Search results for: emotional intelligence

Authors: Qinglu Wu, Anna Wai-Man Choi, Peilian Chi

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Gratitude is one individual strength that not only facilitates the mental health, but also fosters the relationship satisfaction in the romantic relationship. In terms of moral effect theory and stress-and-coping theory of forgiveness, present study not only investigated the association between grateful disposition and relationship satisfaction, but also explored the mechanism by comprehensively examining the potential mediating roles of three profiles of forgiveness (trait forgivingness, decisional forgiveness, emotional forgiveness), another character strength that highly related to the gratitude and relationship satisfaction. Structural equation modeling was used to conduct the multiple mediator model with a sample of 103 Chinese college students in dating relationship (39 male students and 64 female students, Mage = 19.41, SD = 1.34). Findings displayed that both gratitude and relationship satisfaction positively correlated with decisional forgiveness and emotional forgiveness. Emotional forgiveness was the only mediator, and it completely mediated the relationship between gratitude and relationship satisfaction. Gratitude was helpful in enhancing individuals’ perception of satisfaction in romantic relationship through replacing negative emotions toward partners with positive ones after transgression in daily life. It highlighted the function of emotional forgiveness in personal healing and peaceful state, which is important to the perception of satisfaction in relationship. Findings not only suggested gratitude could provide a stability for forgiveness, but also the mechanism of prosocial responses or positive psychological processes on relationship satisfaction. The significant roles of gratitude and emotional forgiveness could be emphasized in the intervention working on the romantic relationship development or reconciliation.

Keywords: decisional forgiveness, emotional forgiveness, gratitude, relationship satisfaction, trait forgivingness

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Authors: Abdul Razak Rahmat, Azizah Ahmad, Azman Ta’aa

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The deployment of Business Intelligence (BI) for organization at the beginning phase is very crucial. Results from the previous studies found that more than half of the BI project fails to meet the objective even though a lot money are spent. Based on that problem, the readiness level of BI for the organization is important to identify in order to reduce the risk before the actual BI project is implemented. In this paper, rigorous literature review on the aspect success factors such as Critical Success Factors (CSFs), Readiness Factors (RFs), Success Factors (SFs), are discussed by different authors. The paper also adopted a few models from previous study as a guide for the assessment of BI readiness. The expected finding from this research is the Business Intelligent Readiness Model (BiRM) as a guild before implement the BI system.

Keywords: business intelligence readiness model, business intelligence for higher learning, BI readiness factors, BI critical success factors(CSF)

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Authors: Kristine Dzagnidze

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The paper equally centers on both the structural and cognitive linguistics in light of phraseologism and its emotional implication. Accordingly, the methods elaborated within the framework of both the systematic-structural and linguo-cognitive theories are identically relevant to the research of mine. In other words, through studying the negotiation process, our attention is drawn upon defining negotiations’ peculiarities, emotion, style and specifics of cognition, motives, aims, contextual characterizations and the quality of cultural context and integration. Besides, the totality of the concepts and methods is also referred to, which is connected with the stage of the development of the emotional linguistic thinking. The latter contextually correlates with the dominance of anthropocentric–communicative paradigm. The synthesis of structuralistic and cognitive perspectives has turned out to be relevant to our research, carried out in the form of intellectual action, that is, on the one hand, the adequacy of the research purpose to the expected results. On the other hand, the validity of methodology for formulating the objective conclusions needed for emotional connotation beyond phraseologism. The mechanism mentioned does not make a claim about a discovery of a new truth. Though, it gives the possibility of a novel interpretation of the content in existence.

Keywords: cognitivism, communication, implication, negotiation

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Authors: Maryam Hazrati, Tengku Aizan Hamid, Rahimah Ibrahim, Siti Aishah Hassan, Farkhondeh Sharif, Zahra Bagheri

