Search results for: PREDICT score

Authors: Asmaa Abazaid, Maram Al-Ostah, Nadeen Abu-Zahra, Ruba Bawab, Refaat Abdel-Razek

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Innovation audit is defined as a tool that can be used to reflect on how the innovation is managed in an organization. The aim of this study is to audit innovation in the second top Engineering Firms in the world, and one of the Small Medium Enterprises (SMEs) companies that are working in United Arab Emirates (UAE). The obtained results are then compared with four international companies from China and Brazil. The Diamond model has been used for auditing innovation in the two companies in UAE to evaluate their innovation management and to identify each company’s strengths and weaknesses from an innovation perspective. The results of the comparison between the two companies (Jacobs and Hyper General Contracting) revealed that Jacobs has support for innovation, its innovation processes are well managed, the company is committed to the development of its employees worldwide and the innovation system is flexible. Jacobs was doing best in all innovation management dimensions: strategy, process, organization, linkages and learning, while Hyper General Contracting did not score as Jacobs in any of the innovation dimensions. Furthermore, the audit results of both companies were compared with international companies to examine how well the two construction companies in UAE manage innovation relative to SABIC (Saudi company), Poly Easy and Arnious (Brazilian companies), Huagong tools and Guizohou Yibai (Chinese companies). The results revealed that Jacobs is doing best in learning and organization dimensions, while PolyEasy and Jacobs are equal in the linkage dimension. Huagong Tools scored the highest score in process dimension among all the compared companies. However, the highest score of strategy dimension was given to PolyEasy. On the other hand, Hyper General Contracting scored the lowest in all of the innovation management dimensions. It needs to improve its management of all the innovation management dimensions with special attention to be given to strategy, process, and linkage as they got scores below 4 out of 7 comparing with other dimensions. Jacobs scored the highest in three innovation management dimensions related to the six companies. However, the strategy dimension is considered low, and special attention is needed in this dimension.

Keywords: Brazil, China, innovation audit, innovation evaluation, innovation management, Saudi Arabia, United Arab Emirates

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

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Authors: K. Hariohm, V. Prakash, J. Saravana Kumar

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Introduction and Rationale: Increased scope of Physiotherapy (PT) practice also has contributed to research in the field of PT. It is essential to determine the production and quality of the clinical trials from India since, it may reflect the scientific growth of the profession. These trends can be taken as a baseline to measure our performance and also can be used as a guideline for the future trials. Objective: To quantify and analyze qualitatively the RCT’s from India from the period 2000-2013’ May, and classify data for the information process. Methods: Studies were searched in the Medline database using the key terms “India”, “Indian”, “Physiotherapy”. Clinical trials only with PT authors were included. Trials out of scope of PT practice and on animals were excluded. Retrieved valid articles were analyzed for published year, type of participants, area of study, PEDro score, outcome measure domains of impairment, activity, participation; ‘a priori’ sample size calculation, region, and explanation of the intervention. Result: 45 valid articles were retrieved from the year 2000-2013’ May. The majority of articles were done on symptomatic participants (81%). The frequencies of conditions repeated more were low back pain (n-7) and diabetes (n-4). PEDro score with mode 5 and upper limit of 8 and lower limit 4 was found. 97.2% of studies measure the outcome at the impairment level, 34% in activity level, and 27.8% in participation level. 29.7% of studies did ‘a priori’ sample size calculation. Correlation of year trend and PEDro score found to be not significant (p>.05). Individual PEDro item analysis showed, randomization (100%), concealment (33%) baseline (76%), blinding-subject, therapist, assessor (9.1%, 0%, 10%), follow-up (89%) ITT (15%), statistics between groups (100%), measures of variance (88 %). Conclusion: The trend shows an upward slope in terms of RCTs published from India which is a good indicator. The qualitative analysis showed some gaps in the clinical trial design, which can be expected to be, fulfilled by the future researchers.

