Search results for: emotional intelligence

Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

Abstract:

As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

Procedia PDF Downloads 144

Authors: Sheng-Fen Fan, Sung-Hui Tseng

Abstract:

Attention deficit hyperactivity deficit (ADHD) child display diverse sensory processing difficulty behaviors. There is less evidence to figure out how the association between executive function and sensory deficit. To determine whether sensory deficit influence the executive functions, we examined sensory processing by SPM and try to indicate hot/cold executive function (EF) by BRIEF2, respectively. We found that the hot executive function deficit might associate with auditory processing in a variety of settings, and vestibular input to maintain balance and upright posture; the cold EF deficit might opposite to the hot EF deficit, the vestibular sensory modulation difficulty association with emotion shifting and emotional regulation. These results suggest that sensory processing might be another consideration factor to influence the higher cognitive control or emotional regulation of EF. Overall, this study indicates the distinction between hot and cold EF impairments with different sensory modulation problem. Moreover, for clinician, it needs more cautious consideration to conduct intervention with ADHD.

Keywords: hot executive function, cold executive function, sensory processing, ADHD

Procedia PDF Downloads 281

Authors: Jurijs Salijevs, Katrina Bolocko

Abstract:

The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

Procedia PDF Downloads 99

Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

Abstract:

The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

Procedia PDF Downloads 89

Authors: Rosanna M. Rooney, Sharinaz Hassan, Maryanne McDevitt, Jacob D. Peckover, Robert T. Kane

Abstract:

Anxiety and depression are the most common mental health problems experienced by Australian children and adolescents. Research into youth mental health points to the importance of considering emotional competence, parental influence on the child’s emotional development, and the fact that cognitions are still developing in childhood when designing and implementing positive psychology interventions. Additionally, research into such interventions has suggested the inclusion of a coaching component aimed at supporting those implementing the intervention enhances the effects of the intervention itself. In light of these findings and given the burden of anxiety and depression in the longer term, it is necessary to enhance the Aussie Optimism Positive Thinking Skills program and evaluate its efficacy in terms of children’s mental health outcomes. It was expected that the enhancement of the emotional and cognitive aspects of the Aussie Optimism Positive Thinking Skills program, the addition of coaching, and the inclusion of a parent manual would lead to significant prevention effects in internalizing problems at post-test, 6- and 18-months after the completion of the intervention. 502 students (9-11 years old) were randomly assigned to the intervention group (n = 347) or control group (n = 155). At each time point (baseline, post-test, 6-month follow-up, and 18-month follow-up), students completed a battery of self-report measures. The ten intervention sessions making up the enhanced Aussie Optimism Positive Thinking Skills program were run weekly. At post-test and 6-month follow-up, the intervention group reported significantly lower depression than the control group, with no group differences at the 18-month follow-up. The intervention group reported significantly lower anxiety than the control group only at the 6-month follow-up, with no group differences in the post-test or at the 18-month follow-up. Results suggest that the enhanced Aussie Optimism Positive Thinking Skills program can reduce depressive and anxious symptoms in the short term and highlight the importance of universally implemented positive psychology interventions.

Keywords: positive psychology, emotional competence, internalizing symptoms, universal implementation

Procedia PDF Downloads 67

Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

Abstract:

This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

Procedia PDF Downloads 84

Authors: Javad Abdi, Azam Famil Khalili

Abstract:

Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

Procedia PDF Downloads 431

Authors: Sultan Ghaleb Aldaihani

Abstract:

- The environment in which educational leadership takes place is becoming increasingly complex due to factors like globalization and rapid technological change. - This is creating a "leadership gap" where the complexity of the environment outpaces the ability of leaders to effectively respond. - Educational leadership involves guiding teachers and the broader school system towards improved student learning and achievement. 2. Implications of Artificial Intelligence (AI) in Educational Leadership: - AI has great potential to enhance education, such as through intelligent tutoring systems and automating routine tasks to free up teachers. - AI can also have significant implications for educational leadership by providing better information and data-driven decision-making capabilities. - Computer-adaptive testing can provide detailed, individualized data on student learning that leaders can use for instructional decisions and accountability. 3. Enhancing Decision-Making Processes: - Statistical models and data mining techniques can help identify at-risk students earlier, allowing for targeted interventions. - Probability-based models can diagnose students likely to drop out, enabling proactive support. - These data-driven approaches can make resource allocation and decision-making more effective. 4. Improving Efficiency and Productivity: - AI systems can automate tasks and change processes to improve the efficiency of educational leadership and administration. - Integrating AI can free up leaders to focus more on their role's human, interactive elements.

