Search results for: regression training

Authors: Michael Ayodeji Boyede

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Studies have shown that workers’ job performance is very low in Nigeria, especially in the food and beverage industry. This trend had been partially attributed to low workers’ self-efficacy, poor self-knowledge, lack of empathy and poor psychological well-being. The descriptive survey design was adopted. Four factories were purposively selected from three states in Southwestern, Nigeria (Lagos, Ogun and Oyo States). Proportionate random sampling techniques were used in selecting 1,820 junior and supervisory cadre workers in Nestle Plc (369), Coca-Cola Plc (392), Cadbury Plc (443) and Nigeria Breweries (616). The five research instruments used were: Workers’ self-efficacy (r=0.81), Workers’ self-knowledge (r=0.78), Workers’ empathy (r=0.74), Workers’ psychological well-being (r=0.70) and Workers’ performance rating (r=0.72) scales. Quantitative data were analysed using Pearson product moment correlation, Multiple regression at 0.05 level of significance. Findings show that there were significant relationships between Workers’ job performance and self-efficacy (r=.56), self-knowledge (r=.54), Empathy (r=.55) and Psychological Well-being (r=.69) respectively. Self-efficacy, self-knowledge, empathy and psychological well-being jointly predict workers’ job performance (F (4,1815) = 491.05) accounting for 52.0% of its variance. Psychological well-being (B=.52). Self-efficacy (B=.10), self-knowledge (B=.11), empathy (B=. 09) had predictive relative weights on workers’ job performance. Inadequate knowledge and training of the supervisors led to a mismatch of workers thereby reducing workers’ job performance. High self-efficacy, empathy, psychological well-being and good self-knowledge influence workers job performance in the food and beverage industry. Based on the finding employers of labour should provide work environment that would enhance and promote the development of these factors among the workers.

Keywords: self-efficacy, self-knowledge, empathy, psychological well-being, job performance

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Authors: Ankit Shah, R. K. Shrivastava

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Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Nagini Sabbineni, Rajini T. V. Kanth, B. V. Kiranmayee

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India’s economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states.

Keywords: agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models

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Authors: Firouz Amani, Adalat Hoseinian, Sajjad Hakimian

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Background: The mortality due to Myocardial Infarction (MI) is often occur during the first hours after onset of symptom. So, for taking the necessary treatment and decreasing the mortality rate, timely visited of the hospital could be effective in this regard. The aim of this study was to investigate the impact of effective factors in mortality of MI patients by using Linear Logistic Regression. Materials and Methods: In this case-control study, all patients with Acute MI who referred to the Ardabil city hospital were studied. All of died patients were considered as the case group (n=27) and we select 27 matched patients without Acute MI as a control group. Data collected for all patients in two groups by a same checklist and then analyzed by SPSS version 24 software using statistical methods. We used the linear logistic regression model to determine the effective factors on mortality of MI patients. Results: The mean age of patients in case group was significantly higher than control group (75.1±11.7 vs. 63.1±11.6, p=0.001).The history of non-cardinal diseases in case group with 44.4% significantly higher than control group with 7.4% (p=0.002).The number of performed PCIs in case group with 40.7% significantly lower than control group with 74.1% (P=0.013). The time distance between hospital admission and performed PCI in case group with 110.9 min was significantly upper than control group with 56 min (P=0.001). The mean of delay time from Onset of symptom to hospital admission (patient delay) and the mean of delay time from hospital admissions to receive treatment (system delay) was similar between two groups. By using logistic regression model we revealed that history of non-cardinal diseases (OR=283) and the number of performed PCIs (OR=24.5) had significant impact on mortality of MI patients in compare to other factors. Conclusion: Results of this study showed that of all studied factors, the number of performed PCIs, history of non-cardinal illness and the interval between onset of symptoms and performed PCI have significant relation with morality of MI patients and other factors were not meaningful. So, doing more studies with a large sample and investigated other involved factors such as smoking, weather and etc. is recommended in future.

