Search results for: learning science

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Vahid Bayrami Rad

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In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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Authors: Leah Plocharczyk, Matthew Conner

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This paper analyzes the relatively new trend of PSE programs which seek to provide education, vocational training, and a college experience to individuals with an intellectual and developmental disability (IDD). Specifically, the paper examines the degree of interaction between PSE programs and the libraries of their college campuses. Using ThinkCollege, a clearinghouse and advocate for PSE programs, the researchers identified 293 programs throughout the country. These were all contacted with an email survey asking them about the nature of their involvement, if any, with the academic libraries on their campus. Where indicated by the responses, the libraries of PSE programs were contacted for additional information about their programming. Responses to the survey questions were tabulated and analyzed quantitatively. Written comments were analyzed for themes which were then tabulated. This paper presents the results of this study. They show obvious preferences for library programming, such as group formal instruction, individual liaisons, embedded reference, and various instructional designs. These are discussed in terms of special education principles of mainstreaming, level of restriction, training demands and cost effectiveness. The work serves as a foundation for best practices that can advance the field.

Keywords: disability studies, instructional design, universal design for learning, assessment methodology

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Vanessa R. Ralph, Leah J. Scharlott, Megan Y. Deshaye, Ryan L. Stowe

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Given the traditions of chemistry teaching, one may not question whether chemical phenomena play a prominent role. Yet, the role of chemical phenomena in an introductory chemistry course may define the extent to which the course is introductory, chemistry, and equitable. Picture, for example, the classic Ideal Gas Law problem. If one envisions a prompt wherein students are tasked with calculating a missing variable, then one envisions a prompt that relies on chemical phenomena as a context rather than as a model to understand the natural world. Consider a prompt wherein students are tasked with applying molecular models of gases to explain why the vapor pressure of a gaseous solution of water differs from that of carbon dioxide. Here, the chemical phenomenon is not only the context but also the subject of the prompt. Deliveries of general and organic chemistry were identified as ranging wildly in the integration of chemical phenomena. The more incorporated the phenomena, the more equitable the assessment task was for students of varying access to pre-college math and science preparation. How chemical phenomena are integrated may very well define whether courses are chemistry, are introductory, and are equitable. Educators of chemistry are invited colleagues to discuss the role of chemical phenomena in their courses and consider the long-lasting impacts of replicating tradition for tradition’s sake.

Keywords: equitable educational practices, chemistry curriculum, content organization, assessment design

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Authors: Douglas Shabe

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The world of the performing musician is one of high pressure that comes from the expected high standards they have to live up to and that they expect from themselves. The pressure that musicians put themselves under can manifest itself in physical problems such as focal dystonia. Knowledge of the contributing factors and potential rehabilitation strategies cannot only give players hope for recovery but also the information to prevent it from happening in the first place. This dissertation presents a multiple case study of two performing brass musicians who developed focal dystonia of the embouchure, also known as embouchure dystonia, combined with an autoethnography of the author’s experience of battling embouchure dystonia and our attempts at recovery. Extensive research into the current state of focal dystonia research was done to establish a base of knowledge. That knowledge was used to develop interview questions for the two participants and interpret the findings of the qualitative data collected. The research knowledge, as well as the qualitative data from the case studies, was also used to interpret the author’s experience. The author determined that behavioral, environmental, and psychological factors were of prime importance in the subjects’ development of focal dystonia and that modifications of those factors are essential for the best chance at recovery.

Keywords: focal dystonia, embouchure dystonia, music teaching and learning, music education

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Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

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The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

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Authors: Sakapas Saengchai, Vilasinee Jintalikhitdee, Mathinee Khongsatid, Nattapol Pourprasert

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This paper studied the participation of people of the five villages of Bang Nang Li Community in Ampawa District, Samut Songkram Province, in designing community planning. The population was 2,755 villagers from the 5 villages with 349 people sampled. The level of involvement was measured by using Likert Five Scale for: preparing readiness of local people in the community, providing information for community and self analysis and learning, designing goals and directions for community development, designing strategic plans for community projects, and operating according to the plans. All process items reported a medium level of involvement except the item of preparing readiness for local people that presented the highest mean score. A test of a correlation between personal factors and level of involvement in designing the community planning unveiled no correlation between gender, age and career. Contrarily, the findings revealed that the villagers’ educational level and community membership status had a correlation with their level of involvement in designing the community planning.

