Search results for: Fisher Score

Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

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The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: Prediction Model, Sensitivity Analysis, Simulation Method, USMLE.

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Authors: Rahma Al Maawali, Hameed Sulaiman

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Air pollution both from point and non-point sources is difficult to control once released in to the atmosphere. There is no engineering method known available to ameliorate the dispersed pollutants. The only suitable approach is the ecological method of constructing green belts in and around the pollution sources. Air pollution in Muscat, Oman is a serious concern due to ever increasing vehicles on roads. Identifying the air pollution tolerance levels of species is important for implementing pollution control strategies in the urban areas of Muscat. Hence, in the present study, Air Pollution Tolerance Index (APTI) for ten avenue tree species was evaluated by analyzing four bio-chemical parameters, plus their Anticipated Performance Index (API) in field conditions. Based on the two indices, Ficus benghalensis was the most suitable one with the highest performance score. Conocarpus erectuse, Phoenix dactylifera, and Pithcellobium dulce were found to be good performers and are recommended for extensive planting. Azadirachta indica which is preferred for its dense canopy is qualified in the moderate category. The rest of the tree species expressed lower API score of less than 51, hence cannot be considered as suitable species for pollution mitigation plantation projects.

Keywords: Air pollution tolerance index, avenue tree species, bio-chemical parameters, Muscat.

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Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm.

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Authors: Farahnaz Amini, Woo Yun Kin, Lazwani Kolandaiveloo

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Availability of different genetic tests after completion of Human Genome Project increases the physicians’ responsibility to keep themselves update on the potential implementation of these genetic tests in their daily practice. However, due to numbers of barriers, still many of physicians are not either aware of these tests or are not willing to offer or refer their patients for genetic tests. This study was conducted an anonymous, cross-sectional, mailed-based survey to develop a primary data of Malaysian physicians’ level of knowledge and perception of gene profiling. Questionnaire had 29 questions. Total scores on selected questions were used to assess the level of knowledge. The highest possible score was 11. Descriptive statistics, one way ANOVA and chi-squared test was used for statistical analysis. Sixty three completed questionnaires were returned by 27 general practitioners (GPs) and 36 medical specialists. Responders’ age ranges from 24 to 55 years old (mean 30.2 ± 6.4). About 40% of the participants rated themselves as having poor level of knowledge in genetics in general whilst 60% believed that they have fair level of knowledge; however, almost half (46%) of the respondents felt that they were not knowledgeable about available genetic tests. A majority (94%) of the responders were not aware of any lab or company which is offering gene profiling services in Malaysia. Only 4% of participants were aware of using gene profiling for detection of dosage of some drugs. Respondents perceived greater utility of gene profiling for breast cancer (38%) compared to the colorectal familial cancer (3%). The score of knowledge ranged from 2 to 8 (mean 4.38 ± 1.67). Non- significant differences between score of knowledge of GPs and specialists were observed, with score of 4.19 and 4.58 respectively. There was no significant association between any demographic factors and level of knowledge. However, those who graduated between years 2001 to 2005 had higher level of knowledge. Overall, 83% of participants showed relatively high level of perception on value of gene profiling to detect patient’s risk of disease. However, low perception was observed for both statements of using gene profiling for general population in order to alter their lifestyle (25%) as well as having the full sequence of a patient genome for the purpose of determining a patient’s best match for treatment (18%). The lack of clinical guidelines, limited provider knowledge and awareness, lack of time and resources to educate patients, lack of evidence-based clinical information and cost of tests were the most barriers of ordering gene profiling mentioned by physicians. In conclusion Malaysian physicians who participate in this study had mediocre level of knowledge and awareness in gene profiling. The low exposure to the genetic questions and problems might be a key predictor of lack of awareness and knowledge on available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling into practice for eligible patients.

Keywords: Gene Profiling, Knowledge, Malaysia, Physician.

