Search results for: emotional and intelligence quotient

Authors: Rithi Baruah

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The aviation industry is one such sectors whose primary aim is to work for the safety and comfort of their clients and customers. The crew members in the aviation industry include pilots, flight attendants, air traffic controllers, baggage personnel and maintenance personnel. This study will concentrate on the frontline employees of the aviation industry, the flight attendants. Flight attendants belong to the niche group of population who are paid to smile. Although the profession seems to be very glamorous, it is physically and psychologically very taxing. Energy at workplace is a fairly new concept and is an organizational resource which helps employee attain their goals. Therefore, the researcher will aim to establish the relationship between relational energy and the major issue of emotional labor and cognitive flexibility among flight attendants. The researcher will hypothesize that there will be a negative relationship between relational energy and emotional labour, and a positive relationship between relational energy and cognitive flexibility. Also, a positive relationship will be expected between cognitive flexibility and emotional labour of cabin crew. A quantitative research design will be used to study the relationship among 50 flight attendants in India. The findings of the research will not only help the aviation sector but will be a major contribution to the existing literature of aviation psychology in India which is scanty. The relationships can also provide scope to develop a model using the same. From crew resource management and aviation psychology perspectives, relationships among the study variables will not only provide scope for helping the aviation employees in particular but also develop the performance and safety of aviation sector at large.

Keywords: cabin crew, cognitive flexibility, emotional labour, relational energy

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Authors: Poojitha Vemula

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Understanding how we use image manipulation to communicate through an audience’s perceptions and conceive visual intelligence. With the use of many software and high-end skills, designers have developed a third eye to combine two different visuals and create the desired image by using photoshop and other software skills. The purpose of visual intelligence is to convey a message to the targeted audience. For instance, the images of models are retouched on their skin to make it more convincing and draw attention from the audience. There are many ways of manipulating an image, such as double exposure, retouching photography inks or paint airbrushing and piecing photos together, or enhancing the brightness and contrast. To understand visual intelligence, a questionnaire survey as well as research was conducted on how image manipulation is used by both the audience and the designers. This depends on the message that needs to be conveyed by the brands. For instance, Fair & Lovely, a brightening cream for ladies use a lot of retouching and effects to show the dramatic change the cream takes effect on dark or dusky faces. Thus the designer’s role is to use their third eye to incorporate the message into visuals. The research and questionnaire survey concludes the perceptions and manipulations used in visual communication. However this is all to make an effortless communication between the designer and the audience by using the skills of the designer and the features provided by the software. The objective of visual intelligence is to covet the message of the brands that advertise their products or services by using visuals through softwares. Conveying a message through visual intelligence requires an audiences perceptions and understanding from the visuals created by the artists or designers. Visual intelligence determines how we use our technical skills to retouch and manipulate an image for a better understanding to convey the message to the targeted audience. This also bridges the communication between the brand and the audience.

Keywords: graphic design, visual communication, convey messages, photoshop, image manipulation

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Authors: Marisa Almeida AraúJo

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Artificial intelligence (AI) tools are being used (including in the criminal justice system) and becomingincreasingly popular. The many questions that these (future) super-beings pose the neuralgic center is rooted in the (old) problematic between rationality and morality. For instance, if we follow a Kantian perspective in which morality derives from AI, rationality will also surpass man in ethical and moral standards, questioning the nature of mind, the conscience of self and others, and moral. The recognition of superior intelligence in a non-human being puts us in the contingency of having to recognize a pair in a form of new coexistence and social relationship. Just think of the humanoid robot Sophia, capable of reasoning and conversation (and who has been recognized for Saudi citizenship; a fact that symbolically demonstrates our empathy with the being). Machines having a more intelligent mind, and even, eventually, with higher ethical standards to which, in the alluded categorical imperative, we would have to subject ourselves under penalty of contradiction with the universal Kantian law. Recognizing the complex ethical and legal issues and the significant impact on human rights and democratic functioning itself is the goal of our work.

