Search results for: healthcare data security

Authors: Subhra Prosun Paul, Shruti Aggarwal

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Now a days Routing Protocol in Wireless Sensor Network has become a promising technique in the different fields of the latest computer technology. Routing in Wireless Sensor Network is a demanding task due to the different design issues of all sensor nodes. Network architecture, no of nodes, traffic of routing, the capacity of each sensor node, network consistency, service value are the important factor for the design and analysis of Routing Protocol in Wireless Sensor Network. Additionally, internal energy, the distance between nodes, the load of sensor nodes play a significant role in the efficient routing protocol. In this paper, our intention is to analyze the research trends in different routing protocols of Wireless Sensor Network in terms of different parameters. In order to explain the research trends on Routing Protocol in Wireless Sensor Network, different data related to this research topic are analyzed with the help of Web of Science and Scopus databases. The data analysis is performed from global perspective-taking different parameters like author, source, document, country, organization, keyword, year, and a number of the publication. Different types of experiments are also performed, which help us to evaluate the recent research tendency in the Routing Protocol of Wireless Sensor Network. In order to do this, we have used Web of Science and Scopus databases separately for data analysis. We have observed that there has been a tremendous development of research on this topic in the last few years as it has become a very popular topic day by day.

Keywords: analysis, routing protocol, research trends, wireless sensor network

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Authors: Saima Q. Memon, Mazhar I. Khaskheli

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The aim of present study was to investigate the efficiency of mulberry leaves for the removal of both arsenic (III) and arsenic (V) from aqueous medium. Batch equilibrium studies were carried out to optimize various parameters such as pH of metal ion solution, volume of sorbate, sorbent doze, and agitation speed and agitation time. Maximum sorption efficiency of mulberry leaves for As (III) and As (V) at optimum conditions were 2818 μg.g-1 and 4930 μg.g-1, respectively. The experimental data was a good fit to Freundlich and D-R adsorption isotherm. Energy of adsorption was found to be in the range of 3-6 KJ/mole suggesting the physical nature of process. Kinetic data followed the first order rate, Morris-Weber equations. Developed method was applied to remove arsenic from real water samples.

Keywords: arsenic removal, mulberry, adsorption isotherms, kinetics of adsorption

Procedia PDF Downloads 281

Authors: J. R. Wang, Y. Chiang, W. S. Hsu, S. H. Chen, J. H. Yang, S. W. Chen, C. Shih, Y. F. Chang, Y. H. Huang, B. R. Shen

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In this research, the RASCAL code was used to simulate and analyze the postulated UF₆ fire accident which may occur in the Institute of Nuclear Energy Research (INER). There are four main steps in this research. In the first step, the UF₆ data of INER were collected. In the second step, the RASCAL analysis methodology and model was established by using these data. Third, this RASCAL model was used to perform the simulation and analysis of the postulated UF₆ fire accident. Three cases were simulated and analyzed in this step. Finally, the analysis results of RASCAL were compared with the hazardous levels of the chemicals. According to the compared results of three cases, Case 3 has the maximum danger in human health.

Keywords: RASCAL, UF₆, safety, hydrogen fluoride

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Authors: Stefanache Stefania, Ioana R. Podina

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Background: Embodied Conversational Agents (ECAs) are revolutionizing education and healthcare by offering cost-effective, adaptable, and portable solutions. Research on the Uncanny Valley effect (UVE) involves various embodied agents, including ECAs. Achieving the optimal level of anthropomorphism, no consensus on how to overcome the uncanniness problem. Objectives: This systematic review aims to identify the user characteristics, agent features, and context factors that influence the UVE. Additionally, this review provides recommendations for creating effective ECAs and conducting proper experimental studies. Methods: We conducted a systematic review following the PRISMA 2020 guidelines. We included quantitative, peer-reviewed studies that examined human-ECA interaction. We identified 17,122 relevant records from ACM Digital Library, IEE Explore, Scopus, ProQuest, and Web of Science. The quality of the predictors, mediators, and moderators adheres to the guidelines set by prior systematic reviews. Results: Based on the included studies, it can be concluded that females and younger people perceive the ECA as more attractive. However, inconsistent findings exist in the literature. ECAs characterized by extraversion, emotional stability, and agreeableness are considered more attractive. Facial expressions also play a role in the UVE, with some studies indicating that ECAs with more facial expressions are considered more attractive, although this effect is not consistent across all studies. Few studies have explored contextual factors, but they are nonetheless crucial. The interaction scenario and exposure time are important circumstances in human-ECA interaction. Conclusions: The findings highlight a growing interest in ECAs, which have seen significant developments in recent years. Given this evolving landscape, investigating the risk of the UVE can be a promising line of research.