Keywords: acute MI, mortality, heart failure, arrhythmia

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Authors: Zakaria S. G. Hegazy, Walid M. A. Ahmed

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This paper examines the dependence structure of Islamic stock markets on Bitcoin’s realized volatility components in bear, normal, and bull market periods. A quantile regression approach is employed, after adjusting raw returns with respect to a broad set of relevant global factors and accounting for structural breaks in the data. The results reveal that upside volatility tends to exert negative influences on Islamic developed-market returns more in bear than in bull market conditions, while downside volatility positively affects returns during bear and bull conditions. For emerging markets, we find that the upside (downside) component exerts lagged negative (positive) effects on returns in bear (all) market regimes. By and large, the dependence structures turn out to be asymmetric. Our evidence provides essential implications for investors.

Keywords: cryptocurrency markets, bitcoin, realized volatility measures, asymmetry, quantile regression

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Authors: Fumiya Sugino, Naohiro Nakamura, Yuji Miyazu

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In earthquake resistant design of buildings, evaluation of vibration characteristics is important. In recent years, due to the increment of super high-rise buildings, the evaluation of response is important for not only the first mode but also higher modes. The knowledge of vibration characteristics in buildings is mostly limited to the first mode and the knowledge of higher modes is still insufficient. In this paper, using earthquake observation records of a SRC building by applying frequency filter to ARX model, characteristics of first and second modes were studied. First, we studied the change of the eigen frequency and the damping ratio during the 3.11 earthquake. The eigen frequency gradually decreases from the time of earthquake occurrence, and it is almost stable after about 150 seconds have passed. At this time, the decreasing rates of the 1st and 2nd eigen frequencies are both about 0.7. Although the damping ratio has more large error than the eigen frequency, both the 1st and 2nd damping ratio are 3 to 5%. Also, there is a strong correlation between the 1st and 2nd eigen frequency, and the regression line is y=3.17x. In the damping ratio, the regression line is y=0.90x. Therefore 1st and 2nd damping ratios are approximately the same degree. Next, we study the eigen frequency and damping ratio from 1998 after 3.11 earthquakes, the final year is 2014. In all the considered earthquakes, they are connected in order of occurrence respectively. The eigen frequency slowly declined from immediately after completion, and tend to stabilize after several years. Although it has declined greatly after the 3.11 earthquake. Both the decresing rate of the 1st and 2nd eigen frequencies until about 7 years later are about 0.8. For the damping ratio, both the 1st and 2nd are about 1 to 6%. After the 3.11 earthquake, the 1st increases by about 1% and the 2nd increases by less than 1%. For the eigen frequency, there is a strong correlation between the 1st and 2nd, and the regression line is y=3.17x. For the damping ratio, the regression line is y=1.01x. Therefore, it can be said that the 1st and 2nd damping ratio is approximately the same degree. Based on the above results, changes in eigen frequency and damping ratio are summarized as follows. In the long-term study of the eigen frequency, both the 1st and 2nd gradually declined from immediately after completion, and tended to stabilize after a few years. Further it declined after the 3.11 earthquake. In addition, there is a strong correlation between the 1st and 2nd, and the declining time and the decreasing rate are the same degree. In the long-term study of the damping ratio, both the 1st and 2nd are about 1 to 6%. After the 3.11 earthquake, the 1st increases by about 1%, the 2nd increases by less than 1%. Also, the 1st and 2nd are approximately the same degree.