Keywords: ethics, artificial intelligence, legal rules, principles, philosophy

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Authors: Arda Ozturk, Turgay Ozgur, Mursit Aksoy, Bahar O. Ozgur, Ozan Yilmaz

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The purpose of this study was to investigate the effect of 8 weeks of basic basketball and volleyball exercises to Bodily-Kinesthetic Intelligence (BKI) levels in 245 (92 girls and 154 boys) adolescents aged between 12 and 14 years. Data collected via Bodily-Kinesthetic Intelligence scale as a subdimension of Multiple Intelligences Inventory. BKI levels were not different between basketball and volleyball groups. Statistical analyses were made based on gender, age groups (12, 13, 14 years) and exercise type. Independent samples t-test revealed that there was no significant difference between boy’s and girl’s BKI levels. One way ANOVA test revealed that there was significant difference between age group’s (12, 13, 14) BKI levels in post-test. However, Paired samples t-test revealed no significant differences between pre-post test results of adolescent’s BKI levels. In conclusion, despite the relatively long-term (8 weeks) physical activity. BKI levels have not shown significant differences.

Keywords: bodily-kinesthetic intelligence, adolescent, basketball, volleyball

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Authors: Shailendra Kumar Mishra

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In this paper, we focus on how contextual factors like the physical presence of other perceivers and then developed induced emotional empathy towards a person with disabilities may reduce the automatic negative stereotypes and then response towards that person. We demonstrated in study 1 that negative attitude based on negative stereotypes assessed on ATDP-test questionnaires on five points Linkert-scale are significantly less negative when participants were tested with a group of perceivers and then tested alone separately by applying 3 (positive, indifferent, and negative attitude levels) X 2 (physical presence condition and alone) factorial design of ANOVA test. In the second study, we demonstrate, by applying regression analysis, in the presence of other perceivers, whether in a small group, participants showed more induced emotional empathy through stronger prosociality towards a high distress target like a person with disabilities in comparison of that of other stigmatized persons such as racial biased or gender-biased people. Thus results show that automatic affective response in the form of induced emotional empathy in perceiver and contextual factors like the presence of other perceivers automatically activate stronger prosocial norms and egalitarian goals towards physically challenged persons in comparison to other stigmatized persons like racial or gender-biased people. This leads to less negative attitudes and behaviour towards a person with disabilities.

Keywords: contextual factors, high distress target, induced emotional empathy, stronger prosociality

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Authors: Khushi, Simrat

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The study aims to investigate the relationship between emotions and employee's social cognition and decision-making among employees. The sample of the study was the total number of participants, which included employees from various industries and job positions. Research papers in the same area were reviewed, providing a comprehensive review of existing literature and theoretical frameworks and shedding light on the interpersonal effects of emotions in the workplace. It emphasizes how one worker's emotions can significantly impact the overall work environment and productivity as well as the work of a common phenomenon known as Emotional contagion at the workplace, affecting social interactions and group dynamics. Therefore, this study concludes that Emotional contagion can lead to a ripple effect within the workplace, influencing the overall atmosphere and productivity. Emotions can shape how employees process information and make choices, ultimately impacting organizational outcomes.

Keywords: employee decision making, social cognition, emotions, industry, emotional contagion, workplace dynamics

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Authors: Yuting Tan, Benchao Fan, Xiaoman Wei, Tao Yang

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In order to investigate the relationship between students’ perceived teacher support, parental emotional support, mastery goal orientation and school belonging, the questionnaire data of 11,898 15-year-olds (5,699 girls and 6,199 boys) in four Chinese provinces and cities (Beijing, Shanghai, Jiangsu and Zhejiang) that participated in PISA 2018 were used. The results showed that: (1) teacher support can positively and significantly predict students' school belonging; (2) mastery goal orientation played the mediating role in the relationship between teacher support and school belonging; (3) the second half path of students’ mastery goal orientation to the mediation process of teacher support and school belonging was regulated by parental emotional support. The results have important educational practice enlightenment for effectively promoting the school belonging of Chinese students.