Keywords: human-computer interaction, uncanny valley effect, embodied conversational agent, systematic review

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Natalia Feruleva

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The goal of this paper is to develop the fraud risk assessment model basing on both relational and financial data and test the impact of the relationships between Russian non-public companies on the likelihood of financial fraud commitment. Relationships mean various linkages between companies such as parent-subsidiary relationship and person-related relationships. These linkages may provide additional opportunities for committing fraud. Person-related relationships appear when firms share a director, or the director owns another firm. The number of companies belongs to CEO and managed by CEO, the number of subsidiaries was calculated to measure the relationships. Moreover, the dummy variable describing the existence of parent company was also included in model. Control variables such as financial leverage and return on assets were also implemented because they describe the motivating factors of fraud. To check the hypotheses about the influence of the chosen parameters on the likelihood of financial fraud, information about person-related relationships between companies, existence of parent company and subsidiaries, profitability and the level of debt was collected. The resulting sample consists of 160 Russian non-public firms. The sample includes 80 fraudsters and 80 non-fraudsters operating in 2006-2017. The dependent variable is dichotomous, and it takes the value 1 if the firm is engaged in financial crime, otherwise 0. Employing probit model, it was revealed that the number of companies which belong to CEO of the firm or managed by CEO has significant impact on the likelihood of financial fraud. The results obtained indicate that the more companies are affiliated with the CEO, the higher the likelihood that the company will be involved in financial crime. The forecast accuracy of the model is about is 80%. Thus, the model basing on both relational and financial data gives high level of forecast accuracy.

Keywords: financial fraud, fraud prediction, non-public companies, regression analysis, relational data

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Jacky Liu

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This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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Authors: Lamia Bouzgarrou, Amira Omrane, Leila Mrabet, Taoufik Khalfallah

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Background and aims: School accidents are one of the leading causes of morbidity and mortality among pupils and students. Indeed, they may induce an elevated number of lost school days, heavy emotional and physical disabilities, and financial costs on the victims and their families. This study aims to evaluate the annual incidence of school accidents in the central Tunisian governorate of Mahdia and to identify the epidemiological profile of victims and risk factors of these accidents. Methods: A retrospective study was conducted over the period of 5 school years, focusing on school accidents that occurred in public educational institutions (primary, basic, secondary and university) in the governorate of Mahdia (area = 2 966 km² and number of inhabitants in 2014 = 410 812). All accidents declared near the only official insurance of this type of injuries (MASU: Mutual School and University Accidents), and initially taken in charge at the University Hospital of Mahdia were included. Data was collected from the MASU reporting forms and the medical records of emergency and other specialized hospital departments. Results: With 3248 identified victims, the annual incidence of school accidents was equal to 0.69 per 100 pupils and students per year. The average age of victims was 14.51 ± 0.059 years and the sex ratio was 1.58. Pupils aged between 12 and 15 years, were concerned by 46.7% of the identified accidents. The practice of sports was the most relevant circumstances of these accidents (76.2 %). In 56.58 % of cases, falls were the leading mechanism. Bruises and fractures were the most frequent lesions (32.43 % and 30.51 %). Serious school accidents were noted in 28% of cases with hospitalization in 2.27 % of them. The average lost school days, was 12.23±1.73 days. Accidents occurring during sports or leisure activities were significantly more serious (p= 0.021). Furthermore, the frequency of hospitalization was significantly higher among boys (2.81% vs. 1.43%; p= 0.035), students ≤11 years (p= 0.008), and following crush trauma (p= 0.000). In addition, the surgical interventions were statistically more frequent among male victims (p=0.00), accidents occurring during physical education sessions (p=0.000); those associated to falls (p=0.000) and to crushes mechanisms (p=0.002), and injuries affecting lower limbs (p=0.000). Following this Multi-varied analysis concluded that the severity of school accident is correlated to the activity practiced during the trauma and the geographical location of the school. Conclusion: Children and adolescents are one of the most vulnerable groups against incidents with the risk of permanent disability, mainly related to the perturbation of the growth process and physiological limitations. Our five-year study, objectified a real elevate incidence of school accident among children and adolescents, with a considerable rate of severe injuries. In any community, the promotion of adolescents and children’s health is an important indicator of the public health level. Thus, it’s important to develop a multidisciplinary prevention strategy of school accident, based on safety and security rules and adapted to the specificity of our context.