Keywords: eigenfrequency, damping ratio, ARX model, earthquake observation records

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Authors: Klára Gajdošíková

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The aim of this study was to examine the quiet eye method and its components using the mobile eye tracking device. Quiet eye training was proven to be beneficial for different sports, including golf. The main idea of this method is to prolong your fixations on a specific place in order to improve your performance. The shot examined in this study is called putt. Its importance is based on its role on a golf course because, many times, it is the last putt that decides whether you win or lose. Quiet eye training helps players be more focused under pressure, control their attention and overall improve their putting success. Six highly skilled golfers with a handicap ranging from - 4 to + 4, aged 23 to 26, participated in a pilot study with the usage of an eye-tracking device. The study took place in an indoor training area at the golf club Hostivař. Crosstabs showed significant differences between individuals' laterality and their gaze into AOI - areas of interest (middle part of the ball, top of the ball, bottom of the ball, back side of the ball). Statistically significant differences were also discovered between the mean fixation duration of participants with AOI on the middle part of the ball and all other AOIs. The results of this study helped us understand the examined phenomena and showed us the next aim in future quiet eye research. Future research should focus on examining a quiet eye on the golf course. Applying a quiet eye and therefore changing the way we concentrate might be beneficial for coaches and players themselves.

Keywords: eye tracking, golf, laterality, quiet eye

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Authors: Inna R. Edara, Haw-Lin Wu

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Positive psychology investigates human strengths and virtues and promotes well-being. Relying on this assumption, positive interventions have been continuously designed to build pleasure and happiness, joy and contentment, engagement and meaning, hope and optimism, satisfaction and gratitude, spirituality, and various other positive measures of well-being. In line with this model of positive psychology and interventions, this study investigated certain measures of well-being in a group of 45 students enrolled in an 18-week positive psychology course and simultaneously engaged in service-oriented interventions that they chose for themselves based on the course content and individual interests. Students’ well-being was measured at the beginning and end of the course. The well-being indicators included positive automatic thoughts, optimism and hope, satisfaction with life, and spirituality. A paired-samples t-test conducted to evaluate the impact of class content and service-oriented interventions on students’ scores of well-being indicators indicated statistically significant increase from pre-class to post-class scores. There were also significant gender differences in post-course well-being scores, with females having higher levels of well-being than males. A two-way between groups analysis of variance indicated a significant interaction effect of age by gender on the post-course well-being scores, with females in the age group of 56-65 having the highest scores of well-being in comparison to the males in the same age group. Regression analyses indicated that positive automatic thought significantly predicted hope and satisfaction with life in the pre-course analysis. In the post-course regression analysis, spiritual transcendence made a significant contribution to optimism, and positive automatic thought made a significant contribution to both hope and satisfaction with life. Finally, a significant test between pre-course and post-course regression coefficients indicated that the regression coefficients at pre-course were significantly different from post-course coefficients, suggesting that the positive psychology course and the interventions were helpful in raising the levels of well-being. The overall results suggest a substantial increase in the participants’ well-being scores after engaging in the positive-oriented interventions, implying a need for designing more positive interventions in education to promote well-being.  

Keywords: hope, optimism, positive automatic thoughts, satisfaction with life, spirituality, well-being

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Authors: Shehu A. Salau, Robiu O. Aliu, Nofiu B. Nofiu

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Nigeria is among countries of the world confronted with food insecurity problem. The agricultural production systems that produces food for the teaming population is not endurable. Attention is thus being given to alternative approaches of intensification such as the use of Sustainable Land Management (SLM) technologies. Thus, this study assessed the effect of SLM technologies on food security of farming households in Kwara State, Nigeria. A-three stage sampling technique was used to select a sample of 200 farming households for this study. Descriptive statistics, Shriar index, Likert scale, food security index and logistic regression were employed for the analysis. The result indicated that majority (41%) of the household heads were between the ages of 51 and 70 years with an average of 60.5 years. Food security index revealed that 35% and 65% of the households were food secure and food insecure respectively. The logistic regression showed that SLM technologies, estimated income, household size, gender and age of the household heads were the critical determinants of food security among farming households. The most effective coping strategies adopted by households geared towards lessening the effects of food insecurity are reduced quality of food consumed, employed off-farm jobs to raise household income and diversion of money budgeted for other uses to purchase foods. Governments should encourage the adoption and use of SLM technologies at all levels. Policies and strategies that reduce household size should be enthusiastically pursued to reduce food insecurity.

