Search results for: Emotional intelligence

Authors: Tahmina Huq

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This paper presents the findings of an action research study that aimed to investigate the efficacy of a visual dialogue strategy in assisting autistic students with intellectual disabilities in managing their immediate emotions and improving their academic achievements. The research sought to explore the effectiveness of teaching self-regulation techniques as an alternative to traditional approaches involving segregation. The study identified visual dialogue as a valuable tool for promoting self-regulation in this specific student population. Action research was chosen as the methodology due to its suitability for immediate implementation of the findings in the classroom. Autistic students with intellectual disabilities often face challenges in controlling their emotions, which can disrupt their learning and academic progress. Conventional methods of intervention, such as isolation and psychologist-assisted approaches, may result in missed classes and hindered academic development. This study introduces the utilization of visual dialogue between students and teachers as an effective self-regulation strategy, addressing the limitations of traditional approaches. Action research was employed as the methodology for this study, allowing for the direct application of the findings in the classroom. The study observed two 15-year-old autistic students with intellectual disabilities who exhibited difficulties in emotional regulation and displayed aggressive behaviors. The research question focused on the effectiveness of visual dialogue in managing the emotions of these students and its impact on their learning outcomes. Data collection methods included personal observations, log sheets, personal reflections, and visual documentation. The study revealed that the implementation of visual dialogue as a self-regulation strategy enabled the students to regulate their emotions within a short timeframe (10 to 30 minutes). Through visual dialogue, they were able to express their feelings and needs in socially appropriate ways. This finding underscores the significance of visual dialogue as a tool for promoting emotional regulation and facilitating active participation in classroom activities. As a result, the students' learning outcomes and social interactions were positively impacted. The findings of this study hold significant implications for educators working with autistic students with intellectual disabilities. The use of visual dialogue as a self-regulation strategy can enhance emotional regulation skills and improve overall academic progress. The action research approach outlined in this paper provides practical guidance for educators in effectively implementing self-regulation strategies within classroom settings. In conclusion, the study demonstrates that visual dialogue is an effective strategy for enhancing emotional regulation in autistic students with intellectual disabilities. By employing visual communication, students can successfully regulate their emotions and actively engage in classroom activities, leading to improved learning outcomes and social interactions. This paper underscores the importance of implementing self-regulation strategies in educational settings to cater to the unique needs of autistic students.

Keywords: action research, self-regulation, autism, visual communication

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Authors: Annabelle Nelson

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This literature review documents indigenous storytelling as it functions to help humans face adversity and find emotional strength by aligning with nature. Archetypes in stories can transform the inner world from a Jungian perspective. Joseph Campbell’s hero-heroine cycle depicts the structure of stories to include a call to adventure, tests, helpers, and a return as the transformed person can help him or herself and even help their communities. By showcasing certain character traits, such as bravery or perseverance or humility, stories give maps for humans to face adversity. The main characters or archetypes in stories, as Carl Jung posited, provide a vehicle that can open consciousness if a listener identifies with the character. As documented in the review, this has many benefits. First, it can open consciousness to the collective unconscious for insight and intuitive clarity, as well as healing and release emotional trauma. The resultant spacious quality of consciousness allows the spiritual self to present insights to conscious awareness. Research in applied youth development programs demonstrates the utility of storytelling to prompt healthy choices and transform difficult life experience into success.

