Search results for: intercultural intelligence

Authors: R. A. Harun, N. M. Ishak, N. Yusoff, S. Amat

Abstract:

This quantitative research is aimed to identify the level of leadership quality and emotional intelligence for members of Students' Representatives Council (SRC) of Malaysian Public Universities (MPU). The variables include the leadership quality and emotional quotient (EQ). 238 SRC members in MPU were selected as subjects of the study. Data were collected using two instruments i.e. Malaysian Emotional Quotient Inventory (MEQI) and Ayu-Noriah Leadership Audit Trail Inventory (Ayu-Noriah, LATI). Data were analyzed using descriptive (mean and percentage). Research findings showed that the subjects scored highly in four out of five EQ domains (Self-Regulations, Self-Motivation, Empathy and Social Skills). However, the subjects scored medium to low in Self-Awareness. Analysis on the sub domains (a total of 28 sub domains) showed that the subjects scored high in 17 sub domains for EQ, whilst another 11 were at medium level. The overall analysis indicates that the subjects have high level of EQ. Findings on their leadership qualities showed that they obtained high scores in all seven factors that were measured i.e. Strategy and Leadership Model, Recruit, Review Performance and Honor, Deploy Strategically, Developing, Engage and Retain and Built HR Capabilities/Line Ownership. The overall score for leadership qualities was found to be high.

Keywords: emotional intelligence, leadership, students representative council, Malaysian public universities

Procedia PDF Downloads 271

Authors: Shalini Tripathi, Pardeep Kumar

Abstract:

The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

Procedia PDF Downloads 132

Authors: Ronit Even Zahav

Abstract:

Objectives: Mother-daughter relationships are often portrayed as one of the most constitutive ties that shape women's identities throughout their lives. Yet, to the best of author’s knowledge, only few studies examine mother-daughter relationships in adulthood in the context of cross-cultural transition. Most of them focus on the mother-daughter relationship among one origin group. Hence, the existing knowledge about these relationships in adulthood, in the context of intercultural transition and encounters between different cultures, remain limited. Based on a critical feminist approach critical and cultural perspectives the current study focuses on a cross-cultural comparison of adult mother-daughter relationships among three groups of origin: Ethiopia, Russia, and Israel. The study aimed to: Explore the voices of women participating in a mother-daughter discourse in the context of gender and ethnicity; examine the differences in the mother-daughter relationship through number of factors (e.g. expectations of similarity and difference, perceptions of gender roles, gender identity, emotional closeness, sharing and stress) and finally, to develop a gender informed tool for understanding the gender dialectic in mother-daughter relationship in the context of cross cultural transitions. Method: 37 dyads of mothers and adult daughters participated in a qualitative study. A semi-structured interview was conducted that included questions about socio-demographic characteristics, language proficiency, social distance, closeness, emotional stress, and expectations of similarity and difference in mother-daughter relationships. Results: Analysis of the findings yielded three relationship patterns of gender dialectic and expectations of similarity and difference that characterize the groups of origin. Ethiopian mothers reported more sharing their daughters, fewer expectations of similarity, and felt more stress in the relationship compered to women from the two other origin groups. Conclusions: The study highlighted the impact of intercultural transition and social exclusion on mother-daughter relationships in adulthood in the context of the gender dialectic and women’s status in society. The presentation will explore the findings that were brought up by participants. The discussion will focus on the practices related to gender dialectic and intersecting inequalities regarding diverse groups and discuss gender development reducing inequalities and promoting empowerment to transform oppressive conditions.

Keywords: gender informed perspectives, gender dialectic, mother-daughter relationships, multiculturalism

Procedia PDF Downloads 67

Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore

Abstract:

In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.