Keywords: agricultural practices, coping strategies, farming households, food security, SLM technologies, logistic regression

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder

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Authors: Mohammed Fakehy, Mohammed Haggag

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The problem of test anxiety considered as one of the most important and most complex psychological problems faced by students of King Saud University, where university students in a need to bring their reassurance and psychological comfort, relieves feeling pain and difficulties of the study. Recently, there are programs and science that help human to change, including the science Linguistic Programming this neural science stems from not just the tips of the need to make the effort or continue to work, but provides the keys in which one can be controlled in the internal environment. Even human potential energy is extracted seeking to achieve success and happiness and excellence. Through the work of the researchers as members of the teaching staff at King Saud University and specialists in the field of psychology noticed the suffering of some students of King Saud University, test anxiety. In an attempt by the researchers to mitigate as much as possible of the unity of this concern, students will have a training program in Neuro Linguistic Programming. The main Question of this study is What is the effectiveness of the impact of a training program using NLP to reduce test anxiety by using a biological feedback. Therefore, the results of this study might serve as a good announcement about the usefulness of NLP programs which influence future research to significant effect of NLP on test anxiety.

Keywords: neuro linguistic programming, test anxiety, biological feedback, king saud

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Authors: José L. Jiménez

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The use of technology in the classroom is an issue that is constantly evolving. Digital age students learn differently than their teachers did, so now the teacher should be constantly evolving their methods and teaching techniques to be more in touch with the student. In this paper a case study presents how were used some of these technologies by accompanying a classroom course, this in order to provide students with a different and innovative experience as their teacher usually presented the activities to develop. As students worked in the various activities, they increased their digital skills by employing unknown tools that helped them in their professional training. The twenty-first century teacher should consider the use of Information and Communication Technologies in the classroom thinking in skills that students of the digital age should possess. It also takes a brief look at the history of distance education and it is also highlighted the importance of integrating technology as part of the student's training.

Keywords: digital tools, on-line learning, social networks, technology

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Authors: Ekapon Thienthaworn

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This research aims to study the reliability of the forecasting factor in social media by using survey research methods with questionnaires. The sampling is the group of undergraduate students in Bangkok. A multiple-step random number of 400 persons, data analysis are descriptive statistics with multivariate regression analysis. The research found the average of the overall trust at the intermediate level for reading the news in social media and the results of the multivariate regression analysis to find out the factors that forecast credibility of the media found the only content that has the power to forecast reliability of undergraduate students in Bangkok to reading the news on social media at the significance level.at 0.05.These can be factors with forecasts reliability of news in social media by a variable that has the highest influence factor of the media content and the speed is also important for reliability of the news.

Keywords: credibility of news, behaviors and attitudes, social media, web board

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Authors: Manar Al-Ateeq

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The building construction industry plays a major role in the economy of the word and the state of Kuwait. This paper evaluates existing new civil site engineers, describes a new system for improvement and insures the importance of prequalifying and developing for new engineers. In order to have a strong base in engineering, educational institutes and workplaces should be responsible to continuously train engineers and update them with new methods and techniques in engineering. As to achieve that, school of engineering should constantly update computational resources to be used in the professions. A survey was prepared for graduated Engineers based on stated objectives to understand the status of graduate engineers in both the public and private sector. Interviews were made with different sectors in Kuwait, and several visits were made to different training centers within different workplaces in Kuwait to evaluate training process and try to improve it. Virtual Reality (VR) technology could be applied as a complement to three-dimensional (3D) modeling, leading to better communication whether in job training, in education or in professional practice. Techniques of 3D modeling and VR can be applied to develop the models related to the construction process. The 3D models can support rehabilitation design as it can be considered as a great tool for monitoring failure and defaults in structures; also it can support decisions based on the visual analyses of alternative solutions. Therefore, teaching computer-aided design (CAD) and VR techniques in school will help engineering students in order to prepare them to site work and also will assist them to consider these technologies as important supports in their later professional practice. This teaching technique will show how the construction works developed, allow the visual simulation of progression of each type of work and help them to know more about the necessary equipment needed for tasks and how it works on site.

