Search results for: English learning barriers

Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

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With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

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Authors: Giselle Martinez Negrette

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Language and culture mutually shape and reflect the human experience. In the learning process, this connection creates and sustains the shared world of learners and educators. Dual Language (DL) programs exemplify this relationship by placing language and culture at the center of their educational approach. These programs, originally conceived to advance social justice in education, aim to foster bilingualism, biliteracy, academic development and sociocultural competence, emphasizing the inseparability of linguistic and cultural growth. Furthermore, because DL programs serve children from diverse cultural, ethnic, and socioeconomic backgrounds, they operate as spaces where linguistic skills and sociocultural understandings are actively cultivated, negotiated, and celebrated. Against this background, this paper examines how two DL teachers see language and culture shaping and reflecting the educational experience, and how their understandings of the relationship influence their mediation of sociocultural competence in their classrooms. This qualitative study employs critical discourse analysis to study in detail participants’ narratives seeking to uncover their perspectives on the “politics” surrounding language use and cultural understandings in their school contexts. Our findings show that these educators are not only keenly aware of the pivotal role that language and culture play in multilingual students’ learning journeys, but they have identified the sociolinguistic “games” taking place in their classrooms. We contend these understandings are pivotal for the critical development of sociocultural competence in DL programs. This study provides DL educators with important conceptual and pedagogical insights regarding the intersection between language and culture in their classrooms and seeks to encourage them to analyze their roles as supporters or opponents of transformative rupture opportunities to contest inequities in education

Keywords: sociocultural competence, critical discourse analysis, dual language programs, language, culture

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Authors: Gerhard Grebe, Johan Marx

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The aim of the study is to assess the state of operational risk management and the adoption of an appropriate risk culture in Ghanaian banks. The Bank of Ghana (BoG) joined the Basel Consultative Group (BCG) of the Basel Committee on Bank Supervision (BCBS) in 2021 and is proceeding with the implementation of the Basel III international regulatory framework for banks. The BoG’s Directive about risk management encourages, inter alia, the creation of an appropriate risk culture by Ghanaian banks. However, it is not evident how the risk management staff of Ghanaian banks experience the risk culture and the implementation of operational risk management in the banks where they are employed. Ghana is a developing economy, and it is addressing challenges with its organisational culture. According to Transparency International, successive Ghanaian governments claim to be fighting corruption, but little success has been achieved so far. This points to a possible lack of accountability, transparency, and integrity in the environment in which Ghanaian banks operate and which could influence their risk culture negatively. Purposive sampling was used for the survey, and the questionnaire was completed byGhanaian bank personnel who specializesin operational risk management, risk governance, and compliance, bank supervision, risk analyses, as well as the implementation of the operational risk management requirements of the Basel regulatory frameworks. The respondents indicated that they are fostering a risk culture and implementing monitoring and reporting procedures; the three lines of defence (3LOD); compliance; internal auditing; disclosure of operational risk information; and receiving guidance from the bank supervisor in an attempt to improve their operational risk management practices. However, the respondents reported the following challenges with staff members who are not inside the risk management departments(in order of priority), namelydemonstrating a risk culture, training and development; communication; reporting and disclosure; roles and responsibilities; performance appraisal; and technological and environmental barriers. Recommendations to address these challenges are provided

