Search results for: online learning environments

Authors: Majid Bayatian, Mohammadreza Ashouri

Abstract:

Releasing hazardous chemicals is one of the major problems for office buildings in the chemical industry and, therefore, environmental risks are inherent to these environments. The adverse health effects of the airborne concentration of benzene have been a matter of significant concern, especially in oil refineries. The chronic and acute adverse health effects caused by benzene exposure have attracted wide attention. Acute exposure to benzene through inhalation could cause headaches, dizziness, drowsiness, and irritation of the skin. Chronic exposures have reported causing aplastic anemia and leukemia at the occupational settings. Association between chronic occupational exposure to benzene and the development of aplastic anemia and leukemia were documented by several epidemiological studies. Numerous research works have investigated benzene emissions and determined benzene concentration at different locations of the refinery plant and stated considerable health risks. The high cost of industrial control measures requires justification through lifetime health risk assessment of exposed workers and the public. In the present study, a Computational Fluid Dynamics (CFD) model has been proposed to assess the exposure risk of office building around a refinery due to its release of benzene. For simulation, GAMBIT, FLUENT, and CFD Post software were used as pre-processor, processor, and post-processor, and the model was validated based on comparison with experimental results of benzene concentration and wind speed. Model validation results showed that the model is highly validated, and this model can be used for health risk assessment. The simulation and risk assessment results showed that benzene could be dispersion to an office building nearby, and the exposure risk has been unacceptable. According to the results of this study, a validated CFD model, could be very useful for decision-makers for control measures and possibly support them for emergency planning of probable accidents. Also, this model can be used to assess exposure to various types of accidents as well as other pollutants such as toluene, xylene, and ethylbenzene in different atmospheric conditions.

Keywords: health risk assessment, office building, Benzene, numerical simulation, CFD

Procedia PDF Downloads 110

Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

Abstract:

Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

Procedia PDF Downloads 32

Authors: Priscilla Eng Lian Murphy

Abstract:

This study examines the nature of student conceptions of mathematics in higher education using quantitative research methods. This study validates the Short Form of Conception of Mathematics survey as well as reveals the epistemological nature of student conceptions of mathematics. Using a random sample of mathematics students in Australia and New Zealand (N=274), this paper highlighted three key findings, of relevance to lecturers in higher education. Firstly, descriptive data shows that mathematics students in Australia and New Zealand reported that mathematics is about numbers and components, models and life. Secondly, models conceptions of mathematics predicted strong examination performances using regression analyses; and thirdly, there is a positive correlation between high mathematics examination scores and cohesive conceptions of mathematics.

Keywords: higher education, learning mathematics, mathematics performances, student conceptions of mathematics

Procedia PDF Downloads 242

Authors: Mark Salisbury

Abstract:

The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

Procedia PDF Downloads 26

Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

Abstract:

Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

Procedia PDF Downloads 319

Authors: Narayana Murthy Akurathi, Vijaya Lakshmi Marella

Abstract:

The literature is reviewed with regard to online Super critical fluid extraction (SFE) coupled directly with supercritical fluid chromatography (SFC) -mass spectrometry that have typically more sensitive than conventional LC-MS/MS and GC-MS/MS. It is becoming increasingly interesting to use on-line techniques that combine sample preparation, separation and detection in one analytical set up. This provides less human intervention, uses small amount of sample and organic solvent and yields enhanced analyte enrichment in a shorter time. The sample extraction is performed under light shielding and anaerobic conditions, preventing the degradation of thermo labile analytes. It may be able to analyze compounds over a wide polarity range as SFC generally uses carbon dioxide which was collected as a by-product of other chemical reactions or is collected from the atmosphere as it contributes no new chemicals to the environment. The diffusion of solutes in supercritical fluids is about ten times greater than that in liquids and about three times less than in gases which results in a decrease in resistance to mass transfer in the column and allows for fast high resolution separations. The drawback of SFC when using carbon dioxide as mobile phase is that the direct introduction of water samples poses a series of problems, water must therefore be eliminated before it reaches the analytical column. Hundreds of compounds analysed simultaneously by simple enclosing in an extraction vessel. This is mainly applicable for pharmaceutical industry where it can analyse fatty acids and phospholipids that have many analogues as their UV spectrum is very similar, trace additives in polymers, cleaning validation can be conducted by putting swab sample in an extraction vessel, analysing hundreds of pesticides with good resolution.

