Search results for: scholarship of teaching and learning (SoTL)

Authors: Khaled Mohammed

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This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

Procedia PDF Downloads 141

Authors: Michal Kozubík, Svetlana Síthová

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Aim: Aim of this study is to introduce the method of instrumental enrichment to people who works in the helping professions, and show further possibilities of its realization with children from socially disadvantaged backgrounds into society. Methods: We focused on Feuerstein’s Instrumental Enrichment method, its theoretical grounds and practical implementation. We carried out questionnaires and directly observed children from the disadvantaged background in Partizánske district. Results: We outlined the issues of children from disadvantaged social environment and their opportunity of social integration using the method. The findings showed the utility of Feuerstein method. Conclusions: We conclude that Feuerstein methods are very suitable for children from socially disadvantaged background and importance of social workers and special educator co-operation.

Keywords: Feuerstein, inclusion, education, socially disadvantaged background

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Authors: Rania A. Aboalela, Javed I. Khan

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This research presents a learning assessment theory of Cognitive Skill in Concept Space (CS2) to measure the assessed knowledge in terms of cognitive skill levels of the concepts. The cognitive skill levels refer to levels such as if a student has acquired the state at the level of understanding, or applying, or analyzing, etc. The theory is comprised of three constructions: Graph paradigm of a semantic/ ontological scheme, the concept states of the theory and the assessment analytics which is the process to estimate the sets of concept state at a certain skill level. Concept state means if a student has already learned, or is ready to learn, or is not ready to learn a certain skill level. The experiment is conducted to prove the validation of the theory CS2.

Keywords: cognitive skill levels, concept states, concept space, knowledge assessment theory

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

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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

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Authors: Nasibullina A., Leonov D.

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The ultrasonography method is actively used for the early diagnosis of various le-sions in the human body, including the mammary gland. The incidence of breast cancer has increased by more than 20%, and mortality by 14% since 2008. The correctness of the diagnosis often directly depends on the qualifications and expe-rience of a diagnostic medical sonographer. That is why special attention should be paid to the practical training of future specialists. Anatomical phantoms are ex-cellent teaching tools because they accurately imitate the characteristics of real hu-man tissues and organs. The purpose of this work is to create a breast phantom for practicing ultrasound diagnostic skills in grayscale and elastography imaging, as well as ultrasound-guided biopsy sampling. We used silicone-like compounds ranging from 3 to 17 on the Shore scale hardness units to simulate soft tissue and lesions. Impurities with experimentally selected concentrations were added to give the phantom the necessary attenuation and reflection parameters. We used 3D modeling programs and 3D printing with PLA plastic to create the casting mold. We developed a breast phantom with inclusions of varying shape, elasticity and echogenicity. After testing the created phantom in B-mode and elastography mode, we performed a survey asking 19 participants how realistic the sonograms of the phantom were. The results showed that the closest to real was the model of the cyst with 9.5 on the 0-10 similarity scale. Thus, the developed breast phantom can be used for ultrasonography, elastography, and ultrasound-guided biopsy training.

Keywords: breast ultrasound, mammary gland, mammography, training phantom, tissue-mimicking materials

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Authors: Priscilla Eng Lian Murphy

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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

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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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

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Authors: Ulrike Dowie, Ralph Grothmann

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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

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Authors: Florin Leon

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This paper describes a simulator of traffic scenarios tailored to facilitate autonomous driving model training for urban environments. With the rising prominence of self-driving vehicles, the need for diverse datasets is very important. The proposed simulator provides a flexible framework that allows the generation of custom scenarios needed for the validation and enhancement of trajectory prediction algorithms. Its controlled yet dynamic environment addresses the challenges associated with real-world data acquisition and ensures adaptability to diverse driving scenarios. By providing an adaptable solution for scenario creation and algorithm testing, this tool proves to be a valuable resource for advancing autonomous driving technology that aims to ensure safe and efficient self-driving vehicles.