Keywords: ghana, operational risk, risk culture, risk management

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Authors: David A. Harness

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Natural evolution of ATP cognitive systems is to meet AI peer review standards. ATP process of axiom selection from Mizar to prove a conjecture would be further refined, as in all human and machine learning, by solving the real world problem of the proposed AI peer review challenge: Determine which conjecture forms the higher confidence level constructive proof between Standard Model of Physics SU(n) lattice gauge group operation vs. present non-standard 4D GEM EOS SU(n) lattice gauge group spatially extended operation in which the photon and electron are the first two trace angular momentum invariants of a gravitoelectromagnetic (GEM) energy momentum density tensor wavetrain integration spin-stress pressure-volume equation of state (EOS), initiated via 32 lines of Mathematica code. Resulting gravitoelectromagnetic spectrum ranges from compressive through rarefactive of the central cosmological constant vacuum energy density in units of pascals. Said self-adjoint group operation exclusively operates on the stress energy momentum tensor of the Einstein field equations, introducing quantization directly on the 4D spacetime level, essentially reformulating the Yang-Mills virtual superpositioned particle compounded lattice gauge groups quantization of the vacuum—into a single hyper-complex multi-valued GEM U(1) × SU(1,3) lattice gauge group Planck spacetime mesh quantization of the vacuum. Thus the Mizar corpus already contains all of the axioms required for relevant DeepMath premise selection and unambiguous formal natural language parsing in context deep learning.

Keywords: automated theorem proving, constructive quantum field theory, information theory, neural networks

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Authors: A. Martins, I. Martins, O. Pereira

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The purpose of this research is to focus on the importance of distributed leadership in universities and Higher Education Institutions (HEIs). The research question is whether there a significant finding in self-reported ratings of leadership styles of those respondents that are studying management. The study aims to further discover whether students are encouraged to become responsible and proactive citizens, to develop their skills set, specifically shared leadership and higher-level skills to inspire creation knowledge, sharing and distribution thereof. Contemporary organizations need active and responsible individuals who are capable to make decisions swiftly and responsibly. Leadership influences innovative results and education play a dynamic role in preparing graduates. Critical reflection of extant literature indicates a need for a culture of leadership and innovation to promote organizational sustainability in the globalised world. This study debates the need for HEIs to prepare the graduate for both organizations and society as a whole. This active collaboration should be the very essence of both universities and the industry in order for these to achieve responsible sustainability. Learning and innovation further depend on leadership efficacy. This study follows the pragmatic paradigm methodology. Primary data collection is currently being gathered via the web-based questionnaire link which was made available on the UKZN notice system. The questionnaire has 35 items with a Likert scale of five response options. The purposeful sample method was used, and the population entails the undergraduate and postgraduate students in the College of Law and Business, University of KwaZulu-Natal, South Africa. Limitations include the design of the study and the reliance on the quantitative data as the only method of primary data collection. This study is of added value for scholars and organizations in the innovation economy.

Keywords: knowledge creation, learning, performance, sustainability

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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: Uliana Morozovskaia

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Immigrants in any country undergo an acculturation process which, in other words, means adaptation to other cultures. It can be divided into four strategies: integration (when an immigrant support home and host culture and language), assimilation (supporting only host culture and language), separation (supporting only home culture and language), and marginalization (an immigrant has no interest in supporting none of the cultures or languages). Canada has experienced a rise in the number of Russian speakers who are immigrating to Canada in the last couple of years. Although there are some studies on Russian-speaking immigrants, a small percentage of them have been focusing on their immigration experience in Canada. This is why the present study aimed to analyze the acculturation experience that Russian-speaking immigrants have when they move to Canada. One hundred participants have been surveyed on SurveyMonkey. They have been asked to share their life experience and opinion about their adaptation process, self-identity in terms of language use and cultural feelings, language preferences, and others. The results showed that Russian-speaking immigrants can successfully adapt to Canadian culture and society, and many of them feel at home being in their host country. Interestingly, such feelings have appeared after they spent some years in Canada. The study also found out that after the immigration, participants were more likely to focus on Canada’s official languages (English and/or French). However, when they became comfortable with the lifestyle and the language, they switched their attention to Russian language maintenance and home culture preservation.