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Background: Emotional abuse is the most common type of spousal abuse. In a long-term marriage which lasts several decades, the couple will be faced with greater vulnerability due to illness, disability, and dependence. Emotional abuse can have a devastating impact on victims, leading to low self-esteem, depression, anxiety, and post-traumatic stress disorder. Research Aim: The aim of this study was to investigate the effects of an emotional-focused psychoeducational intervention (EFPEI) on emotional abuse and marital satisfaction among older adults couples and also to examine the dyadic effects of each partner’s emotional abuse behaviors (EAB) on his/her marital satisfaction (MS) in Shiraz-Iran. Methodology: The study was a randomized controlled trial (RCT). A total of 57 eligible couples were randomly assigned to either the experimental group or the control group. The experimental group received EFPEI, which consisted of 12 sessions, each lasting 90 minutes. The control group did not receive any intervention. Data were collected using demographic questionnaire, Multidimensional Measure of Emotional Abuse (MMEAQ), and Marital Satisfaction Questionnaire for Older People (MSQFOP). The data was analyzed using a variety of statistical methods, including repeated measures ANOVA, path analysis, and correlational analyses. Findings: The results of the study showed that the EFPEI was effective in reducing emotional abuse and increasing marital satisfaction among older adults couples. Specifically, the mean scores for emotional abuse and marital satisfaction were significantly lower in the experimental group than in the control group at the end of the intervention. These effects were maintained at a 3-month follow-up. Moreover, the dyadic analysis revealed that husbands’ EAB had no significant effects on his own marital satisfaction but a significant negative partner effect, while wives’ EAB had significant negative actor and partner effects. Conclusion: The findings of this study provide support for the use of EFPEI as an effective intervention for decreasing emotional abuse and improving marital dissatisfaction among older adults. EFPEI is a short-term, evidence-based intervention that can be delivered by trained professionals. The intervention focuses on helping couples to improve their communication skills, resolve conflict, and build a stronger emotional connection.

Keywords: spouse abuse, emotion, aged, satisfaction, dyadic effect

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Authors: Ktiri Fouad

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Objectives: The present study examined how the polyvalent nursing students of the Higher Institute of Nursing Professions and Health Techniques (ISPITS-Rabat-Morocco) conceived the term "feeling stressed.” We checked whether they were referring to a specific type of sensation (emotional, mental, physical) or both or all of them when they said they were stressed at the time they felt it. Materials and methods: A quantitative cross-sectional study was conducted among students of the three years of polyvalent nursing courses. Using a 7-Likert scale, the students were asked to assess their states of stress and the emotional, mental and physical sensations they were experiencing before and after carrying out a mental arithmetic task. An ordinal logistic regression method was used to investigate the association between the states of stress and the 3 types of sensations. Results: 222 polyvalent nursing students out of 307 were included in the experience. Their increased perceived states of stress after carrying out the mental task were found to be significantly associated with emotional distress and mental fatigue and not with physical tiredness. The mental sensation (mental fatigue) was found to have more effects in predicting the likelihood of feeling stressed. In addition, the lower the intensity of emotional or mental sensation, the more likely the students were to experience stress, given that one of both sensations is held constant, whatever the intensity of the physical sensation. We conclude that the polyvalent nursing students refer to mental fatigue and emotional distress and not to physical tiredness when they say they felt stressed, the mental fatigue having more effects. The implications of the study are discussed.

Keywords: feeling stressed”, emotional sensation, mental sensation, physical sensation

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Authors: Issa M. Shehabat, Huda F. Y. Nimri

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This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.

Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector

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Authors: Mohamed Sharof Mostafa, Atefeh Ahmadi

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Most of traditional single modality psychotherapy and counselling approaches to clients’ problems are based on the application of one therapy in all sessions. Modern developments in these sciences focus on eclectic and integrative interventions to consider all dimensions of an issue and all characteristics of the clients. This paper presents and overview eclectic therapy and its pros and cons. In addition, multiple intelligence theory and its application in eclectic therapy approaches are mentioned.

Keywords: eclectic therapy, client, multiple intelligence theory, dimensions

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Mariana Goncalves, Marlene Matos

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Despite the scientific attention that it has received, the research on the victimization of women continues to neglect some factors that may enhance the risk of women to victimization. This study sought to identify the prevalence and the lifelong trajectories of multiply victimized women (childhood, adolescence, and adulthood), the co-occurrence of different types of victimization, the contexts of occurrence and emotional adjustment and resilience. We used a convenience sample of 120 women multiply victimized, including 35 Portuguese natives and 85 immigrant women (e.g., Brazilian, African) who were recruited from support institutions and shelters. The results documented the similarities and differences concerning victimization between these groups and the intersectional factors that may elucidate vulnerability to victimization. There was a high co-occurrence of types of victimization, particularly in adulthood. The victimization reported occurred frequently in different contexts: familiar, workplace and helping institutions. A higher number of victimization experiences was related with more emotional symptomatology, less familiar cohesion and less social resources. The implications of the results are discussed.