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Authors: K.M. Faraoun, A. Boukelif

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This paper describes a new approach of classification using genetic programming. The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination. The classification of new samples is then performed on the transformed data, and so become much easier. Contrary to the existing GP-classification techniques, the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination. Experiments were first performed using the Fisher-s Iris dataset, and then, the KDD-99 Cup dataset was used to study the intrusion detection and classification problem. Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods [1],[2] and [3], and give a very accepted results compared to other existing techniques proposed in [4],[5],[6],[7] and [8].

Keywords: Genetic programming, patterns classification, intrusion detection

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: Metaphor detection, deep learning, representation learning, embeddings.

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Authors: Carl D. Hays III

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The purpose of this theory paper is to add a reliability indicator to Operating Equipment Effectiveness (OpEE) which is used to evaluate the productivity of machines and equipment with wheels and tracks. OpEE is a derivative of Overall Equipment Effectiveness (OEE) which has been widely used for many decades in factories that manufacture products. OEE has three variables, Availability Rate, Work Rate, and Quality Rate. When OpEE was converted from OEE, the Quality Rate variable was replaced with Travel Rate. Travel Rate is essentially utilization which is a common performance indicator in machines and equipment. OpEE was designed for machines operated in remote locations such as forests, roads, fields, and farms. This theory paper intends to add the Quality Rate variable back to OpEE by including a reliability indicator in the dashboard view. This paper will suggest that the OEE quality variable can be used with a reliability metric and combined with the OpEE score. With this dashboard view of both performance metrics and reliability, fleet managers will have a more complete understanding of equipment productivity and reliability. This view will provide both leading and lagging indicators of performance in machines and equipment. The lagging indicators will indicate the trends and the leading indicators will provide an overall performance score to manage.

Keywords: Operating Equipment Effectiveness, Operating Equipment Effectiveness, IoT, Contamination Monitoring.

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Authors: Kurotimi M. Fems, Francis D. W. Poazi, Helen Opigo

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The concepts of entrepreneurship education together with graduate entrepreneurship have taken centre stage in many countries as a 21^st century strategy for economic growth and development. Entrepreneurship education has been viewed as a pre-requisite tool for a more effective and successful business operation. This paper seeks to verify if entrepreneurship education is pre-requisite to graduate entrepreneurship, and to ascertain if such other factors as the need for achievement, competence and experience etc. also play a foundational role in the choice of a graduate becoming an entrepreneur. The scope of the research study is entrepreneurs within Yenagoa metropolis in Bayelsa state, Nigeria. The sample target is graduates engaged in entrepreneurship activities (graduates who own and run businesses). Stratified sampling technique was used and 101 responses were obtained from a total of 300 questionnaires issued. Bar chart, tables and percentages were used to analyze the collected data. The findings revealed that personality traits, situational circumstance, need for achievement and experience/competence were the foundational factors stimulating graduate entrepreneurs to engage in entrepreneurial pursuits. Of all, personality trait showed the highest score with 73 (73%) out of 101 entrepreneurs agreeing. Experience/Competence and situational circumstances followed behind with 66 (65%) and 63 (62.4%), respectively. Entrepreneurship education revealed the least score with 33 (32.3%) out of 101 participating entrepreneurs. All hope, however, is not lost, as this shows that something can be done to increase the impact of entrepreneurship education on graduate entrepreneurship.

Keywords: Creative destruction, entrepreneurs, entrepreneurship education, graduate entrepreneurship, pre-requisite.

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: N. Hamzah, M. Mahli, A. I. Che-Ani, M. M Tahir, N. A. G. Abdullah, N. M Tawil

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Building inspection is one of the key components of building maintenance. The primary purpose of performing a building inspection is to evaluate the building-s condition. Without inspection, it is difficult to determine a built asset-s current condition, so failure to inspect can contribute to the asset-s future failure. Traditionally, a longhand survey description has been widely used for property condition reports. Surveys that employ ratings instead of descriptions are gaining wide acceptance in the industry because they cater to the need for numerical analysis output. These kinds of surveys are also in keeping with the new RICS HomeBuyer Report 2009. In this paper, we propose a new assessment method, derived from the current rating systems, for assessing the specifically smart school building-s condition and rating the seriousness of each defect identified. These two assessment criteria are then multiplied to find the building-s score, which we called the Condition Survey Protocol (CSP) 1 Matrix. Instead of a longhand description of a building-s defects, this matrix requires concise explanations about the defects identified, thus saving on-site time during a smart school building inspection. The full score is used to give the building an overall rating: Good, Fair or Dilapidated.