Keywords: community development, community planning, people participation, educational level

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Authors: Emiko Suzuki

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Although fitness is defined as the body’s ability to respond to the demand of physical activity without undue fatigue in health science, in media oftentimes physical activity is presented as means to an attractive body rather than a fit and healthy one. Of all types of media, Instagram is becoming an increasingly persuasive source of information and advice on health and fitness, where individuals conceptualize what health and fitness mean for them. However, this user-generated and unregulated platform can be problematic, as it can communicate misleading information about health and fitness and possibly leading individuals to psychological problems such as eating disorders. In fact, previous research has shown that some messages that were posted with a tag that related to inspire others to do fitness, in fact, encouraged distancing the self from the internal needs of the body. For this reason, this present study aims to explore how health and fitness are communicated on Instagram by analyzing images and texts. A content analysis of images that were labeled with particular hashtags was performed, followed by a thematic analysis of texts from the same set of images. The result shows an interesting insight about messages about how health and fitness are communicated from companies through media, then digested and further shared among communities on Instagram. The study explores how the use of visual focused way of communicating health and fitness can lead to the dehumanization of human bodies.

Keywords: Instagram, fitness, dehumanization, body image, embodiment

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Authors: Andrzej Kesiak

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Contemporary theology is often accused of answering questions that nobody is asking, and of employing hermetic language that has lost its communication capacity. There is also a question that theology is asking itself: how theological discourse can still be influential on other disciplines and, how to overcome the separation of theology and belief. Undoubtedly, in the wider spectrum, the theological discourse has been and will be needed. The difficulty is how to find the right model of it, the model that would help theology to enter in dialogue with culture, art, science, and politics. Presumably, there is no only one such model, theology constantly needs to seek such models, and this is probably a never-ending journey; in other words, theology should adopt a profile of ‘a restless being’ if it wants to remain influential. Music, on the other hand, has always been very close to theology; in fact, a huge part of classical music is either sacred or religious. Many composers sought inspiration in religion, liturgy, religious painting and sacred texts. This paper will argue that despite all that it seems that a proper and factual dialogue is still in a starting phase. Such a thing as a reciprocal relationship between theology and music definitely exists, but it has not yet been theoretically developed enough. Correlation between musical and theological disciplines constitutes a very broad and complex discourse. Therefore this study would rather narrow the subject and put it in a specific context: Theology and Music in the XXI. Century. This paper is a text-based study; therefore it will be based on textual-analysis with elements of the text hermeneutics.

Keywords: music, theology, reciprocal relationship between theology and music, XXI Century

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Authors: Verónica Díaz Quezada

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The importance given to the development of the problem solving skill and the requirement to solve problems framed in mathematical or real life contexts, in practice, they are not evidence in relation to the teaching of proportional variations. This qualitative and descriptive study aims to (1) to improve problem solving ability of high school students in Chile, (ii) to elaborate and describe a didactic intervention strategy based on learning situations in proportional variations, focused on solving types of routine problems of various contexts and non-routine problems. For this purpose, participant observation was conducted, test of mathematics problems and an opinion questionnaire to thirty-six high school students. Through the results, the highest academic performance is evidenced in the routine problems of purely mathematical context, realistic, fantasy context, and non-routine problems, except in the routine problems of real context and compound proportionality problems. The results highlight the need to consider in the curriculum different types of problems in the teaching of mathematics that relate the discipline to everyday life situations

Keywords: algebra, high school, proportion variations, nonroutine problem solving, routine problem solving

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Authors: B. Alajmi, L. Marouf, A. S. Chaudhry

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In recent years, increasing emphasis has been placed upon issues concerning the evaluation of health care. In this regard, knowledge management has also been considered an important component of the evaluation process. KM facilitates the transfer of existing knowledge or the development of new knowledge among healthcare staff and patients. This research aimed to examine how hospitals in Kuwait employ knowledge management practices, including capturing, sharing, and generating, and the perceived impact of KM practices on performance of hospitals in Kuwait. Through adopting a quantitative survey method with 277 sample of doctors, the study found that in terms of the three major knowledge management practices – knowledge capturing, sharing, and generating – the adoption of KM practices were rated very low in the sampled hospitals in Kuwait. Hospitals paid little attention to the main activities that support the transfer of expertise among doctors in hospitals. However, as predicted by previous studies, knowledge management practices were perceived to have an impact on hospitals’ performance. Through knowledge capturing, sharing, and generating, hospitals could improve the services they provide through documenting best practices, transforming their hospitals into learning organizations in which lessons learned are captured, stored, and made available for others to learn from.