Keywords: multiple victimization, lifetime, natives, immigrants, prevalence, emotional adjustment

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Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Elyas Akbari, Jafar Hasani, Newsha Dehestani, Mohammad Khaleghi, Alireza Moradi

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The aim of the present study was to assess the effect of emotional experience induction in the mirror neurons systems (MNS) activity with regard to the spectrum of depressive symptoms. For this purpose, at first stage, 449 students of Kharazmi University of Tehran were selected randomly and completed the second version of the Beck Depression Inventory (BDI-II). Then, 36 students with standard Z-score equal or above +1.5 and equal or equal or below -1.5 were selected to construct two groups of high and low spectrum of depressive symptoms. In the next stage, the basic activity of MNS was recorded (mu wave) before presenting the positive and negative emotional video clips by Electroencephalography (EEG) technique. The findings related to emotion induction (neutral, negative and positive emotion) demonstrated that the activity of recorded mirror neuron areas had a significant difference between the depressive and non-depressive groups. These findings suggest that probably processing of negative emotions in depressive individuals is due to the idea that the mirror neurons in motor cortex matched up the activity of cognitive regions with the person’s schema. Considering the results of the present study, it could be said that the MNS provides a substrate where emotional disorders can be studied and evaluated.

Keywords: emotional experiences, mirror neurons, depressive symptoms, negative and positive emotion

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Authors: M. Naidoo

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The concept of moral personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central to the underpinnings of personhood - rather than Western individualism. Personhood in the African context is not an inherent property that a human is born with; rather, it is an ontological journey that one goes on in his or her life with the hopes of attaining personhood. Given the decolonization, projects happening in Africa, and the law-making that is happening in this space within South Africa, it is of paramount importance to consider these views.

Keywords: artificial intelligence, bioethics, law, legal personality

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Authors: Xiao Hu

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Children’s social and emotional development is critical for developing their future relationships and behaviors, and poor social skills may result in serious emotional externalizations such as anxiety, distress and aggression. Recent research has emphasized the role of family socio-economic status on children’s emotional development, and this study contributes to this academic discussion by reviewing how socio-economic status affects children at three critical development stages: infancy (0-3months), pre-school (4 months-5 years) and school aged (6-10 years). Results show a consensus in the research literature on a positive relationship between family socio-economic status and children’s emotional development. Socialization, a crucial development milestone, is highly affected by a family’s socio-economic status, as families with higher incomes have access to improved social environments, healthier parenting styles and greater access to social capital and peer support. In contrast, families with lower income and SES (socio-economic status) have lower access to these benefits and are frequently ignored within social environments. This review concludes with a critical discussion on how family income affects children’s social environment, highlighting the important role that “permanent” income plays in children’s development. Consequently, the review suggests that future governments should provide temporary economic support for lower-income families, allowing children to be raised in a healthy social environment with limited economic fluctuation.

Keywords: family socio-economic status, parenting style, children’s emotional development, family permanent income

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Authors: Iman Abu-Rub

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This research paper examines if Artificial Intelligence is, in fact, racist or not. Different studies from all around the world, and covering different communities were analyzed to further understand AI’s true implications over different communities. The black community, Asian community, and Muslim community were all analyzed and discussed in the paper to figure out if AI is biased or unbiased towards these specific communities. It was found that the biggest problem AI faces is the biased distribution of data collection. Most of the data inserted and coded into AI are of a white male, which significantly affects the other communities in terms of reliable cultural, political, or medical research. Nonetheless, there are various research was done that help increase awareness of this issue, but also solve it completely if done correctly. Governments and big corporations are able to implement different strategies into their AI inventions to avoid any racist results, which could cause hatred culturally but also unreliable data, medically, for example. Overall, Artificial Intelligence is not racist per se, but the data implementation and current racist culture online manipulate AI to become racist.