Keywords: Education, Leadership, Technology, Artificial Intelligence

Procedia PDF Downloads 33

Authors: Tseng-Lung Huang

Abstract:

Sensory breadth experiences, such as visualization, a sense of self-location, and haptic experiences, are critical in an online try-on environment. This research adopts an emotional appeal perspective, including concrete and abstract effects, to clarify the relationship between sensory experience and consumer's behavior intention in an online try-on context. This study employed an augmented reality interactive technology (ARIT) in an online clothes-fitting context and applied snowball sampling using e-mail to invite online consumers, first to use ARIT for trying on online apparel and then to complete a questionnaire. One hundred sixty-eight valid questionnaires were collected, and partial least squares (PLS) path modeling was used to test our hypotheses. The results showed that sensory breadth, by arousing concrete effect, induces impulse buying intention and willingness to pay a price premium of online shopping. Parasocial presence, as an abstract effect, diminishes the effect of concrete effects on willingness to pay a price premium.

Keywords: sensory breadth, impulsive behavior, price premium, emotional appeal, online try-on context

Procedia PDF Downloads 543

Authors: Rodrigo Aguiar, Adelino Ferreira

Abstract:

Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

Procedia PDF Downloads 83

Authors: Olga Leontjeva

Abstract:

In the age of Artificial Intelligence (AI), some organization management approaches need to be adapted or changed. Human Resource Management (HRM) is a part of organization management that is under the managers' focus nowadays, because AI integration into organization activities brings some HRM-connected challenges. The topic became more significant during the crises of many organizations in the world caused by the coronavirus pandemic (COVID-19). The paper presents an approach, which will be used for the study that is going to be focused on the various case analysis. The author of the future study will analyze the cases of the organizations from Latvia and Spain that are grouped by the size, type of activity and area of business. The information for the cases will be collected through structured interviews and online surveys. The main result presented is the questionnaire developed that will be used for the study as well as the definition and description of sampling. The first round of the survey will be based on convenience sampling that is the main limitation of the study. To conclude, the approach developed will help to collect valid data if the organizations participating in the survey are ready to share their cases in depth, so the researchers could draw the right conclusions and generalize compared organizations’ cases. The questionnaire developed for the survey is applicable for both written online data collection as well as for the interviews. The case analysis will help to identify some HRM challenges that are connected to AI integration into organization activities such as management of different generation employees and their training peculiarities.

Keywords: age of artificial intelligence, case analysis, generation Y and Z employees, human resource management

Procedia PDF Downloads 164

Authors: Irfana M., Priyandi Kabasi

Abstract:

Children with specific language impairment (SLI) have difficulty acquiring and using language despite having all the requirements of cognitive skills to support language acquisition. These children have normal non-verbal intelligence, hearing, and oral-motor skills, with no history of social/emotional problems or significant neurological impairment. Nevertheless, their language acquisition lags behind their peers. Phonological complexity can be considered to be the major factor that causes the inaccurate production of speech in this population. However, the implementation of various ranges of complex phonological stimuli in the treatment session of SLI should be followed for a better prognosis of speech accuracy. Hence there is a need to study the levels of phonological complexity. The present study consisted of 7 individuals who were diagnosed with SLI and 10 developmentally normal children. All of them were Hindi speakers with both genders and their age ranged from 4 to 5 years. There were 4 sets of stimuli; among them were minimal contrast vs maximal contrast nonwords, minimal coarticulation vs maximal coarticulation nonwords, minimal contrast vs maximal contrast words and minimal coarticulation vs maximal coarticulation words. Each set contained 10 stimuli and participants were asked to repeat each stimulus. Results showed that production of maximal contrast was significantly accurate, followed by minimal coarticulation, minimal contrast and maximal coarticulation. A similar trend was shown for both word and non-word categories of stimuli. The phonological complexity effect was evident in the study for each participant group. Moreover, present study findings can be implemented for the management of SLI, specifically for the selection of stimuli.