Keywords: school belonging, teacher support, mastery goal orientation, parental emotional support

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Authors: Karima Qayumi, Alex Norta

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The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

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Authors: Loulwah Bokhari, Jori Nazer, Hala Sultan

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Nowadays, artificial intelligence (AI) is used as a foundation for many activities in modern computing applications at home, in vehicles, and in businesses. Many modern machines are built to carry out a specific activity or purpose. This is where the Amazon Alexa application comes in, as it is used as a virtual assistant. The purpose of this paper is to explore the use of Amazon Alexa among people and how it has improved and made simple daily tasks easier for many people. We gave our participants several questions regarding Amazon Alexa and if they had recently used or heard of it, as well as the different tasks it provides and whether it successfully satisfied their needs. Overall, we found that participants who have recently used Alexa have found it to be helpful in their daily tasks.

Keywords: artificial intelligence, Echo system, machine learning, feature for feature match

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Authors: İrem Bulut, Mustafa Z. Söyük, Ertuğrul Yalçın, Simge Şişman-Bal

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Eyewitness testimony is one of the most frequently used methods in criminal cases for the determination of crime and perpetrator. In the literature, the number of studies about the reliability of eyewitness testimony is increasing. The study aims to reveal the factors that affect the short-term and long-term visual memory performance of the participants in the event of an accident. In this context, the effect of the emotional content of the accident and the sounds during the accident on visual memory performance was investigated with eye-tracking. According to the results, the presence of visual and auditory stimuli with emotional content during the accident decreases the participants' both short-term and long-term recall performance. Moreover, the data obtained from the eye monitoring device showed that the participants had difficulty in answering even the questions they focused on at the time of the accident.

Keywords: eye tracking, eyewitness testimony, long-term recall, short-term recall, visual memory

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Authors: Garry Gorman, Nigel McKelvey, James Connolly

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This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.

Keywords: computer science education, artificial intelligence, growth mindset, pedagogy

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Authors: Sandra So, Mohd Roslan Ismail, Safurah Jaafar

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With the rapid proliferation of data in healthcare has provided an opportune platform creation of Artificial Intelligence (AI). AI has brought a paradigm shift for healthcare professionals, promising improvement in delivery and quality. This study aims to determine the perception of healthcare personnel on perceived ease of use, perceived usefulness, and subjective norm toward attitude for artificial intelligence acceptance. A cross-sectional single institutional study of employees’ perception of adopting AI in the hospital was conducted. The survey was conducted using a questionnaire adapted from Technology Acceptance Model and a four-point Likert scale was used. There were 96 or 75.5% of the total population responded. This study has shown the significant relationship and the importance of ease of use, perceived usefulness, and subjective norm to the acceptance of AI. In the study results, it concluded that the determining factor to the strong acceptance of AI in their practices is mostly those respondents with the most interaction with the patients and clinical management.

Keywords: artificial intelligence, machine learning, perceived ease of use, perceived usefulness, subjective norm

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Authors: Fantahun Ibrahim

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The Ethiopian army was one of the largest and most heavily armed ground forces in Africa between 1974 and 1991. It scored a decisive victory over Somalia’s armed forces in March 1978. It, however, failed to withstand the combined onslaught of the northern insurgents from Tigray and Eritrea and finally collapsed in 1991. At the heart of the problem was the army’s huge intelligence failure. The northern insurgents, on the other hand, had a cutting edge in intelligence gathering. Among other things they infiltrated the army high command and managed to get top secrets about the army. Commanders who had fallen into the hands of the insurgents in several battles were told to send letters to their colleagues in the command structure and persuade them to work secretly for the insurgents. Some commanders did work for the insurgents and played a great role in the undoing of military operations. Insurgent commanders were able to warn their fighters about air strikes before jet fighters took off from airfields in the northern theatre. It was not uncommon for leaders of insurgents to get the full details of military operations days before their implementation. Such intelligence failures led to major military disasters like the fall of Afabet (March, 1988), Enda Sellase (February, 1989), Massawa and Debre Tabor (February, 1990), Karra Mishig, Meragna and Alem Ketema (June, 1990). This paper, therefore, seeks to investigate the army’s intelligence failures using untapped archival documents kept at the Ministry of National Defence in Addis Ababa and interviewing key former commanders of the army and ex-leaders of the insurgents.