Keywords: Assessment matrix, building condition survey, rating system, smart school and survey protocol.

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Authors: Mary L. G. S. Senna, Afonso R. Aquino, Veruska C. Dutra, Carlos H. C. Tolentino

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The quality of life index, despite elucidating many discussions, the conceptual subjectivity of the term does not show precision, and consequently, many researchers seek to develop methods aiming to measure this concept, bringing it to a more concrete approach. In this study, the quality of life index method was used to analyze the population of Mateiros, Tocantins, Brazil for quality of life. After data collection, it was compared the quality of life index between the population and the group of beneficiaries of the Brazilian government assistance program Bolsa Família (Family Allowance). Some of the people interviewed receive financial aid from the federal government program Bolsa Família (22%). Comparisons were made among the final score of the quality of life index of the Mateiros population and the following factors: Gender, age, education, those working or not with tourism and those who receive or do not receive the Bolsa Família. It was observed that only the factor, Bolsa Família (p-score 0.0138), shows an association with quality of life improvement, noticing that those who have financial aid had a higher quality of life improvement than the rest of the population. It was concluded that, government assistance has shown a decisive element on the enhancement of Mateiros population quality of life, indicating that similar actions should be maintained.

Keywords: Quality of life index, government aid to families, sustainable tourism, Bolsa Familia.

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Authors: Chua Bee Seok, Shamsul Amri Baharuddin, Rosnah Ismail, Ferlis Bahari, Jasmine Adela Mutang, Lailawati Madlan, Asong Joseph

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The aims of this study were to determine the factor structure and psychometric properties (i.e., reliability and convergent validity) of the Malaysian Multi-Ethnic Discrimination Scale (MMEDS). It consists of 71-items measure experience, strategies used and consequences of ethnic discrimination. A sample of 649 university students from one of the higher education institution in Malaysia was asked to complete MMEDS, as well as Perceived Ethnic and Racial Discrimination. The exploratory factor analysis on ethnic discrimination experience extracted two factors labeled ‘unfair treatment’ (15 items) and ‘Denial of the ethnic right’ (12 items) which accounted for 60.92% of the total variance. The two sub scales demonstrated clear reliability with internal consistency above .70. The convergent validity of the Scale was supported by an expected pattern of correlations (positive and significant correlation) between the score of unfair treatment and denial of the ethnic right and the score of Perceived Ethnic and Racial Discrimination by Peers Scale. The results suggest that the MMEDS is a reliable and valid measure. However, further studies need to be carried out in other groups of sample as to validate the Scale.

Keywords: Factor structure, psychometric properties, exploratory factor analysis.

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Authors: Raif Parlakkaya, Huseyin Cetin, Duygu Irdiren

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By the development of World Wide Web, the usage rate of Internet has rapidly grown globally; and provided a basis for the emergence of electronic business. As well as other sectors, the banking sector has adopted the use of internet with the developments in information and communication technologies. Due to the public disclosure and transparency principle of Corporate Governance, the importance of information disclosure of banks on their web sites has increased significantly. For the purpose of this study, a Bank Disclosure Attribute Index (BDAI) in Turkey has been constructed through classifying the information disclosure on banks’ web sites into general, financial, investors and corporate governance attributes. All 47 banks in Turkish Banking System have been evaluated according to the index with the aim of providing a comparison between banks. By Chi Square Test, Pearson Correlation, T-Test, and ANOVA statistical tools, it has been concluded that the majority of banks in Turkey have shared information on their web sites adequately with respect to their total index score. Although there is a positive correlation between various types of information on banks’ web sites, there is no uniformity among them. Also, no significant difference between various types of information disclosure and bank types has been observed. Compared with the total index score averages of the five largest banks in Turkey, there are some banks that need to improve the content of their web sites.

Keywords: Banking sector, public disclosure, Turkey, web site evaluation.