Keywords: acculturation, Russian-speaking immigrants, adaptation, Canada, immigration, mother tongue preservation

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Authors: Salamatu Sani

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This study is an investigation of how code-mixing manifests in the language development of a Nigerian child, especially in the Hausa speaking environment. It is hinged on the fact that the environment influences the first language acquired by a child regardless of the cultural and/or linguistic background of the parents. The child under investigation has been subjected to close monitoring on her speech hitherto. It is a longitudinal study covering a period of twelve months (January 2018 to December 2018); that was when the subject was between twenty-four and thirty months of age. The speeches have been recorded by means of a tape recorder, video, and a diary. The study employs as a theoretical framework, emergentism, which is an eclectic of the behaviourist and the mentalist theories to the study of language development, for analysis. This is in agreement with the positions of Skinner and Watson. Sequel to this investigation, it was discovered the environment is a major factor that influences the exposure of a child to a language more than the other factors and that, if a child is exposed to more than one language, there is a great tendency for such a child to code-mix and code-switch in her speech production. The child under investigation, in spite of the linguistic background of her parents, speaks the Hausa Language much better than the other languages around her though with remarkable code-mixing with other languages around her such as English and Ebira languages. The study concludes that although a child is born with the innate ability to acquire a particular language, the environment plays a key role to trigger the innate ability and consequently, the child is exposed to the acquisition of the dominant language around her at a particular given time.

Keywords: bilingual, code-mixing, emergentism, environment, Hausa

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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: Anastasia Sorokina

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Graduate language loss or attrition has been well documented in individuals who migrate and become emersed in a different language environment. This phenomenon of first language (L1) attrition is an example of non-pathological (not due to trauma) and can manifest itself in frequent pauses, search for words, or grammatical errors. While the widely experienced loss of one’s first language might seem harmless, there is convincing evidence from the disciplines of Developmental Psychology, Bilingual Studies, and even Psychotherapy that language plays a crucial role in the memory of self. In fact, we remember, store, and share personal memories with the help of language. Dual-Coding Theory suggests that language memory code deterioration could lead to forgetting. Yet, no one has investigated a possible connection between language loss and memory. The present study aims to address this research gap by examining a corpus of 1,495 memories of Russian-English bilinguals who are on a continuum of L1 (first language) attrition. Since phenomenological properties capture how well a memory is remembered, the following descriptors were selected - vividness, ease of recall, emotional valence, personal significance, and confidence in the event. A series of linear regression statistical analyses were run to examine the possible negative effects of L1 attrition on autobiographical memory. The results revealed that L1 attrition might compromise perceived vividness and confidence in the event, which is indicative of memory deterioration. These findings suggest the importance of heritage language maintenance in immigrant communities who might be forced to assimilate as language loss might negatively affect the memory of self.

Keywords: L1 attrition, autobiographical memory, language loss, memory phenomenology, dual coding

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Authors: Jennifer Wallbrown

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It’s not uncommon in the US to see news article headlines about public school teachers being scrutinized for what they are teaching or see the general public weighing in on whether or not they think certain controversial subjects should be addressed in the classroom- such as LGBTQ+ or multicultural literature. Even though this is a subject that has been written about and discussed for years, it continues to be a relevant topic in education as it continues to be a struggle to implement more diverse texts. Although it is valid for teachers to fear controversy when they attempt to create a more diverse or inclusive curriculum, it is a fight worth fighting because of the benefits students can gain from being exposed to a wide range of texts. This paper is different from others of its kind because it addresses many of the counterarguments often made to implementing LGBTQ+ or multicultural literature in secondary classrooms. It not only encourages educators to try to include more diverse texts, but it gives them the tools to address common concerns and be sound in their reasoning for choosing these texts. This can be of interest to those educators who are not English teachers because a truly diverse and inclusive curriculum would include other subjects as well- including history, art, and more. By the end of my proposed paper, readers will feel encouraged to choose more diverse and inclusive texts for their classrooms. They can also be confident that if met with opposition or controversy, as is sometimes common when implementing new texts, that they have sound arguments and reasoning for why they chose to include these texts. This reasoning is that, based on the research, studies have found there are benefits to students studying texts about those different from themselves, because it teaches them empathy and helps fight prejudice.