Keywords: three dimensional modeling (3DM), civil engineers (CE), professional practice (PP), virtual reality (VR)

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Authors: Kamran Taghizadeh

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This study was aimed at evaluating the effect of IMS including occupational health system, environmental management system, and safety and health system on the social responsibility (case study of NISOC`s oil and gas production companies). This study`s objectives include evaluating the IMS situation and its effect on social responsibility in addition of providing appropriate solutions based on the study`s hypotheses as a basis for future. Data collection was carried out by library and field studies as well as a questionnaire. The stratified random method was the sampling method and a sample of 285 employees in addition to the collected data (from the questionnaire) were analyzed by inferential statistics methods using SPSS software. Finally, results of regression and fitted model at a significance level of 5% confirmed all hypotheses meaning that IMS and its items have a significant effect on social responsibility.

Keywords: social responsibility, integrated management, oil and gas production companies, regression

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Authors: Gongbing Shan, Shiming Li, Zhao Zhang, Bingjun Wan

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Badminton originated in ancient civilizations in Europe and Asia more than 2000 years ago. Presently, it is played almost everywhere with estimated 220 million people playing badminton regularly, ranging from professionals to recreational players; and it is the second most played sport in the world after soccer. In Asia, the popularity of badminton and involvement of people surpass soccer. Unfortunately, scientific researches on badminton skills are hardly proportional to badminton’s popularity. A search of literature has shown that the literature body of biomechanical investigations is relatively small. One of the dominant skills in badminton is the forehand overhead smash, which consists of 1/5 attacks during games. Empirical evidences show that one has to adjust the body position in relation to the coming shuttlecock to produce a powerful and accurate smash. Therefore, positioning is a fundamental aspect influencing smash quality. A search of literature has shown that there is a dearth/lack of study on this fundamental aspect. The goals of this study were to determine the influence of positioning and training experience on smash quality in order to discover information that could help learn/acquire the skill. Using a 10-camera, 3D motion capture system (VICON MX, 200 frames/s) and 15-segment, full-body biomechanical model, 14 skilled and 15 novice players were measured and analyzed. Results have revealed that the body positioning has direct influence on the quality of a smash, especially on shuttlecock release angle and clearance height (passing over the net) of offensive players. The results also suggest that, for training a proper positioning, one could conduct a self-selected comfort position towards a statically hanged shuttlecock and then step one foot back – a practical reference marker for learning. This perceptional marker could be applied in guiding the learning and training of beginners. As one gains experience through repetitive training, improved limbs’ coordination would increase smash quality further. The researchers hope that the findings will benefit practitioners for developing effective training programs for beginners.

Keywords: 3D motion analysis, biomechanical modeling, shuttlecock release speed, shuttlecock release angle, clearance height

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Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Fatima Zehra Allahverdi, Nukhet Bayer

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Objective: Three questions were formulated to examine stressful working units (intensive care units, emergency unit nurses) utilizing the self-perception theory and social support theory. This study provides a distinctive input by inspecting the combination of variables regarding stressful working environments. Method: The descriptive research was conducted with the participation of 400 nurses working at Ankara City Hospital. The study used Multivariate Analysis of Variance (MANOVA), regression analysis, and a mediation model. Hypothesis one used MANOVA followed by a Scheffe post hoc test. Hypothesis two utilized regression analysis using a hierarchical linear regression model. Hypothesis three used a mediation model. Result: The study utilized mediation analyses. Findings supported the hypotheses that intensive care units have significantly high scores in virtual communication and virtual tolerance. The number of years on the job, virtual communication, virtual tolerance, and phubbing significantly predicted 51% of the variance of perception of addiction. Interestingly, the number of years on the job, while significant, was negatively related to perception of addiction. Conclusion: The reasoning behind these findings and the lack of significance in the emergency unit is discussed. Around 7% of the variance of phubbing was accounted for through working in intensive care units. The model accounted for 26.80 % of the differences in the perception of addiction.