Keywords: social media, artificial intelligence, racism, discrimination

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Authors: Jill Steel

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Introduction: Animal-assisted learning (AAL) interventions are increasing exponentially, yet a paucity of quality research in the field exists. The aim of this study was to evaluate how the promotion of emotional wellbeing, through AAL, in this case, a dog, may support children’s engagement with reading in a Primary 1 classroom. Research indicates that dogs can provide emotional support to children; by forming a trusting attachment with a non-critical ‘friend’ who confers unconditional positive regard on the child, confidence may be boosted and anxiety reduced. By promoting emotional wellbeing through interactions with the dog, it is hoped that children begin to associate reading with feelings of wellbeing, which then results in increased engagement with reading. Methodology: A review of the literature was conducted. The relationship between emotional wellbeing and learning was explored, followed by an examination of the literature relating to Animal-Assisted Therapy and AAL. Scottish educational policy and legislation were analysed to establish the extent to which AAL might be suitable for the Scottish pedagogical context. An empirical study was conducted in a mainstream Primary 1 classroom over a four-week period. An inclusive approach was adopted whereby all children that wanted to interact with the dog were given the opportunity to do so, and all 25 children subsequently chose to participate. Children were not withdrawn from the classroom. Primary methods included interviews, observations, and questionnaires. Three focus children were selected for closer study. Main Results: Results were remarkably close to previous research and literature. Children’s emotional wellbeing was boosted, and engagement in reading improved. Principal Conclusions and Implications for Field: It was concluded that AAL could support emotional wellbeing and, in turn, promote children’s engagement with reading. The main limitation of the study was its short-term nature, and a longer randomised controlled trial with a larger sample, currently being undertaken by the author, would provide a fuller answer to the research question. Barriers to AAL include health and safety concerns and steps to ensure the welfare of the dog.

Keywords: animal-assisted learning, emotional wellbeing, reading, reading to dogs

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Authors: Prakash Singh

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Employees who are satisfied at their place of work rate their leaders’ intrapersonal competencies as being high. They also believe that a leader’s intrapersonal competencies influence their sense of job satisfaction. Employees who indicate that they are unhappy at their place of work rate their leaders’ intrapersonal competencies as being low. They also believe that a leader’s intrapersonal intelligence influence their feeling of job satisfaction. The leader’s appropriate intrapersonal competencies are crucial to the creation of a motivated and satisfied employee team. In this study, the quantitative research method was used to determine the employees’ perceptions of their leaders’ intrapersonal competencies and their influence on their job satisfaction; the six competencies being self-awareness, self-confidence, self-expression, self-control, adaptability, and optimism. All the competencies of leaders identified in this quantitative study can therefore be described as intervening variables that influence an employee’s sense of job satisfaction. The number of responses that indicate that each of the intrapersonal competencies of a leader that will have an influence on an employee’s sense of job satisfaction, ranges from 93% (a leader’s sense of self-awareness) to 99% (a leader’s ability to be adaptable). As the responses are significantly similar, it can be stated that the respondents indicate that all the intrapersonal competencies of a leader can influence an employee’s sense of job satisfaction. The findings of this study strongly suggest that in order to be satisfied at work, employees prefer to be led by leaders who are confident in their leadership roles; who send out clear, unambiguous messages; who maintain self-control; who are adaptable and flexible;, who face the future with optimism and who support the establishment of a collegial working environment. Evidently, the findings corroborate the hypothesis that employees believe that the intrapersonal competencies of leaders have a positive influence on the employees’ sense of job satisfaction. This study’s findings, therefore, confirm that the key to the leaders’ self-knowledge is access to their own feelings and the ability to discriminate among them and draw upon them to guide behaviour in their organisations. This exploratory study makes a contribution to the emerging research being accomplished on leaders’ intrapersonal intelligence with more research still needing to be attempted to determine to what extent these competencies of leaders can reshape the organizational climate and culture.