Keywords: RCT, PEDro, physical therapy, rehabilitation

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Authors: Sukanya Sripho

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This paper aims to examine the level of roles performed in tourism development by local people residing in Chiang Khan Sub-District Municipality, Loei Province in Northeast of Thailand. In addition, this study also tested whether personal factors had a relationship with the level of roles performed in tourism development. These personal factors included gender, age, educational level, career, position and duty in the community, average income per month, length of residence and involvement in the tourism industry. The findings revealed a high level in each role performed. These roles were ranked from the highest mean score to the lowest mean score as follows: (1) improving and rejuvenating tourist attractions; (2) improving tourist facilities; (3) promoting people participation; (4) publicizing tourist attractions; (5) protecting for safety and security; and (6) surveying and managing the information of tourist attractions. Furthermore, it was found that position and duty in the community, length of residence and involvement in tourism industry had a relationship with the level of roles performed in tourism development at a significance level of 0.05.

Keywords: Role, local municipality administration, tourism development, Thailand

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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: Kartika Marta Budiana

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Low competence in speaking for the students of Non English native speakers have been crucial so far for the teachers in language teaching in Indonesia. This study attempts to explore the effect of video using in teaching speaking onstudents of non-native English speakers at STIE Perbanas Surabaya. This includes investigate the students` attitudes toward the video used in classroom. This is a quantitative research that is an experimental one based on analyses derived the concepts of from teaching speaking and the use of video. There are two classes observed, the experimental and the control one. The experimental consist of 28 students and the control class consists of 25 students. Before the treatment given, both of the group is given the pre-test to check their ability level. Then, after the treatment is given, the post-test is given to the both groups. Then, the students were given treatment how to conduct a meeting that they learnt from a video of business English. The post test was held after they undergone a treatment. The instruments to get the data are the oral test and questionnaire. The data of this study is students` score and from the tests` score it can be seen there is a positive significant difference in the experimental group. The t-test to test hypothesize also shows that it is accepted which said that there is an improvement on the students` speaking competence achievement. In conclusion, the video effects on the significant difference on the students speaking competence achievement.

Keywords: video, teaching, speaking, Indonesia

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Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Manasvi Pinnaka, Brianna Chrisman

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Cystic fibrosis patients often develop lung infections that range anywhere in severity from mild to life-threatening due to the presence of thick and sticky mucus that fills their airways. Since many of these infections are chronic, they not only affect a patient’s ability to breathe but also increase the chances of mortality by respiratory failure. With a publicly available dataset of DNA sequences from bacterial species in the lung microbiome of cystic fibrosis patients, the correlations between different microbial species in the lung and the extent of deterioration of lung function were investigated. 16S sequencing technologies were used to determine the microbiome composition of the samples in the dataset. For the statistical analyses, referencing helped distinguish between taxonomies, and the proportions of certain taxa relative to another were determined. It was found that the Fusobacterium, Actinomyces, and Leptotrichia microbial types all had a positive correlation with the FEV1 score, indicating the potential displacement of these species by pathogens as the disease progresses. However, the dominant pathogens themselves, including Pseudomonas aeruginosa and Staphylococcus aureus, did not have statistically significant negative correlations with the FEV1 score as described by past literature. Examining the lung microbiology of cystic fibrosis patients can help with the prediction of the current condition of lung function, with the potential to guide doctors when designing personalized treatment plans for patients.

Keywords: bacterial infections, cystic fibrosis, lung microbiome, 16S sequencing

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Authors: Gülcan Taşkıran, Ülkü Tatar Baykal

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Aim: To identify nurses’ perceived competencies for disaster preparedness. Background: Recently, the number of disasters has increased worldwide. Since disasters often strike without warning, healthcare providers, especially nurses must be prepared with appropriate competencies for disaster procedures. Nurses’ perceptions of their own competencies for disaster preparedness need to be evaluated to aid in the creation of effective national plans and educational programs. Design: This study was conducted with a descriptive and cross-sectional design. Methods: Nurses’ perceptions were assessed using the 13-item Demographic Profile Questionnaire that is based on previous literature and the 45-item Nurses’ Perception of Core Competencies for Disaster Preparedness Scale (NPCDPS). Data were collected from June to September 2014 from 406 (79.9% return rate) Turkish nurses working in the western region of Turkey. Results: At the end of the study, it was found that out of the nurses whose mean age was 31.27 ± 5.86 and mean of working time was 8.07 ± 6.60 by the time vast majority of the nurses were women (85.7%), married (59.4%), bachelor’s degree holder (88.2%) and service nurses (56.2%). The most potential disaster that nurses think is an earthquake (70.9%) by the time majority of nurses consider having a role as a nurse at every stage of disasters. The mean total point score of nurses’ perception of disaster preparedness was 4.62. The mean total point score of the nurses from the Nurses’ Perception of Core Competencies for Disaster Preparedness Scale was 133.96. When the subscales’ mean scores are examined, the highest average of the mean score is for Technical Skills (44.52), and the lowest is for Critical Thinking Skills (10.47). When the subscales of Nurses’ Perception of Core Competencies for Disaster Preparedness Scale compared with sex, marital status and education level out of independent variable of nurses there is no significant difference (p > 0.05); compared with age group, working years, duty and being with a disaster out of independent variable of nurses there is a significant difference (p ≤ 0.05). Conclusion: Nurses generally perceive themselves as sufficient at a ‘medium level’ in terms of meeting the core competencies that are required for disaster preparedness. Nurses are not adequately prepared for disasters, but they are aware of the need for such preparation and disaster education. Disaster management training should be given to all nurses in their basic education.

