Search results for: online safety

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Simon B. N. Thompson

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Cortisol is important to our immune system, regulates our stress response, and is a factor in maintaining brain temperature. Saliva cortisol is a practical and useful non-invasive measurement that signifies the presence of the important hormone. Electrical activity in the jaw muscles typically rises when the muscles are moved during yawning and the electrical level is found to be correlated with the cortisol level. In two studies using identical paradigms, a total of 108 healthy subjects were exposed to yawning-provoking stimuli so that their cortisol levels and electrical nerve impulses from their jaw muscles was recorded. Electrical activity is highly correlated with cortisol levels in healthy people. The Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details were collected and exclusion criteria applied for voluntary recruitment: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, and stroke. Significant differences were found between the saliva cortisol samples for the yawners as compared with the non-yawners between rest and post-stimuli. Significant evidence supports the Thompson Cortisol Hypothesis that suggests rises in cortisol levels are associated with yawning. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: cortisol, diagnosis, neurological disease, thompson cortisol hypothesis, yawning

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis

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Authors: Aliyu Damri

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In every educational institution, students of mass communication receive training to report events and issues accurately and objectively in accordance with official controls. However, the complex nature of society today made it possible to use WhatsApp platform that revolutionizes the means of sharing information, ideas, and experiences. This paper examined how students in the Department of Mass Communication, Abdu Gusau Polytechnic, Talata Mafara used WhatsApp platform in spreading fake news. It used in depth interview techniques and focus group discussion with students as well as the use of published materials to gather related and relevant data. Also, the paper used procedures involved to analyze long interview content. This procedure includes observation of a useful utterance, development of expanded observation, examination of interconnection of observed comments, collective scrutiny of observation for patterns and themes, and review and analysis of the themes across all interviews for development of thesis. The result indicated that inadequate and absent of official controls guiding the conduct of online information sharing, inaccuracies and poor source verification, lack of gate keeping procedures to ensure ethical and legal provisions, bringing users into the process, sharing all information, availability of misinformation, disinformation and rumor and problem of conversation strongly encouraged the emergence of fake news. Surprisingly, the idea of information as a commodity has increased, and transparency of a source as new ethics emerged.

Keywords: disinformation, fake news, group, mass communication, misinformation, WhatsApp

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Authors: Hela Fathallah

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With 6,500 spoken languages all over the world but 80 percent of online content available only in 10 languages – English, Chinese, Spanish, Japanese, Arabic, Portuguese, German, French, Russian, and Korean – language represents a barrier to the universal access to knowledge, information and services that the internet wants to provide. Translation and its related fields of localization, interpreting, globalization, and internationalization, remove that barrier for billions of people worldwide, unlocking new markets for technology companies, mobile device makers, service providers and language vendors as well. This paper gathers different surveys conducted in different regions of the world that demonstrate a growing demand for consumption of web content with distinctive values and in languages others than the aforementioned ones. It also adds new insights to the contribution of translation in languages preservation. The idea that English is the language of internet and that, in a globalized world, everyone should learn English to cope with new technologies is no longer true. This idea has reached its limits. It collides with cultural diversity and differences around the world and generates an accelerated rate of languages extinction. Studies prove that internet exacerbates this rate and web giants such as Facebook or Google are, today, facing the impact of such a misconception of globalization. For internet and dot-com companies, localization is the solution; they are spending a significant amount of time to understand what people want and to figure out how to provide it. They are committed to making their content accessible, if not in all the languages spoken today, at least in most of them, and to adapting it to most cultures. Technology has broken down the barriers of time and space, and it will break down the language barrier as well by undertaking a process of translation and localization and through a new definition of globalization that takes into consideration these two processes.