Keywords: emotional intelligence, employees’ job satisfaction, leaders’ intrapersonal competencies, leaders’ self-knowledge

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Authors: Supriyadi, Andi Intan Purnamasari, Aminuddin Kasim, Sulbadana, Mohammad Reza

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The development of the Industrial Revolution Era 4.0 brought a significant influence in the administration of countries in all parts of the world, including Indonesia, not only in the administration and economic sectors but the ways and methods of forming laws should also be adjusted. Until now, the process of making laws carried out by the Parliament with the Government still uses the classical method. The law-making process still uses manual methods, such as typing harmonization of regulations, so that it is not uncommon for errors to occur, such as writing errors, copying articles and so on, things that require a high level of accuracy and relying on inventory and harmonization carried out manually by humans. However, this method often creates several problems due to errors and inaccuracies on the part of officers who harmonize laws after discussion and approval; this has a very serious impact on the system of law formation in Indonesia. The use of artificial intelligence in the process of forming laws seems to be justified and becomes the answer in order to minimize the disharmony of various laws and regulations. This research is normative research using the Legislative Approach and the Conceptual Approach. This research focuses on the question of how to use Artificial Intelligence for Harmonization in the Lawmaking Process.

Keywords: artificial intelligence, harmonization, laws, intelligence

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Authors: Polycarp A. Igbojekwe, Chizoba Amajuoyi, Peterson Nwokorie

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The main purpose of this study was to carry out a survey of customer’s aggression towards hotel workers and make contributions on the prevalence and rationale behind customer’s aggression. Data for the study were gathered with a four-point Likert type rating scale. Samples were drawn from frontline hotel employees, managers and customers of twelve (12) hotels selected from three zones of Imo State. Data analyses were conducted using simple percentage, descriptive statistics; and Z-test statistical technique was used to test hypotheses. Among other factors, service failure and verbal abuse by service providers and poor quality product compared to price were identified by customers as the three major factors that can lead to customer aggression. Frontline employees indentified verbal abuse as the most common mode of aggression and that customer aggression causes emotional disturbance in them. The study also revealed that customer aggression is more prevalent in the 1&2 star hotels than it is in 3-5 star hotels. Most of the hotels have not institutionalized systematic approaches needed to effectively face the challenges of customer aggression, thus, customer aggression has become a common feature in the industry. Frontline jobs demand high emotional input. Therefore, we recommend that frontline employees should be given emotional support by their managers and also trained on how to cope with emotional disturbance.

Keywords: customer aggression, emotional disturbance, employee well-being, service failure, verbal abuse

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Authors: Rosa S. Wong, Keith T.S. Tung, H.W. Tsang, Frederick K. Ho, Patrick Ip

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Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention and hyperactive-impulsive behavior. Evidence shows that ADHD and mood problems such as depression and anxiety often co-occur and yet not everyone with ADHD reported elevated emotional problems. Given that cholesterol is essential for healthy brain development including the regions governing emotion regulation, reports found lower cholesterol levels in patients with major depressive disorder and those with suicide attempt behavior compared to healthy subjects. This study explored whether ADHD adolescents experienced more emotional problems and whether emotional problems correlated with cholesterol levels in these adolescents. This study used a portion of data from the longitudinal cohort study which was designed to investigate the long-term impact of family socioeconomic status on child development. In 2018/19, parents of 300 adolescents (average age: 12.57+/-0.49 years) were asked to rate their children’s emotional problems and report whether their children had doctor-diagnosed psychiatric diseases. We further collected blood samples from 263 children to study their lipid profile (total cholesterol, high-density lipoprotein (HDL)-cholesterol, and low-density lipoprotein (LDL)-cholesterol). Regression analyses were performed to test the relationships between variables of interest. Among 300 children, 27 (9%) had ADHD diagnosis. Analysis based on overall sample found no association between ADHD and emotional problems, but when investigating the relationship by gender, there was a significant interaction effect of ADHD and gender on emotional problems (p=0.037), with ADHD males displaying more emotional problems than ADHD females. Further analyses based on 263 children (21 with ADHD diagnosis) found significant interaction effect of ADHD and gender on total cholesterol (p=0.038) and low LDL-cholesterol levels (p=0.013) after adjusting for the child’s physical disease history. Specifically, ADHD males had significantly lower total cholesterol and low lipoprotein-cholesterol levels than ADHD females. In ADHD males, more emotional problems were associated with lower LDL-cholesterol levels (B = -4.26, 95%CI (-7.46, -1.07), p=0.013). We found preliminary support for the association between more emotional problems and lower cholesterol levels in ADHD children, especially among males. Although larger prospective studies are needed to substantiate these claims, the evidence highlights the importance of healthy lifestyle to keep cholesterol levels in normal range which can have positive effects on physical and mental health.