Keywords: super critical fluid extraction (SFE), super critical fluid chromatography (SFC), LCMS/MS, GCMS/MS

Procedia PDF Downloads 373

Authors: Salman Naseer, Usman Zafar, Iqra Zafar

Abstract:

This study explores the implication of Vehicular Adhoc Network (VANET) - in the rural and urban scenarios that is one domain of Mobile Adhoc Network (MANET). VANET provides wireless communication between vehicle to vehicle and also roadside units. The Federal Commission Committee of United States of American has been allocated 75 MHz of the spectrum band in the 5.9 GHz frequency range for dedicated short-range communications (DSRC) that are specifically designed to enhance any road safety applications and entertainment/information applications. There are several vehicular related projects viz; California path, car 2 car communication consortium, the ETSI, and IEEE 1609 working group that have already been conducted to improve the overall road safety or traffic management. After the critical literature review, the selection of routing protocols is determined, and its performance was well thought-out in the urban and rural scenarios. Numerous routing protocols for VANET are applied to carry out current research. Its evaluation was conceded with the help of selected protocols through simulation via performance metric i.e. throughput and packet drop. Excel and Google graph API tools are used for plotting the graphs after the simulation results in order to compare the selected routing protocols which result with each other. In addition, the sum of the output from each scenario was computed to undoubtedly present the divergence in results. The findings of the current study present that DSR gives enhanced performance for low packet drop and high throughput as compared to AODV and DSDV in an urban congested area and in rural environments. On the other hand, in low-density area, VANET AODV gives better results as compared to DSR. The worth of the current study may be judged as the information exchanged between vehicles is useful for comfort, safety, and entertainment. Furthermore, the communication system performance depends on the way routing is done in the network and moreover, the routing of the data based on protocols implement in the network. The above-presented results lead to policy implication and develop our understanding of the broader spectrum of VANET.

Keywords: AODV, DSDV, DSR, Adhoc network

Procedia PDF Downloads 268

Authors: Ulrike Dowie, Ralph Grothmann

Abstract:

Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

Procedia PDF Downloads 155

Authors: Karish Thavabalan, Aman Sutaria, Alistair Ovenell, Annabelle Parkhouse, Numan Baydemir, Theodore Lally

Abstract:

Background: Open discussions surrounding menopause are often associated with stigma, with many women feeling uncomfortable engaging in them with friends, colleagues, and healthcare professionals. Though the barriers regarding safe discussions of symptom management experienced by menopausal women are well documented, existing research offers little insight into whether these were shared by pre-menopausal women. This study aimed to explore the barriers regarding safe discussions about menopausal symptom management as perceived or experienced by pre-menopausal and menopausal women. Methods: This qualitative study was conducted over a 2-month period (March 2022 - April 2022) under the auspices of Imperial College Business School, London, UK. Snowball sampling was used to recruit both menopausal (age 45-70) and pre-menopausal participants (age <45) and sampling continued until data saturation was achieved. Sixteen semi-structured online interviews were conducted, and transcripts were thematically analyzed following Braun and Clarke’s six-step methodology. Results: A total of 7 higher themes regarding safe discussion of menopausal symptom management were identified by both pre-menopausal and menopausal women, including: “ineffective coping mechanisms,” “perceived onus to self-endure,” “lack of workplace support,” “poor knowledge of management approaches,” “poor healthcare infrastructure,” “poor support from friends and family,” “lack of knowledge and interest from a young age.” Conclusion: Identifying the barriers regarding safe discussion helped to highlight which areas require the most significant intervention. Alongside tackling the barriers, menopausal women face, ultimately, there is a pertinent need to address the lack of insight into menopause from a younger age and to encourage earlier discussions so as to not propagate the cycle of stigma.

Keywords: menopause, safe discussion, symptom management, stigma

Procedia PDF Downloads 48

Authors: Alan T. Sassler

Abstract:

Biofouling is a significant issue for ships, especially those based in warm water ports. Biofouling damages hull coatings, degrades platform hydrodynamics, blocks cooling water intakes, and returns, reduces platform range and speed, and increases fuel consumption. Although platforms are protected to some degree by antifouling paints, these paints are much less effective on stationary platforms, and problematic biofouling can occur on antifouling paint-protected stationary platforms in some environments in as little as a matter of weeks. Remediation hull cleaning operations are possible, but they are very expensive, sometimes result in damage to the vessel’s paint or hull and are generally not completely effective. Ultrasound with sufficient intensity focused on specific frequency ranges can be used to prevent the growth of biofouling organisms. The use of ultrasound to prevent biofouling isn't new, but systems to date have focused on protecting platforms by shaking the hull using internally mounted transducers similar to those used in ultrasonic cleaning machines. While potentially effective, this methodology doesn't scale well to large platforms, and there are significant costs associated with installing and maintaining these systems, which dwarf the initial purchase price. An alternative approach has been developed, which uses highly directional pier-mounted transducers to project high-intensity spread-spectrum ultrasonic energy into the water column focused near the surface. This focused energy has been shown to prevent biofouling at ranges of up to 50 meters from the source. Spreading the energy out over a multi-kilohertz band makes the system both more effective and more environmentally friendly. This system has been shown to be both effective and inexpensive in small-scale testing and is now being characterized on a larger scale in selected marinas. To date, test results have been collected in Florida marinas suggesting that this approach can be used to keep ensonified areas of thousands of square meters free from biofouling, although care must be taken to minimize shaded areas.

Keywords: biofouling, ultrasonic, environmentally friendly antifoulant, marine protection, antifouling

Procedia PDF Downloads 47

Authors: Sarah Barnard, John Arnold, Fehmidah Munir, Sara Bosley

Abstract:

Gender issues in higher education continue to represent a complex issue as institutions grapple with the role that organisations can play in combatting inequality. Schemes like Athena SWAN and the Aurora leadership programme in the UK context are attempting to tackle some of the issues around representation and the recognition of women in the sector. This paper is the first of its kind in reporting findings from a mixed-methods longitudinal study on both professional services and academic women in higher education in the UK. Online surveys have been completed by over 2,000 women in the sector. The qualitative elements include interviews with women and their mentors, and diaries with a select group of women. So far results have shown that contrary to the stereotype of women lacking leadership skills or having no desire to go into higher roles, women in the sector consistently assessed their leadership abilities positively, especially but not only regarding interpersonal interaction and facilitation. Over 80% of women agreed that they felt confident about putting themselves forward for positions of responsibility at work. However, qualitative data shows that confidence remains a salient term for how women talk about the challenges they have faced at work. This suggests that the work needed to challenge systemic gender issues requires action to be driven above the individual level. Overall, academics reported more negative experiences than professional services staff. Similarly BAME women’s responses are more negative. Therefore, the study offers some information on the differential experiences of women. In conclusion, women in higher education are undertaking considerable ‘below the radar’ leadership activities in what they perceive to be a somewhat inhospitable hostile workplace culture. The significant amount of effort expended in the sector is affecting slow, partial impacts on gender inequalities.

Keywords: gender, higher education, leadership, longitudinal research

Procedia PDF Downloads 222

Authors: Vijaya

Abstract:

This paper reports the results of a study that measures the level of receptive vocabularies using the Peabody Picture Vocabulary Test (PPVT) in an ESL context. PPVT is a popular standardized test used to measure the vocabulary level of L1 learners. In this study, PPVT was administered to fourteen 9 to 11 year old Indian ESL learners from the fifth standard from a school in Hyderabad. Their performance is compared with the age appropriate performance of L1 learners. Their performance on noun versus verb items is also compared. The results are discussed concerning the learning goals set by the National Council for Educational Research and Training (NCERT) position paper on Teaching of English in India.

Keywords: national council for educational research and training, India, PPVT, second language acquistion, vocabulary acquisition

Procedia PDF Downloads 287

Authors: Abdelrhman Elagez, Rolla Monib

Abstract:

This empirical study investigates the observed risks associated with adopting Artificial Intelligence (AI) technologies in the construction industry and proposes potential mitigation strategies. While AI has transformed several industries, the construction industry is slowly adopting advanced technologies like AI, introducing new risks that lack critical analysis in the current literature. A comprehensive literature review identified a research gap, highlighting the lack of critical analysis of risks and the need for a framework to measure and mitigate the risks of AI implementation in the construction industry. Consequently, an online survey was conducted with 24 project managers and construction professionals, possessing experience ranging from 1 to 30 years (with an average of 6.38 years), to gather industry perspectives and concerns relating to AI integration. The survey results yielded several significant findings. Firstly, respondents exhibited a moderate level of familiarity (66.67%) with AI technologies, while the industry's readiness for AI deployment and current usage rates remained low at 2.72 out of 5. Secondly, the top-ranked barriers to AI adoption were identified as lack of awareness, insufficient knowledge and skills, data quality concerns, high implementation costs, absence of prior case studies, and the uncertainty of outcomes. Thirdly, the most significant risks associated with AI use in construction were perceived to be a lack of human control (decision-making), accountability, algorithm bias, data security/privacy, and lack of legislation and regulations. Additionally, the participants acknowledged the value of factors such as education, training, organizational support, and communication in facilitating AI integration within the industry. These findings emphasize the necessity for tailored risk assessment frameworks, guidelines, and governance principles to address the identified risks and promote the responsible adoption of AI technologies in the construction sector.