Keywords: globalization, internet, localization, translation

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Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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Authors: Hasnizan Aksah, Adi Irfan Che Ani

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Refurbished historic government buildings should perform as intended to support the organization’s goals that enhance occupant satisfaction. However, these buildings may have issues associated with functional performance evaluation. The aim of this study is to develop a Post Occupancy Evaluation (POE) sustainability assessment tool for functional performance evaluation of refurbished historic government buildings. Developing an assessment tool requires a strategic methodology for a logical and cohesive tool that incorporating relevant theories and practical experiences. In this study, mixed method approaches use to collect all necessary data to achieve the objectives of this study. The design of sampling involves are interviews and survey questionnaires to relevant professionals in order to evaluate the criteria and problem encircled in functional performance evaluation. Then, the involvement of expert panels is required in establishing the assessment tool. During the process of investigation on the functional performance criteria, it was discovered that is seen to be critical in aspects of comfort, safety, and services. The proposed assessment tool has a significant role in providing opportunities for the improvement of building performance especially on functional performance for the future historic government building refurbishment project. It is hoped that the tool developed from this study will give benefits to related professionals, public agencies, local municipality, and relevant interested parties in historic building management.

Keywords: refurbished historic government buildings, functional performance, Post Occupancy Evaluation, sustainability

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Authors: M. Ananthakrishnan, Sunil K Patil, Koti Naveen, Inuganti Hemanth Kumar

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State estimation output of EMS forms the base case for all other advanced applications used in real time by a power system operator. Ensuring tuning of state estimator is a repeated process and cannot be left once a good solution is obtained. This paper attempts to demonstrate methods to improve state estimator solution by identifying incorrect modelling and telemetry inputs to the application. In this work, identification of database topology modelling error by plotting static network using node-to-node connection details is demonstrated with examples. Analytical methods to identify wrong transmission parameters, incorrect limits and mistakes in pseudo load and generator modelling are explained with various cases observed. Further, methods used for active and reactive power tuning using bus summation display, reactive power absorption summary, and transformer tap correction are also described. In a large power system, verifying all network static data and modelling parameter on regular basis is difficult .The proposed tuning methods can be easily used by operators to quickly identify errors to obtain the best possible state estimation performance. This, in turn, can lead to improved decision-support capabilities, ultimately enhancing the safety and reliability of the power grid.

Keywords: active power tuning, database modelling, reactive power, state estimator

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Authors: Sajjad Esmaeili Aghdam

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Economics typically conceptualizes individual behavior as the consequence of external states, for example, budgets and prices (or respective beliefs) and choices. As the main goal, we focus on the influence of a range of Behavioral Economics factors on Strategies of Digital Marketing, evaluation of strategies and deformation of it into highly prospective marketing strategies. The different forms of behavioral prospects all lead to the succeeding two main results. First, the steadiness of the economic dynamics in a currency union be contingent fatefully on the level of economic incorporation. More economic incorporation leads to more steady economic dynamics. Electronic word-of-mouth (eWOM) is “all casual communications focused at consumers through Internet-based technology connected to the usage or characteristics of specific properties and services or their venders.” eWOM can take many methods, the most significant one being online analyses. Writing this paper, 72 articles have been gathered, focusing on the title and the aim of the article from research search engines like Google Scholar, Web of Science, and PubMed. Recent research in strategic management and marketing proposes that markets should not be viewed as a given and deterministic setting, exogenous to the firm. Instead, firms are progressively abstracted as dynamic inventors of market prospects. The use of new technologies touches all spheres of the modern lifestyle. Social and economic life becomes unbearable without fast, applicable, first-class and fitting material. Psychology and economics (together known as behavioral economics) are two protruding disciplines underlying many theories in marketing. The wide marketing works papers consumers’ none balanced behavior even though behavioral biases might not continuously be steadily called or officially labeled.

Keywords: behavioral economics, digital marketing, marketing strategy, high impact strategies

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Authors: Mohamed Ali MiladKrem Salem, Sergio F.Breña, Sanjay R. Arwade, Simi T. Hoque

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The location of the main lateral‐load resisting system in high-rise buildings may have positive impacts on sustainability through a reduction in operational energy consumption, and this paper describes an assessment of the accompanying effects on structural performance. It is found that there is a strong influence of design for environmental performance on the structural performance the building, and that systems selected primarily with an eye towards energy use reduction may require substantial additional structural stiffening to meet safety and serviceability limits under lateral load cases. We present a framework for incorporating the environmental costs of meeting structural design requirements through the embodied energy of the core structural materials and also address the issue of economic cost brought on by incorporation of environmental concerns into the selection of the structural system. We address these issues through four case study high-rise buildings with differing structural morphologies (floor plan and core arrangement) and assess each of these building models for cost and embodied energy when the base structural system, which has been suggested by architect Kenneth Yeang based on environmental concerns, is augmented to meet lateral drift requirements under the wind loads prescribed by ASCE 7-10.