Keywords: archetypes, learning, storytelling, transformation

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Authors: Sonto Maputle

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Background: Support during labour increase women's chances of having positive childbirth experiences as well as childbirth outcomes. The purpose of this study was to determine the support provided by midwives to women during labour at the public hospital in Limpopo Province. The study was conducted at the Tertiary hospital in Limpopo Province. Methods: A qualitative, participant observation approach was used. Population consisted of all women that were admitted to deliver their babies and the midwives who provided midwifery care in the obstetric unit of one tertiary public hospital in Limpopo Province. Non-probability, purposive and convenience sampling were used to sample 24 women and 12 midwives. Data were collected through participant observations which included unstructured conversations with the use of observational guide, field notes of events and conversations that occurred when women interact with midwives were recorded verbatim and a Visual Analog Scale to complement the observations. Data was analysed qualitatively but were presented in the tables and bar graphs. Results: Five themes emerged as support provided by midwives during labour, namely; communication between women and midwives, informational support, emotional support activities, interpretation of the experienced labour pain and supportive care activities during labour. Conclusion: The communication was occurring when the midwife was rendering midwifery care and very limited for empowering. The information sharing focused on the assistive actions rather than on the activities that would promote mothers’ participation. The emotional support activities indicated lack of respect and disregard cultural preferences and this contributed to inability to exercise choices in decision-making. The study recommended the implementation of Batho Pele principles in order to provide woman-centred care during labour.

Keywords: communication between women and midwives, labour pains, informational and emotional support, physical comforting measures

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Authors: Gabriele Barrocas, Habon Issa

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The amygdala is one of various brain regions that tend to be pathological in individuals with autism spectrum disorder (ASD). ASD is a prevalent and heterogeneous developmental disorder affecting all ethnic and socioeconomic groups and consists of a broad range of severity, etiology, and behavioral symptoms. Common features of ASD include but are not limited to repetitive behaviors, obsessive interests, and anxiety. Neuroscientists view the amygdala as the core of the neural system that regulates behavioral responses to anxiogenic and threatening stimuli. Despite this consensus, many previous studies and literature reviews on the amygdala’s alterations in individuals with ASD have reported inconsistent findings. In this review, we will address these conflicts by highlighting recent studies which reveal that anatomical and related socio-emotional differences detected between individuals with and without ASD are highly age-dependent. We will specifically discuss studies using functional magnetic resonance imaging (fMRI), structural MRI, and diffusion tensor imaging (DTI) to provide insights into the neuroanatomical substrates of ASD across development, with a focus on amygdala volumes, cell densities, and connectivity.

Keywords: autism, amygdala, development, abnormalities

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Authors: Kate Benedicta Amenador, Dianjian Wang, Bright Nkrumah

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This extensive bibliometric study explores the dynamic influence of artificial intelligence in the field of English as a Foreign Language (EFL) between 2012 and 2024. The study, which examined 4,500 articles from Google Scholar, Modern Language Association Linguistics Abstracts, Web of Science, Scopus, Researchgate, and library genesis databases, indicates that AI integration in EFL is on the rise. This notable increase is ascribed to a variety of transformative events, including increased academic funding for higher education and the COVID-19 epidemic. The results of the study identify leading contributors, prominent authors, publishers and sources, with the United States, China and the United Kingdom emerging as key contributors. The co-occurrence analysis of key terms reveals five clusters highlighting patterns in AI-enhanced language instruction and learning, including evaluation strategies, educational technology, learning motivation, EFL teaching aspects, and learner feedback. The study also discusses the impact of various AIs in enhancing EFL writing skills with software such as Grammarly, Quilbot, and Chatgpt. The current study recognizes limitations in database selection and linguistic constraints. Nevertheless, the results provide useful insights for educators, researchers and policymakers, inspiring and guiding a cross-disciplinary collaboration and creative pedagogical techniques and approaches to teaching and learning in the future.

Keywords: artificial intelligence, bibliometrics study, VOSviewer visualization, English as a foreign language

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Authors: Madihah Shukri

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Research examining whether eating behaviour is related to unhealthy or healthy eating pattern is required to explain the mechanisms underlying obesity, and to inform health intervention aim to prevent and treat obesity. The purpose of this study was to investigate the relationship between eating behaviours and nature of food consumption. Methods: This was a cross-sectional study of 588 adults (males = 231 and females = 357). The Dutch Eating Behaviour Questionnaire (DEBQ) was used to measure restrained, emotional and external eating. Nature of food consumption was assessed by self-reported consumption of fruit and vegetables, sweet food, junk food and snacking. Results: Results revealed that emotional eating was found to be the principal predictor of the consumption of less healthy food (sweet food, junk food and snacking), while external eating predicted sweet food intake. Intake of fruit and vegetable was associated with restrained eating. In light of the significant associations between eating behaviour and nature of food consumption, acknowledging individuals eating styles can have implications for tailoring effective nutritional programs in the context of obesity and chronic disease epidemic.