Keywords: attention-deficit hyperactivity disorder, cholesterol, emotional problems, adolescents

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Authors: Halimat M. Ajose-Adeogun, Zaynab A. Bello

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Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

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Authors: Kapila Warnakulasuriya, Walimuni Janaka Mendis

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In this study, an artificial intelligence-based approach is developed to diagnose abnormal tissues in human or animal bodies by analyzing magnetic resonance signals. As opposed to the conventional method of generating an image from the magnetic resonance signals, which are then evaluated by a radiologist for the diagnosis of abnormalities, in the discussed approach, the magnetic resonance signals are analyzed by an artificial intelligence algorithm without having to generate or analyze an image. The AI-based program compares magnetic resonance signals with millions of possible magnetic resonance waveforms which can be generated from various types of normal tissues. Waveforms generated by abnormal tissues are then identified, and images of the abnormal tissues are generated with the possible location of them in the body for further diagnostic tests.

Keywords: magnetic resonance, artificial intelligence, magnetic waveform analysis, abnormal tissues

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Authors: Seung Yeon Son

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Workers (especially, competent personnel) have been recognized as a core contributor to overall organizational effectiveness. Hence, verifying the determinants of turnover intention is one of the most important research issues. This study tested the influence of perceived organizational support and abusive supervision on employee’s turnover intention. In addition, mediating roles of psychological contract and emotional exhaustion were examined. Data from 255 Korean employees supported all hypotheses Implications for research and directions for future research are discussed.

Keywords: abusive supervision, emotional exhaustion, perceived organizational support, psychological contract, turnover intention

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

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In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: Sahra Setorg

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The purpose of this study was to determine the effect of meta-cognitive therapy on meta-cognitive defects and emotional regulation in industrial substance dependence patients. This quasi-experimental research was conducted with post-test and two-month follow-up design with control and experimental groups. The statistical population consisted of all industrial Substance dependence patients refer to addictive withdrawal clinics in Esfahan city, in Iran in 2013. 45 patients were selected from three clinics through the convenience sampling method and were randomly divided into two experimental groups (15 crack dependences, 15 amphetamine dependences) and one control group (n=15). The meta-cognitive questionnaire (MCQ) and difficulties in emotional regulation questionnaire (DERS) were used as pre-test measures and the experimental groups (crack and amphetamine) received 8 MC therapy sessions in groups. The data were analyzed via multivariate covariance statistic method by spss-18. The results showed that MCT had a significant effect in improving the meta-cognitive defects in crack and amphetamine dependences. Also, this therapy can increase the emotional regulation in both groups (p<0/05).The effect of this therapy is confirmed in two months followup. According to these findings, met-cognitive is as an interface and important variable in prevention, control, and treatment of the new industrial substance dependences.

Keywords: meta-cognitive therapy, meta-cognitive defects, emotional regulation, substance dependence disorder

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Authors: Justyna Minkiewicz

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Artificial Intelligence (AI) applied in the arts may influence the development of AI knowledge in other sectors and then also impact mutual collaboration with the artistic environment. Hence this collaboration may also impact the development of art projects. The paper will reflect the qualitative research outcomes based on in-depth (IDI) interviews within the marketing sector in Poland and desk research. Art is a reflection of the spirit of our times. Moreover, now we are experiencing a significant acceleration in the development of technologies and their use in various sectors. The leading technologies that contribute to the development of the economy, including the creative sector, embrace technologies such as artificial intelligence, blockchain, extended reality, voice processing, and virtual beings. Artificial intelligence is one of the leading technologies developed for several decades, which is currently reaching a high level of interest and use in various sectors. However, the conducted research has shown that there is still low awareness of artificial intelligence and its wide application in various sectors. The study will show how artists use artificial intelligence in their art projects and how it can be translated into practice within the business. At the same time, the paper will raise awareness of the need for businesses to be inspired by the artistic environment. The research proved that there is still a need to popularize knowledge about this technology which is crucial for many sectors. Art projects are tools to develop knowledge and awareness of society and also various sectors. At the same time, artists may benefit from such collaboration. The paper will include selected aspects of mutual relations, areas of possible inspiration, and possible transfers of technological solutions. Those are AI applications in creative industries such as advertising and film, image recognition in art, and projects from different sectors.