Keywords: coarticulation, minimal contrast, phonological complexity, specific language impairment

Procedia PDF Downloads 136

Authors: Yun Chan Lee

Abstract:

Background: End-of-life care is a large area of all nursing practice and student nurses are likely to meet dying patients in many placement areas. It is therefore important to understand the emotional responses and coping strategies of student nurses in order for nursing education systems to have some appreciation of how nursing students might be supported in the future. Methodology: This research used a qualitative phenomenological approach. Six student nurses understanding a degree-level adult nursing course were interviewed. Their responses to questions were analyzed using interpretative phenomenological analysis. Finding: The findings identified 3 main themes. First, the common experience of ‘unpreparedness’. A very small number of participants felt that this was unavoidable and that ‘no preparation is possible’, the majority felt that they were unprepared because of ‘insufficient input’ from the university and as a result of wider ‘social taboos’ around death and dying. The second theme showed that emotions were affected by ‘the personal connection to the patient’ and the important sub-themes of ‘the evoking of memories’, ‘involvement in care’ and ‘sense of responsibility’. The third theme, the coping strategies used by students, seemed to fall into two broad areas those ‘internal’ with the student and those ‘external’. In terms of the internal coping strategies, ‘detachment’, ‘faith’, ‘rationalization’ and ‘reflective skills’ are the important components of this part. Regarding the external coping strategies, ‘clinical staff’ and ‘the importance of family and friends’ are the importance of accessing external forms of support. Implication: It is clear that student nurses are affected emotionally by caring for dying patients and many of them have apprehension even before they begin on their placements but very often this is unspoken. Those anxieties before the placement become more pronounced during and continue after the placements. This has implications for when support is offered and possibly its duration. Another significant point of the study is that participants often highlighted their wish to speak to qualified nurses after their experiences of being involved in end-of-life care and especially when they had been present at the time of death. Many of the students spoke that qualified nurses were not available to them. This seemed to be due to a number of reasons. Because the qualified nurses were not available, students had to make use of family members and friends to talk to. Consequently, the implication of this study is not only to educate student nurses but also to educate the qualified mentors on the importance of providing emotional support to students.

Keywords: nursing students, coping strategies, end-of-life care, emotional responses

Procedia PDF Downloads 155

Authors: Karen V. Lee

Abstract:

The background and significance of this study involve communication in education by a faculty advisor exploring story and music that informs others about a disabled teacher. Social issues draw deep reflection about the emotional turmoil. As a musician becoming a teacher is a passionate yet complex endeavor, the faculty advisor shares a poetic but painful story about a disabled teacher being inducted into the teaching profession. The qualitative research method as theoretical framework draws on autoethnography of music and story where the faculty advisor approaches a professor for advice. His musicianship shifts her forward, backward, and sideways through feelings that evoke and provoke curriculum to remove communication barriers in education. They discover they do not transfer knowledge from educational method classes. Instead, the autoethnography embeds musical language as a metaphorical conduit for removing communication barriers in teacher education. Sub-themes involve communication barriers and educational technologies to ensure teachers receive social, emotional, physical, spiritual, and intervention disability resources that evoke visceral, emotional responses from the audience. Major findings of the study discover how autoethnography of music and story bring the authors to understand wider political issues of the practicum internship for teachers with disabilities. An epiphany reveals the irony of living in a culture of both uniformity and diversity. They explore the constructs of secrecy, ideology, abnormality, and marginalization by evoking visceral and emotional responses from the audience. As the voices harmonize plot, climax, characterization, and denouement, they dramatize meaning that is episodic yet incomplete to highlight the circumstances surrounding the disabled protagonist’s life. In conclusion, the qualitative research method argues for embracing storied experiences that depict communication in education. Scholarly significance embraces personal thoughts and feelings as a way of understanding social phenomena while highlighting the importance of removing communication barriers in education. The circumstance about a teacher with a disability is not uncommon in society. Thus, the authors resolve to removing barriers in education by using stories to transform the personal and cultural influences that provoke new ways of thinking about the curriculum for a disabled teacher.