Keywords: disaster competencies, disaster management, disaster nursing, disaster preparedness, nursing, nursing administration, Turkish nurses

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park

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Automotive interior material consisting of several material layers has the sound-absorbing function. It is difficult to predict sound absorbing coefficient because of several material layers. So, many experimental tunings are required to achieve the target of sound absorption. Therefore, while the car interior materials are developed, so much time and money is spent. In this study, we present a method to predict the sound absorbing performance of the material with multi-layer using physical properties of each material. The properties are predicted by Foam-X software using the sound absorption coefficient data measured by impedance tube. Then, we will compare and analyze the predicted sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If the method is used instead of experimental tuning in the development of car interior material, the time and money can be saved, and then, the development effort can be reduced because it can be optimized by simulation.

Keywords: multi-layer nonwoven, sound absorption coefficient, scaled reverberation chamber, impedance tubes

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Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

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The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

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Authors: Mohamed Aly, Aliaa Rehan Youssef, Emad Sawerees, Mounir Guirgis

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Relevance: Osteoarthritis (OA) is the most common degenerative disease seen in all populations. It causes disability and substantial socioeconomic burden. Evidence supports that exercise are the most effective conservative treatment for patients with OA. Therapists experience and clinical judgment play major role in exercise prescription and scientific evidence for this regard is lacking. The development of clinical prediction rules to identify patients who are most likely benefit from exercise may help solving this dilemma. Purpose: This study investigated whether body mass index and functional ability at baseline can predict patients’ response to a selected exercise program. Approach: Fifty-six patients, aged 35 to 65 years, completed an exercise program consisting of open kinetic chain strengthening and passive stretching exercises. The program was given for 3 sessions per week, 45 minutes per session, for 6 weeks Evaluation: At baseline and post treatment, pain severity was assessed using the numerical pain rating scale, whereas functional ability was being assessed by step test (ST), time up and go test (TUG) and 50 feet time walk test (50 FTW). After completing the program, global rate of change (GROC) score of greater than 4 was used to categorize patients as successful and non-successful. Thirty-eight patients (68%) had successful response to the intervention. Logistic regression showed that BMI and 50 FTW test were the only significant predictors. Based on the results, patients with BMI less than 34.71 kg/m2 and 50 FTW test less than 25.64 sec are 68% to 89% more likely to benefit from the exercise program. Conclusions: Clinicians should consider the described strengthening and flexibility exercise program for patents with BMI less than 34.7 Kg/m2 and 50 FTW faster than 25.6 seconds. The validity of these predictors should be investigated for other exercise.

Keywords: clinical prediction rule, knee osteoarthritis, physical therapy exercises, validity

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Authors: Prashant Verma, Prafulla K. Swain, K. K. Singh, Mukti Khetan