Keywords: sustainable, embodied, Outrigger, skyscraper, morphology, efficiency

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Authors: Ali Saghaei, Negar Ghotbeddin, Ebrahim Rajabzadeh Ghatrami, Milad Maniat

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The use of herbs as natural additives in fish diets are used to enhance the efficiency and safety systems. The use of herbs, garlic, due to the structure and composition of it has beneficial role in human nutrition and animal nutrition. This study was conducted evaluate the effect different levels of garlic (Allium sativum) powder on the some serum biochemical parameters of Oscar fish (Astronotus ocellatus). Fish were divided into four groups fed on diets containing garlic in different levels; 5 g kg˗1, 10 g kg-1, 20 g kg-1, 30 g kg-1 diet and the control group diet was without garlic. A total number of 300 fish was used and Triplicate groups of Oscar fish with initial weight of 12.43±0.24 g were hand-fed to visual satiation at three meals per day. The experiment extended for two months. Total Protein (TP), Albumin (ALB), Globulin (GLB) and Albumin/Globulin (A/G) ratio, were determined. Based on the results, no significant differences were seen among treatments and control groups during the experimental period for TP, ALB, GLB, and A/G ratio (p > 0.05). Although, the highest amount of serum total protein and globulin levels were observed in diet containing 10 g kg-1 of garlic. Also, the highest value of albumin and A/G were observed in diet containing 20 g kg-1 of garlic, but there were no significant difference with other treatments. The results of this study show that addition of garlic Allium sativum to fish diet can improve fish health.

Keywords: garlic (Allium sativum), serum, Oscar fish (Astronotus ocellatus), iran

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Authors: T. Abdulkadir

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Most often, marking and assessment of multiple choice kinds of examinations have been opined by many as a cumbersome and herculean task to accomplished manually in Nigeria. Usually this may be in obvious nexus to the fact that mass numbers of candidates were known to take the same examination simultaneously. Eventually, marking such a mammoth number of booklets dared and dread even the fastest paid examiners who often undertake the job with the resulting consequences of stress and boredom. This paper explores the evolution, as well as the set aim to envision and transcend marking the Multiple Choice Objectives- type examination into a thing of creative recreation, or perhaps a more relaxing activity via the use of the mobile phone. A more “pragmatic” dimension method was employed to achieve this work, rather than the formal “in-depth research” based approach due to the “novelty” of the mobile-smartphone e-Marking Scheme discovery. Moreover, being an evolutionary scheme, no recent academic work shares a direct same topic concept with the ‘use of cell phone as an e-marking technique’ was found online; thus, the dearth of even miscellaneous citations in this work. Additional future advancements are what steered the anticipatory motive of this paper which laid the fundamental proposition. However, the paper introduces for the first time the concept of mobile-smart phone e-marking, the steps to achieve it, as well as the merits and demerits of the technique all spelt out in the subsequent pages.

Keywords: cell phone, e-marking scheme (eMS), mobile phone, mobile-smart phone, multiple choice objectives (MCO), smartphone

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Authors: Norshaffika I. Zaiedy Nor, Andrew P. Smith

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Background: Training is essential to develop individuals’ expertise to meet current and future job demands and to improve work performance. At the same time, individuals’ well-being is crucial to ensure that they can fully and positively carry out their daily duties. In addition to the studies that have examined what constitutes well-being and the factors behind it, many researchers have investigated the predictors of training effectiveness and transfer of training. However, there has been very little integration between them. This study was an attempt to bridge the gap between training effectiveness predictors and well-being. Purpose: This research paper aimed to investigate the association between well-being among employees and psychosocial characteristics, together with training variables. Training variables consist of motivation to learn; learning; implementation intention; and cognitive dissonance. Methodology: In total, 210 workers who had undergone various training programs completed an online survey measuring various psychosocial characteristics, four training variables, and level of well-being. Findings: The results showed that certain types of positive psychosocial characteristics (e.g., positive personality, positive work behaviors, positive work and resources) predict motivation to learn, learning and implementation intention. Meanwhile, negative psychosocial characteristics (e.g. negative work demands and resources, negative coping) predict cognitive dissonance. Also, all the training variables had a moderate to high correlation with well-being. However, after controlling other variables (age, gender, education and psychosocial characteristics), none of the training variables predicted well-being. Self-determination theory, cognitive dissonance theory, and the DRIVE model were used to explain these findings. Conclusion: As there is limited research on the integration of training variables with well-being, this study gives a new perspective in the field of both training and well-being. Further investigations are needed to examine the relationships between them.

