Search results for: emotional intelligence

Authors: Mayar Almasri, Rosa Helmi, Rayana Enany

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This report describes the features of AutoCAD software released by Adobe. It explains how the program makes it easier for engineers and designers and reduces their time and effort spent using AutoCAD. Moreover, it highlights how AutoCAD works, how some of the commands used in it, such as Shortcut, make it easy to use, and features that make it accurate in measurements. The results of the report show that most users of this program are designers and engineers, but few people know about it and find it easy to use. They prefer to use it because it is easy to use, and the shortcut commands shorten a lot of time for them. The feature got a high rate and some suggestions for improving AutoCAD in Aperture, but it was a small percentage, and the highest percentage was that they didn't need to improve the program, and it was good.

Keywords: artificial intelligence, design, planning, commands, autodesk, dimensions

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Authors: Olusegun Omoluwa, Kolawole Israel Anthony

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Pupils with learning disabilities are found in every classroom, but because learning disabilities cannot be seen, the condition is often too neglected. Unless these pupils are recognised and treated, they are likely to become educational discards. This study consequently attempted to determine effects of self-monitoring strategy on homework completion among pupils with learning disabilities. Ninety (90) participants were engaged in the study. Pre-test, post-test, control group quasi experimental design was adopted. Purposive sampling technique was used to select pupils with evidence of learning disabilities from three primary schools in Ondo State. Findings showed that self-monitoring strategy was significant in enhancing homework completion among pupils with learning disabilities. However, gender and self-esteem did not significantly contribute to homework completion. The study therefore recommended that measures such that would uncover unsettling academic, psychological and emotional deficiencies of these pupils through appropriate diagnosis should be undertaken by the parents and teachers, in order for them to have a sense of belonging in the society.

Keywords: self monitoring, home work completion, learning dissabilities, learning

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Authors: Naiara Ozamiz Etcebarria, Sonia Ruiz De Azua Garcia, Agurtzane Ortiz Jauregi, Virginia Guillen Cañas

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Introduction: The most relevant competencies of a health professional are an adequate communication capacity, which will influence the satisfaction of professionals and patients, therapeutic compliance, conflict prevention, clinical outcomes´ improvement and efficiency of health services. The ability of Active listening , empathy, assertiveness and social skills, are important abilities to develop in all professions in which there is a relationship with other people. In the field of health, it is even more important to have adequate qualities so that the treatment with the patient will be adequate and satisfactory. We conducted a research with students of third year in the Degree of Medicine with the objectives: - to know how the active listening, empathy, assertiveness and social skills of students are. - to know if there are differences according to different demographic variables, such as sex, language, age, number of siblings and interest in the subject. Material and Methods: The students of the Third year in the Degree of Medicine (N = 212) participated voluntarily. Sociodemographic data were collected. Descriptive and comparative analysis of the averages of the students with respect to active listening, empathy, assertiveness and social skills were performed. Once the questionnaires were collected, they were entered into the SPSS 21 database. Four communicational aspects were evaluated: The active listening questionnaire, the TECA empathy questionnaire, the ACDA questionnaire and the EHS questionnaire Social Skills Scale. The active listening questionnaire assesses these factors: Listening without interruption and less contradiction, Listening with 100% attention, Listening beyond words, Listening encouraging the other to go deeper. The TECA questionnaire of cognitive and affective empathy evaluates: Adoption of perspectives, Emotional Comprehension, Emphasizing stress, Empathic joy. The EHS questionnaire Social Skills Scale: Self-expression in social situations, Defending one's own rights as a consumer, Expressing anger or dissatisfaction, Refusing to do and cutting interactions off, Making requests, Initiating positive interactions with the other sex. The ACDA questionnaire Assertiveness Assessment Scale evaluates self-assertiveness and heteroaservitivity. Applicability: To train these skills is so important for clinical practice of medical students and these capabilities that can be measured in a longitudinal way time. Ethical-legal aspects: The data were anonymous. The study was approved by the Ethics Committee. Results: The students of the Third year in the Degree of Medicine (34.4% Basque speakers and 65.6% Spanish speakers) with average age 20.93, (27.8% men and 72.2% women). There are no differences in social skills between men and women. The Basque speaker students of are more heteroactive (ACDA) than Spanish students. Active listening has a high correlation with social skills, especially with self-expression in social situations. Listening without interruption has a high correlation with self-expression in social situations and initiating positive interactions with the opposite sex. Adoption of perspectives presents a high correlation with auto- assertiveness. Emotional understanding presents a high correlation with positive interactions with the opposite sex. Empathic joy correlates with self-assertiveness, self-expression in social situations, and initiating positive interactions with the opposite sex.