Keywords: phubbing, social media, working units, years on the job, stress

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Authors: Nathalie Gagnon, Andréanne Gagné, Julie Courcy

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Quebec's vocational education teachers experience an atypical induction process into the workplace and thus face unique challenges. In contrast to elementary and high school teachers, who must undergo initial teacher training in order to access the profession, vocational education teachers, in most cases, are hired based on their professional expertise in the trade they are teaching, without prior pedagogical training. In addition to creating significant stress, which does not foster the acquisition of teaching roles and skills, this approach also forces recruits into a particular posture during their practical training: that of juggling their dual identities as teacher and trainee simultaneously. Recruits are supported by Cooperating Teachers (CPs) who, as experienced educators, take a critical and constructive look at their practices, observe them in the classroom, give them constructive feedback, and encourage them in their reflective practice. Thus, the vocational setting CP also assumes a distinctive posture and role due to the characteristics of the trainees they support. Although it is recognized that preparation, training, and supervision of CPs are essential factors in improving the support provided to trainees, there is little research about how CPs develop their support skills, and very little research focuses on the distinct posture they occupy. However, in order for them to be properly equipped for the important role they play in recruits’ practical training, it is vital to know more about their experience. An individual’s competencies cannot be studied without first examining what characterizes their experience, how they experience any given situation on cognitive, emotional, and motivational levels, in addition to how they act and react in situ. Depending on its nature, the experience will or will not promote the development of a specific competency. The research from which this communication originates focuses on describing the overall experience of vocational education CP in an effort to better understand the mechanisms linked to the development of their mentoring competencies. Experience and competence were, therefore, the two main theoretical concepts leading the research. As per methodology choices, case study methods were used since it proves to be adequate to describe in a rich and detailed way contemporary phenomena within contexts of life. The set of data used was collected from semi-structured interviews conducted with 15 vocational education CP in Quebec (Canada), followed by the use of a data-driven semi-inductive analysis approach to let the categories emerge organically. Focusing on the development needs of vocational education CP to improve their mentoring skills, this paper presents the results of our research, namely the importance of adequate training, better support offered by university supervisors, greater recognition of their role, and specific time slots dedicated to trainee support. The knowledge resulting from this research could improve the quality of support for trainee teachers in vocational education settings and to a more successful induction into the workplace. This communication also presents recommendations regarding the development of training systems that meet the specific needs of vocational education CP.

Keywords: development of competencies, cooperating teacher, mentoring trainee teacher, practical training, vocational education

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Authors: Sotiria Tzivinikou, Dimitra Kagkara

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Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: inclusive education, pre-service, self-efficacy, training program

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Authors: Nkrumak Micheal Atta Ofori

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The Vocational System is a decentralized Studies System implemented in Ghana as vocation studies strategy for grassroot that focuses on providing individuals with the specific skills, knowledge, and training necessary for a particular trade, craft, profession, or occupation. This article asks how devolution of vocational studies to local level authorities produces responsive and accountable representation and sustainable vocational learning under the vocational Studies System. It focuses on two case studies: Asokore Mampong and Atwima kwanwoma Municipal. Then, the paper asks how senior high school are developing new material and social practices around the vocational studies System to rebuild their livelihoods and socio-economic wellbeing. Here, the article focusses on Kumasi District, drawing lessons for the two other cases. The article shows how the creation of representative groups under the Vocational Studies System provides the democratic space necessary for effective representation of community aspirations. However, due to elite capture, the interests of privilege few people are promoted. The state vocational training fails to devolve relevant and discretionary resources to local teachers and do not follow the prescribed policy processes of the Vocational Studies System. Hence, local teachers are unable to promote responsive and accountable representation. Rural communities continue to show great interest in the Vocational Studies System, but the interest is bias towards gaining access to vocational training schools for advancing studies. There is no active engagement of the locals in vocational training, and hence, the Vocational Studies System exists only to promote individual interest of communities. This article shows how ‘failed’ interventions can gain popular support for rhetoric and individual gains.