Keywords: cognitive dissonance, implementation intention, learning, motivation to learn, psychosocial characteristics, well-being

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Authors: H. Haryati, A. Nor Azura

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Over the turn of the century, the advertising landscape has evolved significantly, from print media to digital media. In line with the shift to the advanced science and technology dramatically shake the framework of societies Fifth Industrial Revolution (IR5.0), technological endeavors have increased exponentially, which influenced user interaction more inspiring through online advertising that intentionally leads to buying behavior. Users are more accustomed to interactive content that responds to their actions. Thus, immersive experience has transformed into a new engagement experience To centennials. The purpose of this paper is to investigate pleasure and arousal as the fundamental elements of consumer emotions and affective responses to marketing stimuli. A quasi-experiment procedure will be adopted in the research involving 40 undergraduate students in Nilai, Malaysia. This study employed a 2 (celebrity endorser vs. Social media influencer) X 2 (high and low visual complexity) factorial between-subjects design. Participants will be exposed to a printed version depicting a fashion product endorsed by a celebrity and social media influencers, presented in high and low levels of visual complexity. While the questionnaire will be Distributing during the lab test session is used to control their honesty, real feedback, and responses through the latest Instagram design and engagement. Therefore, the research aims to define the immersive experience on Instagram and the interaction between pleasure and arousal. An advertisement that evokes pleasure and arousal will be likely getting more attention from the target audience. This is one of the few studies comparing the endorses in Instagram advertising. Also, this research extends the existing knowledge about the immersive visual complexity in the context of social media advertising.

Keywords: immersive visual experience, instagram, pleasure, arousal

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Florian Lienert, Peter Costa, Caroline Aurensan, Elaine Melander

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Introduction: Rabies pre-exposure prophylaxis (PrEP) can be given before travel and simplifies post-exposure prophylaxis (PEP). We studied the knowledge about rabies, the uptake of PrEP, and reasons for deciding for or against PrEP in at-risk travelers. We also examined how healthcare professionals (HCPs) counsel on rabies prevention. Methods: On behalf of Bavarian Nordic, Ipsos MORI conducted two online surveys in the USA. Fieldwork from February 24th to April 23rd, 2021, 689 participants aged 18-85 years, visited one of 91 endemic rabies countries in the past 3 years for at least one week, involved in at least 1 of 7 at-risk activities, heard of rabies, positive towards vaccination and chose to take part (surveyed travelers). Secondly, 76 HCPs, with responsibility for advising/ making decisions about vaccination requirements for their patients, personally recommend or prescribe vaccines for rabies, positive towards vaccination and chose to take part (surveyed HCPs). Results: A minority (36%) of surveyed travelers classified rabies as a life-threatening disease. A third of surveyed HCPs (37%) did not discuss rabies vaccination with at-risk travelers, 18% discussed only PEP, 23% only PrEP and 22% both. A minority (21%) of surveyed travelers reported having received rabies vaccination since they were 18. Among those participants (n=145), the most common reasons for deciding to get PrEP were for their own peace of mind (35%) and following an HCP recommendation (32%). Of those who decided not to receive the rabies vaccine (n=319), the most common reasons were that they did not think their risk of rabies was sufficient (23%) and that the HCP did not suggest it (23%). Conclusions: The survey demonstrated knowledge gaps around rabies and low PrEP coverage among surveyed travelers. It also highlighted the role of HCP recommendations and showed that most HCPs did not discuss PrEP with at-risk travelers.