Keywords: autonomous driving, car simulator, machine learning, model training, urban simulation environment

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Authors: Hassan Ali Abood Nassrullah, Jabbar Fadeel Mahdi, Mohammed Salih Mahdi Alkurdi, Ali Al Mousawi, Saad Ibrahim Al-Ghabban, Abdul Amir H. Kadhum, Ahmed Al-Amiery

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Background: Q fever is a zoonotic disease characterized by its clinical polymorphism and can present acutely as fever, pneumonia, hepatitis, and chronically as infective endocarditis, arthritis, osteomyelitis, or hepatitis. Objective: The aim of this study is To estimate the prevalence of cases of Q fever in hospitalized febrile patients in Imam Al Hussain Teaching Medical City in Karbala. Methods: One hundred patients with pyrexia were admitted to the medical ward from 1st August to 31st December 2019. Serological procedures fortified by Enzyme-linked Immunosorbent Assay test. Patients were considered to have acute Q fever when the specific antibodies (IgM and IgG) of phase II of Coxiella burnetii were positive. Results: The mean age of the patients was 35.05±12.93 years; females constituted 60% of them. Eighteen patients (18%) showed positive results for IgM, a lower proportion (13% n=13) had positive IgG levels, and 9% showed equivocal results. Statistical analysis revealed a significant association between positive IgM levels of the female gender and in patients consuming unpasteurized milk. One patient (female aged 60 years) died in the hospital, while all other patients were discharged well. Two female patients were pregnant, and one of them had an abortion. Conclusions: Q fever is more common in febrile patients. The study indicates that this disease should not be overlooked in the differential diagnosis of acute fever. Serological testing should be performed in all patients with acute febrile illness with an unsettling diagnosis.

Keywords: antibodies, frequency, immunoglobulin IgM, Q fever

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Authors: Mohammed Nasser Al-Suqri

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Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

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Authors: M. S. M. Anjalee Umesha Bandara

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Hela Veda Shastra is a science that is an endowment from generation to generation. There is also an individualistic science and indigenous practice of traditional herbs. There are many effective cures for snakes, fractures, head cancer, cuts, lunatics, reflexology, etc. Hela physicians who rescued them from infections caused by snakes have recognized poems to remember the medicines they used to cure the patients. Due to the harmony of the Hela Osu and Hela Knowledge poetry collection, it has become easy for the juniors of the Hela Veda generation to gain medical knowledge. It is a research problem whether it is possible to arrive at a correct conclusion about the patient form of the snake information thread through the existing Dhuta characteristics of Hela Serpa Vedakam. This research was done with the assumption that snake venom can be successfully treated according to its characteristics. In this research, two generations related to the Ratmalavatiya Vedaparamparava and the Vannihatpattu of the Kalla Veda generation have been identified as Veda Paramparas who treat and created Dutha Kavya, including the form of the Serpent Dasthana. They have collected ancient books, documents and interviews related to qualitative research on snake disease treatment. In addition, collecting data by referring to books related to Hela medicine. The ancient indigenous lineage methods that are superior to modern Western science's snake therapy should save the Hela's amazing wealth of wisdom for the future, leaving aside the selfishness of keeping the teaching to themselves.

Keywords: snake venom medicine, vedic genealogy, Dhuta characteristic, snake

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Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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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

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Authors: Sozon, Pok Wei Fong, Sia Bee Chuan, Omar Hamdan Mohammad