Keywords: active listening, assertiveness, communicational skills, empathy, students of medicine

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Sunha Ahn

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Intimate relationships have constructed our embodied experiences and emotional memories, which can become grounded as practical knowledge to some extent and play a critical role in social medicine, particularly, in our well-being and mental health. In South Africa, such relational factors are significant for young women and girls in their emotional development period of time, especially, working as the existence of social and relational pressures over feminine sexual health and choices. This, in turn, brings about the absence/lack of communication in intimate relationships, especially with their parents, which leads to a vicious cycle in sexual health behaviour choices. Drawing upon sociological and socio-anthropological understandings of HIV-related issues, this study provides narrative threads of evidence about South African teenage mothers from early-dating debuted to HIV infection. Their stories consist of a visualised figure in chronicle order, illustrating embodied journeys of sexual health choices surrounding uncommunicative relationships and socially-suppressive environments. Methodologically, this qualitative study explored data from mixed online methods: 1) a case study analysing online comments (N = 12,763) on the South African Springster's website, run by the UK-based NGO, namely, Girl Effect; and 2) In-depth online interviews (N = 21) were conducted with young SA women and girls (16-28 ages) recruited in Cape Town, Pretoria, and Johannesburg, SA. Participants consist of both those living with HIV and without. Ethical approval was gained via the College of Social Sciences Ethical Committee at the University of Glasgow, and informed consent was obtained verbally and in writing from participants in due course. Data were thematically applied to an iteratively developed codebook and analysed. There are three kinds of typical pressures as relational factors for them, including peer pressure, partners or boyfriends, and parents’ reactions. Under the patriarchal and religious-devoted social atmospheres, these relationships work as a source of scaredness among young women and girls who could not talk about their sexual health concerns and rights. Such an inability to communicate with intimate relationships, eventually, emerges as a perpetuated or taken-for-granted social environment in South Africa, insistently leading to an increase in unwanted pregnancies or new HIV infections in young South African women and girls. In this sense, this study reveals the pressing need for open communication between generations with accurate information about HIV/AIDS. This also implies that the sociological feminist praxes in South Africa would help eliminate HIV-related stigma as well as construct open space to reduce gender-based violence and sexually-transmitted infection. Ultimately, this will be a road for supporting sexually healthy decisions and well-being across South African generations.

Keywords: HIV, young women, South Africa, intimate relationships, communication, social medicine

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Authors: Cameron Wilson, Megan Hanrahan, Katie Brittain, Riona McArdle, Alison Keogh, Lynn Rochester

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Background: The loss of mobility and functional dependence is a significant marker in the progression of neurodegenerative diseases such as Parkinson’s Disease (PD). Pharmacological, surgical, and therapeutic treatments are available that can help in the management and amelioration of PD symptoms; however, these only prolong more severe symptoms. Accordingly, ensuring people with PD can maintain independence and a healthy wellbeing are essential in establishing an effective treatment option for those afflicted. Existing literature reviews have examined experiences in engaging with PD treatment options and the impact of PD on independence and wellbeing. Although, the literature fails to explore the influence of treatment options on independence and wellbeing and therefore misses what people value in their treatment. This review is the first that synthesises the impact of mobility-related treatments on independence and wellbeing in people with PD and their carers, offering recommendations to clinical practice and provides a conceptual framework (in development) for future research and practice. Objectives: To explore the impact of mobility-related treatment (both pharmacological and non-pharmacological) on the independence and wellbeing of people with PD and their carers. To propose a conceptual framework to patients, carers and clinicians which captures the qualities people with PD value as part of their treatment. Methods: We performed a critical interpretive synthesis of qualitative evidence, searching six databases for reports that explored the impact of mobility-related treatments (both drug and non-pharmacological) on independence and wellbeing in Parkinson’s Disease. The types of treatments included medication (Levodopa and Amantadine), dance classes, Deep-Brain Stimulation, aquatic therapies, physical rehabilitation, balance training and foetal transplantation. Data was extracted, and quality was assessed using an adapted version of the NICE Quality Appraisal Tool Appendix H before being synthesised according to the critical interpretive synthesis framework and meta-ethnography process. Results: From 2301 records, 28 were eligible. Experiences and impact of treatment pathway on independence and wellbeing was similar across all types of treatments and are described by five inter-related themes: (i) desire to maintain independence, (ii) treatment as a social experience during and after, (iii) medication to strengthen emotional health, (iv) recognising physical capacity and (v) emphasising the personal journey of Parkinson’s treatments. Conclusion: There is a complex and inter-related experience and effect of PD treatments common across all types of treatment. The proposed conceptual framework (in development) provides patients, carers, and clinicians recommendations to personalise the delivery of PD treatment, thereby potentially improving adherence and effectiveness. This work is vital to disseminate as PD treatment transitions from subjective and clinically captured assessments to a more personalised process supplemented using wearable technology.