Keywords: CDSS, EHR, business intelliegence, tools

Procedia PDF Downloads 137

Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

Abstract:

This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

Procedia PDF Downloads 52

Authors: R. Kanthavel, R. Yogesh Kumar, T. Narendrakumar, B. Santhosh, S. Surya Prakash

Abstract:

This paper primarily focuses on developing an affordable personal assistant and the implementation of it in the field of Artificial Intelligence (AI) to create a virtual assistant/friend. The problem in existing home automation techniques is that it requires the usage of exact command words present in the database to execute the corresponding task. Our proposed work is ATOM a.k.a ‘Artificial intelligence Talking Omnipresent Machine’. Our inspiration came from an unlikely source- the movie ‘Iron Man’ in which a character called J.A.R.V.I.S has omnipresence, and device controlling capability. This device can control household devices in real time and send the live information to the user. This device does not require the user to utter the exact commands specified in the database as it can capture the keywords from the uttered commands, correlates the obtained keywords and perform the specified task. This ability to compare and correlate the keywords gives the user the liberty to give commands which are not necessarily the exact words provided in the database. The proposed work has a higher flexibility (due to its keyword extracting ability from the user input) comparing to the existing work Intelligent Home automation System (IHAS), is more accurate, and is much more affordable as it makes use of WI-FI module and raspberry pi 2 instead of ZigBee and a computer respectively.

Keywords: home automation, speech recognition, voice control, personal assistant, artificial intelligence

Procedia PDF Downloads 336

Authors: Sirine Sayed, Mostapha Tarfaoui, Abdelmalek Toumi, Youssef Qarssis, Mohamed Daly, Chokri Bouraoui

Abstract:

This paper delves into the combination of additive manufacturing (AM) and artificial intelligence (AI) to solve challenges related to the mechanical behavior of AM-produced parts. The article highlights the fundamentals and benefits of additive manufacturing, including creating complex geometries, optimizing material use, and streamlining manufacturing processes. The paper also addresses the challenges associated with additive manufacturing, such as ensuring stable mechanical performance and material properties. The role of AI in improving the static behavior of AM-produced parts, including machine learning, especially the neural network, is to make regression models to analyze the large amounts of data generated during experimental tests. It investigates the potential synergies between AM and AI to achieve enhanced functions and personalized mechanical properties. The mechanical behavior of parts produced using additive manufacturing methods can be further improved using design optimization, structural analysis, and AI-based adaptive manufacturing. The article concludes by emphasizing the importance of integrating AM and AI to enhance mechanical operations, increase reliability, and perform advanced functions, paving the way for innovative applications in different fields.

Keywords: additive manufacturing, mechanical behavior, artificial intelligence, machine learning, neural networks, reliability, advanced functionalities

Procedia PDF Downloads 9

Authors: Xiaochen Mu

Abstract:

Whether in common law countries that adhere to the "commercial copyright theory" or in civil law countries that center around "author's rights," the standards for judging originality have undergone continuous adjustments in response to the development of information technology. The adherence to originality standards does not arbitrarily dictate that all types of works be judged according to a single standard of originality, nor does it rigidly ignore the changes in creative methods and dissemination models brought about by technology. Adjustments and interpretations should be allowed based on the different forms of expression of works. Appropriate adjustments and interpretations are our response to technological advancements. However, what should be upheld are the principles and bottom lines of these adjustments and interpretations, namely the legislative intent and purpose of copyright law, which are to encourage the creation and dissemination of outstanding cultural works and to promote the flourishing of culture.

Keywords: generative artificial intelligence, originality, works, copyright

Procedia PDF Downloads 41

Authors: Leonard Kabeya Mukeba Yakasham

Abstract:

The theoretical machinery from singularity theory introduced by Glolubitsky, Stewart, and Schaeffer, to study equivariant bifurcation problem is completed and expanded wile generalized to the multiparameter context. In this setting the finite deterinancy theorem or normal forms, the stability of equivariant bifurcation problem, and the structural stability of universal unfolding are discussed. With Yakam Matrix the solutions are limited for some partial differential equations stochastic nonlinear of the open questions in singularity artificial intelligence for future.