Keywords: Ethiopian army, intelligence, infiltration, insurgents

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Authors: Jhansi Rani Boda, G. Sunitha

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Worldwide, the financial markets are influenced by several factors such as the changes in economic and political processes that occur in the country and the globe, information diffusion and approachability and so on. Yet, the foremost important factor is the investor’s reaction and perception. For an individual investor, decision-making process can be perceived as a continuous process that has significant impact of their psychology while making investment decisions. Behavioral finance relies on research of human and social recognition and emotional tolerance studies to identify and understand the investment decisions. This article aims to report the research of individual investor’s financial behavior in a historical perspective. This article uncovers the investor’s psychology in investment decision making focusing on the investor’s rationality with an explanation of psychological and emotional factors that affect investing. The results of the study are revealed by means of Graphical visualization.

Keywords: behavioral finance, psychology, investor’s behavior, psychological and emotional factors

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Authors: Danah S. Alabdulmohsin

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Due to the fast growth of organizational data as well as the emergence of new technologies such as artificial intelligence (AI), organizations tend to utilize these new technologies in their enterprise information systems (EIS) either to overcome the issues they struggle with or to enhance their functions. The aim of this paper is to review the potential role of AI technologies in EIS, namely: enterprise resource planning systems (ERP), customer relation management systems (CRM), supply chain management systems (SCM), knowledge systems (KM), and human resources management systems (HRM). The paper provided the definitions of these systems as well as the definitions of AI technologies that have been used in EIS. In addition, the paper discussed the challenges that organizations might face while integrating AI with their information systems and explained why some organizations fail in achieving successful implementations of the integration.

Keywords: artificial intelligence, AI, enterprise information system, EIS, integration

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Authors: Nurezlin Mohd Azib, Pan Kok Chang

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This quantitative study investigates the effects of major and minor modes, and contributing musical parameter of tempo, to the emotional perceptions of ‘happy’ and ‘sad’ in piano music among subjects aged 9-17 years old. The study was conducted in two phases; survey-questionnaire, and listening activity. Subjects (N=31) were sampled from piano music students’ population in Bangi, Selangor. In the survey-questionnaire, subjects answered 20 questions on demographic characteristics, music listening and preference, and understanding of emotional perception in music. In the listening activity, subjects listened to 20 untitled piano music excerpts and rated the emotion perceived for each excerpt, whether ‘happy’ or ‘sad’. Results from survey-questionnaire show that most percentage of subjects are 11 years old, in Grade 1, of 3 years of learning piano, prefer classical music, always listen to music, prefer both major and minor modes’ music, and find it easy to understand emotion in music, as well as major and minor modes. Results from listening activity show that 60 % of major mode music are perceived as ‘major-happy’, while 60 % too, of minor mode music are perceived as ‘minor-sad’. However, Chi-square test of independence statistical analysis indicates that there are no association and significant relationship between modes (major and minor) and ‘happy’, as well as ‘sad’ perceptions (x2 (1, N = 20) = 0.80, p = 0.371), at the significance level of p ≤ 0.05. Contrastingly, there are association and significant relationship between tempo (fast and slow), and ‘happy’, as well as ‘sad’ perceptions (x2 (1, N = 20) = 9.899, p = 0.005). Therefore, it is concluded that tempo plays an important role in effects of major and minor mode to ‘happy’ and ‘sad’ emotional perceptions in piano music among subjects aged 9 to 17 in this study.

Keywords: effects, emotional perceptions, major and minor modes, piano music

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Authors: A. S. Issa, S. K. Q. AL-Omari

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In this paper, we investigate certain spaces of generalized functions for the Fourier and Fourier type integral transforms. We discuss convolution theorems and establish certain spaces of distributions for the considered integrals. The new Fourier type integral is well-defined, linear, one-to-one and continuous with respect to certain types of convergences. Many properties and an inverse problem are also discussed in some details.