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Authors: Vita Strazdina, Aleksandrs Jemeljanovs, Vita Sterna

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Not all proteins have the same nutritional value, since protein quality strongly depends on its amino acid composition and digestibility. The meat of game animals could be a high protein source because of its well-balanced essential amino acids composition. Investigations about biochemical composition of game meat such as wild boar (Sus scrofa scrofa), roe deer (Capreolus capreolus) and beaver (Castor fiber) are not very much. Therefore, the aim of the investigation was evaluate protein composition of game meat hunted in Latvia. The biochemical analysis, evaluation of connective tissue and essential amino acids in meat samples were done, the amino acids score were calculate. Results of analysis showed that protein content 20.88-22.05% of all types of meat samples is not different statistically. The content of connective tissue from 1.3% in roe deer till 1.5% in beaver meat allowed classified game animal as high quality meat. The sum of essential amino acids in game meat samples were determined 7.05–8.26g100g-1. Roe deer meat has highest protein content and lowest content of connective tissues among game meat hunted in Latvia. Concluded that amino acid score for limiting amino acids phenylalanine and tyrosine is high and shows high biological value of game meat.

Keywords: Dietic product, game meat, amino acids, scores.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: Steven W. Carruthers

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The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: Effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating.

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Authors: Ammal M. Metwally, Ghada A. Abdel-Latif, Walaa A. Fouad, Thanaa M. Rabah, Amira Mohsen, Fatma A. Shaaban, Iman I. Salama

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The study aimed at determining the impact of chronic hepatitis C virus (HCV) infection on patients’ Quality of Life (QoL), its relation to geographical characteristics of patients, awareness of the disease, treatment regimen, co-morbid psychiatric or other diseases. 457 patients were randomly selected from ten National Treatment Reference Centers of Ministry of Health hospitals from four community locations representing Egypt. Health related QoL assessment questionnaire with the 36-item Short Form used for assessment of the enrolled patients. The study showed no significant difference between HCV patients in different governorates as regards total QoL. Females, illiterate patients and those had bilharziasis, diabetes mellitus, hypertension or were depressed had significantly the lowest QoL score. HCV patients who knew the danger of the disease had significant lower mean score of physical and mental health components. Optimal care of overall well-being of HCV patients requires adequate knowledge of their neurological and psychological status. It is important to know how to cope with having a family member with hepatitis C and more importantly to know what should you say and what shouldn’t you say as a positive hopeful attitude is essential for combating HCV chronic infection.

Keywords: Hepatitis C virus chronic infection, physical health component and mental health component of QoL, total quality of life.

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Authors: Rami N. Khushaba, Ahmed Al-Ani, Adel Al-Jumaily

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One of the approaches enabling people with amputated limbs to establish some sort of interface with the real world includes the utilization of the myoelectric signal (MES) from the remaining muscles of those limbs. The MES can be used as a control input to a multifunction prosthetic device. In this control scheme, known as the myoelectric control, a pattern recognition approach is usually utilized to discriminate between the MES signals that belong to different classes of the forearm movements. Since the MES is recorded using multiple channels, the feature vector size can become very large. In order to reduce the computational cost and enhance the generalization capability of the classifier, a dimensionality reduction method is needed to identify an informative yet moderate size feature set. This paper proposes a new fuzzy version of the well known Fisher-s Linear Discriminant Analysis (LDA) feature projection technique. Furthermore, based on the fact that certain muscles might contribute more to the discrimination process, a novel feature weighting scheme is also presented by employing Particle Swarm Optimization (PSO) for estimating the weight of each feature. The new method, called PSOFLDA, is tested on real MES datasets and compared with other techniques to prove its superiority.

Keywords: Discriminant Analysis, Pattern Recognition, SignalProcessing.

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Authors: C. Caçador, M. J. Reis Lima, J. Oliveira, M. J. Veiga, M. Teixeira Veríssimo, F. Ramos, M. C. Castilho, E. Teixeira-Lemos

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In the present study we evaluated the nutritional status of 214 institutionalized elderly residents of both genders, aged 65 years and older of 11 care homes located in the district of Viseu (center of Portugal). The evaluation was based on anthropometric measurements and the Mini Nutritional Assessment (MNA) score.