Keywords: equivariant bifurcation, symmetry singularity, equivariant jets and transversality; normal forms, universal unfolding instability, structural stability, artificial intelligence, pdens, yakam matrix

Procedia PDF Downloads 25

Authors: Moshe Davidian, Shlomo Mark, Yotam Lurie

Abstract:

With the rapid development of technology and the concomitant growth in the capability of Artificial Intelligence (AI) systems and their power, the ethical challenges involved in these systems are also evolving and increasing. In recent years, various organizations, including governments, international institutions, professional societies, civic organizations, and commercial companies, have been choosing to address these various challenges by publishing ethical codes for AI systems. However, despite the apparent agreement that AI should be “ethical,” there is debate about the definition of “ethical artificial intelligence.” This study investigates the various AI ethical codes and their key ethical values. From the vast collection of codes that exist, it analyzes and compares 25 ethical codes that were found to be representative of different types of organizations. In addition, as part of its literature review, the study overviews data collected in three recent reviews of AI codes. The results of the analyses demonstrate a convergence around seven key ethical values. However, the key finding is that the different AI ethical codes eventually reflect the type of organization that designed the code; i.e., the organizations’ role as regulator, user, or developer affects the view of what ethical AI is. The results show a relationship between the organization’s role and the dominant values in its code. The main contribution of this study is the development of a list of the key values for all AI systems and specific values that need to impact the development and design of AI systems, but also allowing for differences according to the organization for which the system is being developed. This will allow an analysis of AI values in relation to stakeholders.

Keywords: artificial intelligence, ethical codes, principles, values

Procedia PDF Downloads 107

Authors: Shahnaz Bashir, Abel Usoro, Imran Khan

Abstract:

Hofstede’s culture model is an important model to study culture between different societies. He collected data from world-wide and performed a comprehensive study. Hofstede’s cultural model is widely accepted and has been used to study cross cultural influences in different areas like cross-cultural psychology, cross cultural management, information technology, and intercultural communication. This study investigates the societal cultural aspects of knowledge sharing in virtual communities.

Keywords: knowledge management, knowledge sharing, societal culture, virtual communities

Procedia PDF Downloads 405

Authors: Heejin Song

Abstract:

Employing a critical action research approach that rejects essentialist onto-epistemological orientations to research in English language teaching (ELT) and interrogates the hegemonic relations in the knowledge construction and reconstruction processes, this study illuminates how an action research-informed pedagogical practice can transform the English for academic purposes (EAP) teaching to be more culturally and linguistically inclusive and critically oriented for English language learners’ advancement in academic literacies skills. More specifically, this paper aims to showcase the action research-informed pedagogical innovations that emphasize multilingual learners’ multiliteracies engagement and experiential education-oriented learning to facilitate the development of learners’ academic literacies, intercultural communicative competence, and inclusive global citizenship in the context of Canadian university EAP classrooms. The pedagogical innovations through action research embarked in response to growing discussions surrounding pedagogical possibilities of plurilingualism in ELT and synchronous online teaching. The paper is based on two iterations of action research over the pandemic years between 2020 and 2022. The data includes student work samples, focus group interviews, anonymous surveys, teacher feedback and comments on student work and teaching reflections. The first iteration of the action research focused on the affordances of multimodal expressions in individual learners’ academic endeavors for their literacy skills development through individual online activities such as ‘my language autobiography,’ ‘multimodal expression corner’ and public speeches. While these activities help English language learners enhance their knowledge and skills of English-spoken discourses, these tasks did not necessarily require learners’ team-based collaborative endeavors to complete the assigned tasks. Identifying this area for improvement in the instructional design, the second action research cycle/iteration emphasized collaborative performativity through newly added performance/action-based innovative learning tasks, including ‘situational role-playing’, ‘my cooking show & interview’, and group debates in order to provide learners increased opportunities to communicate with peers who joined the class virtually from different parts of the world and enhance learners’ intercultural competence through various strategic and pragmatic communicative skills to collaboratively achieve their shared goals (i.e., successful completion of the given group tasks). The paper exemplifies instances wherein learners’ unique and diverse linguistic and cultural strengths were amplified, and critical literacies were further developed through learners’ performance-oriented multiliteracies engagement. The study suggests that the action research-informed teaching practice that advocates for collaborative multiliteracies engagement serves to facilitate learners’ activation of their existing linguistic and cultural knowledge and contributes to the development of learners’ academic literacy skills. Importantly, the study illuminates that such action research-informed pedagogical initiatives create an inclusive space for learners to build a strong sense of connectedness as global citizens with increased intercultural awareness in their community of language and cultural practices, and further allow learners to actively participate in the construction of ‘collaborative relations of power’ with their peers.