Keywords: risk management, construction, artificial intelligence, technology

Procedia PDF Downloads 27

Authors: Delband Yekta Moazami

Abstract:

Background: For proper care and treatment of HIV patients and drug users, the medical staff and physicians must have a correct and positive attitude and knowledge towards such patients. We aimed to assess the attitudes in a sample of health care workers (HCW) working in different hospitals and clinics and medical students in Georgia towards HIV infected people and drug users in Tbilisi. Method: We conducted a cross-sectional study to assess attitudes of health care workers towards people living with HIV and drug users in hospitals and clinics in Tbilisi. The study was carried out from 1st of May 2020 till 30th of September 2020. Data were collected using a self-administered structured online questionnaire. With this tool we evaluated four facets of attitudes: Discrimination, Acceptance of HIV/AIDS patients, Acceptance of drug users and Fear. All data were imported and analyzed with the software SPSS 22 for windows. Results: In total data was collected from168 respondents, that among them 107 (65%) were women and majority of the participants were medical doctors. Women had more acceptance attitudes rather than men towards drug abusers. We found significant differences regarding expressing negative attitudes among HCW who were more than 50 years old comparing with other age groups in all four aspects. Medical doctors expressed more acceptances towards people with HIV and drug users comparing two other groups. Also our study revealed that the group with working experience 21 years and more, showed more discriminatory attitudes comparing other groups. Conclusion: Based on our study findings, there are significant differences regarding respondent’s attitudes based on gender, medical specialty and working experience in health care system. People struggling with HIV and drug use need nonjudgmental and positive behaviors from health care workers and physicians in order to help them for harm reduction and receiving appropriate treatment.

Keywords: hiv, addiction, attitudes, healthcare workers

Procedia PDF Downloads 61

Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

Abstract:

The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

Procedia PDF Downloads 138

Authors: Ritvik Chauhan, Vijay Kumar Baraik

Abstract:

Crime is a rare event on earth surface. It is not simple but a complex event occurring in a spatio- temporal environment. Crime is one of the most serious security threats to human environments as it may result in harm to the individuals through the loss of property, physical and psychological injuries. The conventional studies done on different nature crime was mostly related to laws, psychological, social and political themes. The geographical areas are heterogeneous in their environmental conditions, associations between structural conditions, social organization which contributing specific crimes. The crime pattern analysis is made through theories in which criminal events occurs in persistent, identifiable patterns in a particular space and time. It will be the combined analysis of spatial factors and rational factors to the crime. In this study, we are analyzing the combined factors for the origin of crime against children. Children have always been vulnerable to victimization more because they are silent victims both physically and mentally to crimes and they even not realize what is happening with them. Their trusting nature and innocence always misused by criminals to perform crimes. The nature of crime against children is changed in past years like child rape, kidnapping &abduction, selling & buying of girls, foeticide, infanticide, prostitution, child marriage etc turned to more cruel and inhuman. This study will focus on understanding the space-time pattern of crime against children during the period 2001-2012. It also makes an attempt to explore and ascertain the association of crimes categorised against children, its rates with various geographical and socio-demographic factors through causal analysis using selected indicators (child sex-ratio, education, literacy rate, employment, income, etc.) obtained from the Census of India and other government sources. The outcome of study will help identifying the high crime regions with specified nature of crimes. It will also review the existing efforts and exploring the new plausible measure for tracking, monitoring and minimization of crime rate to meet the end goal of protecting the children from crimes committed against them.