Keywords: knowledge management, hospitals, knowledge management practices, knowledge management tools, performance

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Authors: Hamad Aldosari

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The purpose of this study is to investigate the status of sexism, or gender discrepancies, in current pedagogical and curricular practices in EFL learning higher education settings. Qualitative and quantitative analyses of both course contents and pedagogies in Saudi higher education institutions are to be discussed with reference to female/male topic presentation in dialogs and reading passages, sex-based activity types, stereotyped sex roles and the masculine generic conceptions of male superiority subliminally related in EFL curriculum and pedagogical practices, as well as the causes and effects of segregated language education practices in Saudi Arabia from a holistic vantage point of analysis. Analysis findings show that language educational practices including educational settings and segregation are gender-biased in attitude, but with regard to curriculum, sexism has not been traced. Findings also show that sexism is rampant due to socio-cultural aspects of language education rather than to religious reasons: a finding that seems to mirror the institutionalized unfair sex discrimination to the disadvantage of women in the Arabian societies at large.

Keywords: genderism, sex segregation, Saudi Arabia, EFL

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Authors: Poom Thiparapkul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that doesn't translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: user experience design, user experience, electric vehicle, dashboard design, Thailand driver.

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Authors: Khaled M. Alhawiti

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Reading capability is a major segment of language competency. On the other hand, discovering topical writings at a fitting level for outside and second language learners is a test for educators. We address this issue utilizing natural language preparing innovation to survey reading level and streamline content. In the connection of outside and second-language learning, existing measures of reading level are not appropriate to this errand. Related work has demonstrated the profit of utilizing measurable language preparing procedures; we expand these thoughts and incorporate other potential peculiarities to measure intelligibility. In the first piece of this examination, we join characteristics from measurable language models, customary reading level measures and other language preparing apparatuses to deliver a finer technique for recognizing reading level. We examine the execution of human annotators and assess results for our finders concerning human appraisals. A key commitment is that our identifiers are trainable; with preparing and test information from the same space, our finders beat more general reading level instruments (Flesch-Kincaid and Lexile). Trainability will permit execution to be tuned to address the needs of specific gatherings or understudies.

Keywords: natural language processing, trainability, syntactic simplification tools, education

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Authors: Galila Aisyah Latif Amini, Husnul Khatimah, Citra Amelia

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Smoking among women is of particular concern for the maternal and child health community due to the strong association between prenatal smoking and adverse birth outcomes. Pregnancy is perceived to be a unique reason for smoking cessation, as motivation to care for the unborn fetus. This study aimed to find out the determinants of smoking cessation among pregnant women. Method that we use in this study is systematic review. We identified relevant studies by searching on science database online through SAGE journals, Proquest, Scopus, Emerald, JSTOR, and Springerlink. Journals were screened by title and abstract according to the research topic then filtered using the criteria exclusion and inclusion. And then we did critical appraisal. The results of the four studies reviewed were found that the determinant of smoking cessation are parity, the level of education, socioeconomic status, household SHS exposure, smoking habits of both parents, partner smoking status, psychological factors, antenatal care, intervention for health care provider, age smoking duration. The factor most strongly associated with smoking cessation is parity (OR 2,55; Cl 2,34-2,77). The results of this study are expected to give advice for developing future smoking cessation and relapse prevention programs.

Keywords: pregnancy, smoking cessation, tobacco use cessation, smoking

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Authors: H. H. Goh, K. C. Goh, T. W. Seow, N. S. Said, S. E. P. Ang

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Malaysia is rich with historic buildings, particularly in Penang and Malacca states. Restoration activities are increasingly important as these states are recognized under UNESCO World Heritage Sites. Restoration activities help to maintain the uniqueness and value of a heritage building. However, increasing in restoration activities has resulted in large quantities of waste. To cope with this problem, the 3R concept (reduce, reuse and recycle) is introduced. The 3R concept is one of the waste management hierarchies. This concept is still yet to apply in the building restoration industry compared to the construction industry. Therefore, this study aims to promote the 3R concept in the heritage building restoration industry. This study aims to examine the importance of 3R concept and to identify challenges in applying the 3R concept in the heritage building restoration industry. This study focused on contractors and consultants who are involved in heritage restoration projects in Penang. Literature review and interviews helps to reach the research objective. Data that obtained is analyzed by using content analysis. For the research, application of 3R concept is important to conserve natural resources and reduce pollution problems. However, limited space to organise waste is the obstruction during the implementation of this concept. In conclusion, the 3R concept plays an important role in promoting environmental conservation and helping in reducing the construction waste

Keywords: 3R Concept, heritage building, restoration activities, building science