The mean age of the subjects was 82.3 ± 6.1 years-old. Most of the elderly residents were female (72.0%). The majority had 4 years of formal education (51.9%) and was widowed (74.3%) or married (14.0%).

Men presented a mean age of 81.2±8.5 years-old, weight 69.3±14.5 kg and BMI 25.33±6.5 kg/m². In women, the mean age was 84.5±8.2 years-old, weight 61.2±14.7 kg and BMI 27.43±5.6 kg/m².

The evaluation of the nutritional status using the MNA score showed that 24.0% of the residents show a risk of undernutrition and 76.0% of them were well nourished.

There was a high prevalence of obese (24.8%) and overweight residents (33.2%) according to the BMI. 7.5% were considered underweight.

We also found that according to their waist circumference measurements 88.3% of the residents were at risk for cardiovascular disease (CVD) and 64.0% of them presented very high risk for CVD (WC≥88 cm for women and WC ≥102 cm for men).

The present study revealed the coexistence of a dual form of malnutrition (undernourished and overweight) among the institutionalized Portuguese concomitantly with an excess of abdominal adiposity. The high prevalence of residents at high risk for CVD should not be overlooked.

Given the vulnerability of the group of institutionalized elderly, our study highlights the importance of the classification of nutritional status based on both instruments: the BMI and the MNA.

Keywords: Nutritional status, MNA, BMI, elderly.

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Authors: J. Hossen, A. Rahman, K. Samsudin, F. Rokhani, S. Sayeed, R. Hasan

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The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a novel Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data sets. A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and rules by the fuzzy c-means clustering and Apriori algorithm technique, respectively. The generated adaptive fuzzy inference engine is adjusted by the least-squares fit and a conjugate gradient descent algorithm towards better performance with a minimal set of rules. The proposed MAFIE is able to reduce the number of rules which increases exponentially when more input variables are involved. The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher-s Iris and Wisconsin breast cancer data sets and shown to be very competitive.

Keywords: Apriori algorithm, Fuzzy C-means, MAFIE, TSK

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Authors: Y. T. Gee, I. N. Umar

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Students’ achievement and motivation in learning English in Malaysia is a worrying trend as it is lagging behind several other countries in Asia. Thus, necessary actions have to be taken by the parties concerned to overcome this problem. The purpose of this research was to study the effects of drill and practice courseware on students’ achievement and motivation in learning English language. A multimedia courseware was developed for this purpose. The independent variable was the drill and practice courseware while the dependent variables were the students’ achievement and motivation. Their achievement was measured using pre-test and post-test scores, while motivation was measured using a questionnaire. A total of 60 students from three vernacular primary schools in a northern state in Malaysia were randomly selected in this study. The findings indicate: (1) a significant difference between the students’ pre-test and posttest scores after using the courseware, (2) no significant difference in the achievement score between male and female students after using the courseware, (3) a significant difference in motivation score between the female and the male students, and (4) while the female students scored significantly higher than the male students in the aspects of relevance, confidence and satisfaction, no significant difference in terms of attention was observed between them. Overall, the findings clearly indicate that although the female students are significantly more motivated than their male students, they are equally good in terms of achievement after learning from the courseware. Through this study, the drill and practice courseware is proven to influence the students’ learning and motivation.

Keywords: Courseware, drill and practice, English learning, motivation.