Keywords: children and adolescents, children health, injuries and disability, school accident

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Authors: Abdullah Bal, Sevdenur Bal

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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.

Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware

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Authors: Lucia Carrion Gordon, Maria Gabriela Lopez Yanez

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This project focuses on heritage concepts and their importance in every evolving and changing Digital Era where system solutions have to be sustainable, efficient and suitable to the basic needs. The prototype has to cover the principal requirements for the case studies. How to preserve the sociological ideas of dances in Ecuador like ‘La Bomba’ is the best example and challenge to preserve the intangible data. The same idea is applicable with books and music. The History and how to keep it, is the principal mission of Heritage Preservation. The dance of La Bomba is rooted on a specific movement system whose main part is the sideward hip movement. La Bomba´s movement system is the surface manifestation of a whole system of knowledge whose principal characteristics are the historical relation of Chote˜nos with their land and their families.

Keywords: digital preservation, heritage, IT management, data, metadata, ontology, serendipity

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Authors: Oluwaseun Ijiwade, Chris Davison, Kelvin Gregory

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In Australia, like other parts of the world, the debate on how to enhance teachers using assessment data to inform teaching and learning of English as an Additional Language (EAL, Australia) or English as a Foreign Language (EFL, United States) have occupied the centre of academic scholarship. Traditionally, this approach was conceptualised as ‘Formative Assessment’ and, in recent times, ‘Assessment for Learning (AfL)’. The central problem is that teacher-made tests are limited in providing data that can inform teaching and learning due to variability of classroom assessments, which are hindered by teachers’ characteristics and assessment literacy. To address this concern, scholars in language education and testing have proposed a uniformed large-scale computer-based assessment program to meet the needs of teachers and promote AfL in language education. In Australia, for instance, the Victoria state government commissioned a large-scale project called 'Tools to Enhance Assessment Literacy (TEAL) for Teachers of English as an additional language'. As part of the TEAL project, a tool called ‘Reading and Vocabulary assessment for English as an Additional Language (RVEAL)’, as a diagnostic language assessment (DLA), was developed by language experts at the University of New South Wales for teachers in Victorian schools to guide EAL pedagogy in the classroom. Therefore, this study aims to provide qualitative evidence for understanding beliefs about the diagnostic language assessment (DLA) among EAL teachers in primary and secondary schools in Victoria, Australia. To realize this goal, this study raises the following questions: (a) How do teachers use large-scale assessment data for diagnostic purposes? (b) What skills do language teachers think are necessary for using assessment data for instruction in the classroom? and (c) What factors, if any, contribute to teachers’ beliefs about diagnostic assessment in a large-scale assessment? Semi-structured interview method was used to collect data from at least 15 professional teachers who were selected through a purposeful sampling. The findings from the resulting data analysis (thematic analysis) provide an understanding of teachers’ beliefs about DLA in a classroom context and identify how these beliefs are crystallised in language teachers. The discussion shows how the findings can be used to inform professional development processes for language teachers as well as informing important factor of teacher cognition in the pedagogic processes of language assessment. This, hopefully, will help test developers and testing organisations to align the outcome of this study with their test development processes to design assessment that can enhance AfL in language education.