Keywords: parkinson's disease, medication, treatment, dance, review, healthcare, delivery, levodopa, social, emotional, psychological, personalised healthcare

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Authors: Ashutosh Mishra, Nikhil Goyal

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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

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Authors: Bodhayan Nandi, Shubhajit Roy Chowdhury

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This paper presents the development of a portable blood glucose monitoring device based on Near-Infrared Spectroscopy. The system supports Internet connectivity through WiFi and uploads the time series data of glucose concentration of patients to a server. In addition, the server is given sufficient intelligence to predict the future pathophysiological state of a patient given the current and past pathophysiological data. This will enable to prognosticate the approaching critical condition of the patient much before the critical condition actually occurs.The server hosts web applications to allow authorized users to monitor the data remotely.

Keywords: non invasive, blood glucose concentration, microcontroller, IoT, application server, database server

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Authors: Catherine Constantinidis (Nee Tsacalos)

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This paper presents one aspect of the larger Masters qualitative study exploring the roles of married Greek Orthodox clergy, the Priest and Presbytera, under the wing of the Greek Orthodox Archdiocese of Australia. This ground breaking research necessitated the creation of primary data within a phenomenological paradigm drawing from lived experiences of the Priests and Presbyteres in contemporary society. As a Social Worker, a bilingual (Greek/English) Mental Health practitioner and a Presbytera, the questions constantly raised and pondered are: Who do the Priest and Presbytera turn to when they experience difficulties or problems? Where do they go for support? What is in place for their emotional and psychological health and well-being? Who cares for the spiritual carer? Who is there to catch our falling clergy and their wives? What is their 'safety net'? Identified phenomena of angst, stress, frustration and confusion experienced by the Priest and (by extension) the Presbytera, within their position, coupled with basic assumptions, perceptions and expectations about their roles, the role of the organisation (the Church), and their role as spouse often caused confusion and in some cases conflict. Unpacking this complex and multi-dimensional relationship highlighted not only the roller coaster of emotions, potentially affecting their physical and mental health, but also the impact on the interwoven relationships of marriage and ministry. The author considers these phenomena in the light of bilingual cultural and religious organisational practice frameworks, specifically the Greek Orthodox Church, whilst filtering these findings through a mental health lens. One could argue that it is an expectation that clergy (and by default their wives) take on the responsibility to be kind, nurturing and supportive to others. However, when it comes to taking care of self, they are not nearly as kind. This research looks at a recurrent theme throughout the interviews where all participants talked about limited support systems and poor self care strategies and the impact this has on their ministry, mental, emotional, and physical health and ultimately on their relationships with self and others. The struggle all participants encountered at some point in their ministry was physical, spiritual and psychological burn out. The overall aim of the researcher is to provide a voice for the Priest and the Presbytera painting a clearer picture of these roles and facilitating an awareness of struggles and dilemmas faced in their ministry. It is hoped these identified gaps in self care strategies and support systems will provide solid foundations for building a culturally sensitive, empathetic and effective support system framework, incorporating the spiritual and psychological well-being of the Priest and Presbytera, a ‘safety net’. A supplementary aim is to inform and guide ministry practice frameworks for clergy, spouses, the church hierarchy and religious organisations on a local and global platform incorporating some sort of self-care system.