Keywords: education, diverse, inclusive, multicultural, lgbtq+, pedagogy

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Authors: Hanjin Yan

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The English Romantic George Gordon Byron (1788-1824) was widely celebrated by men of letters in early republican China as a Satanic freedom fighter challenging classical poetics and traditional values. However, Wu Mi (1894-1978), the most persistent critic of contemporary iconoclasm, perceived Byron as a paragon of self-righteous poet-exiles who maintained moral integrity and achieved poetic excellence during times of frustration, just like canonized classical Chinese poets. Wu Mi not only composed lengthy imitations of the third canto of Byron’s Childe Harold’s Pilgrimage (1816) but also patronized a rendering of the canto. Taking André Lefevere’s rewriting theory as a framework, this paper explores the interplay of ideology and poetics by examining Wu Mi’s imitations against Byron’s original and its Chinese translation patronized by Wu Mi. Textual analysis shows that Wu Mi’s approach to Byron’s poetry was informed not only by his endeavor to invigorate classical Chinese poetics, but also by his program to preserve China’s cultural traditions and integrate Western new humanism, a theory proposed by his Harvard mentor Irving Babbitt (1865-1933). This study reveals how Byron was appropriated to serve conflicting poetic and ideological purposes in early republican China and suggests that imitation as a type of rewriting merits further attention.

Keywords: George Gordon Byron, ideology, imitation, poetics, translation

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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: Anna-Maria Saarela

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At the Savonia University of Applied Sciences (UAS), curriculum and studies have been improved by applying an Open Innovation Space approach (OIS). It is based on multidisciplinary action learning. The key elements of OIS-ideology are work-life orientation, and student-centric communal learning. In this approach, every participant can learn from each other and innovations will be created. In this social innovation educational approach, all practices are carried out in close collaboration with enterprises in real-life settings, not in classrooms. As an example, in this paper, Savonia UAS’s Future Food RDI hub (FF) shows how OIS practices are implemented by providing food product development and consumer research services for enterprises in close collaboration with academicians, students and consumers. In particular one example of OIS experimentation in the field is provided by a consumer research carried out utilizing verbal analysis protocol combined with audio-visual observation (VAP-WAVO). In this case, all co-learners were acting together in supermarket settings to collect the relevant data for a product development and the marketing department of a company. The company benefitted from the results obtained, students were more satisfied with their studies, educators and academicians were able to obtain good evidence for further collaboration as well as renewing curriculum contents based on the requirements of working life. In addition, society will benefit over time as young university adults find careers more easily through their OIS related food science studies. Also this knowledge interaction model re-news education practices and brings working-life closer to educational research institutes.

Keywords: collaboration, education, food science, industry, knowledge transfer, RDI, student

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Elli Karampela

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In Specters of Marx (1993), Jacques Derrida refers to the ghost as an Other presence that occupies the space of the self and emanates from there, haunting in its shadowy pastness and threatening/striving to break free. In times of change, ghosts both reflect the dissolution of set principles and voice traumas of the past that create a sense of fear and instability. This paper observes the way female ghosts create connections with the living in the poetry of Joanna Baillie and Anne Bannerman, both integral, albeit under-researched in different ways, writers of the English Romantic period working in the aftermath of the French Revolution. Especially at the beginning of the nineteenth century, when ghost narratives were devoured by readers and enjoyed as stories that re-awakened sensation in times of revolution, there was at the same time fear of intrusion by terror’s unruly forces that threatened to turn the readers restless. The ghost was particularly dangerous because it was associated with memory and the intrusion of past trauma in the here and now. As will be seen, both Baillie and Bannerman explore the idea of the female ghost’s ‘return’ (a Freudian term that will be approached) which breaks both time and space boundaries to raise the suppressed female voice, threaten stability, and correct wrongs. As a result, the varied manifestations of female ghosts render Baillie and Bannerman active in the contemporary discourse about human rights and the reclamation of the agency.