Keywords: vocational studies system, devolution of vocational studies, local-level authorities, senior high schools and vocational learning, community aspirations and representation

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Authors: Jessica Terese Mueller, Christoph Breitsprecher, Mike Oliver Mosko

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Due to an unusually high number of asylum seekers entering Germany over the course of the past few years, the need for community interpreters has increased dramatically, in order to make the communication between asylum seekers and various actors in social and governmental agencies possible. In the field of social work in particular, there are community interpreters who possess a wide spectrum of qualifications spanning from state-certified professional interpreters with graduate degrees to lay or ad-hoc interpreters with little to no formal training. To the best of our knowledge, Germany has no official national quality standards for the training of community interpreters at present, which would serve to professionalise this field as well as to assure a certain degree of quality in the training programmes offered. Given the current demand for trained community interpreters, there is a growing number of training programmes geared toward qualifying community interpreters who work with asylum seekers in Germany. These training programmes range from short one-day workshops to graduate programmes with specialisations in Community Interpreting. As part of a larger project to develop quality standards for the qualification of community interpreters working with asylum seekers in the field of social work, a needs assessment was performed in the city-state of Hamburg and the state of North Rhine Westphalia in the form of focus groups and individual interviews with relevant actors in the field in order to determine the content and practical knowledge needed for community interpreters from the perspectives of those who work in and rely on this field. More specifically, social workers, volunteers, certified language and cultural mediators, paid and volunteer community interpreters and asylum seekers were invited to take part in focus groups in both locations, and asylum seekers, training providers, researchers, linguists and other national and international experts were individually interviewed. The responses collected in these focus groups and interviews have been analysed using Mayring’s concept of content analysis. In general, the responses indicate a high degree of overlap related to certain categories as well as some categories which seemed to be of particular importance to certain groups individually, while showing little to no relevance for other groups. For example, the topics of accuracy and transparency of the interpretations, as well as professionalism and ethical concerns were touched on in some form in most groups. Some group-specific topics which are the focus of experts were topics related to interpreting techniques and more concretely described theoretical and practical knowledge which should be covered in training programmes. Social workers and volunteers generally concentrated on issues regarding the role of the community interpreters and the importance of setting and clarifying professional boundaries. From the perspective of service receivers, asylum seekers tended to focus on the importance of having access to interpreters who are from their home region or country and who speak the same regiolect, dialect or variety as they do in order to prevent misunderstandings or misinterpretations which might negatively affect their asylum status. These results indicate a certain degree of consensus with trainings offered internationally for community interpreters.

Keywords: asylum seekers, community interpreting, needs assessment, quality standards, training

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Asma Dill

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The aim of this study is to explore the role of HRM practices in SMEs success. The role of HRM practices in large enterprises is relatively known, on the other hand, small and medium enterprises (SMEs) companies have not been greatly studied in relation to the HRM practices in the past. Although, there is a lack of literature and empirical research in this area, several studies in the recent years emphasized on the importance of the HRM practices for the success of the SMEs. This study finds out relationship of HRM practices and SMESs performances. The objective is to analyze significant impacts of HRM practices (training, performance appraisal, compensation and employee development) on SMEs success, to determine whether SMEs recognize the importance of HRM practices in their businesses. To carry out this research a survey research strategy was followed. The sample frame for this study consisted of firms that belong to the services and commerce sector, employing at least 50 employees. The final research sample consisted of questionnaires. Descriptive statistical methods have been used during quantitative analysis to explore the relations. The findings of the study revealed that HRM practices have a significant influence on the performance of SMEs, and the better the HRM practice, the higher the performance of the SMEs. HRM practices, including, training, compensation, performance appraisal and employee development, have been found to be significantly and positively related to business success. Outcome of the study will provide useful guidelines to the business organizations. This study contributes to knowledge by providing insights on the impact of HRM practices on SMEs performance.