Keywords: rabies, pre-exposure prophylaxis, travel, travel health, post-travel care, rabies treatment, vaccine, post-exposure, prophylaxis, at-risk, education, PrEP, PEP

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Authors: Abdulnasser Ahmed Haza’a, Marzoq Ali Odhah, Saddam Ahmed Al-Ahdal, Abdulfatah Saleh Al-Jaradi, Gamil Ghaleb Alrubaiee

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Patient safety in hospitals is an essential professional indicator that should be noticed. The threat of fires is potentially the most dangerous risk that could harm patients and personnel. The aim of the study is to assess the knowledge of operating room (OR) staff toward prevention and control sources of fires. Between March 1 and March 30, 2022, data collection was done. A descriptive cross-sectional study was conducted. The sample of the study consisted of 89 OR staff from different governmental hospitals. Convenient sampling was applied to select the sample size. Official approvals were obtained from selected settings for start collection data. Data were collected using a close-ended questionnaire and tested for knowledge. This study was conducted in four governmental hospitals in Sana'a, Yemen. Most of the OR staff were male. Of these, 50.6% of them were operation technician professionals. More than two-thirds of OR staff have less than ten years of experience; 93% of OR staff had inadequate knowledge of sources of fires, and inadequate knowledge of them toward controls and prevention of fires (73%, 79.8%), respectively; 77.5% of OR staff had inadequate knowledge of prevention and control sources of fires. The study concluded that most of OR staff had inadequate knowledge of sources, controls, and prevention of fires, while 22.5% of them had adequate knowledge of prevention and control sources of fires. We recommended the implementation of training programs toward sources, controls, and prevention of fires or related workshops in their educational planning for OR staff of hospitals.

Keywords: knowledge, operation rooms staff, fires, prevention

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Joan O. Ogundele, Aladesanmi A. Oshodi, Adekunle I. Amoo

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Abstract In-vitro multi-enzyme protein digestibility (IVMPD) and some anti-nutritional factors (ANF) of five melon (egusi) seed flours (MSF) and their protein isolates (PI) were carried out. Their PI have potentials comparable to that of soya beans. It is important to know the IVMPD and ANF of these protein sources as to ensure their safety when adapted for use as alternate protein sources to substitute for cow milk, which is relatively expensive in Nigeria. Standard methods were used to produce PI of Citrullus colocynthis, Citrullus vulgaris, African Wine Kettle gourd (Lageneria siceraria I), Basket Ball gourd (Lagenaria siceraria II) and Bushel Giant Gourd (Lageneria siceraria III) seeds and to determine the ANF and IVMPD of the MSF and PI unheated and at 37oC. Multi-enzymes used were trypsin, chymotrypsin and peptidase. IVMPD of MSF ranged from (70.67±0.70) % (C. vulgaris) to (72.07± 1.79) % (L.siceraria I) while for their PI ranged from 74.33% (C.vulgaris) to 77.55% (L.siceraria III). IVMPD of the PI were higher than those of MSF. Heating increased IVMPD of MSF with average value of 79.40% and those of PI with average of 84.14%. ANF average in MSF are tannin (0.11mg/g), phytate (0.23%). Differences in IVMPD of MSF and their PI at different temperatures may arise from processing conditions that alter the release of amino acids from proteins by enzymatic processes. ANF in MSF were relatively low, but were found to be lower in the PI, therefor making the PI safer for human consumption as an alternate source of protein.

Keywords: Anti-nutrients, Enzymatic protein digestibility, Melon (egusi)., Protein Isolates.