Keywords: crime against children, geographic profiling, spatio-temporal analysis, hotspot

Procedia PDF Downloads 199

Authors: Thiru Vandeyar

Abstract:

The present study set out to determine how Q methodology may be used as an inclusive education policy development process. Utilising Q-methodology as a strategy of inquiry, this qualitative instrumental case study set out to explore how teachers, as a crucial but often neglected human resource, may be included in developing policy. A social constructivist lens and the theoretical moorings of Proudford’s emancipatory approach to educational change anchored in teachers’ ‘writerly’ interpretation of policy text was employed. Findings suggest that Q-method is a unique research approach to include teachers’ voices in policy development. Second, that beliefs, attitudes, and professionalism of teachers to improve teaching and learning using ICT are integral to policy formulation. The study indicates that teachers have unique beliefs about what statements should constitute a school’s information and communication (ICT) policy. Teachers’ experiences are an extremely valuable resource in and should not be ignored in the policy formulation process.

Keywords: teachers, q-methodology, education policy, ICT

Procedia PDF Downloads 70

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 142

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

Abstract:

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

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

Procedia PDF Downloads 54

Authors: Frazer G. Thompson

Abstract:

Israel is a nation of cultural and historical diversity, yet the success factors for a modern Bedouin-Arab high-tech entrepreneur seem to be different from those of other Jewish-Israeli citizens. The purpose of this descriptive narrative case study is to explore how an Arab-Israeli all Negev-Bedouin technology company has succeeded in the Israeli high-tech industry by utilizing technology and engineering career opportunities available to Bedouin youth for ‘Sadel Tech,’ at Be’er-Sheva, the Negev, Israel. Methods: The strategy of inquiry seeks to explore real-life contextual understandings, multi-level perspectives, and the cultural influences of personal, community, educational, and entrepreneurial factors. The research methodology includes in-depth one-on-one interviews, focus group sessions, and overt observation to explore the meaning and understanding of the constructs toward determining the effect all or a few of the elements may have on the overall success factors of the company. Results: Study results indicate that the state-run educational system in Israel fails to adequately integrate important aspects of Bedouin culture into the learning environment. However, Bedouin entrepreneurs are finding ways to compensate for these inadequacies by utilizing non-traditional methods of teaching, learning, and doing business. Government incentives for Bedouin start-ups are also recognized as contributors. Employees of Sadel live and work in the Negev, the Gaza Strip, and the West Bank, further informing the study that the traditions of tribal etiquette continue to contribute to modern Bedouin-Arab business culture. Conclusion: Bedouin's business success in Israel is a multi-dimensional concept. While cultural acumen plays a prominent and unique role for both Arab-Israelis and Jewish-Israelis in economic and entrepreneurial pursuits, the marginalization of the Bedouin continues to contribute to the lack of educational and professional opportunities for Bedouin in Israel. Although recognized as important at the government level, programs necessary to implement the infrastructure required to support Bedouin entrepreneurship in Israel remain infantile. The Israeli Government is providing opportunities through grants and other incentives for Bedouin entrepreneurial start-ups, indicating that Israel has recognized the impact of this growing demographic. However, although many Bedouin graduates from University each year with advanced degrees, opportunities for Bedouin within the Israeli high-tech sector remain scarce.

Keywords: Bedouin education, Bedouin entrepreneur, economic anthropology, ethnic business opportunities, Israeli tech, Silicon Wadi

Procedia PDF Downloads 102

Authors: Nikhil Byanna, Abdolghani Ebrahimi, Diego Klabjan

Abstract:

How does one objectively measure the performance of an individual offensive lineman in the NFL? The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.

Keywords: offensive lineman, player performance, NFL, machine learning

Procedia PDF Downloads 126

Authors: Isaiah Phillip Smith

Abstract:

It is reported that alcohol consumption accounts for 3 million annual deaths globally, thus, it is a significant public health challenge internationally. The excessive consumption of alcohol is argued in literature to be related to problematic behaviors like crime, accident, fighting, violence, and unprotected sex, among others. Alcohol consumption among university students in South Africa particularly is considered endemic – with a prevalence rate of 25.27%, 32.34%, and 23.34% across universities, colleges, and high schools. Adopting the tenets of social learning and ecological theories, the culture of drinking amongst male university students is critically explored. This study found that age, gender, early exposure to alcohol, and peer pressure are significant factors contributing to alcohol consumption amongst university students. While participants acknowledged that moderate and responsible consumption of alcohol is necessary, they agree that it does not translate to responsible drinking behaviours.