Keywords: care for the carer, mental health, Priest, Presbytera, religion, support system

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Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

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Authors: Zahide Tepeli Temiz, Itir Tari Comert

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Attachment patterns based on early emotional interactions between infant and primary caregiver continue to be influential in adult life, in terms of mental health and behaviors of individuals. Several studies reveal that infant-caregiver relationships have impressed the affect regulation, coping with stressful and negative situations, general satisfaction of life, and self image in adulthood, besides the attachment styles. The present study aims to examine the relationships between university students’ attachment style and their self-esteem, alexithymic features, satisfaction of life, and level of resilience. In line with this aim, the hypothesis of the prediction of attachment styles (anxious and avoidant) over life satisfaction, self-esteem, alexithymia, and psychological resilience was tested. Additionally, in this study Structural Equational Modeling was conducted to investigate the mediational role of self-esteem in the relationship between attachment styles and alexithymia, life satisfaction, and resilience. This model was examined with path analysis. The sample of the research consists of 425 university students who take education from several region of Turkey. The participants who sign the informed consent completed the Demographic Information Form, Experiences in Close Relationships-Revised, Rosenberg Self-Esteem Scale, The Satisfaction with Life Scale, Toronto Alexithymia Scale, and Resilience Scale for Adults. According to results, anxious, and avoidant dimensions of insecure attachment predicted the self-esteem score and alexithymia in positive direction. On the other hand, these dimensions of attachment predicted life satisfaction in negative direction. The results of linear regression analysis indicated that anxious and avoidant attachment styles didn’t predict the resilience. This result doesn’t support the theory and research indicating the relationship between attachment style and psychological resilience. The results of path analysis revealed the mediational role self esteem in the relation between anxious, and avoidant attachment styles and life satisfaction. In addition, SEM analysis indicated the indirect effect of attachment styles over alexithymia and resilience besides their direct effect. These findings support the hypothesis of this research relation to mediating role of self-esteem. Attachment theorists suggest that early attachment experiences, including supportive and responsive family interactions, have an effect on resilience to harmful situations in adult life, ability to identify, describe, and regulate emotions and also general satisfaction with life. Several studies examining the relationship between attachment styles and life satisfaction, alexithymia, and psychological resilience draw attention to mediational role of self-esteem. Results of this study support the theory of attachment patterns with the mediation of self-image influence the emotional, cognitive, and behavioral regulation of person throughout the adulthood. Therefore, it is thought that any intervention intended for recovery in attachment relationship will increase the self-esteem, life satisfaction, and resilience level, on the one side, decrease the alexithymic features, on the other side.

Keywords: alexithymia, anxious attachment, avoidant attachment, life satisfaction, path analysis, resilience, self-esteem, structural equation

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Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

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Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

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Authors: Owen Cegielski, Kristi Maida, Danny Morales, Sylvia L. Mendez

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This study explores the challenges and threats US secondary educators experience in incorporating culturally relevant education (CRE) practices in their classrooms. CRE is a social justice pedagogical practice used to connect student’s cultural references to academic skills and content, to promote critical reflection, to facilitate cultural competence, and to critique discourses of power and oppression. Empirical evidence on CRE demonstrates positive student educational outcomes in terms of achievement, engagement, and motivation. Additionally, due to the direct focus on uplifting diverse cultures through the curriculum, students experience greater feelings of belonging, increased interest in the subject matter, and stronger racial/ethnic identities. When these teaching practices are in place, educators develop deeper relationships with their students and appreciate the multitude of gifts they (and their families) bring to the classroom environment. Yet, educators regularly report being unprepared to incorporate CRE in their daily teaching practice and identify substantive gaps in their knowledge and skills in this area. Often, they were not exposed to CRE in their educator preparation program, nor do they receive adequate support through school- or district-wide professional development programming. Through a descriptive phenomenological research design, 20 interviews were conducted with a diverse set of secondary school educators to explore the challenges and threats they experience in incorporating CRE practices in their classrooms. The guiding research question for this study is: What are the challenges and threats US secondary educators face when seeking to incorporate CRE practices in their classrooms? Interviews were grounded by the theory of challenge and threat states, which highlights the ways in which challenges and threats are appraised and how resources factor into emotional valence and perception, as well as the potential to meet the task at hand. Descriptive phenomenological data analysis strategies were utilized to develop an essential structure of the educators’ views of challenges and threats in regard to incorporating CRE practices in their secondary classrooms. The attitude of the phenomenological reduction method was adopted, and the data were analyzed through five steps: sense of the whole, meaning units, transformation, structure, and essential structure. The essential structure that emerged was while secondary educators display genuine interest in learning how to successfully incorporate CRE practices, they perceive it to be a challenge (and not a threat) due to lack of exposure which diminishes educator capacity, comfort, and confidence in employing CRE practices. These findings reveal the value of attending to emotional valence and perception of CRE in promoting this social justice pedagogical practice. Findings also reveal the importance of appropriately resourcing educators with CRE support to ensure they develop and utilize this practice.