Keywords: beliefs, diagnostic language assessment, English as an additional language, teacher cognition

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Authors: Shierwin Agagen Cabunilas

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Countless Filipinos are reeling in dire economic inequality while many others are victims of human trafficking. Where there is extreme economic inequality, majority of the Filipinos are deprived of basic needs to have a good life, i.e., decent shelter, safe environment, food, quality education, social security, etc. The problem on human trafficking poses a scandal and threat in respect to human rights and dignity of a person on matters of sex, gender, ethnicity and race among others. The economic inequality and trafficking in persons are social pathologies that needed considerable amount of attention and visible solution both in the national and international level. However, the Philippine government seems falls short in terms of goals to lessen, if not altogether eradicate, the dire fate of many Filipinos. The lack of solidarity among Filipinos seems to further aggravate injustice and create hindrances to economic equity and protection of Filipinos from syndicated crimes, i.e., human trafficking. Indifference towards the welfare and well-being of the Filipino people trashes them into an unending cycle of marginalization and neglect. A transnational solidaristic action in response to these concerns is imperative. The subsequent sections will first discuss the notion of solidarity and the motivating factors for collective action. While solidarity has been previously thought of as stemming from and for one’s own community and people, it can be argued as a value that defies borders. Solidarity bridges peoples of diverse societies and cultures. Although there are limits to international interventions on another’s sovereignty, such as, internal political autonomy, transnational solidarity may not be an opposition to solidarity with people suffering injustices. Governments, nations and institutions can work together in securing justice. Solidarity thus is a positive political action that can best respond to issues of economic, class, racial and gender injustices. This is followed by a critical analysis of some data on Philippine economic inequality and human trafficking and link the place of transnational solidaristic arrangements. Here, the present work is interested on the normative aspect of the problem. It begins with the section on economic inequality and subsequently, human trafficking. It is argued that a transnational solidarity is vital in assisting the Philippine governing bodies and authorities to seriously execute innovative economic policies and developmental programs that are justice and egalitarian oriented. Transnational solidarity impacts a corrective measure in the economic practices, and activities of the Philippine government. Moreover, it is suggested that in order to mitigate Philippine economic inequality and human trafficking concerns it involves a (a) historical analysis of systems that brought about economic anomalies, (b) renewed and innovated economic policies, (c) mutual trust and relatively high transparency, and (d) grass-root and context-based approach. In conclusion, the findings are briefly sketched and integrated in an optimistic view that transnational solidarity is capable of influencing Philippine governing bodies towards socio-economic transformation and development of the lives of Filipinos.

Keywords: Philippines, Filipino, economic inequality, human trafficking, transnational solidarity

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Authors: Larry Lai, Evans Leung

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Falun gong is a self-proclaimed religious group that has been under crackdown by Beijing for more than two decades. Diaosi, on the other hand, is an emerging community with members loosely connected on the internet through different online social platforms, centering around the sharing of different hobbies and interests. Diaosi community has been transformed from a potential threat to the Chinese authority for different causes to a pro-government force. This paper seeks to explain the different strategies adopted by the People's Republic of China (PRC) regime in handling these two potential threatening communities. Both communities share some obvious similarities: (1) both have massive nation-wide participation; (2) both have attempted to challenge the PRC's authority through contentious means; (3) both have high level of mobility, online or offline; and (4) both have at first been unnoticed until the threat against the PRC have taken form. But the strategies the PRC endorsed against the communities were, in many ways, different. The question is: if the strategy against Falun Gong has been an effective one, why used other strategies against Diaosi? The authors argue that the main reason for using different strategies lies in the differences between the two communities in terms of (i) the nature of the groups, and (ii) the group dynamics. Lastly, based on this analysis, the authors attempt to explore the possible strategies that the PRC would adopt against the Hong Kong cyber-world political community in light of the latest national security law in Hong Kong.