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Authors: Sara Iqbal

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Introduction:Renal transplant is increasingly one of the most popular transplants within the UK; with an aging population along with obesity epidemic we are witnessing increasing rates of diabetes – one of the commonest indications for renal transplant. However, the demand is far greater than supply. Many donors are provided by women of child-bearing age; however the long-term effects are still uncertain. Aim:Determine pregnancy outcomes and complications of women of child-bearing age following renal donation. Methods: A review of the current available literature was preformed using MEDLINE and EMBASE up to 2014. Search criteria included key terms such as pregnancy outcome post-renal donor, pregnancy outcomes and complications. Relevant articles were selected based on pure methodological medical research, after careful analysis, they were recorded within this review. Results: Out of 1141 women involved in transplant studies, 574 pregnancies reported having donated a single-renal donor prior to pregnancy. Of which a staggering miscarriage rate 32.4% (n=186) was reported, amongst this other complications included gestational hypertension of 10% (n=59) and gestational diabetes 2.3% (n=13). Other significantly noted complications included chronic hypertension, low-birth weights, and pregnancy-related death. Conclusions: After unilateral renal donor transplant, haemodynamics change along with pregnancy, predisposing women to developing several complications compared to pregnancies with no history any renal-donor transplant. Despite this, further investigation is required in order to accurately determine the safety of renal-donors in women of child-bearing age.

Keywords: renal transplant, pregnancy, complications, medical and health sciences

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Authors: Marcya Burden, Savonna Greer

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In the wake of social unrest around the world, protest movements have been captured like never before. As protest movements have evolved, so too have their visibility and sources of coverage. Long gone are the days of print media as our only glimpse into the action surrounding a protest. Now, with social networks such as Facebook, Instagram and Snapchat, we have access to real-time video footage of protest movements and human rights activism that can reach millions of people within seconds. This research paper investigated various social media network platforms’ statistical usage data in the areas of human rights activism and protest movements, paralleling with other past forms of media coverage. This research demonstrates that social networks are extremely important to protest movements and human rights activism. With over 2.9 billion users across social media networks globally, these platforms are the heart of most recent protests and human rights activism. This research shows the paradigm shift from the Selma March of 1965 to the more recent protests of Ferguson in 2014, Ni Una Menos in 2015, and End Sars in 2018. The research findings demonstrate that today, almost anyone may use their social networks to protest movement leaders and human rights activists. From a student to an 80-year-old professor, the possibility of reaching billions of people all over the world is limitless. Findings show that 82% of the world’s internet population is on social networks 1 in every 5 minutes. Over 65% of Americans believe social media highlights important issues. Thus, there is no need to have a formalized group of people or even be known online. A person simply needs to be engaged on their respective social media networks (Facebook, Twitter, Instagram, Snapchat) regarding any cause they are passionate about. Information may be exchanged in real time around the world and a successful protest can begin.

Keywords: activism, protests, human rights, networks

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Authors: Despoina Christodoulopoulou

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The current research study investigated how connection with Korean celebrities may impact Greek and South Korean young adults’ body image perception given Korea’s distinct appearance norms. The study employed a qualitative methodology and semi-structured interviews were used for the gathering of data. Greek participants resided in Thessaloniki, Greece, whereas South Korean participants lived in Gwangju, South Korea. The study was approved by The American College of Thessaloniki’s (ACT) Institutional Review Board. Face-to-face interviews were conducted with the Greek sample, and online interviews with the South Korean sample. Thematic analysis was utilized to determine the findings. Findings illustrated that a close bond with Korean celebrities can impact participants’ body image perception. The Greek sample’s body image was positively influenced by their connection with Korean celebrities, whereas Korean sample’s was negatively influenced. Such distinction is due to celebrities’ nationality and their adherence to culturally acceptable standards of slimness, muscularity and facial appeal. It also appeared that Korean male celebrities promote body positivity more than their female counterparts. Findings showed that Korean culture appearance norms constitute a risk factor influencing Korean young adults’ body dissatisfaction. Thus, Korean mental health professionals might be informed from this paper on preserving Korea’s youth mental health.

Keywords: parasocial relationships, celebrity worship, Korean wave, body image concerns, body dissatisfaction, Greek young adults, South Korean young adults

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Authors: Ashraf Osman

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Effective deployable bridges that are characterized by an increased capacity to weight ratio are recently needed for post-disaster rapid mobility and military operations. In deployable bridging, replacing metals as the fabricating material with advanced composite laminates as lighter alternatives with higher strength is highly advantageous. This article presents a hierarchical optimization strategy of a composite bridge treadway considering maximum strength design and bridge weight minimization. Shape optimization of a generic deployable bridge beam cross-section is performed to achieve better stress distribution over the bridge treadway hull. The developed cross-section weight is minimized up to reserving the margins of safety of the deployable bridging code provisions. Hence, the strength of composite bridge plates is maximized through varying the plies orientation. Different loading cases are considered of a tracked vehicle patch load. The orthotropic plate properties of a composite sandwich core are used to simulate the bridge deck structural behavior. Whereas, the failure analysis is conducted using Tsai-Wu failure criterion. The naturally inspired particle swarm optimization technique is used in this study. The proposed technique efficiently reduced the weight to capacity ratio of the developed bridge beam.