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Authors: Thossaporn Thossansin

Abstract:

This paper presents the development of a mobile application for students at the Faculty of Information Technology, Rangsit University (RSU), Thailand. RSU upgrades an enrollment process by improving its information systems. Students can download the RSU APP easily in order to access the RSU substantial information. The reason of having a mobile application is to help students to access the system regardless of time and place. The objectives of this paper include: 1. To develop an application on iOS platform for those students at the Faculty of Information Technology, Rangsit University, Thailand. 2. To obtain the students’ perception towards the new mobile app. The target group is those from the freshman year till the senior year of the faculty of Information Technology, Rangsit University. The new mobile application, called as RSU APP, is developed by the department of Information Technology, Rangsit University. It contains useful features and various functionalities particularly on those that can give support to students. The core contents of the app consist of RSU’s announcement, calendar, events, activities, and ebook. The mobile app is developed on the iOS platform. The user satisfaction is analyzed from the interview data from 81 interviewees as well as a Google application like a Google form which 122 interviewees are involved. The result shows that users are satisfied with the application as they score it the most satisfaction level at 4.67 SD 0.52. The score for the question if users can learn and use the application quickly is high which is 4.82 SD 0.71. On the other hand, the lowest satisfaction rating is in the app’s form, apps lists, with the satisfaction level as 4.01 SD 0.45.

Keywords: Mobile application, development of mobile application, framework of mobile development, software development for mobile devices.

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Authors: Zahra Emami, Mohammad Ebrahim Khamseh, Nahid Hashemi Madani, Iman Kermani

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The aim of the study was to map scientific research on adrenal gland diseases in the Middle East countries through the Web of Science database using scientometric analysis. Data were analyzed with Excel software; and HistCite was used for mapping of the scientific texts. In this study, from a total of 268 retrieved records, 1125 authors from 328 institutions published their texts in 138 journals. Among 17 Middle East countries, Turkey ranked first with 164 documents (61.19%), Israel ranked second with 47 documents (15.53%) and Iran came in the third place with 26 documents. Most of the publications (185 documents, 69.2%) were articles. Among the universities of the Middle East, Istanbul University had the highest science production rate (9.7%). The Journal of Clinical Endocrinology & Metabolism had the highest TGCS (243 citations). In the scientific mapping, 7 clusters were formed based on TLCS (Total Local Citation Score) & TGCS (Total Global Citation Score). considering the study results, establishment of scientific connections and collaboration with other countries and use of publications on adrenal gland diseases from high ranking universities can help in the development of this field and promote the medical practice in this regard. Moreover, investigation of the formed clusters in relation to Congenital Hyperplasia and puberty related disorders can be research priorities for investigators.

Keywords: Mapping, scientific research, adrenal gland diseases, scientometric.

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Authors: Neilal A. Isaac, Madison Edwards, Kirthana Sugunathevan, Mohan Kumar

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The COVID-19 pandemic challenged the education system and forced medical schools to transition to online learning. With this transition, one of the major concerns for students and educators was to ensure that Physical Examination (PE) skills were still being mastered. Thus, the formative peer assessment model was designed to enhance the learning of PE skills during the COVID-19 pandemic in the online learning landscape. Year 1 and year 2 students enrolled in clinical skills courses at the University of Medicine and Health Sciences, St. Kitts were asked to record themselves demonstrating PE skills with a healthy patient volunteer after every skills class. Each student was assigned to exchange feedback with one peer in the course. At the end of the first two semesters of this learning activity, a cross-sectional survey was conducted for the two cohorts of year-1 and year-2 students. The year-1 cohorts most frequently rated the peer assessment exercise as 4 on a 5-point Likert scale, with a mean score of 3.317 [2.759, 3.875]. The year-2 cohorts most frequently rated the peer assessment exercise as 4 on a 5-point Likert scale, with a mean score of 3.597 [2.978, 4.180]. Students indicated that guidance from faculty, flexible deadlines, and detailed and timely feedback from peers were areas for improvement in this process.

Keywords: COVID-19 pandemic, distant learning, online medical education, peer assessment, physical examination.

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Authors: Yanto Santosa, Catharina Yudea

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The rapid growth of oil palm industry in Indonesia raised many negative accusations from various parties, who said that oil palm plantation is damaging the environment and biodiversity, including birds. Since research on oil palm plantation impacts on bird diversity is still limited, this study needs to be developed in order to gain further learning and understanding. Data on bird diversity were collected in March 2018 in KJNP Estate, Riau Province using strip transect method on five different land cover types (young, intermediate, and old growth of oil palm plantation, high conservation value area, and crops field or the baseline). The observations were conducted simultaneously, with three repetitions. The result shows that the baseline has 19 species of birds and land cover after the oil palm plantation has 39 species. HCV (high conservation value) area has the highest increase in diversity value. Oil palm plantation has changed the composition of bird species. The highest similarity index is shown by young growth oil palm land cover with total score 0.65, meanwhile the lowest similarity index with total score 0.43 is shown by HCV area. Overall, the existence of oil palm plantation made a positive impact by increasing bird species diversity, with total 23 species gained and 3 species lost.