Keywords: contentious politics, Diaosi, Falun Gong, Hong Kong, People's Republic of China

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization

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Authors: Sara Ali Alokley, Mansour Saleh Albarrak

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This paper investigates the dependency or clustering of extremes in the financial returns data by estimating the extremal index value θ∈[0,1]. The smaller the value of θ the more clustering we have. Here we apply the method of Ferro and Segers (2003) to estimate the extremal index for a range of threshold values. We compare the dependency structure of extremes in the developed and emerging markets. We use the financial returns of the stock market index in the developed markets of US, UK, France, Germany and Japan and the emerging markets of Brazil, Russia, India, China and Saudi Arabia. We expect that more clustering occurs in the emerging markets. This study will help to understand the dependency structure of the financial returns data.

Keywords: clustring, extremes, returns, dependency, extermal index

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Authors: Nawaporn Thongnut

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The objective was to study the process and how to prepare the accounting of the Thai temples and to study the performance and quality in the accounting preparation of the temples in accordance with the regulation. The population was the accountants and individuals involved in the accounting preparation of 17 temples in the suburban Bangkok. The measurement used in this study was questionnaire. The statistics used in the analysis are the descriptive statistic. The data was presented in the form of percentage tables to describe the data on the demographic characteristics. The study found that temple wardens were responsible for the accounting and reporting of the temples. Abbots were to check the accuracy of the accounts in the monasteries. Mostly, there was no account auditing of the monasteries from the outside. The practice when receiving income for most of the monasteries had been keeping financial document in an orderly manner.

Keywords: corporate social responsibility, creating shared value, management accountant’s roles, stock exchange of Thailand

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Authors: Man Guo, Wenyong Tan

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By combining spatial syntax with data obtained from field visits, this paper interprets the internal relationship between spatial morphology and spatial cognition in Lidukou Village. By comparing the obtained data, it is recognized that the spatial integration degree of Lidukou Village is positively correlated with the spatial cognitive intention of local villagers. The part with a higher spatial cognitive degree within the village is distributed along the axis mainly composed of Shuxiang Road. And the accessibility of historical relics is weak, and there is no systematic relationship between them. Aiming at the morphological problem of Lidukou Village, optimization strategies have been proposed from multiple perspectives, such as optimizing spatial mechanisms and shaping spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

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Authors: A.D. Susanti, W. B. Sediawan, S.K. Wirawan, Budhijanto, Ritmaleni

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Oryzanol content in rice bran oil (RBO) naturally has high antioxidant activity. Its reviewed has several health properties and high interested in pharmacy, cosmetics, and nutrition’s. Because of the low concentration of oryzanol in crude RBO (0.9-2.9%) then its need to be further processed for practical usage, such as via adsorption process. In this study, investigation and adjustment of adsorption equilibrium models were conducted through the kinetic data approachments. Mathematical modeling on kinetics of batch adsorption of oryzanol separation from RBO has been set-up and then applied for equilibrium results. The size of adsorbent particles used in this case are usually relatively small then the concentration in the adsorbent is assumed to be not different. Hence, the adsorption rate is controlled by the rate of oryzanol mass transfer from the bulk fluid of RBO to the surface of silica gel. In this approachments, the rate of mass transfer is assumed to be proportional to the concentration deviation from the equilibrium state. The equilibrium models applied were Langmuir, coefficient distribution, and Freundlich with the values of the parameters obtained from equilibrium results. It turned out that the models set-up can quantitatively describe the experimental kinetics data and the adjustment of the values of equilibrium isotherm parameters significantly improves the accuracy of the model. And then the value of mass transfer coefficient per unit adsorbent mass (kca) is obtained by curve fitting.