Keywords: poetry, romanticism, spectrality, trauma, women

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Authors: Dorcas Matowe

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Inequality in health care for racial and ethnic minorities continues to be a growing concern for many Americans. Some of the barriers hindering the elimination of health disparities include lack of insurance, socioeconomic status (SES), and racism. This study will specifically focus on the association between some of these factors- health care access, which includes insurance coverage and frequency of doctor visits, race, ethnicity, and health status. The purpose of this study will be to address the following questions: is having health insurance associated with increased doctor visits? Are racial and ethnic minorities with health insurance more or less likely to see a doctor? Is the association between having health insurance moderated by being an ethnic minority? Given the current implications of the 2010 Affordable Care Act, this study will highlight the need to prioritize health care access for minorities and confront institutional racism. Critical Race Theory (CRT) will demonstrate how racism has reinforced these health disparities. This quantitative study design will analyze secondary data from the 2015 Behavioral Risk Factor Surveillance System (BRFSS) questionnaire, a telephone survey conducted annually in all 50 states and three US territories by state health departments in conjunction with the Center for Disease Control (CDC). Non-identifying health-related data is gathered annually from over 400,000 adults 18 years and above about their health status and use of preventative services. Through Structural Equation Modeling (SEM), the relationship between the predictor variables of health care access, race, and ethnicity, the criterion variable of health status, and the latent variables of emotional support and life satisfaction will be examined. It is hypothesized that there will be an interaction between certain racial and ethnic minorities who went to see a doctor, had insurance coverage, experienced racism, and the quality of their health status, emotional support, and life satisfaction.

Keywords: ethnic minorities, health disparities, health access, racism

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Authors: Fatemeh Rezaei, Mohammad H. Yarmohammadian, Masoud Ferdosi, Abbas Haghshnas

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Background: Failure Modes and Effect Analysis is now having known as the main methods of risk assessment and the accreditation requirements for many organizations. The Risk Priority Number (RPN) approach is generally preferred, especially for its easiness of use. Indeed it does not require statistical data, but it is based on subjective evaluations given by the experts about the Occurrence (O i), the Severity (Si) and the Detectability (D i) of each cause of failure. Methods: This study is a quantitative – qualitative research. In terms of qualitative dimension, method of focus groups with inductive approach is used. To evaluate the results of the qualitative study, quantitative assessment was conducted to calculate RPN score. Results; We have studied patient’s journey process in surgery ward and the most important phase of the process determined Transport of the patient from the holding area to the operating room. Failures of the phase with the highest priority determined by defining inclusion criteria included severity (clinical effect, claim consequence, waste of time and financial loss), occurrence (time- unit occurrence and degree of exposure to risk) and preventability (degree of preventability and defensive barriers) and quantifying risks priority criteria in the context of RPN index. Ability of improved RPN reassess by root cause (RCA) analysis showed some variations. Conclusions: Finally, It could be concluded that understandable criteria should have been developed according to personnel specialized language and communication field. Therefore, participation of both technical and clinical groups is necessary to modify and apply these models.

Keywords: failure mode, effects analysis, risk priority number(RPN), health system, risk assessment

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Authors: Palak Sadhwani, Susie Pryor

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This paper investigates interprofessional collaboration (IPC) in the context of entrepreneurship education. Collaboration has been found to enhance problem solving, leverage expertise, improve resource allocation, and create organizational efficiencies. However, research suggests that successful collaboration is hampered by individual and organizational characteristics. IPC occurs when two or more professionals work together to solve a problem or achieve a common objective. The necessity for this form of collaboration is particularly prevalent in cross-disciplinary fields. In this study, we utilize social exchange theory (SET) to examine IPC in the context of an entrepreneurship living learning community (LLC) at a large university in the Western United States. Specifically, we explore these research questions: How are rules or norms established that govern the collaboration process? How are resources valued and distributed? How are relationships developed and managed among and between parties? LLCs are defined as groups of students who live together in on-campus housing and share similar academic or special interests. In 2007, the Association of American Colleges and Universities named living communities a high impact practice (HIP) because of their capacity to enhance and give coherence to undergraduate education. The entrepreneurship LLC in this study was designed to offer first year college students the opportunity to live and learn with like-minded students from diverse backgrounds. While the university offers other LLC environments, the target residents for this LLC are less easily identified and are less apparently homogenous than residents of other LLCs on campus (e.g., Black Scholars, LatinX, Women in Science and Education), creating unique challenges. The LLC is a collaboration between the university’s College of Business & Public Administration and the Department of Housing and Residential Education (DHRE). Both parties are contributing staff, technology, living and learning spaces, and other student resources. This paper reports the results an ethnographic case study which chronicles the start-up challenges associated with the co-creation of the LLC. SET provides a general framework for examining how resources are valued and exchanged. In this study, SET offers insights into the processes through which parties negotiate tensions resulting from approaching this shared project from very different perspectives and cultures in a novel project environment. These tensions occur due to a variety of factors, including team formation and management, allocation of resources, and differing output expectations. The results are useful to both scholars and practitioners of entrepreneurship education and organizational management. They suggest probably points of conflict and potential paths towards reconciliation.