Keywords: eating behaviour, food consumption, adult, Malaysia

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Authors: Juanita Morris

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The purpose of this study will examine the mediating relationships between the theories of intelligence, mathematics anxiety, gender stereotype threat, meta-cognition and math performance through the use of eye tracking technology, affecting student perception and problem-solving abilities. The participants will consist of (N=80) female graduate students. Test administered were the Abbreviated Math Anxiety Scale, Tobii Eye Tracking software, gender stereotype threat through Google images, and they will be asked to describe their problem-solving approach allowed to measure metacognition. Participants will be administered mathematics problems while having gender stereotype threat shown to them through online images while being directed to look at the eye tracking software Tobii. We will explore this by asking ‘Is mathematics anxiety associated with the theories of intelligence and gender stereotype threat and how does metacognition and math performance place a role in mediating those perspectives?’. It is hypothesized that math-anxious students are more likely affected by the gender stereotype threat and that may play a role in their performance? Furthermore, we also want to explore whether math anxious students are more likely to be an entity theorist than incremental theorist and whether those who are math anxious will be more likely to be fixated on variables associated with coefficients? Path analysis and independent samples t-test will be used to generate results for this study. We hope to conclude that both the theories of intelligence and metacognition mediate the relationship between mathematics anxiety and gender stereotype threat.

Keywords: math anxiety, emotions, affective domains fo learning, cognitive underlinings

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Authors: Yaa Asuaba Duopah, Lisa Moran, Khalifa Elmusharaf, Dervla Kelly

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Background: Research has identified a strong link between stress and drug use behaviours. Also, it has been established that the prolonged use of crack cocaine stimulates emotional, cognitive, neurological, and social changes. This paper examines the psychosocial stressors associated with crack cocaine use. Methodology: The study is qualitative and adopts a critical realist approach. Data was collected through 26 face-to-face, in-depth, semi-structured interviews with people who use crack cocaine. Study participants were recruited through two addiction services using purposive. Participants consisted of 15 males and 11 females between the ages of 24-57 years. Data were analysed using thematic analysis. Results: Cravings, financial hardship, family breakdown, and emotional stimulation were revealed as psychosocial stressors associated with crack cocaine use. Conclusion: Addressing the psychosocial stressors identified in this paper through targeted interventions and supportive policies is crucial for improving the well-being of persons who use crack cocaine. Collaboration between addiction, mental health, and support services is recommended to develop and deliver these interventions.

Keywords: psychological stress, substance misuse disorder, mental health, coping

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Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: criminal digital evidence, social media, ontologies, reasoning

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Authors: Weber-Lewerenz Bianca

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Digitization is developing fast and has become a powerful tool for digital planning, construction, and operations. Its transformation bears high potentials for companies, is critical for success, and thus, requires responsible handling. This study provides an assessment of calls made in the sustainable development goals by the United Nations (SDGs), White Papers on AI by international institutions, EU-Commission and German Government requesting for the consideration and protection of values and fundamental rights, the careful demarcation between machine (artificial) and human intelligence and the careful use of such technologies. The study discusses digitization and the impacts of artificial intelligence (AI) in construction engineering from an ethical perspective by generating data via conducting case studies and interviewing experts as part of the qualitative method. This research evaluates critically opportunities and risks revolving around corporate digital responsibility (CDR) in the construction industry. To the author's knowledge, no study has set out to investigate how CDR in construction could be conceptualized, especially in relation to the digitization and AI, to mitigate digital transformation both in large, medium-sized, and small companies. No study addressed the key research question: Where can CDR be allocated, how shall its adequate ethical framework be designed to support digital innovations in order to make full use of the potentials of digitization and AI? Now is the right timing for constructive approaches and apply ethics-by-design in order to develop and implement a safe and efficient AI. This represents the first study in construction engineering applying a holistic, interdisciplinary, inclusive approach to provide guidelines for orientation, examine benefits of AI and define ethical principles as the key driver for success, resources-cost-time efficiency, and sustainability using digital technologies and AI in construction engineering to enhance digital transformation. Innovative corporate organizations starting new business models are more likely to succeed than those dominated by conservative, traditional attitudes.