Keywords: action research, EAP, higher education, multiliteracies

Procedia PDF Downloads 79

Authors: Samer Muthana Sarsam, Abdul Samad Shibghatullah, Chit Su Mon, Abd Aziz Alias, Hosam Al-Samarraie

Abstract:

Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education. However, their specific role within the educational context and the level of legal support for their implementation remain unclear. Therefore, this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. To achieve this objective, English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the collected tweets. User sentiments, including disgust, surprise, sadness, anger, fear, joy, anticipation, and trust, as well as positive and negative sentiments, were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

Keywords: generative artificial intelligence chatbots, bard, higher education, topic modelling, sentiment analysis

Procedia PDF Downloads 83

Authors: PR

Abstract:

Renewable energy is a sustainable substitute to fossil fuels, which are depleting and attributing to global warming as well as greenhouse gas emissions. Renewable energy innovations including solar, wind, and geothermal have grown significantly and play a critical role in meeting energy demands recently. Consequently, Artificial Intelligence (AI) could further enhance the benefits of renewable energy systems. The combination of renewable technologies and AI could facilitate the development of smart grids that can better manage energy distribution and storage. AI thus has the potential to optimize the efficiency and reliability of renewable energy systems, reduce costs, and improve their overall performance. The conventional methods of using smart micro-grids are to connect these micro-grids in series or parallel or a combination of series and parallel. Each of these methods has its advantages and disadvantages. In this study, the proposal of using the method of connecting microgrids in a spiral manner is investigated. One of the important reasons for choosing this type of structure is the two-way reinforcement and exchange of each inner layer with the outer and upstream layer. With this model, we have the ability to increase energy from a small amount to a significant amount based on exponential functions. The geometry used to close the smart microgrids is based on nature.This study provides an overview of the applications of algorithms and models of AI as well as its advantages and challenges in renewable energy systems.

Keywords: artificial intelligence, renewable energy sources, spiral model, optimize

Procedia PDF Downloads 8

Authors: Martha Serrano-Arias, Martha Frías-Armenta

Abstract:

Significant results have been found both supporting universality of emotion recognition and cultural background influence. Thus, the aim of this research was to test a Mexican version of the MTSI in different cultures to find differences in their performance. The MTSI-Mx assesses through a scenario approach were subjects must evaluate real persons. Two target persons were used for the construction, a man (FS) and a woman (AD). The items were grouped in four variables: Picture, Video, and FS and AD scenarios. The test was applied to 201 students from Mexico and Germany. T-test for picture and FS scenario show no significance. Video and AD had a significance at the 5% level. Results show slight differences between cultures, although a more comprehensive research is needed to conclude which culture can perform better in this kind of assessments.

Keywords: emotion recognition, MTSI, social intelligence, transcultural study

Procedia PDF Downloads 325

Authors: Gabriel Chavira, Jorge Orozco, Salvador Nava, Eduardo Álvarez, Julio Rolón, Roberto Pichardo

Abstract:

Ambient Intelligence promotes a shift in computing which involves fitting-out the environments with devices to support context-aware applications. One of main objectives is the reduction to a minimum of the user’s interactive effort, the diversity and quantity of devices with which people are surrounded with, in existing environments; increase the level of difficulty to achieve this goal. The mobile phones and their amazing global penetration, makes it an excellent device for delivering new services to the user, without requiring a learning effort. The environment will have to be able to perceive all of the interaction techniques. In this paper, we present the PICTAC model (Perceiving touch Interaction through TAgging Context), which similarly delivers service to members of a research group.

