Search results for: machine resistance training

Authors: Muhammad Fathurridho

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Grammar as a rule used by every language to be understood by everyone is always related to syntax and morphology. Arabic grammar is different with another languages’ grammars. It has more rules and difficulties. This paper aims to investigate and describe the English grammatical errors of machine translation systems in translating Arabic sentences, including declarative, exclamation, imperative, and interrogative sentences, specifically in year 2018 which can be supported with artificial intelligence’s role. The Arabic sample sentences which are divided into two; verbal and nominal sentence of several Arabic published texts will be examined as the source language samples. The translated sentences done by several popular online machine translation systems, including Google Translate, Microsoft Bing, Babylon, Facebook, Hellotalk, Worldlingo, Yandex Translate, and Tradukka Translate are the material objects of this research. Descriptive method that will be taken to finish this research will show the grammatical errors of English target language, and classify them. The conclusion of this paper has showed that the grammatical errors of machine translation results are varied and generally classified into morphological, syntactical, and semantic errors in all type of Arabic words (Noun, Verb, and Particle), and it will be one of the evaluations for machine translation’s providers to correct them in order to improve their understandable results.

Keywords: Arabic, Arabic-English translation, machine translation, grammatical errors

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Authors: Nisith K. Datta, Rakesh Bharti

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The purpose of the study was to find out the effects of Aquatic and Land plyometric training on selected physical variables in intercollegiate male handball players. To achieve this purpose of the study, forty five handball players of Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat were selected as players at random and their age ranged between 18 to 21 years. The selected players were divided into three equal groups of fifteen players each. Group I underwent Aquatic plyometric training, Group II underwent Land plyometric training and Group III Control group for three days per week for twelve weeks. Control Group did not participate in any special training programme apart from their regular activities as per their curriculum. The following physical fitness variables namely speed; leg explosive power and agility were selected as dependent variables. All the players of three groups were tested on selected dependent variables prior to and immediately after the training programme. The analysis of covariance was used to analyze the significant difference, if any among the groups. Since, three groups were compared, whenever the obtained ‘F’ ratio for adjusted post test was found to be significant, the Scheffe’s test to find out the paired mean differences, if any. The 0.05 level of confidence was fixed as the level of significance to test the ‘F’ ratio obtained by the analysis of covariance, which was considered as an appropriate. The result of the study indicates due to Aquatic and Land plyometric training on speed, explosive power, and agility has been improved significantly.

Keywords: aquatic training, explosive power, plyometric training, speed

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Authors: Chih-Chia Lin, Ching-Ying Huang, Cheng-Hong Liu, Wen-Lin Wang

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A complete fuel cell stack comprises several single cells with end plates, bipolar plates, gaskets and membrane electrode assembly (MEA) components. Electrons generated from cells are conducted through bipolar plates. The amount of cells' components increases as the stack voltage increases, complicating the fuel cell assembly process and mass production. Stack assembly error influence cell performance. PEM fuel cell stack importing laser welding technique could eliminate transverse deformation between bipolar plates to promote stress uniformity of cell components as bipolar plates and MEA. Simultaneously, bipolar plates were melted together using laser welding to decrease interface resistance. A series of experiments as through-plan and in-plan resistance measurement test was conducted to observe the laser welding effect. The result showed that the through-plane resistance with laser welding was a drop of 97.5-97.6% when the contact pressure was about 1MPa to 3 MPa, and the in-plane resistance was not significantly different for laser welding.

Keywords: PEM fuel cell, laser welding, through-plan, in-plan, resistance

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

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Authors: Rosita Kanapeckaite

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Every year, some candidates who enroll in Generolas Jonas Zemaitis Military Academy of Lithuania do not complete a basic seven weeks cadet course and leave the Academy. Experience in other countries shows that psychological resilience grit and intrinsic motivation can lead to better course completion results. We examined the psychological resilience grit and intrinsic motivation as predictors of better results among newcomers who participate in the Cadet Basic Training (CBT) course. Based on past research and theory of other countries' military academies, we expected that resilience grit, and intrinsic motivation would predict performance in the Cadet Basic Training course. Results of regression analyses revealed that resilience and grit can predict better course results, but intrinsic motivation can not predict retention. These findings suggest that resilience and grit assessment and training may prove valuable in enhancing performance and retention within military training environments.

Keywords: military, intrinsic motivation, grit, resilience

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Ramazan Hasanzadeh, Leyla Vatandoust

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This study examined the efficacy of motivation management training for students’ academic achievement and self-concept. The pretest–posttest quasi-experimental study used a cluster random sampling method to select subjects for the experimental (20 subjects) and control (20 subjects) groups. posttest was conducted with both groups to determine the effect of the training. An academic achievement and academic self-concept questionnaire (grade point average requirement) was used for the pretest and posttest. The results showed that the motivation management training increased academic self-concept and academic achievement.