Keywords: case study, ethnography, interprofessional collaboration, social exchange theory

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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: 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: Vinay Gupta, Seema Malhotra

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Background: Patients who usually consume tobacco are unaware of its ill effects completely therefore it becomes necessary to educate and counselling them after obtaining their knowledge about tobacco. Aim: To measure prevalence of tobacco use among dental outpatients and to evaluation of tobacco user attending dental outpatients (OPD) prepared to quit. Methods: A cross-sectional survey, which was carried out on patients attending Outside Patient Department (OPD) of dental college of King Georges Medical University, Lucknow, India. All the patients who consumed tobacco attending the Dental College were asked to participate in the study. The questionnaire was written in English/ Hindi (local language). Participation in this study was voluntary and the questionnaire was anonymous and self-administered. The proposal of this survey had been approved by the ethical committee of institution. Informed consent was obtained from all the participants. Results: Prevalence of tobacco user attending the Dental OPD was 46.4%. Male tobacco user represented 85.9%. Smokeless tobacco (57%) user were more than smoking (1.4%) and 18.9% were using both smokeless and smoking tobacco. 40.7% start using tobacco since less than 5 years. 55.3% uses tobacco after get up in the morning. 87.1% tobacco user knows that it cause cancer. 54.8% respond that warning sign on packet/pouch effect on mind but due to addiction, it would not work out. 54.8% attempted for quitting but not successful. 90.0% willing to quit in future if facility provide. Conclusion: Higher prevalence of tobacco usage among study population and will to quit in future shows need of cessation clinic in every dental institution in India.

Keywords: tobacco, knowledge, practice, counselling

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Authors: Omolara Lade, David Oloke

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The approach to water management worldwide is currently in transition, with a shift from centralised infrastructures to greater consideration of decentralised technologies, such as rainwater harvesting (RWH). However, in Nigeria, implementation of sustainable water management, such as RWH systems, is inefficient and social, environmental and technical barriers, concerns and knowledge gaps exist, which currently restrict its widespread utilisation. This inefficiency contributes to water scarcity, water-borne diseases, and loss of lives and property due to flooding. Meanwhile, several RWH technologies have been developed to improve SWM through both demand and storm-water management. Such technologies involve the use of reinforced concrete cement (RCC) storage tanks, surface water reservoirs and ground-water recharge pits as storage systems. A framework was developed to assess the significance and extent of water management problems, match the problems with existing RWH-based solutions and develop a robust ready-to-use decision support tool that can quantify the costs and benefits of implementing several RWH-based storage systems. The methodology adopted was the mixed method approach, involving a detailed literature review, followed by a questionnaire survey of household respondents, Nigerian Architects and Civil Engineers and focus group discussion with stakeholders. 18 selection attributes have been defined and three alternatives have been identified in this research. The questionnaires were analysed using SPSS, excel and selected statistical methods to derive weightings of the attributes for the tool. Following this, three case studies were modelled using RainCycle software. From the results, the MDA model chose RCC tank as the most appropriate storage system for RWH.