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Objective: In India, around 20,000 women die every year due to abortion-related complications. In the modelling of count variables, there is sometimes a preponderance of zero counts. This article concerns the estimation of various count regression models to predict the average number of spontaneous abortion among women in the Punjab state of India. It also assesses the factors associated with the number of spontaneous abortions. Materials and methods: The study included 27,173 married women of Punjab obtained from the DLHS-4 survey (2012-13). Poisson regression (PR), Negative binomial (NB) regression, zero hurdle negative binomial (ZHNB), and zero-inflated negative binomial (ZINB) models were employed to predict the average number of spontaneous abortions and to identify the determinants affecting the number of spontaneous abortions. Results: Statistical comparisons among four estimation methods revealed that the ZINB model provides the best prediction for the number of spontaneous abortions. Antenatal care (ANC) place, place of residence, total children born to a woman, woman's education and economic status were found to be the most significant factors affecting the occurrence of spontaneous abortion. Conclusions: The study offers a practical demonstration of techniques designed to handle count variables. Statistical comparisons among four estimation models revealed that the ZINB model provided the best prediction for the number of spontaneous abortions and is recommended to be used to predict the number of spontaneous abortions. The study suggests that women receive institutional Antenatal care to attain limited parity. It also advocates promoting higher education among women in Punjab, India.

Keywords: count data, spontaneous abortion, Poisson model, negative binomial model, zero hurdle negative binomial, zero-inflated negative binomial, regression

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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: internet banking, websites evaluation, customer adoption, Turkey

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Authors: Dong-Ho Kim, Zheng-Xun Jin, Yong-Woon Cha, Su-Sang Lim, Sang-Won Han, Chang-Taek Hyun

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As construction is a labor-intensive industry, it is important to identify and manage labor quantities for accurate progress management of the construction project. However, the progress management that focuses on construction cost calculated based on materials rather than labor quantities has led to a difference in the implementation of cost and progress of the actual construction. In addition, since it is not easy to predict accurate labor quantities in the estimation of labor quantity-based progress rate, there have been limited researches into the progress rate estimation based on labor quantity. Accordingly, this study proposed a process for labor quantity-based progress rate estimation using a standard of estimate to predict accurate progress rate of the construction project in Republic Korea. It is expected that the utilization of the proposed process will help to identify the progress rate closer to that of the actual site management and adjust the workforce in each construction type, thereby contributing to improving construction efficiency.

Keywords: labor based, labor cost, progress management, progress rate, progress payment

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Authors: Şefika Dilek Güven, Gülden Küçükakça

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Objective: Learning the process of interaction with patient occurs within the process of nursing education. For this reason, it is considered to provide an opportunity for questioning and rearrangement of nursing education programs by assessing attitudes of nursing students towards caring nurse-patient interaction. Method: This is a descriptive study conducted in order to assess attitudes of nursing students towards caring nurse-patient interaction. The study was conducted with 318 students who were studying at nursing department of Semra and Vefa Küçük Health High School, Nevşehir Hacı Bektaş Veli University in 2015-2016 academic year and agreed to participate in the study. “Personal Information Form” prepared by the researchers utilizing the literature and “Caring Nurse-Patient Interaction Scale (CNPIS)”, who Turkish validity and reliability were conducted by Atar and Aştı, were used in the study. The Cronbach α coefficient of CNPIS was found as 0.973 in the study. Permissions of the institution and participants were received before starting to conduct study. Significance test of the difference between two means, analysis of variance, and correlation analysis were used to assess the data. Results: Average age of nursing students participating in the study was 20.72±1.91 and 74.8% were female, and 28.0% were the fourth-year students. 52.5% of the nursing students stated that they chose nursing profession willingly, 80.2% did not have difficulty in their interactions with patients, and 84.6% did not have difficulty in their social relationships. CNPIS total mean score of nursing students was found to be 295.31±40.95. When the correlation between total CNPIS mean score of the nursing students in terms of some variables was examined; it was determined there was a significant positive correlation between ages of the nursing students and total mean score of CNPIS (r=0.184, p=0.001). CNPIS total mean score was found to be higher in female students compared to male students, in 3rd–year students compared to students studying at other years, in those choosing their profession willingly compared to those choosing their profession unwillingly, in those not having difficulty in relations with the patients compared to those having difficulty, and in those not having difficulty in social relationships compared to those having difficulty. It was determined there was a significant difference between CNPIS total mean scores in terms of the year and state of having difficulty in social relationships (p<0,005). Conclusion: Nursing students had positive attitudes towards caring nurse-patient interactions, attitudes of nursing students, who were female, studying at 3rd year, chose nursing profession willingly, did not have difficulty in patient relations, and did not have difficulty in social relationships, towards caring nurse-patient interaction were found to be more positive. In the line with these results; it can be recommended to organize activities for introducing nursing profession to the youth preparing for the university, to use methods that will increase further communication skills to nursing students during their education, to support students in terms of communication skills, and to involve activities that will strengthen their social relationships.