Keywords: culturally relevant education, descriptive phenomenology, social justice practice, US secondary education

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Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: Melika Masjedi

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Post-Traumatic Stress Disorder (PTSD) has a significant impact on the mental health and relationship dynamics of couples, leading to decreased marital satisfaction. This study examines the mediating role of sexual and romantic relationship dynamics in relation to PTSD and marital satisfaction among Iranian couples. Using a sample of 107 participants, quantitative methods were utilized to assess variables such as relationship functioning, PTSD symptom severity, and the influence of sexual and romantic interactions. The findings demonstrate a strong correlation between heightened PTSD symptoms and reduced marital satisfaction, particularly in the domains of intimacy and emotional connection. The study highlights the importance of addressing relational dynamics to improve marital outcomes in PTSD-affected couples.

Keywords: intimacy, marital satisfaction, PTSD, relationship dynamics, trauma

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Authors: Shulamit Sternin, Raymond M. McKie, Carter Winberg, Robb N. Travers, Terry P. Humphreys, Elke D. Reissing

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Issues surrounding sexual consent negotiation have become a major topic of societal concern. The majority of current research focuses on the complexities of sexual consent negotiations and the multitude of nuanced issues that surround the consent obtainment of heterosexual adults in post-secondary educational institutions. To date, the only study that has addressed sexual consent negotiation behaviour in same-sex relationships focused on the extent to which individuals used a variety of different verbal and nonverbal sexual consent behaviours to initiate or respond to sexual activity. The results were consistent with trends found within heterosexual individuals; thus, suggesting that the current understanding of sexual consent negotiation, which is grounded in heterosexual research, can serve as a strong foundation for further exploration of sexual consent negotiation within same-sex relationships populations. The current study quantitatively investigated the differences between heterosexual men and gay and bisexual men (GBM) in their understanding of sexual consent negotiation. Exploring how the perceptions of GBM differ from heterosexual males provides insight into some of the unique challenges faced by GBM. Data were collected from a sample of 252 heterosexual men and 314 GBM from Canada, the United States, and Western Europe. Participants responded to the question, 'do you think sexual consent and sex negotiation is different for heterosexual men compared to gay men? If so, how?' by completed an online survey. Responses were analysed following Braun & Clarke’s (2006) six phase thematic analysis guidelines. Inter-rater coding was validated using Cohen’s Kappa value and was calculated at (ϰ = 0.84), indicating a very strong level of agreement between raters. The final thematic structure yielded four major themes: understanding of sexual interaction, unique challenges, scripted role, and universal consent. Respondents spoke to their understanding of sexual interaction, believing GBM sexual consent negotiation to be faster and more immediate. This was linked to perceptions of emotional attachment and the idea that sexual interaction and emotional involvement were distinct and separate processes in GBM sexual consent negotiation, not believed to be the case in heterosexual interactions. Unique challenges such as different protection concerns, role declaration, and sexualization of spaces were understood to hold differing levels of consideration for heterosexual men and GBM. The perception of a clearly defined sexual script for GBM was suggested as a factor that may create ambiguity surrounding sexual consent negotiation, which in turn holds significant implications on unwanted sexual experiences for GBM. Broadening the scope of the current understanding of sexual consent negotiation by focusing on heterosexual and GBM population, the current study has revealed variations in perception of sexual consent negotiation between these two populations. These differences may be understood within the context of sexual scripting theory and masculinity gender role theory. We suggest that sexual consent negotiation is a health risk factor for GBM that has not yet been adequately understood and addressed. Awareness of the perceptions that surround the sexual consent negotiation of both GBM and heterosexual men holds implications on public knowledge, which in turn can better inform policy making, education, future research, and clinical treatment.