Keywords: compensation, employee performance, HRM practices, training

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Mara Aparecida De Castilho Lopes. Maria Eliza Mattosinho Bernardes

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The education of deaf individuals in Brazil is grounded in the bilingual approach, which presupposes Brazilian Sign Language (Libras) as the first language for these students. In this perspective, Portuguese should be taught as a second language in its written form, ensuring that deaf students also have access to various academic subjects in sign language. Brazilian legislation (Federal Decree No. 5626 of 2005) mandates the teaching of Brazilian Sign Language in university teacher training programs, but there is no pre-established minimum workload. As a result, there is a significant disparity in the teaching and quality of teacher education across the Brazilian territory. Added to this fact is the general lack of awareness within society regarding the linguistic status of Libras, leading to a shortage of competent teachers for its use and instruction, particularly in higher education. Recently, Federal Law No. 14191 of 2021 established bilingual education for the deaf as a mode of instruction, indicating the need for adjustments in teacher training within higher education teacher preparation programs. Given this context, the objective of the present study was to analyze the teaching proposals for Brazilian Sign Language for students in teacher training programs at public universities in Brazil, presenting alternatives to overcome the current models and academic pathways of teaching and learning. In addition to analyzing Brazilian teaching models, an analysis of a continuing education model for teachers in a French institution was also conducted - considering the historical Franco-Brazilian path of deaf education in Brazil. The analysis of the current teacher training model for deaf education in Brazil revealed that initial exposure to sign language and its linguistic structure is not sufficient to provide future teachers with opportunities to reflect on bilingual teaching methods and practices, as seen in other definitions of bilingualism - bilingual education for proficient listeners in two oral languages. As a result, a training proposal was developed for an experimental interdisciplinary course, integrating the curriculum of an initial and continuing teacher training program alongside the Alfredo Bossi Chair at the University of São Paulo. This proposal is structured into three disciplines, which constitute consecutive moments in teacher education: Fundamental Aspects of Brazilian Sign Language, Bilingual Teaching Methodology, and Teaching Investigation Project - interdisciplinary engagement in the field of deafness. The last offered discipline represents an interdisciplinary supervised internship proposal, considering the multi-professional context that constitutes deaf education within a bilingual approach. In interdisciplinary work within the field of deafness, dialogue between teachers and other professionals who work with deaf students from different perspectives - teachers, speech therapists, and sign language interpreters - is frequently necessary. Through alternative avenues, these actions aim to direct the linguistic development of deaf students within their learning processes. Based on the innovative curriculum proposal described here, the intention is to contribute to the enhancement of teacher education in Brazil, with the goal of ensuring bilingual education for deaf students.

Keywords: bilingual education, teacher training, historical-cultural approach, interdisciplinary education, inclusive education

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Authors: Radwa R. El-Saadany , Medhat Abu Zeid, Tarek Omar, Marwa S. Maqsoud

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Attention deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders characterized by attention deficit, hyperactivity, and impulsivity. Neurofeedback (NF) is one of the neurotherapy treatments that cause brain wave changes. Method: The current pseudo-experimental study with a pre–post-test design was conducted on a population of children with attention deficit hyperactivity disorder (ADHD).The sample size comprised of (30) children selected by random sampling method and assigned to two therapeutic groups: First therapeutic group received a neurofeedback program. Based on QEEG, it reached (10) children. The second therapeutic group received an organization skills training program, it reached (10) and the control group that did not receive programs, it reached (10) children. Results: There are significant differences between pre- and post-assessments among therapeutic groups in reducing the three core symptoms of ADHD in favor of post measurement. There are no significant differences between post-assessment and follow up measurement of the therapeutic groups.

Keywords: QEEG-based neurofeedback therapy program, organizational skills training program, attention deficit hyperactivity disorder

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

Procedia PDF Downloads 299