epic novel apart from the critical works of literary artists that have been dished out over time.

Keywords: literature, popular culture, unoka, things fall apart

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Shiu-Wan Hung, Che-Wei Chang, Han-Yu Lin

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Internet celebrities possess high visibility and a great number of fans on the Internet and are the targets that various companies are keen to collaborate with. This study investigated the para-social interaction and its antecedents among internet celebrities and their fans. The effects of Internet celebrity advertising from the perspectives of source credibility and endorser suitability were studied. This study gathered 283 valid questionnaires from people who regularly follow internet celebrities for analysis. The experimental results suggest that expertise has the most significant and direct influence on advertising. Additionally, Internet celebrities with high attractiveness can better influence the thinking of their fans and enhance homophily. However, when considering the construction of source credibility, the direct influence of attractiveness is the least significant, suggesting that the attractiveness of internet celebrities can only promote advertising via the mediating effect of homophily.

Keywords: celebrity, para-social interaction, homophily, source credibility

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Authors: Kouzi Katia

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This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

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Authors: Somaye Sabetnia

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This paper is accomplished to probe Susanna Kaysen’s memoir Girl, Interrupted in the light of Michel Foucault’s theory of madness comprehensively set forth in his History of Madness (1961). It is an endeavor to analysis this novel based on Foucault’s idea of madness. In his archeological study of madness, Foucault introduces a way to perceive madness and its association with dominant discourses. He argues that the concept of madness is constructed within the social context, and different institutions affect its definition. Furthermore, he takes into consideration how each era treats madness, and affirms that in modern times, people considered mad are exiled out of cities, confined in madhouses, and later in clinics where they are treated with drugs. Set after World War II, the novel under observation highlights women’s conditions in which they were becoming a housewife or following their own desires; in fact, choosing the second one results in labeling mad. The protagonist of novel is labeled 'mad,' and is hence impelled to go to asylums where so-called patients are under the vigilant surveillance of the authorities to go through the process of 'normalization.' To discern how she is considered 'mad,' this article probes the dominant discourse of the time when the stories take place to provide a better understanding of madness under the impact of social, cultural, and political conditions. It examines how a so-called mad considered 'Other' and treated after being confined by the disciplinary system of the asylum in a panoptic world. In addition to, it describes the aim of treatment is to punish and control a patient not to cure. This article aims to indicate that Susanna Kaysen tries to picture what is defined as women’s madness is the result of the patriarchal society of the post-war America as well as the mental illness has nothing to do with blood; it is rather the result of the social inequality of the age.

Keywords: clinical treatment, disciplining and punishment, dominant discourse, normalization, other, panoptic world, reason vs. unreason

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Authors: Abosede Ijabadeniyi, Jeevarathnam P. Govender

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Prevailing strategic Corporate Social Responsibility (CSR) research is predominantly centred around the predictive implications of the construct on behavioural outcomes. This phenomenon limits the depth of our understanding of the trajectory of strategic CSR. The purpose of this paper is to investigate the mediating effects of CSR expectations on the relationship between consumer value and purchase behaviour by identifying the implications of the multidimensionality of CSR (economic, legal, ethical and philanthropic) on the latter. Drawing from the stakeholder theory and its interplay with the prevalence of Ubuntu values; the underlying force which governs the values of South African camaraderie, we hypothesise that the multidimensionality of CSR expectations has positive mediating effects in the relationship between consumer value and purchase behaviour. Partial Least Square (PLS) path modelling was employed, using six measures of the average path coefficient (APC) to test the relationship between the constructs. Results from a sample of mall shoppers of (n=411), based on a survey conducted across five major malls in Durban, South Africa, indicate that only the legal dimension of CSR serves as a mediating factor in the relationship among the constructs. South Africa’s unique history of segregation, leading to the proliferation of spontaneous organisational approach to CSR and higher expectations of organisational legitimacy are identified as antecedents of consumers’ reliance on the law (legal CSR) to redress the ills of the past, sustainable development, and socially responsible behaviour. The paper also highlights theoretical and managerial implications for future research.

Keywords: consumer value, corporate marketing, corporate social responsibility, purchase behaviour, Ubuntu

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Authors: Nazia Jabeen, Denis Hyams-Ssekasi

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The study focuses on the determinants of food waste management (FWM) in one of the urban areas of Pakistan. One hundred and two households from the urban areas of Pakistan took part in the study via self-completed questionnaires, and data were analyzed. The research findings indicate that food waste management is a recurring issue, and households must do more to minimize or create business opportunities. Most households agree that food waste has significant implications for the community if not utilized and managed correctly. The value creation deriving from this zero-value resource provides a platform where householders see the benefit of food waste management. Based on the findings, this study acknowledges that food waste has significant economic and social impacts on the community. It concludes that minimization and optimum utilization of food waste create a pathway to business opportunities in urban areas.

Keywords: economic, social, food waste management, business opportunities, value creation

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Authors: Sultana Razia

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The purpose of this study was to investigate the effect of early therapeutic intervention on children with an autism spectrum disorder. Participants were 140 children with autism spectrum disorder from Autism Corner in a selected rehabilitation center of Bangladesh. This study included children who are at aged of 18-month to 36-month and who were taking occupational therapy and speech and language therapy from the autism center. They were primarily screened using M-CHAT; however, children with other physical disabilities or medical conditions were excluded. 3-months interventions of 6 sessions per week are a minimum of 45-minutes long per session, one to one interaction followed by parent-led structured home-based therapy were provided. The results indicated that early intensive therapeutic intervention improves understanding, social skills and sensory skills. It can be concluded that therapeutic early intervention has a positive effect on diminishing symptoms of Autism Spectrum Disorder.

Keywords: autism, m-chat, reciprocal social behavior, CRP

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Authors: Zhaohui Tian

Abstract:

China’s growing and deepening engagement in Africa has attracted numerous controversial debates on Chinese-African social-racial relations both in the media and academia. Most research tends to discuss this issue and the tensions involved at the state level, but limited attention has been given to the individual relating processes of those two racial groups from an intercultural politeness evaluation angle. Thus, taking Kenya as a country focus and putting it under recent perspectives on pragmatics and politeness, this study explores the Chinese-Kenyan workplace relating experience in Chinese-owned companies with the aim to offer new insights on Chinese-African social-racial tensions. The original data were collected through 25 interviews from 29 Chinese and Kenyan participants working in different Chinese companies and industries, some of which had been later on converted into 182 short story data in order to better capture the process and content dimensions of their experiences using Spencer &Kádár’s politeness evaluation model. Both interview and story data were analysed in MAXQDA to understand the personal relating process and the criteria they were drawing from when making evaluative judgements of their relations. The result particular draws attention to tensions around goals, rights, and obligations, and social-moral dimensions that had been underrepresented in intercultural and pragmatics literature. The study offers alternative empirical insights into Chinese-Kenyan relations from an intercultural politeness management perspective and the possible mismatches of the evaluative criteria that potentially cause tension in this context.

Keywords: chinese-kenyan, evaluation, relating, workplace

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