Keywords: Boehmian, Fourier integral, Fourier type integral, generalized quotient

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Sahar El-Achkar, Mizan Ahmad

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Poor adaptation of developmental milestones over the lifespan can significantly impact emotional experiences and Satisfaction with Life (SWL) post-retirement. Thus, it is important to understand how adaptive behaviour over the life course can predict emotional experiences. Broadly emotional experiences are either Positive Affect (PA) or Negative Affect (NA). This study sought to explore the impact of successful adaptation of developmental milestones throughout one’s life on emotional experiences and satisfaction with life following retirement. A cross-sectional self-report survey was completed by 132 Australian retirees between the ages 55 and 70 years. Three hierarchical regression models were fitted, controlling for age and gender, to predict PA, NA, and SWL. The full model predicting PA was statistically significant overall, F (8, 121) = 17.97, p < .001, account for 57% of the variability in PA. Industry/Inferiority were significantly predictive of PA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting SWL, F (8, 121) = 11.05, p < .001, accounting for 45% of the variability in SWL. Trust/Mistrust and Ego Integrity/Despair were significantly predictive of SWL. A sense of industry post-retirement is important in generating PA. These results highlight that individuals presenting with adaptation and identity issues are likely to present with adjustment challenges and unpleasant emotional experiences post-retirement. This supports the importance of identifying and understanding the benefits of successful adaptation and development throughout the lifespan and its significance for the self-concept. Most importantly, the quality of lives of many may be improved, and the future risk of continued poor emotional experiences and SWL post-retirement may be mitigated. Specifically, the clinical implications of these findings are that they support the promotion of successful adaption over the life course and healthy ageing.

Keywords: adaptation, development, negative affect, positive affect, retirement, satisfaction with life

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Authors: Abimbola Akintounde

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Supporting the social and emotional needs of young adolescents has become an emergent concern for schools around the world. Yet educators remain in a dilemma regarding the optimum approach for integrating social and emotional learning (SEL) into their content area instruction. The purpose of this study was to explore the perception of secondary students regarding their schoolwide SEL interventions. Twenty-four International Baccalaureate students in a final year mathematics course at an American Public Secondary School near Washington D. C. were randomly selected for participation in this study via an online electronic survey. The participants in this study used Likert-scale items to rate the effectiveness of the socio-emotional and character development programs being implemented at their schools. Respondents also ranked their preferred mode of delivery of social and emotional support programs. About 71% of the teenagers surveyed preferred SEL support rendered via interactive team-building activities and games, 42% of the high school students in the study ranked focus group discussions as their preferred format for SEL interventions, while only 13% of the respondents in the study regarded lectures and presentations as their preferred mode of SEL delivery. About one-fourth of the study participants agreed that explicit instruction was critical to enhancing students’ wellness, 79% agreed that SEL programs should foster less teacher talk, while 88% of the students indicated that student engagement was critical to their mental health. Eighty percent of the teenagers surveyed decried that the focus of their school-wide social and emotional programs was poorly prioritized. About two-thirds of the students agreed that social justice and equity issues should be embedded in their schools’ advisory programs. More than half of the respondents agitated for strategies for managing stress and their school workload. About 54% of the respondents also clamored for SEL programs that reinforce emotion regulation and coping strategies for anxiety. Based on the findings of this study, recommendations were proffered for best practices in the design and implementation of effective learner-friendly social and emotional development interventions.

Keywords: SEL, math anxiety, student support, emotion regulation, social awareness, self awareness, self management, relationship building

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Authors: Roshanak Farjad, Amirhossein Hosseini