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Owing to the widespread phenomenon of plagiarism and cheating in higher education institutions (HEIs), it is now difficult to ensure academic integrity and quality education. Moreover, the COVID-19 pandemic has intensified the issue by shifting educational institutions into virtual teaching and assessment mode. Thus, there is a need to carry out an extensive and holistic systematic review of the literature to highlight plagiarism and cheating in both prevalence and form among HEIs. This paper systematically reviews the literature concerning academic plagiarism and cheating in HEIs to determine the most common forms and suggest strategies for resolution and boosting the academic integrity of students. The review included 45 articles and publications for the period from February 12, 2018, to September 12, 2022, in the Scopus database aligned with the Systematic Review and Meta-Analysis (PRISMA) guidelines in the selection, filtering, and reporting of the papers for review from which a conclusion can be drawn. Based on the results, out of the studies reviewed, 48% of the quantitative results of students were plagiarized and obtained through cheating, with 84% coming from the fields of Humanities. Moreover, Psychology and Social Sciences studies accumulated 9% and 7% articles respectively. Based on the results, individual factors, institutional factors, and social and cultural factors have contributed to plagiarism and cheating cases in HEIs. The resolution of this issue can be the establishment of ethical and moral development initiatives and modern academic policies and guidelines supported by technological strategies of testing.

Keywords: plagiarism, cheating, systematic review, academic integrity

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Authors: Antti Nurminen, Avleen Malhi

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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

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

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

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Authors: Bersufekad Wubie

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Introduction: Near visual impairment is presenting near visual acuity of the eye worse than N6 at a 40 cm distance. Teachers' regular duties, such as reading books, writing on the blackboard, and recognizing students' faces, need good near vision. If a teacher has near-visual impairment, the work output is unsatisfactory. Objective: The study was aimed to assess the prevalence and associated factors near vision impairment among school teachers at Gondar city Northwest Ethiopia, August 2022. Methods: To select 567 teachers in Gondar city schools, an institutional-based cross-sectional study design with a multistage sampling technique were used. The study was conducted in selected schools from May 1 to May 30, 2022. Trained data collectors used well-structured Amharic and English language questionnaires and ophthalmic instruments for examination. The collected data were checked for completeness and entered into Epi data version 4.6, then exported to SPSS version 26 for further analysis. A binary and multivariate logistic regression model was fitted. And associated factors of the outcome variable. Result: The prevalence of near visual impairment was 64.6%, with a confidence interval of 60.3%–68.4%. Near visual impairment was significantly associated with age >= 35 years (AOR: 4.90 at 95% CI: 3.15, 7.65), having prolonged years of teaching experience (AOR: 3.29 at 95% CI: 1.70, 4.62), having a history of ocular surgery (AOR: 1.96 at 95% CI: 1.10, 4.62), smokers (AOR: 2.21 at 95% CI: 1.22, 4.07), history of ocular trauma (AOR : 1.80 at 95%CI:1.11,3.18 and uncorrected refractive error (AOR:2.01 at 95%CI:1.13,4.03). Conclusion and recommendations: This study showed the prevalence of near vision impairment among school teachers was high, and it is not a problem of the presbyopia age group alone; it also happens at a young age. So teachers' ocular health should be well accommodated in the school's eye health.

Keywords: Gondar, near visual impairment, school, teachers

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Authors: Nikhil Byanna, Abdolghani Ebrahimi, Diego Klabjan

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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

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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

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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

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Authors: Leen Sulaimani, Maryam Hafiz, Naba Ali, Roba Alsharif

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One of Amazon’s most crucial online systems is artificial intelligence. Amazon would not have a worldwide successful online store, an easy and secure way of payment, and other services if it weren’t for artificial intelligence and machine learning. Amazon uses AI to expand its operations and enhance them by upgrading the website daily; having a strong base of artificial intelligence in a worldwide successful business can improve marketing, decision-making, feedback, and more qualities. Aiming to have a rational AI system in one’s business should be the start of any process; that is why Amazon is fortunate that they keep taking care of the base of their business by using modern artificial intelligence, making sure that it is stable, reaching their organizational goals, and will continue to thrive more each and every day. Artificial intelligence is used daily in our current world and is still being amplified more each day to reach consumer satisfaction and company short and long-term goals.