Keywords: communication in education, communication barriers, autoethnography, teaching

Procedia PDF Downloads 237

Authors: Valentina Colonnello, Paolo Maria Russo

Abstract:

Decades of cross-species affective neuroscience research by Panksepp and others have identified basic evolutionarily preserved subcortical emotional systems that humans share with mammals and many vertebrates. These primary emotional systems encode unconditional affective responses and contribute to the development of personality traits throughout ontogenesis and interactions with the environment. The Affective Neuroscience Personality Scale (ANPS) measures individual differences in affective personality traits associated with the basic emotional systems of CARE, PLAY, SEEKING, SADNESS, FEAR, and ANGER, along with Spirituality, which is a more cognitively and socially refined expression of affectivity. Though the ANPS’s power to predict human psychological distress has been documented, to the best of our knowledge, its predictive power for psychological wellbeing has not been explored. This study therefore investigates the relationship between affective neuroscience traits and psychological wellbeing facets. Because the emotional systems are thought to influence cognitively-mediated mental processes about the self and the world, understanding the relationship between affective traits and psychological wellbeing is particularly relevant to understanding the affective dimensions of health. In a cross-sectional study, healthy participants (n = 402) completed the ANPS and the Psychological Wellbeing scale. Multiple regressions revealed that each facet of wellbeing was explained by two to four affective traits, and each trait was significantly related to at least one aspect of wellbeing. Specifically, SEEKING predicted all the wellbeing facets, except for positive relations; CARE predicted personal growth, positive relations, purpose in life, and self-acceptance; PLAY and, inversely, ANGER predicted positive relations; SADNESS inversely predicted autonomy, while FEAR inversely predicted purpose in life. SADNESS and FEAR inversely predicted environmental mastery and self-acceptance. Finally, Spirituality predicted personal growth, positive relations, and self-acceptance. These findings are the first to show the relationship between affective neuroscience personality traits and psychological wellbeing. They also call attention to the distinctive role of FEAR and PANIC traits in psychological wellbeing facets, thereby complementing or even overcoming the traditional personality approach to neuroticism as a global trait.

Keywords: affective neuroscience, individual differences, personality, wellbeing

Procedia PDF Downloads 117

Authors: Darren Edwards, Thomas Pinna

Abstract:

Background: Interoception and heart rate variability have been found to predict outcomes of mental health and well-being. However, these have usually been investigated independently of one another. Objectives: This review aimed to explore the associations between interoception and heart rate variability (HRV) with emotion regulation (ER) and ER strategies within the existing literature and utilizing systematic review methodology. Methods: The process of article retrieval and selection followed the preferred reporting items for systematic review and meta-analyses (PRISMA) guidelines. Databases PsychINFO, Web of Science, PubMed, CINAHL, and MEDLINE were scanned for papers published. Preliminary inclusion and exclusion criteria were specified following the patient, intervention, comparison, and outcome (PICO) framework, whilst the checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) framework was used to help formulate the research question, and to critically assess for bias in the identified full-length articles. Results: 237 studies were identified after initial database searches. Of these, eight studies were included in the final selection. Six studies explored the associations between HRV and ER, whilst three investigated the associations between interoception and ER (one of which was included in the HRV selection too). Overall, the results seem to show that greater HRV and interoception are associated with better ER. Specifically, high parasympathetic activity largely predicted the use of adaptive ER strategies such as reappraisal, and better acceptance of emotions. High interoception, instead, was predictive of effective down-regulation of negative emotions and handling of social uncertainty, there was no association with any specific ER strategy. Conclusions: Awareness of one’s own bodily feelings and vagal activation seem to be of central importance for the effective regulation of emotional responses.

Keywords: emotional regulation, vagal tone, interoception, chronic conditions, health and well-being, psychological flexibility

Procedia PDF Downloads 111

Authors: Agnes Crisostomo, Alvin Joseph Mapoy

Abstract:

This is a qualitative study which focuses on ten (10) children, with a mean age of 13.6, working in fireworks factories in Bocaue, Bulacan. The municipality of Bocaue was chosen since it is the center of trade for fireworks, and child laborers can easily penetrate in factories here. The researcher wanted to know what the possible negative effects are caused by working at an early age of a child in the physical, psychosocial, intellectual and emotional aspects of life. Results showed that social status of their parents and their lack of income forced the children to work for their family. Second, the child laborers still allot time for studying. They still do not give up in pursuing education even if they experience fatigue and illness which affect their physical development. Third, working has a great influence to the child’s life. Fourth, through socializing with others, they become more aware of life’s hardships. Usually, their co-workers are also their family members and friends; this is how they know the social status is their place, that due to poverty even the children should work for a living. Fifth, these child laborers are still hoping for a better future. Despite of their poor situation, they are still hoping that they can turn it upside down through education, perseverance and determination.