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Fecal incontinence (FI) is a stressful condition for children and their parents that may affect the patient’s psychological well-being. Evaluating the patients’ psychological status may help physicians manage the disease effectively. This study aimed to assess the emotional and behavioral disturbances in children with FI who were referred to the pediatric gastroenterology clinic in Mofid Children’s Hospital from April 2021 to 2022. This cross-sectional study included children (over four years old) with chronic constipation and fecal incontinence. The diagnosis of chronic constipation and FI were made according to Rome-IV criteria. The Child Behavior Checklist (CBCL) evaluated patients’ emotional, behavioral, and social problems. One hundred one patients with a mean age of 7.96 years were enrolled in the study; 67.32% were males. According to CBCL, 12% (12 patients) indicated emotional and behavioral problems, with CBCL scores in the clinical or at-risk range. We detected anxious/depressed problems in five (4.95%), withdrawn/depressed problems in eight (7.92%), somatic complaints in seven (6.93%), social problems in eight (7.92%), thought problems in nine (8.91%), attention problems in seven (6.93%), rule-breaking behavior in two (1.98%), and aggressive behavior in nine (8.91%) patients. The risk of internalizing and externalizing disorders was reported in four (3.96%) and five (4.95%) patients. Also, eight (7.92%) and seven (6.93%) patients had clinical symptoms of internalizing and externalizing disorders, respectively. There was no significant relationship between patients’ age and gender with the CBCL scores in any subscales. However, there was a significant difference in the total score among the age groups (P = 0.04). The relatively high prevalence of emotional, behavioral, and social problems in our study corroborates the importance of psychological screening of children with FI during the treatment process.

Keywords: chronic constipation, child behavior checklist (CBCL), fecal incontinence, rome-IV criteria

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Authors: Vithya Veeramani, Karunanidhi Subbaiah

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Emotional problems were found to be the predominant cause of suicide and second leading cause of death among adolescents in India. Emotional problems seem to be the underlying cause for various other severe psycho-social problems experienced in adolescence and also in later years of life. The Corporation schools in Chennai city are named as Chennai High School or Chennai Higher Secondary School run by the Corporation of Chennai. These schools fulfill the educational needs of students who hail from lower socio-economic status living in slums of the Chennai city. Adolescent students of Chennai schools tend to lack basic needs like food, clothes, shelter, etc. Some of the other significant problems faced by them are broken family, lack of parental support, frequent quarrel between parents, alcoholic parents, drug abuse and substance abuse among parents and neighbors, extended family, illiterate parents, deprivation of love and care, and lack of sense of belongingness. This prevailing condition may affect them emotionally and could lead to maladaptive behaviour, aggressiveness, poor interpersonal relationship with others, school refusal behaviour, school drop-out, suicide, etc. Therefore, it is very important to investigate the emotional problems faced by the adolescent students studying in Chennai schools, Chennai. A cross-sectional survey design was used to find the prevalence of emotional problems among adolescent students. Cluster sampling technique was used to select the schools for the present study considering the school as a cluster. In total, there are 15 zones, under the control of Chennai Corporation, of which only 7 zones have Corporation Schools in Chennai city, comprising of 32 Chennai Higher Secondary Schools and 38 Chennai High Schools. Out of these 70 schools, 29 schools comprising of 17 high schools and 12 higher secondary schools were selected randomly using lottery method. A sample of 2594 adolescent students from 9th standard and 11th standard was chosen for the study. Percentage analysis was done to find out the prevalence rate of emotional problems among adolescents students studying in Chennai Schools. Results of the study revealed that, out of 2594 students surveyed, 21.04% adolescent students were found to have academic problems (n = 546), 15.99% adolescent students had social problems (n = 415), behaviour problems was found to be prevalent among 12.87% adolescent students (n = 334), depression was prevalent among 15.88% adolescent students (n = 412) and anxiety was prevalent among 14.42% adolescent students (n = 374). Prevalence of emotional problems among male and female revealed that academic problems were more prevalent compared to other problems. Behaviour problems were least prevalent among boys and anxiety was least prevalent among girls than other problems. The overall prevalence rate of emotional problems was found to be on an increasing trend among adolescent students of low socio-economic status in Chennai city. The findings indicated the need for intervention to prevent and rehabilitate these adolescent students.