Keywords: construction engineering, digitization, digital transformation, artificial intelligence, ethics, corporate digital responsibility, digital innovation

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Authors: Roberto Feltrero, Sara Osuna-Acedo

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Responsible Research and Innovation have to accomplish one fundamental aim: everybody has to participate in the benefits of innovation, but also innovation has to be democratic; that is to say, everybody may have the possibility to participate in the decisions in the innovation process. Particularly, a democratic and inclusive model of social participation and innovation includes persons with disabilities and people at risk of discrimination. Innovations on Artificial Intelligence for social development have to accomplish the same dual goal: improving equality for accessing fields of public interest like education, training and public services, as well as improving civic and democratic participation in the process of developing such innovations for all. This research aims to develop innovations, policies and policy recommendations to apply and disseminate such artificial intelligence and social model for making educational and administrative processes more accessible. First, designing a citizen participation process to engage citizens in the designing and use of artificial intelligence tools for public services. This will result in improving trust in democratic institutions contributing to enhancing the transparency, effectiveness, accountability and legitimacy of public policy-making and allowing people to participate in the development of ethical standards for the use of such technologies. Second, improving educational tools for lifelong learning with AI models to improve accountability and educational data management. Dissemination, education and social participation will be integrated, measured and evaluated in innovative educational processes to make accessible all the educational technologies and content developed on AI about responsible and social innovation. A particular case will be presented regarding access for all to educational tools and public services. This accessibility requires cognitive adaptability because, many times, legal or administrative language is very complex. Not only for people with cognitive disabilities but also for old people or citizens at risk of educational or social discrimination. Artificial Intelligence natural language processing technologies can provide tools to translate legal, administrative, or educational texts to a more simple language that can be accessible to everybody. Despite technological advances in language processing and machine learning, this becomes a huge project if we really want to respect ethical and legal consequences because that kinds of consequences can only be achieved with civil and democratic engagement in two realms: 1) to democratically select texts that need and can be translated and 2) to involved citizens, experts and nonexperts, to produce and validate real examples of legal texts with cognitive adaptations to feed artificial intelligence algorithms for learning how to translate those texts to a more simple and accessible language, adapted to any kind of population.

Keywords: responsible research and innovation, AI social innovations, cognitive accessibility, public participation

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Authors: Alejandra Sierra, Maria de los Angeles Covarrubias, Guillermo Julian Gonzalez, Noe Alfaro

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The objective of this study was to identify the cultural dimensions of the terms unplanned pregnancy and unwanted pregnancy built by adolescent women, through the focus of the social representations. Two associative methods were used: free listings and the paired comparison. 72 female students between the ages of 15 and 19 were interviewed, from the downtown area of Leon Guanajuato, Mexico. Words related to inducer terms were classified into five thematic categories: facilitators, consequences, reactions, expectations, and lexicon. The results showed that the social representations of unplanned pregnancy highlighted elements related to economic difficulties and negative emotional aspects, while unwanted pregnancy was associated with negative emotional aspects such as anger, anxiety, and sadness. The meanings each person attributes to terms related to pregnancy are culturally constructed and differ between populations; therefore, more attention should be paid to understanding the cultural meanings and attitudes of people in fertility decision-making, including also the views of adolescent men and other types of population, stratified by age groups and social conditions.