Keywords: Bird diversity, crops field, impact of oil palm plantation, KJNP estate.

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Authors: Kamolrat Turner, Somporn Rakkwamsuk, Ladda Leungratanamart

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The aim of this descriptive study was to determine the perception of 21^st century skills among nursing professors and nursing students at Boromarajonani College of Nursing, Chonburi. A total of 38 nursing professors and 75 second year nursing students took part in the study. Data were collected by 21^st century skills questionnaires comprised of 63 items. Descriptive statistics were used to describe the findings. The results have shown that the overall mean scores of the perception of nursing professors on 21^st century skills were at a high level. The highest mean scores were recorded for computing and ICT literacy, and career and leaning skills. The lowest mean scores were recorded for reading and writing and mathematics. The overall mean scores on perception of nursing students on 21^st century skills were at a high level. The highest mean scores were recorded for computer and ICT literacy, for which the highest item mean scores were recorded for competency on computer programs. The lowest mean scores were recorded for the reading, writing, and mathematics components, in which the highest item mean score was reading Thai correctly, and the lowest item mean score was English reading and translate to other correctly. The findings from this study have shown that the perceptions of nursing professors were consistent with those of nursing students. Moreover, any activities aiming to raise capacity on English reading and translate information to others should be taken into the consideration.

Keywords: 21st century skills, perception, nursing instructor, nursing student.

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Authors: Kazem Alirezalu, Javad Hesari, Zabihollah Nemati, Boukaga Farmani

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The application of natural plant extracts which are rich in promising antioxidants and antimicrobial ingredients in the production of frankfurter-type sausages addresses consumer demands for healthier, more functional meat products. The effects of olive leaves, green tea and Urtica dioica L. extracts on physicochemical, microbiological and sensory characteristic of frankfurter-type sausage were investigated during 45 days of storage at 4 °C. The results revealed that pH and phenolic compounds decreased significantly (P < 0.05) in all samples during storage. Sausages containing 500 ppm green tea extract (1.78 mg/kg) showed the lowest TBARS values compared to olive leaves (2.01 mg/kg), Urtica dioica L. (2.26 mg/kg) extracts and control (2.74 mg/kg). Plant extracts significantly (P < 0.05) reduced the count of total mesophilic bacteria, yeast and mold by at least 2 log cycles (CFU/g) than those of control samples. Sensory characteristics of texture showed no difference (P > 0.05) between sausage samples, but sausage containing Urtica dioica L. extract had the highest score regarding flavor, freshness odor, and overall acceptability. Based on the results, sausage containing plant extracts could have a significant impact on antimicrobial activity, antioxidant capacity, sensory score, and shelf life stability of frankfurter-type sausage.

Keywords: Antimicrobial, antioxidant, frankfurter-type sausage, green tea, olive oil, shelf life, Urtica dioica L.

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Authors: Vladyslav Povoroznyuk, Nataliia Dzerovych, Larysa Martynyuk, Tetiana Kovtun