Keywords: alcohol, drinking, university, students

Procedia PDF Downloads 109

Authors: Reinhard Haas, Amela Ajanovic

Abstract:

In recent years especially electricity generation from intermittent sources like wind and solar has increased remarkably. To balance electricity supply over time calls for storages has been launched. Because intermittency also exists over longer periods – months, years, especially the need for long-term electricity storages is discussed. The major conclusions of our analysis are: (i) Despite many calls for a prophylactic construction of new storage capacities with respect to all centralized long-term storage technologies the future perspectives will be much less promising than currently indicated in several papers and discussions; (ii) new long term hydro storages will not become economically attractive in general in the next decades; however, daily storages will remain the cheapest option and the most likely to be competitive; (iii) For PtG-technologies it will also become very hard to compete in the electricity markets despite a high technological learning potential. Yet, for hydrogen and methane there are prospects for use in the transport sector.

Keywords: storages, electricity markets, power-to-gas, hydro pump storages, economics

Procedia PDF Downloads 462

Authors: Amro Matyori, Fatimah Sherbeny, Askal Ali, Olayiwola Popoola

Abstract:

Objectives: The study evaluated the impact of COVID-19 on anxiety levels in the general population in the United States. Methods: The study used an online questionnaire. It adopted the Generalized Anxiety Disorder Assessment (GAD-7) instrument. It is a self-administered scale with seven items used as a screening tool and severity measure for generalized anxiety disorder. The participants rated the frequency of anxiety symptoms in the last two weeks on a Likert scale, which ranges from 0-3. Then the item points are summed to provide the total score. Results: Thirty-two participants completed the questionnaire. Among them, 24 (83%) females and 5 (17%) males. The age range of 18-24-year-old represented the most respondents. Only one of the participants tested positive for the COVID-19, and 39% of them, one of their family members, friends, or colleagues, tested positive for the coronavirus. Moreover, 10% have lost a family member, a close friend, or a colleague because of COVID-19. Among the respondents, there were ten who scored approximately five points on the GAD-7 scale, which indicates mild anxiety. Furthermore, eight participants scored 10 to 14 points, which put them under the category of moderate anxiety, and one individual who was categorized under severe anxiety scored 15 points. Conclusions: It is identified that most of the respondents scored the points that put them under the mild anxiety category during the COVID-19 pandemic. It is also noticed that severe anxiety was the lowest among the participants, and people who tested positive and/or their family members, close friends, and colleagues were more likely to experience anxiety. Additionally, participants who lost friends or family members were also at high risk of anxiety. It is obvious the COVID-19 outcomes and too much thinking about the pandemic put people under stress which led to anxiety. Therefore, continuous assessment and monitoring of psychological outcomes during pandemics will help to establish early well-informed interventions.

Keywords: anxiety and covid-19, covid-19 and mental health outcomes, influence of covid-19 on anxiety, population and covid-19 impact on mental health

Procedia PDF Downloads 191

Authors: Zhichao Song, Swanand Vaidya

Abstract:

Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

Procedia PDF Downloads 95

Authors: Sujui Yang, Peeraya Somsak, Markus Blut

Abstract:

This research examines the international tourists in Chiang Mai, Thailand. It aims to study non-Thai tourists’ of this region to better understand their behavior and motives influencing the choice of cultural heritage tourists in Chiang Mai, Thailand. The data includes questionnaires of 250 tourists in the study area. The most important motives influencing decisions choices are several concerning customers’ perspectives on tourist destinations in cultural heritage in Chiang Mai province. Thai tourists in Chiang Mai are single, 72.5 percent are in the age of 21-40 years old and 50% of sample group are from central and northern of Thailand. Tourists’ motives capture the factor loading as well as the corresponding show 5 components: relaxation motives, place/ physical motives, learning motives, image motives, and achievement motives.

Keywords: tourists motives, cultural heritage, Chiang Mai, customers’ perspectives

Procedia PDF Downloads 361

Authors: Islam Abou El-Magd, Elham Ali, Moahmed Zakzouk, Nesreen Khairy, Naglaa Zanaty

Abstract:

Maine environment and coastal zone are wealthy with natural resources that contribute to the local economy of Egypt. The Gulf of Suez and Red Sea area accommodates diverse human activities that contribute to the local economy, including oil exploration and production, touristic activities, export and import harbors, etc, however, it is always under the threat of pollution due to human interaction and activities. This research aimed at integrating in-situ measurements and remotely sensed data with hydrodynamic model to map and simulate the oil pollution. High-resolution satellite sensors including Sentinel 2 and Plantlab were functioned to trace the oil pollution. Spectral band ratio of band 4 (infrared) over band 3 (red) underpinned the mapping of the point source pollution from the oil industrial estates. This ratio is supporting the absorption windows detected in the hyperspectral profiles. ASD in-situ hyperspectral device was used to measure experimentally the oil pollution in the marine environment. The experiment used to measure water behavior in three cases a) clear water without oil, b) water covered with raw oil, and c) water after a while from throwing the raw oil. The spectral curve is clearly identified absorption windows for oil pollution, particularly at 600-700nm. MIKE 21 model was applied to simulate the dispersion of the oil contamination and create scenarios for crises management. The model requires precise data preparation of the bathymetry, tides, waves, atmospheric parameters, which partially obtained from online modeled data and other from historical in-situ stations. The simulation enabled to project the movement of the oil spill and could create a warning system for mitigation. Details of the research results will be described in the paper.

Keywords: oil pollution, remote sensing, modelling, Red Sea, Egypt

Procedia PDF Downloads 327

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

Abstract:

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

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

Procedia PDF Downloads 353

Authors: Americo Pereira, Ricardo Carvalho, Pedro Carvalho, Luis Corte-Real

Abstract:

Generating 3D content is a task mostly done by hand. It requires specific knowledge not only on how to use the tools for the task but also on the fundamentals of a 3D environment. In this work, we show that automatic generation of content can be achieved, from a scene script, by leveraging existing tools so that non-experts can easily engage in a 3D content generation without requiring vast amounts of time in exploring and learning how to use specific tools. This proposal carries several benefits, including flexible scene synthesis with different levels of detail. Our preliminary results show that the automatically generated content is comparable to the content generated by users with low experience in 3D modeling while vastly reducing the amount of time required for the generation and adds support to implement flexible scenarios for visual scene visualization.

Keywords: 3D virtualization, multimedia, scene script, synthesis

Procedia PDF Downloads 248

Authors: Vivian A. Panes, Raymond John S. Rebong, Miel Q. Diaz

Abstract:

Moringa oleifera Lam. is known mainly for its high nutritional value and medicinal properties contributing to its popular reputation as a 'miracle plant' in the tropical climates where it usually grows. The main objective of this study is to discover the genes and gene products involved in abiotic stress-induced activity that may impact the M. oleifera Lam. mature seeds as well as their corresponding functions. In this study, RNA-sequencing and de novo transcriptome assembly were performed using two assemblers, Trinity and Oases, which produced 177,417 and 120,818 contigs respectively. These transcripts were then subjected to various bioinformatics tools such as Blast2GO, UniProt, KEGG, and COG for gene annotation and the analysis of relevant metabolic pathways. Furthermore, FPKM analysis was performed to identify gene expression levels. The sequences were filtered according to the 'response to stress' GO term since this study dealt with stress response. Clustered Orthologous Groups (COG) showed that the highest frequencies of stress response gene functions were those of cytoskeleton which make up approximately 14% and 23% of stress-related sequences under Trinity and Oases respectively, recombination, repair and replication at 11% and 14% respectively, carbohydrate transport and metabolism at 23% and 9% respectively and defense mechanisms 16% and 12% respectively. KEGG pathway analysis determined the most abundant stress-response genes in the phenylpropanoid biosynthesis at counts of 187 and 166 pathways for Oases and Trinity respectively, purine metabolism at 123 and 230 pathways, and biosynthesis of antibiotics at 105 and 102. Unique and cumulative GO term counts revealed that majority of the stress response genes belonged to the category of cellular response to stress at cumulative counts of 1,487 to 2,187 for Oases and Trinity respectively, defense response at 754 and 1,255, and response to heat at 213 and 208, response to water deprivation at 229 and 228, and oxidative stress at 508 and 488. Lastly, FPKM was used to determine the levels of expression of each stress response gene. The most upregulated gene encodes for thiamine thiazole synthase chloroplastic-like enzyme which plays a significant role in DNA damage tolerance. Data analysis implies that M. oleifera stress response genes are directed towards the effects of climate change more than other stresses indicating the potential of M. oleifera for cultivation in harsh environments because it is resistant to climate change, pathogens, and foreign invaders.

Keywords: stress response, genes, Moringa oleifera, transcriptomics

Procedia PDF Downloads 127