Keywords: artificial intelligence, Amazon, business, customer, decision making

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Authors: Sujui Yang, Peeraya Somsak, Markus Blut

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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

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Authors: Omar Mayyas

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Clinical decision-making (CDM) is essential to community health nursing (CHN) education. For this reason, nursing educators are responsible for developing these skills among nursing students because nursing students are exposed to highly critical conditions after graduation. However, due to limited exposure to real-world situations, many nursing students need help developing clinical decision-making skills in this area. Therefore, the impact of Virtual Simulation (VS) on community health nursing students' clinical decision-making in nursing education has to be investigated. This study aims to examine the difference in CDM ability among CHN students who received traditional education compared to those who received VS classes, to identify the factors that may influence CDM ability differences between CHN students who received a traditional education and VS classes, and to provide recommendations for educational programs that can enhance the CDM ability of CHN students and improve the quality of care provided in community settings. A mixed-method study will conduct. A randomized controlled trial will compare the CDM ability of CHN students who received 1hr traditional class with another group who received 1hr VS scenario about diabetic patient nursing care. Sixty-four students in each group will randomly select to be exposed to the intervention from undergraduate nursing students who completed the CHN course at York University. The participants will receive the same Clinical Decision Making in Nursing Scale (CDMNS) questionnaire. The study intervention will follow the Medical Research Council (MRC) approach. SPSS and content analysis will use for data analysis.

Keywords: clinical decision-making, virtual simulation, community health nursing students, community health nursing education

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

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

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

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Authors: Stephanie Cheng, Benjamin Poh, Vivyan Tay, Sachin Mathur

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Aim: Diabetes mellitus (DM) is a worldwide pandemic affecting 500 million people. It is known to be associated with increased susceptibility to soft tissue infections (STI). Despite being a major public health burden, the literature relating the effects of DM and the presentation, severity and healing of STIs in general surgical patients remain limited. Methods: We conducted a retrospective review of all patients admitted with STI in a tertiary teaching hospital over a 12-month period. Patient demographics and surgical outcomes were collected and analyzed. Results: During the study period, 1059 patients were admitted for STIs, of which 936 (88%) required surgical intervention. Diabetic patients were presented with a higher body-mass index (BMI) (28 vs 26), larger abscess size (24 vs 14 cm²) and a longer length of stay (LOS)(4.4 days vs 2.9 days). They also underwent a higher proportion of wide debridement as well as application of negative pressure wound therapy (NPWT) (42% vs 35%). More diabetic patients underwent subsequent re-operation within the same sitting (8 vs 4). There were no differences in re-admission rates within 30 days nor subsequent abscess formation in those followed for 6 months. Conclusion: The incidence of STIs among DM patients represents a significant disease burden; surgeons should consider intensive patient counseling and partnering with primary care providers in order to help reduce the incidence of future STI admissions based on lifestyle modification and glucose control.

Keywords: general surgery, emergency general surgery, acute care surgery, soft tissue infections, diabetes mellitus

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

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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

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Authors: Aparna Datta, Mahabub Alam

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Animal welfare is comparatively new area of research in Bangladesh and welfare concern for animal is increasing day by day. The study was conducted to investigate the animal welfare violations during treatment at different level of hospitals in Bangladesh and India. This study was conducted between January and May, 2017. The recorded data (N=180) were categorized into eight major types of violation like - delay in starting treatment, non-specific treatment, surgery without anesthesia, use of unsterilized needle, rough and painful handling, fearful approach, multiple pricking during injection and use of blunt needle. Categorized groups were analyzed according to different hospitals like Upazila Veterinary Hospitals, Bangladesh (UVHs), SAQ-Teaching Veterinary Hospital, Bangladesh (SAQTVH) and Veterinary College and Research Institute, India (VCRI). Among all hospitals, violation during treatment more frequently occurred in UVH. Among all violations, surgery without anesthesia was only found in UVH (80%) and it was belong to considerable number of cases (80%). In the view of other major violations like - non-specific treatment was 69% in UVHs, 13% in SAQTVH and 5% in VCRI. Use of unsterilized instruments during treatment was also higher in UVHs (65%) than SAQTVH (5%) and VCRI (1%). But delay in starting treatment varied insignificantly and it was 26-42% across the different levels of hospitals. Although multiple pricking during injection was found 30% cases in UVH, but statistical variations with other level of hospitals were unnoticed (p>0.05). The findings of this study will help to take necessary steps to control violation against animal welfare during treatment. A comprehensive study considering all levels of hospitals including field treatment is also recommended to find out the welfare violations during treatment.