Keywords: adolescent, qualitative research, unplanned pregnancy, unwanted pregnancy

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Authors: Baker Ssekitto, Ambrose Mbogo

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The study reveals that indeed agriculture employs over 70% of Uganda’s population, of which majority are youth and women. The study further reveals that over 70% of the farmers are smallholder farmers based in rural areas, whose operations are greatly affected by; climate change, weak digital skills, limited access to productivity knowledge along value chains, limited access to quality farm inputs, weak logistics systems, limited access to quality extension services, weak business intelligence, limited access to quality markets among others. It finds that the emerging 4th industrial revolution powered by artificial intelligence, 5G and data science will provide possibilities of addressing some of these challenges. Furthermore, the study finds that despite rapid development of ICT4Agric Innovation, their uptake is constrained by a number of factors including; limited awareness of these innovations, low internet and smart phone penetration especially in rural areas, lack of appropriate digital skills, inappropriate programmes implementation models which are project and donor driven, limited articulation of value addition to various stakeholders among others. Majority of farmers and other value chain actors lacked knowledge and skills to harness the power of ICTs, especially their application of ICTs in monitoring and evaluation on quality of service in the extension system and farm level processes.

Keywords: artificial intelligence, productivity, ICT4agriculture, value chain, logistics

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: P. Sawatnatee, S. Udomsuk, K-N. Areerak, K-L. Areerak, A. Srikaew

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The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional method. The controller design using the proposed technique can be used to create the software package for engineers to achieve the optimal controller design of the induction motor speed control based on the indirect vector concept.

Keywords: indirect vector control, induction motor, adaptive tabu search, control design, artificial intelligence

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Authors: Pawit Monkolprasit, Proud Arunrangsiwed

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It was important to understand the impact of media in young adolescents. The animated film, Khun Tong Dang the Inspirations (2015), was purposefully created for teaching young children to have a positive personal trait. The current study used this film as the case study. The objective is to understand the relationship between the good characteristic of movie audiences and their perception of the good characteristic of a movie character. One-hundred students from various age ranges responded to quantitative questionnaires. The questions included their age, gender, perception about their own personal traits, perception about their experiences with others, and perception about the bravery, intelligence, and gratefulness of the character. It was found that a good personal trait has a strong relationship with the perception of bravery, intelligence, and gratefulness of the character.

Keywords: impact of media, children, personal trait, prosocial content

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Authors: Chiou-Fang Liou

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Cancer has been one of the most life-threaten diseases worldwide for 30+ years. The influences of cancer illness include symptoms from cancer itself along with its treatments. The quality of life among patients diagnosed with cancer during cancer treatments has been conceptualized within four domains: Functional Well-Being, Social Well-Being, Physical Well-Being, and Emotional Well-Being. Patients with cancer often need to make adjustments to face all the challenges. The middle-range theory of Resourcefulness and Quality of life has been applied to explore factors contributing to cancer patients’ needs. Resourcefulness is defined as sets of skills that can be learned and consisted of Person and Social Resourcefulness. Empirical evidence also supported a possible relationship between Resourcefulness and Quality of Life. However, little is known about the extent to which the two concepts are related to each other. This study, therefore, applied a multivariate technique, Canonical Correlation Analysis, to identify the relationship between the two sets of variables with multi-dimensional measures, the Resourcefulness and Quality of Life in Cancer patients receiving treatments. After IRB approval, this multi-centered study took place at two medical centers in the Central Region of Taiwan. Sample A total of 186 patients with various cancer diagnoses and either receiving radiation therapy or chemotherapy consented to and answered questionnaires. The Import findings of the Generalized F test identified two typical sets with several linear relations and explained a total of 79.1% of the total variance. The first typical set found Personal Resourcefulness negatively related to Social Well-being, Functional being, Emotional Well-being, and Physical, in that order. The second typical set found Social Resourcefulness negatively related to Functional Well-being and Physical-being yet positively related to Social Well-being and Emotional Well-being. Discussion and Conclusion, The results of this presented study supported the statistically significant relationship between two sets of variables that are consistent with the theory. In addition, the results are considerably important in cancer patients receiving cancer treatments.