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Authors: Yula Milshteyn

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The present study focuses on the science of the “Soul” in Islamic Medieval Psychology.The main objective of the current essay is to analyze the concept of the “soul” in relation to “mental” disorders, in the philosophical psychology and medicinal treatise of Ibn Sina, a Muslim Persian physician-philosopher (known as Avicenna in the Western world) (981-1037 CE). The examination will concentrate on the nature of the soul, and the relationship of the soul to the body, as well as the manifestation of health and sickness in soul and body, The analysis draws on Avicenna’s Psychology (Kitab al-Najat or The Book of Salvation), Remarks and Admonitions (Al-isharat wa al-tanbihat), and the medical treatise – The Canon of Medicine (al-Qānūn fī al-Ṭibb). Avicenna’s psychology of the soul is primarily based on Aristotelian and Neo-platonic paradigms. For Avicenna, soul is a metaphysical, independent substance, which in modern terms implies independence of human consciousness from the material body. The soul however, is linked to the body and controls all its’ faculties or functions. It is suggested that in the specific case study of schizophrenia, it is a disorder pertained to both, soul and body and can be characterized as a multi-faceted neurobiological, physiological, psychological and metaphysical spiritual phenomenon.

Keywords: Avicenna, canon of the medicine, mental disorders, psychology, schizophrenia, soul-body

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Authors: Promise Ekpo Osaine, Daniel Melesse

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Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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Authors: Engku Haliza Engku Ibrahim, Isarji Sarudin, Ainon Jariah Muhamad

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It is generally agreed that many factors contribute to one’s reading comprehension and there is consensus that vocabulary size one of the main factors. This study explores the relationship between second language learners’ vocabulary size and their reading comprehension scores. 130 Malay pre-university students of a public university participated in this study. They were students of an intensive English language programme doing preparatory English courses to pursue bachelors degree in English. A quantitative research method was employed based on the Vocabulary Levels Test by Nation (1990) and the reading comprehension score of the in-house English Proficiency Test. A review of the literature indicates that a somewhat positive correlation is to be expected though findings of this study can only be explicated once the final analysis has been carried out. This is an ongoing study and it is anticipated that results of this research will be finalized in the near future. The findings will help provide beneficial implications for the prediction of reading comprehension performance. It also has implications for the teaching of vocabulary in the ESL context. A better understanding of the relationship between vocabulary size and reading comprehension scores will enhance teachers’ and students’ awareness of the importance of vocabulary acquisition in the L2 classroom.

Keywords: vocabulary size, vocabulary learning, reading comprehension, ESL

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Authors: Muhammad Akram, Qamar Naseem, Imtiaz Ahmad

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The purpose of this study was to correlate students’ perceptions of teacher effectiveness with their academic achievement in English and Mathematics at the secondary level (grade 9th) based on five national professional standards for teacher evaluation in Pakistan (subject matter knowledge, instructional planning and strategies, assessment, learning environment, effective communication. A Students’ Perceptions of Teacher Effectiveness Questionnaire (SPTEQ) was developed by the researchers to collect data from 2009 students from forty public girls and boys high/ higher secondary schools in district Khanewal, Pakistan. The overall reliability of the SPTEQ was α=.86. The study found a significant positive relationship among all the five factors of teacher effectiveness construct. The study also showed significant, positive relationship between teacher effectiveness factors and students’ achievement in English and mathematics. No significant differences were found between male and female students’ perceptions about their English teacher effectiveness. The implications include students’ personal attachments with their teachers that might convince them to overrate their teachers.

Keywords: communication, students’ achievement, teacher effectiveness, teaching strategies, teaching strategies

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Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

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In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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Authors: Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Lidija Jevrić, Evgenija Djurendić, Jovana Ajduković

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In the present study, the molecular modeling of a series of 24 17-picolyl and 17-picolinylidene androstane derivatives whit significant anticancer activity was carried out. Modelling of studied compounds was performed by CS ChemBioDraw Ultra v12.0 program for drawing 2D molecular structures and CS ChemBio3D Ultra v12.0 for 3D molecular modelling. The obtained 3D structures were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. Full geometry optimization was done by the Austin Model 1 (AM1) until the root mean square (RMS) gradient reached a value smaller than 0.0001 kcal/Åmol using Molecular Orbital Package (MOPAC) program. The obtained physicochemical, lipophilicity and topological descriptors were used for analysis of molecular similarities and dissimilarities applying suitable chemometric methods (principal component analysis and cluster analysis). These results are the part of the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina and CMST COST Action CM1306.