Keywords: adsorption equilibrium, adsorption kinetics, oryzanol, rice bran oil

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Authors: Turan Cetinkaya

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The aim of this study is to determine the relation of the level of social anxiety to various variables of the students in physical education and sports departments. 229 students who are studying at the departments of physical education and sports teaching, sports management and coaching in Ahi Evran University, College of Physical Education and Sports participate in the research. Personal information tool and social anxiety scale consisting 30 items were used as data collection tool in the research. Distribution, frequency, t-test and ANOVA test were used in the comparison of the related data. As a result of statistical analysis, social anxiety levels do not differ according to gender, income level, sports type and national player status.

Keywords: social anxiety, undergraduates, sport, unıversty

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Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in pipe bends caused by particles is a major obstacle in the oil and gas fields and might cause the breakdown of production equipment. This work studied the effects imposed by flow velocity and impact of solid particles diameter in an elbow; erosion rate was verified with experimental data using the computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model was employed to calculate the air/solid particle flow in an elbow. One erosion model and three-particle rebound models were used to predict the erosion rate on the 90° elbows. The generic erosion model was used in the CFD-based erosion model, and after comparing it with experimental data, results showed agreement with the CFD-based predictions as observed.

Keywords: erosion, prediction, elbow, computational fluid dynamics

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Authors: M. Hijazi, A. Zeki, A. Ismail

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An enormous amount of valuable human knowledge is preserved in documents. The rapid growth in the number of machine-readable documents for public or private access requires the use of automatic text classification. Text classification can be defined as assigning or structuring documents into a defined set of classes known in advance. Arabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information written in the Arabic language on the web. This paper presents a review on the published researches of Arabic Text Classification using classical data representation, Bag of words (BoW), and using conceptual data representation based on semantic resources such as Arabic WordNet and Wikipedia.

Keywords: Arabic text classification, Arabic WordNet, bag of words, conceptual representation, semantic relations

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Authors: Jared Cheves, Amanda DeChent, Joyce Pan

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Total knee replacements (TKAs) are one of the most common but painful surgical procedures performed in the United States. Currently, the gold standard for postoperative pain management is the utilization of opioids. However, in the wake of the opioid epidemic, the healthcare system is attempting to reduce opioid consumption by trialing innovative opioid sparing analgesic techniques such as continuous peripheral nerve blocks (CPNB) and continuous periarticular infiltration (CPAI). The alleviation of pain, particularly during the first 72 hours postoperatively, is of utmost importance due to its association with delayed recovery, impaired rehabilitation, immunosuppression, the development of chronic pain, the development of rebound pain, and decreased patient satisfaction. While both CPNB and CPAI are being used today, there is limited evidence comparing the two to the current standard of care or to each other. An extensive literature review was performed to explore the safety profiles and effectiveness of CPNB and CPAI in reducing reported pain scores and decreasing opioid consumption. The literature revealed the usage of CPNB contributed to lower pain scores and decreased opioid use when compared to opioid-only control groups. Additionally, CPAI did not improve pain scores or decrease opioid consumption when combined with a multimodal analgesic (MMA) regimen. When comparing CPNB and CPAI to each other, neither unanimously lowered pain scores to a greater degree, but the literature indicates that CPNB decreased opioid consumption more than CPAI. More research is needed to further cement the efficacy of CPNB and CPAI as standard components of MMA in TKA procedures. In addition, future research can also focus on novel catheter-free applications to reduce the complications of continuous catheter analgesics.