Keywords: cancer, canonical correlation analysis, quality of life, resourcefulness

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Authors: Sheila S. Silang

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This research seeks to make an impact analysis on multiple intelligence as the basis for differentiated classroom instruction in TLE. It will also address the felt need of how TLE subject could be taught effectively exhausting all the possible means.This study seek the effect of giving different instruction according to the ability of the students in the following objectives: 1. student’s technological skills enhancement, 2. learning potential improvements 3. having better linkage between school and community in a need for soliciting different learning devices and materials for the learner’s academic progress. General Luna, Quezon is composed of twenty seven barangays. There are only two public high schools. We are aware that K-12 curriculum is focused on providing sufficient time for mastery of concepts and skills, develop lifelong learners, and prepare graduates for tertiary education, middle-level skills development, employment, and entrepreneurship. The challenge is with TLE offerring a vast area of specializations, how would Multiple Intelligence play its vital role as basis in classroom instruction in acquiring the requirement of the said curriculum? 1.To what extent do the respondent students manifest the following types of intelligences: Visual-Spatial, Body-Kinesthetic, Musical, Interpersonal, Intrapersonal, Verbal-Linguistic, Logical-Mathematical and Naturalistic. What media should be used appropriate to the student’s learning style? Visual, Printed Words, Sound, Motion, Color or Realia 3. What is the impact of multiple intelligence as basis for differentiated instruction in T.L.E. based on the following student’s ability? Learning Characteristic and Reading Ability and Performance 3. To what extent do the intelligences of the student relate with their academic performance? The following were the findings derived from the study: In consideration of the vast areas of study of TLE, and the importance it plays in the school curriculum coinciding with the expectation of turning students to technologically competent contributing members of the society, either in the field of Technical/Vocational Expertise or Entrepreneurial based competencies, as well as the government’s concern for it, we visualize TLE classroom teachers making use of multiple intelligence as basis for differentiated classroom instruction in teaching the subject .Somehow, multiple intelligence sample such as Linguistic, Logical-Mathematical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Spatial abilities that an individual student may have or may not have, can be a basis for a TLE teacher’s instructional method or design.

Keywords: education, multiple, differentiated classroom instruction, impact analysis

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Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: Chen Xi, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Tong Zhiyuan

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature has led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using YOLOv5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network

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Authors: Japnoor Garcha, Andrew P. Smith, A. James

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There has been a significant increase in the prevalence and estimates of neurodevelopmental disorders, especially autism spectrum disorders, in the last decade. The literature has seen increasing research on understanding wellbeing and mental health. To understand the association and interaction of wellbeing and mental health with autism and ADHD, a survey was given to 560 secondary school students. The survey used the wellbeing process questionnaire, the autism spectrum quotient, the ADHD self-report scale, and the strengths and difficulties questionnaire. The analysis conducted using SPSS showed that there was a significant correlation between anxiety, depression, A.Q., and ADHD. Anxiety and depression were also significantly correlated with all wellbeing and SDQ variables. The regression analysis showed that anxiety was significantly associated with positive wellbeing, negative wellbeing, emotional problems, and prosocial behaviour, whereas depression was significantly associated with positive wellbeing, negative wellbeing, physical health, flourishing, conduct problems, emotional problems and peer problems.