Keywords: sexual consent, negotiation, heterosexual men, GBM, sexual script

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Authors: Molly Meadows

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Following the presidency of Donald J. Trump, Americans have become hyperaware of ethnocentrisms that plague the culture. The president's egoist ethics encouraged a divide between what the citizens of the US identified as just or unjust. In the race for global supremacy and leading ideology, fears have arisen, exacerbated by the ethnocentricity of the country's leader, pointing to the possible harmful ethical standards of competing nations. Due to the concept of ethical absolutism, an international code of ethics would not be possible, and the changes needed to eliminate the stigma surrounding other cultures of thought would need to come from the governing body of the US. As the current leading global ideology, the US would need its government to embody a transformational leadership style in order to unite the motivations of the citizens and encourage intercultural tolerance.

Keywords: ethics, transformational leadership, American politics, egoism, cultural intelligence, ethical relativism

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Authors: Baiju Soren

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This research investigates village residents' feelings about rural landscapes and their attitudes toward preserving them, as well as the impact of attachment on participation in preserving those environments. To understand these relationships, 100 respondents from Bandudumha village : a tribal village, Mayurbhanj district of Odisha, were interviewed with a set of questionnaires and photographs. This framework is based on the idea that establishing environmental oversight and desire to cooperate in the development and preservation process can help to establish community values and meaning tied to places. As a result, a personal connection to the rural environment will be explored through an examination of place attachment, landscape choice, and the possible conservation value of landscapes to the people who live there. The findings suggest that commitment to a place can lead to unique ideas on collaborative preservation and the creation of truly relevant, socially inclusive landscapes. Furthermore, the data show how emotional ties to locations provide social support and provide insight into people–place relationships.

Keywords: participation in preservation, place attachment, preservation, rural landscape, sense of place

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Authors: Sookbin Im, Myounglyun Heo

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This study aims at analyzing composition and effects of the preliminary intervention to promote resiliency of children whose parents suffer mental illness, and considerations according to the program, and developing the resiliency promotion program for children of psychiatric patients. For participants of preliminary intervention, they were recruited through a community mental health and social welfare center in a city, and there were 10 children (eight girls and two boys) who are from second to five graders in elementary school, and whose parents suffer schizophrenia, depression, or alcoholism, etc. The program was conducted in the seminar room of the community mental illness and social welfare center from October to December 2015 and from July to September 2016. The elements of resiliency were figured out by reviewing the literature. And therapeutic activities to promote resiliency was composed, and total twice, 8 sessions(two hours, once a week) were applied. Each session consisted of playgroup activities, art activities, and role-playing with feedback for achieving goals to promote self-awareness, self-efficacy, positive outlook, ability to solve problems, empathy for others, peer group acceptance, having goals and aspirations, and assertiveness. In addition, auxiliary managers as many as children played a role as mentor and role model, and children's behaviors were collected by participatory observation. As a result of the study, four children quit the program because the schedules of their own school programs were overlapped with it. Therefore, six children completed the program. Children who completed it became active, positive, decreased compulsive actions, and increased self-expressions. The participants reacted the 8-session program is too short and regretted about it. However, recruiting the participants were difficult, and too distracting children caused negative influences in the group activities. Based on the results, the program was developed as follows: The program would consist of total 11 sessions, and the first eight sessions would be made of plays, art activities, role-plays, and presentations for promoting self-understanding, improving positiveness, providing meaning for experiences, emotional control, and interpersonal relations. In order to balance various contents, methods such as structuring environments, storytelling, emotional coaching, and group feedback would be applied, and the ninth to eleventh sessions would be booster sessions consisting of optional activities for children. This program is for children who attend school with active linguistic communications and interactions with peers. Especially, considering that effective development starts at around 10 years old, it would be for children who are third and fourth graders in elementary school. These result showed that this program was useful for improving the key elements of resiliency such as positive thinking or impulse control. It is suggested the necessary of resiliency promoting program model and practical guidance with comprehensive measuring methods(narratives, drawing, self-reported questionnaire, behavioral observation). Also, it is necessary to make a training program for the coaches or leaders to operate this program to spread out for child health.