Keywords: child labor, emotional, intellectual, psychosocial

Procedia PDF Downloads 263

Authors: Dean J. Hill

Abstract:

This paper undertakes the task of conducting an in-depth textual analysis of the cli-fi genre. It examines how writing in the genre contributes to expressing and facilitating the articulation of environmental consciousness through the form of narrative. The paper begins by situating cli-fi within the literary continuum of ecological narratives and identifying the unique textual characteristics and thematic preoccupations of this area. The paper unfolds how cli-fi transforms the esoteric nature of climate science into credible narrative forms by drawing on language use, metaphorical constructs, and narrative framing. It also involves how descriptive and figurative language in the description of nature and disaster makes climate change so vivid and emotionally resonant. The work also points out the dialogic nature of cli-fi, whereby the characters and the narrators experience inner disputes in the novel regarding the ethical dilemma of environmental destruction, thus demanding the readers challenge and re-evaluate their standpoints on sustainability and ecological responsibilities. The paper proceeds with analysing the feature of narrative voice and its role in eliciting empathy, as well as reader involvement with the ecological material. In looking at how different narratorial perspectives contribute to the emotional and cognitive reaction of the reader to text, this study demonstrates the profound power of perspective in developing intimacy with the dominating concerns. Finally, the emotional arc of cli-fi narratives, running its course over themes of loss, hope, and resilience, is analysed in relation to how these elements function to marshal public feeling and discourse into action around climate change. Therefore, we can say that the complexity of the text in the cli-fi not only shows the hard edge of the reality of climate change but also influences public perception and behaviour toward a more sustainable future.

Keywords: cli-fi genre, ecological narratives, emotional arc, narrative voice, public perception

Procedia PDF Downloads 30

Authors: Mohammad Moussa Khalaf

Abstract:

As a significant term in Arab music, ṭarab identifies a particular expression of feelings and emotions, especially in the vocal practice of Arab music. Ṭarab aims to take both the performer and the audience from a normal feeling state to a new state of spiritual feeling through the art of mawwāl. Because of the expertise required for mawwāl, the ability to reach ṭarab has long been considered an indication that a musician has reached a high musical level. Another significant Islamic concept related to feelings and emotions is khushūʿ. It is known that one of the ways to get Khāsheʿ (humble to God) is the artistic reading of the holy Qur’ān. The artistic recitation of the Qur’ān is tajwīd. Like mawwāl, tajwīd requires a high-level rendition to lead the listener to the special emotional state. The research will focus on the relationships between ṭarab, khushūʿ, tajwīd, and mawwāl in Islamic-Arab culture in a way that has not been addressed previously. The relationships between tajwid and mawwāl, ṭarab and khushūʿ would be identified through the examination of musical factors, socio-cultural factors, and emotional factors.

Keywords: Arab music, Ṭarab, Mawwāl, Khushūʿ, Tajwīd, Islam

Procedia PDF Downloads 90

Authors: M. Ben Slimene, M.-S. Ouali

Abstract:

Asset management of urban infrastructures faces a multitude of challenges that need to be overcome to obtain a reliable measurement of performances. Predicting the performance of slowly aging systems is one of those challenges, which helps the asset manager to investigate specific failure modes and to undertake the appropriate maintenance and rehabilitation interventions to avoid catastrophic failures as well as to optimize the maintenance costs. This article presents a methodology for modeling the deterioration of slowly degrading assets based on an operating history. It consists of extracting degradation profiles by grouping together assets that exhibit similar degradation sequences using an unsupervised classification technique derived from artificial intelligence. The obtained clusters are used to build the performance prediction models. This methodology is applied to a sample of a stormwater drainage culvert dataset.

Keywords: artificial Intelligence, clustering, culvert, regression model, slow degradation

Procedia PDF Downloads 104

Authors: Reggie Chandra

Abstract:

Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

Procedia PDF Downloads 164

Authors: Mykah W. Sumoldao, Maria Erissa C. Susa, Triny Cate M. Telan, Christian Arvin M. Torres, Jasmine I. Udasco, Franceis Jeramil M. Walis, Shellyn S. Wandagan, Janine May M. Warding, Queenie Diana Rose P. Zalun Hope Lulet A. Lomioan

Abstract:

This descriptive phenomenological study explored the lived experiences of the primary caregiver of schizophrenia patients at the Acute Crisis Intervention Service in Cagayan Valley Medical Center. The research aimed to understand the emotional, physical, and financial challenges these primary caregivers face. Data was gathered through interviews with nine (9) primary caregivers and analyzed using Colaizzi’s seven-step method. Two main themes emerged: Experience/ Challenges (Emotional, Physical, and Financial Challenges) and Managing Mechanisms (Support Systems and Resilience and Commitment). The study found that primary caregivers deal with a complex mix of difficulties, often with limited resources. They rely heavily on personal strength, faith, family, friends and community support to manage their roles. The findings highlighted the need for better support systems to ease primary caregivers' burdens. Financial aid, respite care, and mental health support are crucial for improving primary caregivers' quality of life and the care they provide. Additionally, raising awareness about primary caregivers' challenges can foster a supportive community, with more help from local organizations and government entities. Thus, this study provided insights into the caregiving experiences of those supporting schizophrenia patients. It emphasized the importance of practical support and emotional resilience. By addressing these needs, a more supportive environment can be created, benefiting both primary caregivers and their patients.

Keywords: primary caregiver burden, mental health, primary caregiver well-being, primary caregiver

Procedia PDF Downloads 17

Authors: Snezana Svetozarevic

Abstract:

The aim of the research was to determine whether there were significant changes in perceptions of family functioning by families in Serbia 12 months after the coronavirus (COVID-19) outbreak has been declared a global pandemic. Above all, what has protected families in the face of the global crisis caused by COVID-19. The Self-Report Family Inventory, II version (SFI-II; Beavers and Hampson, 2013) and the Inventory of Family Protective Factors (IFPF; Gardner et al., 2008) were used to assess family functioning and protective factors. Currently, families perceive their functioning as more problematic regarding family emotional expressiveness, conflict, cohesion, and global family health/competence. Adaptive appraisal based on positive coping experiences significantly predicted values on emotional expressiveness, conflict, leadership, and global family health/competence dimensions -a higher prevalence of this factor was associated with more optimal family functioning and fewer problems. The growing problem in family functioning with the beginning of the pandemic is inevitable. However, our research confirmed that it is not enough to take into account what families do to survive. It is equally important to learn about what they do to thrive i.e., to study the family resilience.

Keywords: family, coping, resilience, pandemic, COVID-19

Procedia PDF Downloads 94

Authors: Jonas Colin

Abstract:

Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

Procedia PDF Downloads 68

Authors: Karen V. Lee

Abstract:

The background and significance of this study involves an autoethnographic story that shares research results about how music and movies influence the suicide of a new music teacher working in a public school. The performative narrative duet demonstrates how music and movies highlight social issues when the new teacher cannot cope with allegations surrounding professional issues. Both university advisors are drawn into deep reflection about the wider political issues that arise around the transition from the student-teacher internship process to the teaching career with the stark reality of teaching profession in the 21st century. This performance of story and music creates a transformative composition of reading, hearing, feeling while provoking visceral and emotional responses. Sometimes, young teachers are forced to take a leave of absence to reflect upon their practice with adolescents. In this extreme circumstance, the outcome was suicide. The qualitative research method involves an autoethnographic story as the author is methodologist, theoretician, and participant. Sub-themes surround film, music education and how movie resources have influenced his tragic misguided decision regarding social, emotional, physical, spiritual, and practical strategies to cope with the allegations. Major findings from this story demonstrate how lived experiences can resonate the importance of providing more education and resources to new teachers. The research provides substantive contribution, aesthetic merit, as the impact of movies and music influences the suicide. The reflexive account of storied sensory experiences situated in culture settings becomes a way to describe and seek verisimilitude by evoking lifelike and believable feelings from others. Sadly, the circumstance surrounding the story involving the allegations of a teacher sexually harassing a student is not uncommon in society. However, the young teacher never received counseling to cope with the allegations but instead was influenced by music and movies and opted for suicide. In conclusion, stories share the implications for film and media studies as music and movies can encourage a moral mission to empower individuals with despair and emotional impairment to embrace professional support to assist with emotional and legal challenges encountered in the field of teaching. It is from media studies that education and awareness surrounding suicide can disseminate information about the tragic outcome.