Keywords: total knee arthroplasty, continuous peripheral nerve blocks, continuous periarticular infiltration, opioid, multimodal analgesia

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Authors: Ł. Morawiński, C. Jasiński, M. Jurkiewicz, S. Bou Habib, M. Bondyra

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With the development of optics, electronics, and computers, vision systems are increasingly used in various areas of life, science, and industry. Vision systems have a huge number of applications. They can be used in quality control, object detection, data reading, e.g., QR-code, etc. A large part of them is used for measurement purposes. Some of them make it possible to obtain a 3D reconstruction of the tested objects or measurement areas. 3D reconstruction algorithms are mostly based on creating depth maps from data that can be acquired from active or passive methods. Due to the specific appliance in airfield technology, only passive methods are applicable because of other existing systems working on the site, which can be blinded on most spectral levels. Furthermore, reconstruction is required to work long distances ranging from hundreds of meters to tens of kilometers with low loss of accuracy even with harsh conditions such as fog, rain, or snow. In response to those requirements, HRESS (Heliport REmote Safeguard System) was developed; which main part is a rotational head with a two-camera stereovision rig gathering images around the head in 360 degrees along with stereovision 3D reconstruction and point cloud combination. The sub-pixel analysis introduced in the HRESS system makes it possible to obtain an increased distance measurement resolution and accuracy of about 3% for distances over one kilometer. Ultimately, this leads to more accurate and reliable measurement data in the form of a point cloud. Moreover, the program algorithm introduces operations enabling the filtering of erroneously collected data in the point cloud. All activities from the programming, mechanical and optical side are aimed at obtaining the most accurate 3D reconstruction of the environment in the measurement area.

Keywords: airfield monitoring, artificial intelligence, stereovision, 3D reconstruction

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Authors: Eman Mohamed Ali Elalwani

Abstract:

The Libyan heritage buildings are currently facing a number of crises that pose a threat to their structural integrity, functionality, and overall performance. One of the challenges pertains to the loss of community identity, which has arisen due to the lack of awareness and unconscious behavior of the residents. An additional issue arises from inadequate site management practices, including the implementation of modern techniques and innovative building materials that are incompatible with structural elements, resulting in the deformation of certain sections of the buildings. The security concerns of the city, along with the ongoing civil conflict, fostered a conducive environment for violations, resulting in the vandalism of certain monuments in the city. However, the degradation of this valuable heritage is mainly attributed to the city's neglect and pollution. The elevated groundwater level resulting from pollution has led to erosion in the building's foundations. Mitigating these negative consequences through strategic interventions and rehabilitation is required to preserve this treasure. In order to assist the local community in recovering from those crises, this paper stated a viable strategy for promoting preservation efforts that aimed at safeguarding the heritage sites while also providing guidance to decision-makers and the local community on how to avoid these crises, preserve, enhance, and recognize the significance of the Libyan heritage.

Keywords: cultural heritage, historical buildings, Tripoli’s old city, Red Castle, crises, preservation

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Authors: John Ahluwalia

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As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Why is it that Canada has not shared the same fate as the US (and many other nations) that have realized much worse outcomes relative to the COVID-19 pandemic? Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal healthcare is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, Canada, GIS, temporal analysis, ESRI

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Authors: T. Garba, Y. Y. Babanyara, M. Isah, A. K. Muktari, R. Y. Abdullahi

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The increased in demand of fuel wood for heating, cooking and sometimes bakery has continued to exert appreciable impact on natural vegetation. This study focus on the use of multi-temporal data from land sat TM of 1986, land sat EMT of 1999 and lands sat ETM of 2006 to investigate the changes of Natural Vegetation resulting from charcoal production activities. The three images were classified based on bare soil, built up areas, cultivated land, and natural vegetation, Rock out crop and water bodies. From the classified images Land sat TM of 1986 it shows natural vegetation of the study area to be 308,941.48 hectares equivalent to 50% of the area it then reduces to 278,061.21 which is 42.92% in 1999 it again depreciated to 199,647.81 in 2006 equivalent to 30.83% of the area. Consequently cultivated continue increasing from 259,346.80 hectares (42%) in 1986 to 312,966.27 hectares (48.3%) in 1999 and then to 341.719.92 hectares (52.78%). These show that within the span of 20 years (1986 to 2006) the natural vegetation is depreciated by 119,293.81 hectares. This implies that if the menace is not control the natural might likely be lost in another twenty years. This is because forest cleared for charcoal production is normally converted to farmland. The study therefore concluded that there is the need for alternatives source of domestic energy such as the use of biomass which can easily be accessible and affordable to people. In addition, the study recommended that there should be strong policies enforcement for the protection forest reserved.