Keywords: children, mental, parents, resilience

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Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen

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In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence

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Authors: Badrane Hasnaa, Bouzahir Brahim

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This article examines the impact of fintech technologies on crowdfunding, particularly their potential to enhance financial inclusion and promote responsible finance. It explores how the adoption of blockchain, artificial intelligence, and other fintech innovations is transforming crowdfunding by making it more accessible, transparent, and ethical. By analyzing case studies and recent data, the article illustrates how these technologies help overcome traditional barriers to financing while promoting sustainable financial practices. The findings suggest that integrating fintech into crowdfunding can not only broaden access to funding for marginalized populations but also encourage more responsible management of financial resources, contributing to a fairer and more resilient economy.

Keywords: crowdfunding, fintech, inclusion financière, finance responsible, blockchain, resilience financière

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Authors: Sarah Mohammed, Huda Allagany, Ayah Barakat, Muna Elyas

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This paper delves into the history and development of ChatGPT, tracing its evolution from its inception by OpenAI to its current state, and emphasizing its design improvements and strategic partnerships. It also explores the performance and applicability of ChatGPT versions 3.5 and 4 in various contexts, examining its capabilities and limitations in producing accurate and relevant responses. Utilizing a quantitative approach, user satisfaction, speed of response, learning capabilities, and overall utility in academic performance were assessed through surveys and analysis tools. Findings indicate that while ChatGPT generally delivers high accuracy and speed in responses, the need for clarification and more specific user instructions persists. The study highlights the tool's increasing integration across different sectors, showcasing its potential in educational and professional settings.

Keywords: artificial intelligence, chat GPT, analysis, education

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Authors: K. Kiniwa, S. Kitagawa, M. Kawamoto, H. Uchiyama

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This study aims to identify phenomenologically the embodiment of soccer in order to analyze soccer games. In this paper the authors focused on the embodiment of sports and the embodiment of the goal type ball games of team sports. The authors revealed that the embodiment of sports is represented by inverse proportional body. It is possible for this structure (body scheme) of intercorporeality of sports to be compared to the symbolic figure of Uroboros which is a monster connected the tails of two snakes. The embodiment of the goal type ball games of team sports has dependency on situation and complexity. In doing this, it revealed that soccer is sensitive and emotional sports.

Keywords: intercorporeality, structure, body scheme, Uroboros, inverse proportional body, dependency on situation, complexity

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Authors: Hsiu-Hua Cheng, Chi-Wei Chen

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Lurking behaviour is common in information-seeking oriented communities. Transferring users with lurking behaviour to be contributors can assist virtual communities to obtain competitive advantages. Based on the ecological cognition framework, this study proposes a model to examine the antecedents of lurking behaviour in information-seeking oriented virtual communities. This study argues desire for emotional support, desire for information support, desire for performance-approach, desire for performance -avoidance, desire for mastery-approach, desire for mastery-avoidance, desire for ability trust, desire for benevolence trust, and desire for integrity trust effect on lurking behaviour. This study offers an approach to understanding the determinants of lurking behaviour in online contexts.

Keywords: lurking behaviour, the ecological cognition framework, Information-seeking oriented virtual communities, desire

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Aron Witkowski, Andrzej Wodecki