Keywords: rainwater harvesting, modelling, hydraulic assessment, whole life cost, decision support system

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Authors: Tsung-Han Lin, Chia-Han Yang

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Recently, it’s obvious that many hotels not only provide customized service, but offer local culture to give customers different experiences. Luxury decoration and fancy equipment are not enough anymore. Customers expect that hotels not just as an accommodation, but connecting to their trips. Therefore, culture becomes significant when developing marketing strategy for hotels. Tainan, located in south of Taiwan, is the city full of culture that some hospitality industries promote their hotels exactly base on culture. Historic Tainan (台南; táinán), is a city of ancient monuments, delicious food and, above all, temples: there are more gods worshipped and more festivals and rituals observed in Tainan than in any other place in Taiwan. The oldest and most absorbing parts of Tainan are historic Anping, on the west side of town by the sea, and the cultural zones in the heart of the old city; the latter were created specifically to make things easier for visitors, with city information, signs and maps tailored to each zone and well-marked in English. The Chihkan, Dong-an Fang, Five Canals and Confucius Temple cultural zones contain the richest concentration of sights – reckon on spending at least two days to do them justice. As a result, the study aims to analyze the significance of culture on marketing strategies and C and H two hotels in Tainan city as case studies conducting the comparison of cultural marketing and experience marketing to provide a framework for hotels to develop their marketing strategies.

Keywords: cultural marketing, hospitality, historical city, Tainan city

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Authors: Carrollyne Aasen, Laverne Seales

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With increased Latinx communities within the United States, specifically in California, and more universities receiving designations of Hispanic-Serving institutions, Spanish programs have evolved to include more targeted and applicable practical skills. The Spanish program in the Languages and Cultures Department at California Lutheran University incorporated an interdisciplinary project with the Communication Department to create student-generated Spanish-language news inserts, which serve as a sister publication to the English-language student newspaper, The Echo. California Lutheran University is a Hispanic-Serving Institution, meaning it is an accredited undergraduate institution with full-time Hispanic/Latinx students equivalent to at least 25 percent of the total students enrolled. As a Hispanic Serving Institution with growing numbers of bilingual students, faculty, staff, and community members, the need for more information aimed at Hispanic/Latinx communities increased, resulting in the opportunity to reflect topics of interest by community members. This project was developed to fulfill the Spanish program's goals for proficiency by using the American Council on the Teaching of Foreign Languages guidelines and the university's need to support students and the community's voices. This article describes the stages from inception to production and the incorporation of journalism principles into the Spanish curriculum.

Keywords: interdisciplinary, media, foreign languages, HSI

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Authors: Sotiria Tzivinikou, Dimitra Kagkara

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Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: inclusive education, pre-service, self-efficacy, training program

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Authors: Nkrumak Micheal Atta Ofori

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The Vocational System is a decentralized Studies System implemented in Ghana as vocation studies strategy for grassroot that focuses on providing individuals with the specific skills, knowledge, and training necessary for a particular trade, craft, profession, or occupation. This article asks how devolution of vocational studies to local level authorities produces responsive and accountable representation and sustainable vocational learning under the vocational Studies System. It focuses on two case studies: Asokore Mampong and Atwima kwanwoma Municipal. Then, the paper asks how senior high school are developing new material and social practices around the vocational studies System to rebuild their livelihoods and socio-economic wellbeing. Here, the article focusses on Kumasi District, drawing lessons for the two other cases. The article shows how the creation of representative groups under the Vocational Studies System provides the democratic space necessary for effective representation of community aspirations. However, due to elite capture, the interests of privilege few people are promoted. The state vocational training fails to devolve relevant and discretionary resources to local teachers and do not follow the prescribed policy processes of the Vocational Studies System. Hence, local teachers are unable to promote responsive and accountable representation. Rural communities continue to show great interest in the Vocational Studies System, but the interest is bias towards gaining access to vocational training schools for advancing studies. There is no active engagement of the locals in vocational training, and hence, the Vocational Studies System exists only to promote individual interest of communities. This article shows how ‘failed’ interventions can gain popular support for rhetoric and individual gains.

Keywords: vocational studies system, devolution of vocational studies, local-level authorities, senior high schools and vocational learning, community aspirations and representation

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