Keywords: ADHD traits, anxiety, autistic traits, depression

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Authors: Min-Ha Hong, Kee-Won Kim, Seung-Hoon Kim

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The character in the story-based content, such as novels and movies, is one of the core elements to understand the story. In particular, the character’s tendency is an important factor to analyze the story-based content, because it has a significant influence on the storyline. If readers have the knowledge of the tendency of characters before reading a novel, it will be helpful to understand the structure of conflict, episode and relationship between characters in the novel. It may therefore help readers to select novel that the reader wants to read. In this paper, we propose a method of extracting the tendency of the characters from a novel written in Korean. In advance, we build the dictionary with pairs of the emotional words in Korean and English since the emotion words in the novel’s sentences express character’s feelings. We rate the degree of polarity (positive or negative) of words in our emotional words dictionary based on SenticNet. Then we extract characters and emotion words from sentences in a novel. Since the polarity of a word grows strong or weak due to sentence features such as quotations and modifiers, our proposed method consider them to calculate the polarity of characters. The information of the extracted character’s polarity can be used in the book search service or book recommendation service.

Keywords: character tendency, data mining, emotion word, Korean novel

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Authors: Yao Chen

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Empathy is crucial for teachers working with teenagers in secondary school. Despite that, little attention was paid to English language teachers’ experiences of empathy in class. Empathy contains cognitive, emotional, and behavioral components that are manifested in the teaching practice. The qualitative study focused on how Chinese ELT teachers expressed empathy in interaction with students in public high schools and private institutions and what factors might lead them to show empathy in different ways. Four participants were invited to attend the individual interviews to share their stories about their empathic experiences. Classroom observation was conducted to investigate teachers’ language use in teaching and non-verbal communication with students to witness their behavior of expressing empathy. Through thematic analysis, three main themes relevant to different types of empathy in teachers’ interaction with students were generated: 1) perspective taking, 2) emotional connections, 3) action taking. Based on the participants’ statements of their personal experiences, the discussion concluded the reasons for their differences in expressing empathy. The result underlined the significance of the role of empathy in building a rapport with students and motivating their language learning. Further implications for the role of empathy in ELT teachers’ professional development are also discussed.

Keywords: teacher empathy, experiences, interaction with students, ELT class

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Authors: Prakash Singh, Piet Maphodisa Kgohlo

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Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

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Authors: Sasha Goodwin

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Sex offenders are often viewed as a homogenous group, but they encompass a diverse range of individuals with varying characteristics and offenses. The principal aim of this study was to ascertain how members of the Australian public perceive and define a sex offender while also investigating the emotional underpinnings associated with these attitudes and definitions. To assess public attitude, this study used the innovative utilization of visual methodologies to assess the public's perception of sex offenders. The study employed the iSquare approach, a visual methodology framework that offers unique viewpoints and insights into public attitudes toward sex offenders. Through the utilization of this approach, this study established an academic foundation for a deeper understanding of the public's perception of sex offenders. The data analysis revealed that most participants associated sex offenders with strong negative emotions, primarily disgust and anger. The findings of this research point towards the potential for fostering a social environment characterized by evidence-based discussions instead of reactionary punitive responses. Promoting a comprehensive understanding of the diverse nature of sexual offenders aims to broaden perceptions, fostering constructive attitudes.

Keywords: visual methodologies, public perception, sex offenders, offender characteristics, emotional attitudes, isquare approach, attitudes

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Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Mehrdad Karimi, Farshad Negintaji

Abstract:

This study has examined the appearance of identity in the urban landscape and its effects on the natural factors. For this purpose, the components of place identity, emotional attachment, place dependence and social bond which totally constitute place attachment, measures it in three domains of cognitive (place identity), affective (emotional attachment) and behavioral (place dependence and social bond). In order to measure the natural factors, three components of the absolute elements, living entities, natural elements have been measured. The study is descriptive and the statistical population has been Yasouj, a city in Iran. To analyze the data the SPSS software has been used. The results in two level of descriptive and inferential statistics have been investigated. In the inferential statistics, Pearson correlation coefficient test has been used to evaluate the research hypotheses. In this study, the variable of identity is in high level and the natural factors are also in high level. These results indicate a positive relationship between place identity and natural factors. Development of environment and reaching the quality level of the personality or identity will develop the individual and society.

Keywords: identity, place identity, landscape, urban landscape, landscaping

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Authors: Samir Hessas

Abstract:

Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

Abstract:

In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

Abstract:

This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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