Keywords: nurse-patient interaction, nursing student, patient, communication

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Authors: Mohammad Hadi Mahmoodi, Azam Ghonchepoor, Sheilan Sohrabi

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The present study was conducted to investigate the effect of foreign language classroom anxiety and ambiguity tolerance on EFL Learners’ listening proficiency. In so doing, 442 EFL learners were randomly selected form Azad University and some accredited language institutions in Hamaden, and were given the Foreign Language Classroom Anxiety Scale (FLCAS) (1983), and Second Language Tolerance of Ambiguity Scale (SLTAS) (1995). Participants’ listening proficiency level was determined through listening scores gained in standardized exams given by university professors or institutes in which they studied English. The results of two-way ANOVA revealed that listening proficiency was significantly affected by the interaction of anxiety and AT level of the participants. Each of the two variables were categorized in three levels of High, Mid, and Low. The highest mean score of listening belonged to the group with low degree of anxiety and high degree of ambiguity tolerance, and the lowest listening mean score was gained by the group with high level of anxiety and low level of tolerance of ambiguity. Also, the findings of multiple regressions confirmed that anxiety was the stronger predictor of listening comprehension in contrast with tolerance of ambiguity. Furthermore, the result of Pearson correlation coefficient showed that there was a significant negative relationship between the participants’ foreign language classroom anxiety and their ambiguity tolerance level.

Keywords: Foreign Language Classroom Anxiety, Second language tolerance of ambiguity, Listening proficiency

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Authors: Chun-Qing Li, Hassan Baji, Wei Yang

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Corrosion of steel in reinforced concrete structures is a major problem worldwide. The volume expansion of corrosion products causes concrete cover cracking, which could lead to delamination of concrete cover. The time to cover cracking plays a key role to the assessment of serviceability of reinforced concrete structures subjected to corrosion. Many analytical, numerical, and empirical models have been developed to predict the time to cracking initiation due to corrosion. In this study, a numerical model based on finite element modeling of corrosion-induced cracking process is used. In order to predict the service life based on time to cover initiation, the numerical approach is coupled with a probabilistic procedure. In this procedure, all the influential factors affecting time to cover cracking are modeled as random variables. The results show that the time to cover cracking is highly variables. It is also shown that rust product expansion ratio and the size of more porous concrete zone around the rebar are the most influential factors in predicting service life of corrosion-affected structures.

Keywords: corrosion, crack width, probabilistic, service life

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Authors: Chuanphit Chumkhong

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This research aimed 1) to study the effects of the management of Active Learning among 3rd year students enrolled in teacher’s profession courses and 2) to assess the satisfaction of the students with courses using the Active Learning approach. The population for the study consisted of 442 3rd year undergraduate students enrolled in two teacher education courses in 2015: Curriculum Development and Learning Process Management. They were 442 from 11 education programs. Respondents for evaluation of satisfaction with Active Learning management comprised 432 students. The instruments used in research included a detailed course description and rating scale questionnaire on Active Learning. The data were analyzed using arithmetic mean and standard deviation. The results of the study reveal the following: 1. Overall, students gain a better understanding of the Active Learning due to their actual practice on the activity of course. Students have the opportunity to exchange learning knowledge and skills. The AL teaching activities make students interested in the contents and they seek to search for knowledge on their own. 2. Overall, 3rd year students are satisfied with the Active Learning management at a ‘high’ level with a mean score (μ) of 4.12 and standard deviation (σ) of. 51. By individual items, students are satisfied with the 10 elements in the two courses at a ‘high’ level with the mean score (μ) between 3.79 to 4.41 and a standard deviation (σ) between to 68. 79.