Keywords: artificial intelligence, business, art, creative industry, technology

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Authors: Sandeep Reddy, Sonia Allan, Simon Coghlan, Paul Cooper

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Artificial Intelligence (AI) and its application in medicine has generated ample interest amongst policymakers and clinicians. Successes with AI in medical imaging interpretation and clinical decision support are paving the way for its incorporation into routine healthcare delivery. While there has been a focus on the development of ethical principles to guide its application in healthcare, challenges of this application go beyond what ethics principles can address thus requiring robust governance frameworks. Also, while ethical challenges of medical artificial intelligence are being discussed, the ethics of deploying AI in lower-income countries receive less attention than in other developed economies. This creates an imperative not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort.

Keywords: artificial intelligence, global health, governance, ethics

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Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

Abstract:

With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

Procedia PDF Downloads 452

Authors: Maria T. Mamba, Febe Marl G. Paat

Abstract:

The illustrious estimation that psychology majors, psychologists and allied psychology practitioners as expert behavior analysts, if not, “life enthusiasts” spurred two essentially linked endeavors. First, the reconsideration of the time-honored ingenuity and expectations from psychologists such as the ability to perceive ways to undertake a range of difficulties, the ability to apply psychology in order to self-regulate and to display personal integrity, and among others. Second, is to ascertain solid support to uphold aforesaid expectations. This study achieved its goals by having explored how two burgeoning constructs- RQ and EQ play parts in the lives of psychology people. Having involved the total population of psychology majors in Cagayan State University along with the use of Emotional Quotient Test and Resilience Assessment Questionnaire, the study provides a précis of how perceived “champions” of psychological well-being respond emotionally to different situations and deal effectively with and even thrive on the demands of frequently changing environmental circumstances. Significant findings about how the major variables correlated with the population’s demographic profile (e.g. age, sex, and year level) were also accounted. To realize a more academic concept with the present study, significant connections between RQ (self-assurance, personal vision, flexible and adaptable, organized, problem solver, interpersonal competence, socially connected, and active) and EQ (e.g. emotional maturity, emotional sensitivity, and emotional competency) dimensions were uncovered.

Keywords: emotional quotient, resilience quotient, psychology majors, exploring

Procedia PDF Downloads 451

Authors: Louis Placido F. Lachica

Abstract:

Freshman year in college, being a transition from high school to college, requires students to adjust by equipping themselves with competencies that will make them survive in college. This study conducted at in a state university in the Philippines aimed to determine the quality of school life and linguistic intelligence of 214 randomly selected college freshmen. Frequency counts and percentages were used to analyze quality of school life and linguistic intelligence. The chi-square test was utilized to determine significant relationship between quality of school life and linguistic intelligence and selected demographic variables. Results on quality of school life revealed that availability of religious books and paperbacks at home were significantly related to relationship with teachers. None of the selected demographic characteristics were significantly related to sense of achievement. Parents’ highest educational attainment was significantly related with opportunity at school. The availability of general references and song hits were significantly and highly significantly related to sense of identity which means that these promoted their sense of identity since their peers also preferred its availability. Type of high school graduated from was significantly related with students’ self-esteem. Graduates of public high schools have higher boosted self-esteem than those from private high schools. Both type of high school graduated from and reading materials available at home (religious books) had a highly significant relationship with linguistic intelligence. In addition, there was a significant relationship between time spent in reading per day and linguistic intelligence. There was a highly significant relationship between quality of school life in terms of relationship with teachers and sense of achievement with linguistic intelligence. Further, sense of identity and linguistic intelligence were significantly related.

Keywords: quality of school life, linguistic intelligence, college freshmen, state university

Procedia PDF Downloads 356

Authors: Tarek Aboueldahab, Hanan Farag

Abstract:

Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization

Procedia PDF Downloads 190