Keywords: music, movies, suicide, narrative, autoethnography

Procedia PDF Downloads 229

Authors: Ahmed Atef, Mohamed Alhasheem, Eman Beshr

Abstract:

In this paper, an enhanced DC microgrid design is proposed using the DAB converter as a conversion unit in order to harvest the maximum power from the PV array. Each connected DAB converter is controlled with an enhanced control strategy. The controller is based on the artificial intelligence (AI) technique to regulate the terminal PV voltage through the phase shift angle of each DAB converter. In this manner, no need for a Maximum Power Point Tracking (MPPT) unit to set the reference of the PV terminal voltage. This strategy overcomes the stability issues of the DC microgrid as the response of converters is superior compared to the conventional strategies. The proposed PV interface system is modelled and simulated using MATLAB/SIMULINK. The simulation results reveal an accurate and fast response of the proposed design in case of irradiance changes.

Keywords: DC microgrid, DAB converter, parallel operation, artificial intelligence, fast response

Procedia PDF Downloads 780

Authors: Balamurugan L.

Abstract:

Artificial intelligence (AI) and its applications in Intellectual Property Rights (IPR) has been significantly growing in recent years. In last couple of years, AI tools for Patent Research and Patent Analytics have been well-stabilized in terms of accuracy of references and representation of identified patent insights. However, AI tools for Patent Prosecution and Patent Litigation are still in the nascent stage and there may be a significant potential if such market is explored further. Our research is primarily focused on identifying potential whitespaces and schematic algorithms to automate the Patent Prosecution and Patent Litigation Process of the Intellectual Property. The schematic algorithms may assist leading AI tool developers, to explore such opportunities in the field of Intellectual Property. Our research is also focused on identification of pitfalls of the AI. For example, Information Security and its impact in IPR, and Potential remediations to sustain the IPR in the digital environment.

Keywords: artificial intelligence, patent analytics, patent drafting, patent litigation, patent prosecution, patent research

Procedia PDF Downloads 61

Authors: Hae-Won Seo, Yong-Gu Lee

Abstract:

Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.

Keywords: connected-car, data modeling, route planning, navigation system

Procedia PDF Downloads 371

Authors: Mohd Anuar Awang Idris, Muhammad Nubli Abdul Wahab, Nora Yusma Mohamed Yusoff

Abstract:

Wudu’ (Ablution) and Zikr are amongst some of the spiritual tools which may help an individual control his mind, emotion and attitude. These tools are deemed to be able to deliver a positive impact on an individual’s psychophysiology. The main objective of this research is to determine the effects of Wudu’ (Ablution) and Zikr therapy using the biofeedback emWave application and technology. For this research, 13 students were selected as samples from the students’ representative body at the University Tenaga National, Malaysia. The DASS (Depression Anxiety Stress Scale) questionnaire was used to help with the assessment and measurement of each student’s ability in controlling his or her emotions before and after the therapies. The biofeedback emWave technology was utilized to monitor the student’s psychophysiology level. In addition, the data obtained from the Heart rate variability (HRV) test have also been used to affirm that Wudu’ and Zikr had had significant impacts on the student’s success in controlling his or her emotional pressure.

Keywords: biofeedback EmWave, emotion, psychophysiology, wudu’, zikr

Procedia PDF Downloads 199

Authors: Ahmed Radwan, Ahmed Abdel Ghaney

Abstract:

This paper delves into the transformative potential of artificial intelligence (AI) in fostering creativity within the domain of architecture education, especially with a specific emphasis on its implications within the Design Studios; the convergence of AI and architectural pedagogy has introduced avenues for redefining the boundaries of creative expression and problem-solving. By harnessing AI-driven tools, students and educators can collaboratively explore a spectrum of design possibilities, stimulate innovative ideation, and engage in multidimensional design processes. This paper investigates the ways in which AI contributes to architectural creativity by facilitating generative design, pattern recognition, virtual reality experiences, and sustainable design optimization. Furthermore, the study examines the balance between AI-enhanced creativity and the preservation of core principles of architectural design/education, ensuring that technology is harnessed to augment rather than replace foundational design skills. Through an exploration of Egypt's architectural heritage and contemporary challenges, this research underscores how AI can synergize with cultural context and historical insights to inspire cutting-edge architectural solutions. By analyzing AI's impact on nurturing creativity among Egyptian architecture students, this paper seeks to contribute to the ongoing discourse on the integration of technology within global architectural education paradigms. It is hoped that this research will guide the thoughtful incorporation of AI in fostering creativity while preserving the authenticity and richness of architectural design education in Egypt and beyond.

Keywords: architecture, artificial intelligence, architecture education, Egypt

Procedia PDF Downloads 73