Keywords: adolescents, corporation schools, emotional problems, prevalence

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Authors: Vadivel Ayyasamy

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The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation

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Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech

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Authors: David Martinez-Pernia, Alvaro Rivera-Rei, Alejandro Troncoso, Gonzalo Forno, Andrea Slachevsky, David Huepe, Victoria Silva-Mack, Jorge Calderon, Mayte Vergara, Valentina Carrera

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Background: Recent theories in the field of emotions have taken the relevance of motor control beyond a system related to personal autonomy (walking, running, grooming), and integrate it into the emotional dimension. However, to our best knowledge, there are no studies that specifically investigate how emotional stimuli related to motor control modify emotional states in terms of postural control and phenomenological experience. Objective: The main aim of this work is to investigate the emotions produced by stimuli of bodily imbalance (neutral, pleasant and unpleasant) in the postural control and the phenomenological experience of young, healthy adults. Methodology: 46 healthy young people are shown emotional videos (neutral, pleasant, motor unpleasant, and non-motor unpleasant) related to the body imbalance. During the period of stimulation of each of the videos (60 seconds) the participant is standing on a force platform to collect temporal and spatial data of postural control. In addition, the electrophysiological activity of the heart and electrodermal activity is recorded. In relation to the two unpleasant conditions (motor versus non-motor), a phenomenological interview is carried out to collect the subjective experience of emotion and body perception. Results: Pleasant and unpleasant emotional videos have significant changes with respect to the neutral condition in terms of greater area, higher mean velocity, and greater mean frequency power on the anterior-posterior axis. The results obtained with respect to the electrodermal response was that the pleasurable and unpleasant conditions produced a significant increase in the phasic component with respect to the neutral condition. Regarding the electrophysiology of the heart, no significant change was found in any condition. Phenomenological experiences in the two unpleasant conditions differ in body perception and the emotional meaning of the experience. Conclusion: Emotional stimuli related to bodily imbalance produce changes in postural control, electrodermal activity, and phenomenological experience. This experimental setting could be relevant to be implemented in people with motor disorders (Parkinson, Stroke, TBI) to know how emotions affect motor control.

Keywords: body imbalance stimuli, emotion, phenomenological experience, postural control

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Authors: László Schmidt

Abstract:

In the context of artificial intelligence, we need to pay primary and particular attention to ethical principles not only in the design process but also during the application process. According to the European Commission's Ethical Guidelines, AI must have three main characteristics: it must be legal, ethical and stabil. We must never lose sight of the ethical principles because we risk that this new technology will not help democratic decision-making under the rule of law, but will, on the contrary, destroy it. The rapid spread and use of artificial intelligence poses an enormous challenge to both lawmaking and law enforcement. On legislation because AI permeates many areas of our daily lives that the legislator must regulate. We can see how challenging it is to regulate e.g., selfdriving cars/taxis/vans etc. Not to mention, more recently, cryptocurrencies and Chat GPT, the use of which also requires legislative intervention, from copyright to scientific use and even law of succession. Artificial intelligence also poses an extraordinary challenge to law enforcement. In criminal cases, police and prosecutors can make great use of AI in investigations, e.g. in forensics, DNA samples, reconstruction, identification, etc. But it can also be of great help in the detection of crimes committed in cyberspace. In criminal or civil court proceedings, AI can also play a major role in the evaluation of evidence and proof. For example, a photo or video or audio recording could be immediately revealed as genuine or fake. Likewise, the authenticity or falsification of a document could be determined much more quickly and cheaply than with current procedure (expert witnesses). Neither the current Hungarian Civil Procedure Act nor the Criminal Procedure Act allows the use of artificial intelligence in the evidentiary process. However, this should be changed. To use this technology in court proceedings would be very useful. The procedures would be faster, simpler, and therefore cheaper. Artificial intelligence could also replace much of the work of expert witnesses. Its introduction into judicial procedures would certainly be justified, but with due respect for human rights, the right to a fair trial and other democratic and rule of law guarantees.