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Purpose: This study aims to explore the feasibility and effectiveness of utilizing Generative Artificial Intelligence (GenAI) agents as product managers within the manufacturing sector. It seeks to evaluate whether current GenAI capabilities can fulfill the complex requirements of product management and deliver comparable outcomes to human counterparts. Study Design/Methodology/Approach: This research involved the creation of a support application for product managers, utilizing high-quality sources on product management and generative AI technologies. The application was designed to assist in various aspects of product management tasks. To evaluate its effectiveness, a study was conducted involving 10 experienced product managers from the manufacturing sector. These professionals were tasked with using the application and providing feedback on the tool's responses to common questions and challenges they encounter in their daily work. The study employed a mixed-methods approach, combining quantitative assessments of the tool's performance with qualitative interviews to gather detailed insights into the user experience and perceived value of the application. Findings: The findings reveal that GenAI-based product management agents exhibit significant potential in handling routine tasks, data analysis, and predictive modeling. However, there are notable limitations in areas requiring nuanced decision-making, creativity, and complex stakeholder interactions. The case study demonstrates that while GenAI can augment human capabilities, it is not yet fully equipped to independently manage the holistic responsibilities of a product manager in the manufacturing sector. Originality/Value: This research provides an analysis of GenAI's role in product management within the manufacturing industry, contributing to the limited body of literature on the application of GenAI agents in this domain. It offers practical insights into the current capabilities and limitations of GenAI, helping organizations make informed decisions about integrating AI into their product management strategies. Implications for Academic and Practical Fields: For academia, the study suggests new avenues for research in AI-human collaboration and the development of advanced AI systems capable of higher-level managerial functions. Practically, it provides industry professionals with a nuanced understanding of how GenAI can be leveraged to enhance product management, guiding investments in AI technologies and training programs to bridge identified gaps.

Keywords: generative artificial intelligence, GenAI, NPD, new product development, product management, manufacturing

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Authors: Aydin Azizi, Aburrahman Tanira

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The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.

Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel

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Authors: Jasna Hrncic

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Poor family relations predict depression, but also to other mental health issues. Mediating effect of self-efficacy and differentiation of self and moderating effect of decreased accessibility and/or success of other adaptive and defensive mechanisms for overcoming social disadvantages could explain depression as a specific outcome of dysfunctional family relations. The present study analyzes the mediation effect of self-efficacy and differentiation of self from poor family functioning to depressive symptoms and the moderation effect of deprivation of liberty on the listed mediation effect. Deprivation of liberty has, as a general consequence, a decreased accessibility and/or success of many adaptive and defensive mechanisms. It is hypothesized that: 1) self-efficacy and differentiation of self will mediate between family functioning and depressiveness in the total sample, and 2) deprivation of liberty will moderate the stated relations. Cross-sectional study was conducted among 323 male juveniles in Serbia divided in three groups: 98 adolescents deprived of their liberty due to antisocial behavior (incarcerated antisocial group - IAG), 121 adolescents with antisocial behavior in their natural setting (antisocial control group - CAG) and 105 adolescents in general population (general control group - CGG). The CAG was included along with GCG to control the possible influence that comorbidity of antisocial behavior and depressiveness could have on results. Instruments for family relations assessment were: for a whole family of origin the emotional exchange scale and individuation scale from GRADIR by Knezevic, and for a relationship with mother PCS-YSR and CRPBI by barber, and intimacy, rejection, sacrifice, punishment, demands, control and internal control by Opacic and Kos. Differentiation of self (DOS) is measured by emotional self scale (Opacic), self-efficacy (SE) by general incompetence scale by Bezinovic, and depression by BDI (Back), CES-D (Radloff) and D6R (Momirovic). Two-path structural equation modeling based on most commonly reported fit indices, showed that the mediation model had unfavorable fit to our data for total sample [(χ2 (1, N = 324) = 13.73); RMSEA= .20 (90% CI= [.12, .30]); CFI= .98; NFI= .97; AIC=31.73]. Path model provided an adequate fit to the data only for AIG - and not to the data from ACG and GCG. SE and DOS mediated the relationship between PFF and depressiveness. Test of the indirect effects revealed that 23.85% of PFF influences on depressiveness is mediated by these two mediators (the quotient of mediated effect = .24). Test of specific indirect effects showed that SE mediates 22.17%, while DOS mediates 1.67% of PFF influence on depressiveness. Lack of expected mediation effect could be explained by missing other potential mediators (i.e., relationship with that father, social skills, self-esteem) and lower variability of both predictor and criterion variable due to their low levels on the whole sample and on control subsamples. Results suggested that inaccessibility and/or successfulness of other adaptive and defensive mechanisms for overcoming social disadvantages has a strong impact on the mediation effect of self/efficacy and differentiation of self from poor family functioning to depressive symptoms. Further researches could include other potential mediators and a sample of clinically depressed people.

Keywords: antisocial behavior, mediating effect, moderating effect, natural setting, incarceration

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Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso

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Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.

Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow

Procedia PDF Downloads 87