Keywords: CFRP deployable bridges, disaster relief, military bridging, optimization of composites, particle swarm optimization

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Authors: Md. Shafiullah

Abstract:

This study delves into the evolving landscape of urban childcare in Bangladesh, focusing on the experiences and challenges faced by parents in Dhaka city. This paper argues that the traditional childcare arrangement of city families is inadequate to meet the development needs of children. The study aims to explore the childcare challenges faced by urban parents as they transition from traditional family-based childcare networks to alternative caregiving arrangements amidst urbanization, economic shifts, and social transformations. Utilizing a mixed-method research approach, combining quantitative surveys (n = 200) and four qualitative interviews, the research examines the parental viewpoints on childcare practices and the role of societal norms and values. The study finds childcare crises in both the family and daycare settings. In family care, caregiving suffers from the less availability of grandparents, a lack of skills of caregivers, and a lack of child interaction. As for the daycare, it is affected by the absence of appropriate policies, a lack of quality, health and safety concerns, affordability issues, and cultural concerns. Additionally, the study highlights inadequacies in childcare policies and regulatory frameworks, calling for comprehensive reforms to address the childcare vacuum in urban areas. By shifting the focus from developed to developing countries, this study contributes to the literature and suggests policy implications for Bangladesh and beyond.

Keywords: childcare, child development, childcare policy, daycare, Bangladesh

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Feiruz Ab'lah, Zarini Ismail, Mohamad Zaki Hassan, Siti Nadia Mohd Bakhori, Mohamad Azlan Suhot, Mohd Yusof Md. Daud, Shamsul Sarip

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The construction industry is one of the major sectors in Malaysia. Apart from providing facilities, services, and goods it also offers employment opportunities to local and foreign workers. In fact, the construction workers are exposed to a hazardous level of noises that generated from various sources including excavators, bulldozers, concrete mixer, and piling machines. Previous studies indicated that the piling and concrete work was recorded as the main source that contributed to the highest level of noise among the others. Therefore, the aim of this study is to obtain the noise exposure during piling process and to determine the awareness of workers against noise pollution at the construction site. Initially, the reading of noise was obtained at construction site by using a digital sound level meter (SLM), and noise exposure to the workers was mapped. Readings were taken from four different distances; 5, 10, 15 and 20 meters from the piling machine. Furthermore, a set of questionnaire was also distributed to assess the knowledge regarding noise pollution at the construction site. The result showed that the mean noise level at 5m distance was more than 90 dB which exceeded the recommended level. Although the level of awareness regarding the effect of noise pollution is satisfactory, majority of workers (90%) still did not wear ear protecting device during work period. Therefore, the safety module guidelines related to noise pollution controls should be implemented to provide a safe working environment and prevent initial occupational hearing loss.

Keywords: construction, noise awareness, noise pollution, piling machine

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Authors: Sarah P. Wuebbolt, Ashlee N. Sawyer-Mays