Keywords: androstane derivatives, anticancer activity, chemometrics, molecular descriptors

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Authors: Cristina Sanchez-Sanchez

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Although there seems to be a growing interest in the study of the citizen’s happiness as an alternative measure of a country’s progress to GDP, happiness as a public concern is still an ambiguous concept, hard to define. Moreover, different notions are used indiscriminately to talk about the same thing. This investigation aims to determine the conceptions of happiness, well-being and quality of life that originate from the indexes that different governments and public institutions around the world have created to study them. Through the Scoping Review method, this study identifies the recent academic research in this field (a total of 267 documents between 2006 and 2016) from some of the most popular social sciences databases around the world, Web of Science, Scopus, JSTOR, Sage, EBSCO, IBSS and Google Scholar, and in Spain, ISOC and Dialnet. These 267 documents referenced 53 different indexes and researches. The Grounded Theory method has been applied to a sample of 13 indexes in order to identify the main categories they use to determine these three concepts. The results show that these are multi-dimensional concepts and similar indicators are used indistinctly to measure happiness, well-being and quality of life.

Keywords: common good, grounded theory, happiness economics, happiness index, quality of life, scoping review, well-being

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Authors: Trilochana Dash, Chandan Kumar Sahoo

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In today's environment of intensive industrialization, the role of business in societal modernization is critical. The concept of corporate social responsibility (CSR) arose due to rising societal awareness of company conduct. Corporations that practice CSR devote a portion of their profits to society’s sustainable development (SD). The concept of CSR and SD has increased the impact of industries on society. In this study, bibliometric analysis was conducted using the “R” programming language to determine the comprehensiveness of CSR and SD. From 2003 to 2022, bibliometric data was collected from two databases: Scopus and Web of Science (WOS). According to the findings, CSR and SD research has risen exponentially in the past two decades, and “Corporate Social Responsibility and Environment Management” emerged as the most influential journal in this field. The findings also show that relatively very few researchers collaborate in CSR and SD research in the last twenty years. It is widely acknowledged that most CSR and SD research is conducted in developed countries and developing countries undergoing fast industrialization. Thematic evolution and cluster analysis clearly show that the notion of CSR and SD among scholars has been quite popular over the last two decades. Finally, limitations and future directions are discussed.

Keywords: corporate social responsibility, sustainable development, bibliometric analysis, “R” programming language, visualization, holistic picture

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, Rebecca K. Rossi, Yanmin Yuan, Xianpei Li

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The fiscal growth of any country hinges on the prudent administration of water resources. The river Yamuna and Ganga are measured as the life line of India as it affords the needs for life to endure. Earth observation over remote sensing images permits the precise description and identification of ingredients on the superficial from space and airborne platforms. Multiple and heterogeneous image sources are accessible for the same geographical section; multispectral, hyperspectral, radar, multitemporal, and multiangular images. In this paper, a taxonomical learning of the fluvial geomorphological features of river Yamuna and Ganga over doon valley using color fusion of multispectral remote sensing images was performed. Experimental results exhibited that the segmentation based colorization technique stranded on pattern recognition, and color mapping fashioned more colorful and truthful colorized images for geomorphological feature extraction.

Keywords: color fusion, geomorphology, fluvial processes, multispectral images, pattern recognition

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Authors: M. Kastek, M. Kowalski, M. Szustakowski, H. Polakowski, T. Sosnowski

Abstract:

Development of highly efficient security systems is one of the most urgent topics for science and engineering. There are many kinds of threats and many methods of prevention. It is very important to detect a threat as early as possible in order to neutralize it. One of the very challenging problems is detection of dangerous objects hidden under human’s clothing. This problem is particularly important for safety of airport passengers. In order to develop methods and algorithms to detect hidden objects it is necessary to determine the thermal signatures of such objects of interest. The laboratory measurements were conducted to determine the thermal signatures of dangerous tools hidden under various clothes in different ambient conditions. Cameras used for measurements were working in spectral range 0.6-12.5 μm An infrared imaging Fourier transform spectroradiometer was also used, working in spectral range 7.7-11.7 μm. Analysis of registered thermograms and hyperspectral datacubes has yielded the thermal signatures for two types of guns, two types of knives and home-made explosive bombs. The determined thermal signatures will be used in the development of method and algorithms of image analysis implemented in proposed monitoring systems.

Keywords: hyperspectral detection, nultispectral detection, image processing, monitoring systems

Procedia PDF Downloads 336

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

Abstract:

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

Procedia PDF Downloads 447

Authors: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

Abstract:

This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: academic identity, digitized lecture, embodied learning, performance coaching

Procedia PDF Downloads 323