Keywords: active learning teaching model, teacher’s professional courses, professional courses, curriculum and instruction teacher's

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Authors: Ali Ahmadi, Maryam Abbasi, Mohammad Mehdi Parsaei

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Background: Stress in the workplace today is one of the most important public health concerns and a serious threat to the health of the workforce worldwide. Occupational stress can cause occupational events and reduce quality of life. As a result, it has a very undesirable impact on the performance of organizations, companies, and their human resources. This study aimed to evaluate the relationship between job stress dimensions and occupational accidents in industrial factories in Southwest Iran. Materials and Methods: This cross-sectional study was conducted among 200 workers in the summer of 2023 in the Southwest of Iran. To select participants, we used a convenience sampling method. The research tools in this study were the Health and Safety Executive (HSE) stress questionnaire with 35 questions and 7 dimensions and demographic information. A high score on this questionnaire indicates that there is low job stress and pressure. All workers completed the informed consent form. Univariate analysis was performed using chi-square and T-test. Multiple regression analysis was used to estimate the odds ratios (OR) and 95% confidence interval (CI) for the association of stress-related factors with job accidents in participants. Stata 14.0 software was used for analysis. Results: The mean age of the participants was 39.81(6.36) years. The prevalence of job accidents was 28.0% (95%CI: 21.0, 34.0). Based on the results of the multiple logistic regression with the adjustment of the effect of the confounding variables, one increase in the score of the demand dimension had a protective impact on the risk of job accidents(aOR=0.91,95%CI:0.85-0.95). Additionally, an increase in one of the scores of the managerial support (aOR=0.89, 95% CI: 0.83-0.95) and peer support (aOR=0.76, 95%CI: 0.67-87) dimensions was associated with a lower number of job accidents. Among dimensions, an increase in the score of relationship (aOR=0.89, 95%CI: 0.80-0.98) and change (aOR=0.86, 95%CI: 0.74-0.96) reduced the odds of the accident's occurrence among the workers by 11% and 16%, respectively. However, there was no significant association between role and control dimensions and the job accident (p>0.05). Conclusions: The results show that the prevalence of job accidents was alarmingly high. Our results suggested that an increase in scores of dimensions HSE questioners is significantly associated with a decrease the accident occurrence in the workplace. Therefore, planning to address stressful factors in the workplace seems necessary to prevent occupational accidents.

Keywords: HSE, Iran, job stress occupational accident, safety, occupational health

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Authors: Emni Omar Daw Hussin, Pathmawathi Subramanian, Wong Li Ping

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Background: To provide quality care at the end of life, nurses should possess knowledge and skills to provide effective end-of-life care, as well as develop the attitudes and interpersonal competence to provide compassionate care. Aim: This study aimed to assess nurses’ knowledge and attitude towards end of life care and caring for terminal ill patients and to examine relationships among demographic variables and nurse’s knowledge and attitudes toward end of life care and caring for terminal ill patients. Method: a cross-sectional study was conducted at 1 tertiary hospital located in Kuala Lumpur, Malaysia. Self-administrative questionnaire was used to collect data from 553 nurses from over all departments except emergency department, operation theater and outpatient clinic. Two tools were used in this study, the Frommelt’s Attitude Toward Care of the Dying (FATCOD) Scale to assess the nurses’ attitude and End of Life Knowledge Assessment to assess the nurses’ knowledge. Result: the result of this study yielded that, the majority of participants (54.8%) and (54.4%) have less positive attitude and knowledge towards end of life care and caring for terminal ill patients respectively. As well as there is no significant relationship were found between nurses’ ethnicity, religion, and the total score of FATCOD scale; End of Life Knowledge Assessment score. On other hand there is significant relationship among nurses’ age, working experience, level of education, attending any post basic courses and the total score of both FATCOD scale and End of Life Knowledge Assessment. Conclusion: A lack of education and experience and post basic course about end of life care and palliative care may contribute to the negative attitudes and poor knowledge regarding end of life care. Providing sufficient courses about end of life care could enhance the nurses’ knowledge towards end of life care, as well as providing a reflective narrative environment in which nurses can express their personal feelings about death and dying could be a potentially effective approach. Implication for Practice: This study elaborates the need for further research to develop an effective educational programs to enhance nurses’ knowledge and to promote positive attitude towards death and dying, as well as enhance communication skills, and coping strategies.