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Obesity and osteoporosis are the two diseases whose increasing prevalence and high impact on the global morbidity and mortality, during the two recent decades, have gained a status of major health threats worldwide. Obesity purports to affect the bone metabolism through complex mechanisms. Debated data on the connection between the bone mineral density and fracture prevalence in the obese patients are widely presented in literature. There is evidence that the correlation of weight and fracture risk is sitespecific. This study is aimed at determining the connection between the bone mineral density (BMD) and trabecular bone score (TBS) parameters in Ukrainian women suffering from obesity. We examined 1025 40-89-year-old women, divided them into the groups according to their body mass index: Group A included 360 women with obesity whose BMI was ≥30 kg/m2, and Group B – 665 women with no obesity and BMI of <30 kg/m2. The BMD of total body, lumbar spine at the site L1-L4, femur and forearm were measured by DXA (Prodigy, GEHC Lunar, Madison, WI, USA). The TBS of L1- L4 was assessed by means of TBS iNsight® software installed on our DXA machine (product of Med-Imaps, Pessac, France). In general, obese women had a significantly higher BMD of lumbar spine, femoral neck, proximal femur, total body and ultradistal forearm (p<0.001) in comparison with women without obesity. The TBS of L1-L4 was significantly lower in obese women compared to nonobese women (p<0.001). The BMD of lumbar spine, femoral neck and total body differed to a significant extent in women of 40-49, 50- 59, 60-69 and 70-79 years (p<0.05). At same time, in women aged 80-89 years the BMD of lumbar spine (p=0.09), femoral neck (p=0.22) and total body (p=0.06) barely differed. The BMD of ultradistal forearm was significantly higher in women of all age groups (p<0.05). The TBS of L1-L4 in all the age groups tended to reveal the lower parameters in obese women compared with the nonobese; however, those data were not statistically significant. By contrast, a significant positive correlation was observed between the fat mass and the BMD at different sites. The correlation between the fat mass and TBS of L1-L4 was also significant, although negative. Women with vertebral fractures had a significantly lower body weight, body mass index and total body fat mass in comparison with women without vertebral fractures in their anamnesis. In obese women the frequency of vertebral fractures was 27%, while in women without obesity – 57%.

Keywords: Bone mineral density, trabecular bone score, obesity, women.

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Authors: Okolie Uchenna, Ehiemere Ijeoma, Ezenduka Pauline, Ogbu Sylvester

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A cross sectional survey design was used to collect data from 370 diabetic patients. Two instruments were used in obtaining data; in-depth interview guide and researchers- developed questionnaire. Fisher's exact test was used to investigate association between the identified factors and nonadherence. Factors identified were: socio-demographic factors such as: gender, age, marital status, educational level and occupation; psychosocial obstacles such as: non-affordability of prescribed diet, frustration due to the restriction, limited spousal support, feelings of deprivation, feeling that temptation is inevitable, difficulty in adhering in social gatherings and difficulty in revealing to host that one is diabetic; health care providers obstacles were: poor attitude of health workers, irregular diabetes education in clinics , limited number of nutrition education sessions/ inability of the patients to estimate the desired quantity of food, no reminder post cards or phone calls about upcoming patient appointments and delayed start of appointment / time wasting in clinics.

Keywords: Behavior change, diabetes mellitus, dietarymanagement, diet adherence.

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Authors: Nadir A. Carreón, Christa Sonderer, Aakarsh Rao, Roman Lysecky

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With the advent of complex software and increased connectivity, security of life-critical medical devices is becoming an increasing concern, particularly with their direct impact to human safety. Security is essential, but it is impossible to develop completely secure and impenetrable systems at design time. Therefore, it is important to assess the potential impact on security and safety of exploiting a vulnerability in such critical medical systems. The common vulnerability scoring system (CVSS) calculates the severity of exploitable vulnerabilities. However, for medical devices, it does not consider the unique challenges of impacts to human health and privacy. Thus, the scoring of a medical device on which a human life depends (e.g., pacemakers, insulin pumps) can score very low, while a system on which a human life does not depend (e.g., hospital archiving systems) might score very high. In this paper, we present a Medical Vulnerability Scoring System (MVSS) that extends CVSS to address the health and privacy concerns of medical devices. We propose incorporating two new parameters, namely health impact and sensitivity impact. Sensitivity refers to the type of information that can be stolen from the device, and health represents the impact to the safety of the patient if the vulnerability is exploited (e.g., potential harm, life threatening). We evaluate 15 different known vulnerabilities in medical devices and compare MVSS against two state-of-the-art medical device-oriented vulnerability scoring system and the foundational CVSS.

Keywords: Common vulnerability system, medical devices, medical device security, vulnerabilities.

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