Keywords: charcoal, classification, data, images, land use, natural vegetation

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Authors: Elisavet Arsenaki

Abstract:

Paracetamol overdose is associated with significant and possibly permanent consequences including hepatotoxicity, acute and chronic liver failure, and death. This quality improvement project explores the prevalence of accidental iatrogenic paracetamol overdose in hospital patients with a low body weight, defined as <50kg and assesses the impact of educational posters in trying to reduce it. The study included all adult inpatients on the admissions ward, a short stay ward for patients requiring 12-72 hour treatment, and consisted of three cycles. Each cycle consisted of 3 days of data collection in a given month (data collection for cycle 1 occurred in January 2022, February 2022 for cycle 2 and March 2022 for cycle 3). All patients given paracetamol had their prescribed dose checked against their charted weight to identify the percentage of adult inpatients <50kg who were prescribed 1g of paracetamol instead of 500mg. In the first cycle of the audit, data were collected from 83 patients who were prescribed paracetamol on the admissions ward. Subsequently, four A4 educational posters were displayed across the ward, on two separate occasions and with a one-month interval in between each poster display. The aim of this was to remind prescribing doctors of their responsibility to check patient body weight prior to prescribing paracetamol. Data were collected again one week after each round of poster display, from 72 and 70 patients respectively. Over the 3 cycles with a cumulative 225 patients, 15 weighed <50kg (6.67%) and of those, 5 were incorrectly prescribed 1g of paracetamol, yielding a 33.3% prevalence of accidental iatrogenic paracetamol overdose in adult inpatients. In cycle 1 of the project, 3 out of 6 adult patients weighing <50kg were overdosed on paracetamol, meaning that 50% of low weight patients were prescribed the wrong dose of paracetamol for their weight. In the second data collection cycle, 1 out of 5 <50kg patients were overdosed (20%) and in the third cycle, 1 out of 4 (25%). The use of educational posters resulted in a lower prevalence of accidental iatrogenic paracetamol overdose in low body weight adult inpatients. However, the differences observed were statistically insignificant (p value 0.993 and 0.995 respectively). Educational posters did not induce a significant decrease in the prevalence of accidental iatrogenic paracetamol overdose. More robust strategies need to be employed to further decrease paracetamol overdose in patients weighing <50kg.

Keywords: iatrogenic, overdose, paracetamol, patient, safety

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Authors: Sautma Ronni Basana, Zeplin Jiwa Husada Tarigan, Widjojo Suprapto

Abstract:

Companies have already implemented the Enterprise Resource Planning (ERP) system to increase the data integration so that they can improve their business performance. Although some companies have managed to implement the ERP well, they still need to improve gradually so that the ERP functions can be optimized. To obtain a faster and more accurate data, the key users and IT department have to customize the process to suit the needs of the company. In reality, sustaining the ERP technology system requires soft and hard ERP so it enables to improve the business performance of the company. Soft and hard ERP are needed to build a tough system to ensure the integration among departments running smoothly. This research has three questions. First, is the soft ERP bringing impacts to the hard ERP and system integration. Then, is the hard ERP having impacts to the system integration. Finally, is the business performance of the manufacturing companies is affected by the soft ERP, hard ERP, and system integration. The questionnaires are distributed to 100 manufacturing companies in East Java, and are collected from 90 companies which have implemented the ERP, with the response rate of 90%. From the data analysis using PLS program, it is obtained that the soft ERP brings positive impacts to the hard ERP and system integration for the companies. Then, the hard ERP brings also positive impacts to the system integration. Finally, the business process performance of the manufacturing companies is affected by the system integration, soft ERP, and hard ERP simultaneously.

Keywords: soft ERP, hard ERP, system integration, business performance

Procedia PDF Downloads 409