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Non-medical prescription and other drug (NMPOD) use has been a significant public health issue for the last few decades, with problematic use increasing among university students more recently. The current study focused on associations between NMPOD use and mental health, well-being, and world beliefs among young adults. Young adults (N=513) completed online questionnaires assessing stress, demographic characteristics, self-esteem, NMPOD use, coping mechanisms, and anxiety. A substantial portion of participants reported using cannabis (48.5%, n=249), while smaller portions of participants reported using stimulants (26.7%, n = 137), sedatives (17.2%, n=88), opioids (10.8%, n=55), and hallucinogens (14.4%, n=74). Five hierarchical logistic regressions were performed to determine the independent relationships between mental health, well-being, and world belief factors and NMPOD use for the five classes of substances. After controlling for demographic factors (age, gender, race/ethnicity, sexual orientation, and religious affiliation), depression was associated with increased non-medical stimulant, opioid, and cannabis use; coping self-efficacy was associated with increased hallucinogen use, and attendance of worship services was associated with decreased non-medical cannabis and hallucinogen use. Results suggest that depression was strongly associated with non-medical stimulant, opioid, and cannabis use, and attendance of worship services was protective against cannabis and hallucinogen use. To the best of our knowledge, this is one of the first studies to investigate the relationships between mental health, well-being, world beliefs, and NMPOD use among young adults. The present study illuminates future targets for intervention, such as increased access to mental health diagnosis and treatment and the exploration of the roles of religion and shared community in the prevention of drug use among young adults.

Keywords: cannabis, mental health, non-medical prescription and other drug use, world beliefs

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Authors: Addisu Tadesse Sahile, Mussie Wubshet Teka, Solomon Muluken Ayehu

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Background: Diabetes is one of the common public health problems of the century that was estimated to affect one in a tenth of the world population by the year 2030, where diabetes ketoacidosis is one of its common acute complications. Objectives: The aim of this review was to assess the magnitude of diabetes ketoacidosis among patients with type 1 diabetes in Ethiopia. Methods: A systematic data search was done across Google Scholar, PubMed, Web of Science, and African Online Journals. Two reviewers carried out the selection, reviewing, screening, and extraction of the data independently by using a Microsoft Excel Spreadsheet. The Joanna Briggs Institute's prevalence critical appraisal tool was used to assess the quality of evidence. All studies conducted in Ethiopia that reported diabetes ketoacidosis rates among type 1 diabetes were included. The extracted data was imported into the comprehensive meta-analysis version 3.0 for further analysis. Heterogeneity was checked by Higgins’s method, whereas the publication bias was checked by using Beggs and Eggers’s tests. A random-effects meta-analysis model with a 95% confidence interval was computed to estimate the pooled prevalence. Furthermore, subgroup analysis based on the study area (Region) and the sample size was carried out. Result and Conclusion: After review made across a total of 51 articles, of which 12 articles fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of diabetes ketoacidosis among type 1 diabetes in Ethiopia was 53.2% (95%CI: 43.1%-63.1%). The highest prevalence of DKA was reported in the Tigray region of Ethiopia, whereas the lowest was reported in the Southern region of Ethiopia. Concerned bodies were suggested to work on the escalated burden of diabetes ketoacidosis in Ethiopia.

Keywords: DKA, Type 1 diabetes, Ethiopia, systematic review, meta-analysis

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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

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

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Authors: Bataineh Abdallah, Alabdallah Ghaith, Alkharabshe Abdalhameed

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Social media is an umbrella term for different types of online communication channels. The most prominent forms can be divided into four categories: Collaborative projects (e.g. Wikipedia, comparison-shopping sites), blogs (e.g. Twitter), content communities (e.g. Youtube), social networking sites (e.g. Facebook) social media allow consumers to share their opinions, criticisms and suggestions in public. Facebook launched in 2004, initially targeted college students and later started including everyone has become the most popular sites amongst the young generation for connecting with friends and relatives and for the communication of ideas. In 2013 Facebook penetration rate reached 41.4% of the population making it the most popular social networking site in Jordan. Accordingly, the purpose of this research is to examine the impact of perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment and subjective norms on users' satisfaction and continuance intention to use Facebook in Jordan. Using a structured questionnaire, the primary data was collected from 584 users who have an active Facebook accounts. Multiple regression analysis was employed to test the research model and hypotheses. The research findings indicate that perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment, and subjective norms have a positive and significant effect on users' satisfaction and continuance intention to use Facebook. The findings also indicated that the strongest predictors, based on beta values, on both users' satisfaction and continuance intention to use Facebook is subjective norms and respectively, perceived enjoyment, perceived usefulness, perceived ease of us, and perceived trust. Research results, recommendations, and future research opportunities are also discussed.

Keywords: perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment, perceived subjective norms, users' satisfaction, continuance intention, Facebook

Procedia PDF Downloads 469