Keywords: artificial intelligence, judiciary, Hungarian, court practice

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Authors: Latika Choudhary

Abstract:

“The potential benefits of Artificial Intelligence are huge, So are the dangers.” - Dave Water. Artificial intelligence is one of the facet of Information technology domain which despite several attempts does not have a clear definition or ambit. However it can be understood as technology to solve problems via automated decisions and predictions. Artificial intelligence is essentially an algorithm based technology which analyses the large amounts of data and then solves problems by detecting useful patterns. Owing to its automated feature it will not be wrong to say that humans & AI have more utility than humans alone or computers alone.1 For many decades AI experienced enthusiasm as well as setbacks, yet it has today become part and parcel of our everyday life, making it convenient or at times problematic. AI and related technology encompass Intellectual Property in multiple ways, the most important being AI technology for management of Intellectual Property, IP for protecting AI and IP as a hindrance to the transparency of AI systems. Thus the relationship between the two is of reciprocity as IP influences AI and vice versa. While AI is a recent concept, the IP laws for protection or even dealing with its challenges are relatively older, raising the need for revision to keep up with the pace of technological advancements. This paper will analyze the relationship between AI and IP to determine how beneficial or conflictual the same is, address how the old concepts of IP are being stretched to its maximum limits so as to accommodate the unwanted consequences of the Artificial Intelligence and propose ways to mitigate the situation so that AI becomes the friend it is and not turn into a potential foe it appears to be.

Keywords: intellectual property rights, information technology, algorithm, artificial intelligence

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Authors: Anamika Devi

Abstract:

Based on Vygotsky’s cultural, historical theory and Hedegaard’s concept of transition, this study aims to investigate to propose strategies to maintain digital wellbeing of children and parents during and post COVID pandemic. Due COVID 19 pandemic, children and families have been facing new challenges and sudden changes in their everyday life. While children are juggling to adjust themselves in new circumstance of onsite and online learning settings, parents are juggling with their work-life balance. A number of papers have identified that the COVID-19 pandemic has affected the lives of many families around the world in many ways, for example, the stress level of many parents increased, families faced financial difficulties, uncertainty impacted on long term effects on their emotional and social wellbeing. After searching and doing an intensive literature review from 2020 and 2021, this study has found some scholarly articles provided solution or strategies of reducing stress levels of parents and children in this unprecedented time. However, most of them are not underpinned by proper theoretical lens to ensure they validity and success. Therefore, this study has proposed strategies that are underpinned by theoretical lens to ensure their impact on children’s and parents' emotional wellbeing during and post COVID-19 era. The strategies will highlight on activities for positive coping strategies to the best use of family values and digital technologies.

Keywords: onsite and online learning, strategies, emotional wellbeing, tips, and strategies, COVID19

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Authors: Darius Jakimavicius

Abstract:

Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

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Authors: Myoungsoon You, Heejung Son

Abstract:

During a pandemic, hospital workers should protect not only their vulnerable patients but also themselves from the consequences of rapidly spreading infection. However, the evidence on the psychological impact of an outbreak on hospital workers is limited. In this study, we aim to assess hospital workers’ psychological well-being and function at the workplace after an outbreak, by focusing on ‘psychological resilience’. Specifically, the effects of risk appraisal, emotional experience, and coping ability on resilience indicated by the likelihood of post-traumatic syndrome disorder and willingness to work were investigated. Such role and position of each factor were analyzed using a path model, and the result was compared between the healthcare worker and non-healthcare worker groups. In the investigation, 280 hospital workers who experienced the 2015 Middle East Respiratory Syndrome outbreak in South Korea have participated. The result presented, in both groups, the role of the appraisal of risk and coping ability appeared consistent with a previous research, that was, the former interrupted resilience while the latter facilitated it. In addition, the role of emotional experience was highlighted as, in both groups, emotional disruption not only directly associated with low resilience but mediated the effect of perceived risk on resilience. The differences between the groups were also identified, which were, the role of emotional experience and coping ability was more prominent in the non-HCW group in explaining resilience. From the results, implications on how to support hospital personnel during an outbreak in a way to facilitate their resilience after the outbreak were drawn.

Keywords: hospital workers, emotions, infectious disease outbreak, psychological resilience

Procedia PDF Downloads 220