Keywords: animal welfare, treatment, veterinary hospitals, violations

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Authors: Raquel Pérez Estébanez

Abstract:

Context: The study focuses on the importance of informed and engaged university students in relation to sustainable development goals (SDGs). It explores existing literature on students' perceptions, knowledge, and actions regarding these goals. Research Aim: The aim of this research is to assess the level of commitment and knowledge about the SDGs among university students, specifically within their university environment. The study was conducted during the 2022-2023 academic year. Methodology: The methodology used in this study is empirical. A questionnaire was prepared and administered to university students from a public university in Spain. The response rate was 80%. The questionnaire was then validated using a Cronbach test, which resulted in a reliability coefficient of 88%. The data collected was analyzed using SPSS software. Confirmatory factor analysis (CPA) was initially conducted to strengthen the factors, followed by multivariate analysis to delve deeper into the topic and identify the factors that explain the SDG model. Findings: The primary results of the study revealed that factors such as cooperative learning, action statements, perceived functions for universities, sources of information about sustainable development that students use, actions taken by students for sustainable development reasons in the past month, and attitudes towards education for sustainable development (ESD) contribute to an understanding of the awareness of university students regarding the SDGs. Theoretical Importance: The findings highlight the importance of further research and collaborative efforts to enhance SDG education. It emphasizes the role of higher education institutions (HEIs) in fostering the learning of skills and values, preparing students for decision-making, and promoting pluralistic development and sustainable societies. The study also emphasizes the need to link sustainability not only to environmental aspects but also to social and economic considerations. Data Collection and Analysis Procedures: The questionnaire was administered to university students, resulting in an 80% response rate. The collected data was validated using a Cronbach test to ensure reliability. SPSS software was used for data analysis, starting with confirmatory factor analysis (CPA) and followed by multivariate analysis. Questions Addressed: The research aimed to address the level of commitment and knowledge about the SDGs among university students, specifically within their university environment. It also sought to identify factors that contribute to the understanding of awareness among university students regarding the SDGs. Conclusion: The study highlights the importance of informed and engaged university students in relation to the SDGs. It emphasizes the role of higher education institutions in fostering sustainable development education and preparing students for decision-making. The findings suggest the need for further research and collaborative efforts to enhance SDG education and foster a sustainable future.

Keywords: SDG, awareness, higher education, ESD

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Authors: Ugwu Elias Ikechukwu

Abstract:

Discussions on bilingualism have always dwelt on how the mother tongue interferes with the target language. This interference is considered a serious problem in second language learning. Usually, the interference has been phonological. But the objective of this research is to explore how the target language interferes with the mother tongue. In the case of the Igbo language, it interferes with English mostly at the phonological level while English interferes with Igbo at the realm of vocabulary. The result is a new language \"Engligbo\" which is a hybrid of English and Igbo. The Igbo language spoken by about 25 million people is one of the three most prominent languages in Nigeria. This paper discusses the phenomenal Engligbo, and other implications for Igbo learners of English. The method of analysis is descriptive. A number of recommendations were made that would help teachers handle problems arising from such mutual interferences.

Keywords: reciprocal interferences, bilingualism, implications, language pedagogy

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Authors: Caihong Sun, Xizi Zhang

Abstract:

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

Procedia PDF Downloads 222