Keywords: knowledge, attitude, nurse, end of life care

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Authors: Hong Wu, Naiji Lu

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Improvement of health behavior among people with chronic diseases is vital for increasing longevity and enhancing quality of life. This paper researched the causal effects of informal care on the compliance with doctor’s health advices – smoking control, dietetic regulation, weight control and keep exercising – among older people with chronic diseases in China, which is facing the challenge of aging. We addressed the selection bias by using propensity score matching in the estimation process. We used the 2011-2012 national baseline data of the China Health and Retirement Longitudinal Study. Our results showed informal care can help improve health behavior of older people. First, informal care improved the compliance of smoking controls: whether smoke, frequency of smoking, and the time lag between wake up and the first cigarette was all lower for these older people with informal care; Second, for dietetic regulation, older people with informal care had more meals every day than older people without informal care; Third, three variables: BMI, whether gain weight and whether lose weight were used to measure the outcome of weight control. There were no significant difference between group with informal care and that without for BMI and the possibility of losing weight. Older people with informal care had lower possibility of gain weight than that without; Last, for the advice of keeping exercising, informal care increased the probability of walking exercise, however, the difference between groups for moderate and vigorous exercise were not significant. Our results indicate policy makers who aim to decrease accidents should take informal care to elders into account and provide an appropriate policy to meet the demand of informal care. Our birth policy and postponed retirement policy may decrease the informal caregiving hours, so adjustments of these policies are important and urgent to meet the current situation of aged tendency of population. In addition, government could give more support to develop organizations to provide formal care, such as nursing home. We infer that formal care is also useful for health behavior improvements.

Keywords: chronic diseases, compliance, CHARLS, health advice, informal care, older people, propensity score matching

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Authors: Navid Kaboudi, Ali Shayanfar

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Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.

Keywords: logistic regression, breastfeeding, descriptors, penetration

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Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

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The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

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Authors: Rorlinda Yusof, Siti Aishah Hassan, Afifah Mohamad Radzi, Mohd Hakimie Zainal Abidin, Amran Rasli, Inderbir Sandhu

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The purpose of this study is to examine the self-identities of gifted and talented students and the relationship between self-identity and academic accomplishment. A random sample of 300 students enrolled in a secondary education programme at the Pusat GENIUS@pintar Negara was chosen as respondents of a 151-item holistic-identity component development tool. The validity of the instrument was assessed using Principal Components Analysis and Factor Analysis via an inter-Item Correlation Matrix (Loading values 0.44 to 0.86), which resulted in the formation of eight dimensions. The Cronbach's Alpha was calculated to determine the instrument's reliability (the overall result was 0.98). The results showed that students' holistic-identity profiles were relatively high (mean=4.09, standard deviation=0.449). In addition, spiritual identity received the greatest mean score (4.34) out of the eight components of identity investigated, while leadership identity received the lowest mean score (3.88). A conceptual framework for Islamic school leadership is recommended to implement spiritual values without differentiation to harmonize spiritual and intellectual intelligence among all the students. Some benchmarking studies with other centres for gifted and talented students are recommended for further research.

Keywords: holistic self-identity, academic achievement, self-development programme, counselling services, gifted and talented students

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Authors: Kuixi Du, Thomas J. Lipscomb

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The proficiency in Mathematics skills is fundamental to success in the STEM disciplines. In the US, beginning college students who are placed in remedial/developmental Mathematics courses frequently struggle to achieve academic success. Therefore, Mathematics remediation in college has become an important concern, and providing Mathematics remediation is a prevalent way to help the students who may not be fully prepared for college-level courses. Programs vary, however, and the effectiveness of a particular remedial Mathematics program must be empirically demonstrated. The purpose of this study was to apply the sharp regression discontinuity (RD) technique to determine the effectiveness of the Jack Leaps Summer (JLS) Mathematic remediation program in supporting improved Mathematics learning outcomes among newly admitted Mathematics students in the South Dakota State University. The researchers studied the newly admitted Fall 2019 cohort of Mathematics majors (n=423). The results indicated that students whose pretest score was lower than the cut-off point and who were assigned to the JLS program experienced significantly higher scores on the post-test (Math 101 final score). Based on these results, there is evidence that the JLS program is effective in meeting its primary objective.

Keywords: causal inference, mathematisc remedial program evaluation, quasi-experimental research design, regression discontinuity design, cohort studies

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Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

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Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

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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 satus, MNA, BMI, elderly

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