Keywords: ambient intelligence, tagging context, touch interaction, touching services

Procedia PDF Downloads 384

Authors: Jinan Laurentia Woo

Abstract:

This paper explores the intersection of technology, music education, and social-emotional learning (SEL) with a focus on Latin America. It delves into the impact of music education on social-emotional skills development, highlighting the universal significance of music across various life stages. The integration of artificial intelligence (AI) in music education is discussed, emphasizing its potential to enhance learning experiences. The paper also examines the implementation of SEL strategies in Latin American public schools, emphasizing the importance of fostering social-emotional well-being in educational settings. Challenges such as unequal access to technology and education in the region are addressed, calling for further research and investment in tech-assisted music education.

Keywords: music education, social emotional learning, educational technology, Latin America, artificial intelligence, music

Procedia PDF Downloads 58

Authors: Magda Silva

Abstract:

This paper presents the empirical and the theoretical principles associated with the Duke in Brazil Summer Program. Using a sociocultural model and critical theory, this study abroad maximizes students’ ability to enrich language competence, intercultural skills, and critical thinking. The fourteen-year implementation of this project demonstrates the global importance of foreign language teaching as the program unfolds into real life scenarios within the cultures of distinct regions of Brazil; Cosmopolitan Rio, in the southeast, and rural Belém, northern Amazon region.

Keywords: study abroad, critical thinking, sociocultural theory, foreign language, empirical, theoretical

Procedia PDF Downloads 409

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: artificial intelligence and office, NLP, deep learning, text classification

Procedia PDF Downloads 200

Authors: Antti Nurminen, Avleen Malhi

Abstract:

Significant progress in intelligent systems in combination with exceedingly wide application domains having machine learning as the core technology are usually opaque, non-intuitive, and commonly complex for human users. We use innovative IoT technology which monitors and analyzes moisture, humidity, luminosity and temperature levels to assist end users for optimization of environmental conditions for their houseplants. For plant health monitoring, we construct a system yielding the Normalized Difference Vegetation Index (NDVI), supported by visual validation by users. We run the system for a selected plant, basil, in varying environmental conditions to cater for typical home conditions, and bootstrap our AI with the acquired data. For end users, we implement a web based user interface which provides both instructions and explanations.

Keywords: explainable artificial intelligence, intelligent agent, IoT, NDVI

Procedia PDF Downloads 163

Authors: Xiaojiao Duan, Zhaoxia Yi, Maria Assumpta Komugabe, Munirpallam A. Venkataramanan

Abstract:

This study explores stakeholders' perceptions and use of AI in university admissions using a conceptual model. The model suggests that AI expertise mediates the relationship between various factors (positions, experience, perceived benefits, concerns) and the desire to adopt AI. By reviewing existing research, the study identifies variables, correlations, and research gaps. The findings highlight the influence of institutional positions, AI expertise, knowledge, perceived advantages, and concerns on attitudes and intentions toward AI implementation. The review provides a framework for future research, emphasizes ethical AI use, and offers practical insights for admissions stakeholders.

Keywords: artificial intelligence, college admissions, ethical considerations, technology adoption, perceptions of AI

Procedia PDF Downloads 57

Authors: Silvia Zanazzi

Abstract:

Artificial intelligence (AI) has become an integral part of our world, transitioning from scientific exploration to practical applications that impact daily life. The emergence of generative AI is reshaping education, prompting new questions about the role of teachers, the nature of learning, and the overall purpose of schooling. While AI offers the potential for optimizing teaching and learning processes, concerns about discrimination and bias arising from training data and algorithmic decisions persist. There is a risk of a disconnect between the rapid development of AI and the goals of building inclusive educational environments. The prevailing discourse on AI in education often prioritizes efficiency and individual skill acquisition. This narrow focus can undermine the importance of collaborative learning and shared experiences. A growing body of research challenges this perspective, advocating for AI that enhances, rather than replaces, human interaction in education. This study aims to examine the relationship between AI and education critically. Reviewing existing research will identify both AI implementation’s potential benefits and risks. The goal is to develop a framework that supports the ethical and effective integration of AI into education, ensuring it serves the needs of all learners. The theoretical reflection will be developed based on a review of national and international scientific literature on artificial intelligence in education. The primary objective is to curate a selection of critical contributions from diverse disciplinary perspectives and/or an inter- and transdisciplinary viewpoint, providing a state-of-the-art overview and a critical analysis of potential future developments. Subsequently, the thematic analysis of these contributions will enable the creation of a framework for understanding and critically analyzing the role of artificial intelligence in schools and education, highlighting promising directions and potential pitfalls. The expected results are (1) a classification of the cognitive biases present in representations of AI in education and the associated risks and (2) a categorization of potentially beneficial interactions between AI applications and teaching and learning processes, including those already in use or under development. While not exhaustive, the proposed framework will serve as a guide for critically exploring the complexity of AI in education. It will help to reframe dystopian visions often associated with technology and facilitate discussions on fostering synergies that balance the ‘dream’ of quality education for all with the realities of AI implementation. The discourse on artificial intelligence in education, highlighting reductionist models rooted in fragmented and utilitarian views of knowledge, has the merit of stimulating the construction of alternative perspectives that can ‘return’ teaching and learning to education, human growth, and the well-being of individuals and communities.

Keywords: education, artificial intelligence, teaching, learning

Procedia PDF Downloads 20

Authors: Parisa Mansour

Abstract:

Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

Procedia PDF Downloads 63

Authors: Chandan Hegde, K. Ashwini

Abstract:

Commonsense reasoning is the simulation of human ability to make decisions during the situations that we encounter every day. It has been several decades since the introduction of this subfield of artificial intelligence, but it has barely made some significant progress. The modern computing aids also have remained impotent in this regard due to the absence of a strong methodology towards commonsense reasoning development. Among several accountable reasons for the lack of progress, drawing inference out of commonsense knowledge-base stands out. This review paper emphasizes on a detailed analysis of representation of reasoning uncertainties and feasible prospects of programming aids for drawing inferences. Also, the difficulties in deducing and systematizing commonsense reasoning and the substantial progress made in reasoning that influences the study have been discussed. Additionally, the paper discusses the possible impacts of an effective inference technique in commonsense reasoning.

Keywords: artificial intelligence, commonsense reasoning, knowledge base, uncertainty in reasoning

Procedia PDF Downloads 187

Authors: Fiyinfoluwa Giwa, Nicholas Ngepah

Abstract:

This paper investigates the relationship between the Fourth Industrial Revolution and food security in South Africa. The Ordinary Least Square was adopted from 2012 Q1 to 2021 Q4. The study used artificial intelligence investment and the food production index as the measure for the fourth industrial revolution and food security, respectively. Findings reveal a significant and positive coefficient of 0.2887, signifying a robust statistical relationship between AI adoption and the food production index. As a policy recommendation, this paper recommends the introduction of incentives for farmers and agricultural enterprises to adopt AI technologies -and the expansion of digital connectivity and access to technology in rural areas.

Keywords: Fourth Industrial Revolution, food security, artificial intelligence investment, food production index, ordinary least square

Procedia PDF Downloads 75

Authors: Naci Büyükkaracığan

Abstract:

Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.

Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics

Procedia PDF Downloads 410

Authors: M. Caramihai, Irina Severin

Abstract:

This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques

Procedia PDF Downloads 420

Authors: Arwa Alnowaiser, Hala Shoukri

Abstract:

The ‘FreeAITherapist’ is an artificial intelligence application that uses the power of AI to offer advice and mental health counseling to its users through its chatbot services. The AI therapist is designed to understand users' issues, concerns, and problems and respond appropriately; it provides empathy and guidance and uses evidence-based therapeutic techniques. With its user-friendly platform, it ensures accessibility for individuals in need, regardless of their geographical location. This website was created in direct response to the growing demand for mental health support, aiming to provide a cost-effective and confidential solution. Through promising confidentiality, it considers user privacy and data security. The ‘FreeAITherapist’ strives to bridge the gap in mental health services, offering a reliable resource for individuals seeking guidance and counseling to improve their overall well-being.

Keywords: artificial intelligence, mental health, AI therapist, website, counseling

Procedia PDF Downloads 44

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 149

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 103