Keywords: motivation management, academic self-concept, academic achievement, students

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Authors: Shannon O’Donnell, Matthew Driller, Gregory Jacobson, Steve Bird

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Stress hormone levels in a competition vs. training setting are yet to be evaluated in elite female athletes. The effect that these levels of stress have on subsequent sleep quality and quantity is also yet to be investigated. The aim of the current study was to evaluate different psychophysiological stress markers in competition and training environments and the subsequent effect on sleep indices in an elite female athlete population. The study involved 10 elite female netball athletes (mean ± SD; age = 23 ± 6 yrs) providing multiple salivary hormone measures and having their sleep monitored on two occasions; a match day, and a training day. The training and match were performed at the same time of day and were matched for intensity and duration. Saliva samples were collected immediately pre (5:00 pm) and post session (7:15 pm), and at 10:00 pm and were analysed for cortisol concentrations. Sleep monitoring was performed using wrist actigraphy to assess total sleep time (TST), sleep efficiency (SE%) and sleep latency (SL). Cortisol levels were significantly higher (p < 0.01) immediately post the match vs post training (mean ± SD; 0.925 ± 0.341 μg/dL and 0.239 ± 0.284 μg/dL, respectively) and at 10:00pm (0.143 ± 0.085 μg/dL and 0.072 ± 0.064 μg/dL, respectively, p < 0.01). The difference between trials was associated with a very large effect (ES: 2.23) immediately post (7:15 pm) and a large effect (ES: 1.02) at 10:00 pm. There was a significant reduction in TST (mean ± SD; -117.9 ± 111.9 minutes, p < 0.01, ES: -1.89) and SE% (-7.7 ± 8.5%, p < 0.02, ES: -0.79) on the night following the netball match compared to the training session. Although not significant (p > 0.05), there was an increase in SL following the netball match v the training session (67.0 ± 51.9 minutes and 38.5 ± 29.3 minutes, respectively), which was associated with a moderate effect (ES: 0.80). The current study reports that cortisol levels are significantly higher and subsequent sleep quantity and quality is significantly reduced in elite female athletes following a match compared to a training session.

Keywords: cortisol, netball, performance, recovery

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Authors: Mohammed Benmostefa

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In the industrial production of large series or even medium series, there are vibration problems. In continuous operations, technical devices result in vibrations in solid bodies and machine components, which generate solid noise and/or airborne noise. This is because vibrations are the mechanical oscillations of an object near its equilibrium point. In response to the problems resulting from these vibrations, a number of remedial acts and solutions have been put forward. These include insulation of machines, insulation of concrete masses, insulation under screeds, insulation of sensitive equipment, point insulation of machines, linear insulation of machines, full surface insulation of machines, and the like. Following this, the researcher sought not only to raise awareness on the possibility of lowering the vibration frequency in industrial machines but also to stress the significance of procedures involving the pre-installation process of machinery, namely, setting appropriate installation and start-up methods of the machine, allocating and updating imprint folders to each machine, and scheduling maintenance of each machine all year round to have reliable equipment, gain cost reduction and maintenance efficiency to eventually ensure the overall economic performance of the company.

Keywords: maintenance, vibration, efficiency, production, machinery

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Authors: Marjan Ghazisaeedi, Azadeh Bashiri

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Background: Attention-Deficit/Hyperactivity Disorder(ADHD), is one of the most common psychiatric disorders in early childhood that in addition to its main symptoms provide significant deficits in the areas of educational, social and individual relationship. Considering the importance of rehabilitation in ADHD patients to control these problems, this study investigated the advantages of computer-based cognitive training in these patients. Methods: This review article has been conducted by searching articles since 2005 in scientific databases and e-Journals and by using keywords including computerized cognitive rehabilitation, computer-based training and ADHD. Results: Since drugs have short term effects and also they have many side effects in the rehabilitation of ADHD patients, using supplementary methods such as computer-based cognitive training is one of the best solutions. This approach has quick feedback and also has no side effects. So, it provides promising results in cognitive rehabilitation of ADHD especially on the working memory and attention. Conclusion: Considering different cognitive dysfunctions in ADHD patients, application of the computerized cognitive training has the potential to improve cognitive functions and consequently social, academic and behavioral performances in patients with this disorder.

Keywords: ADHD, computer-based cognitive training, cognitive functions, rehabilitation

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Authors: Eric Noe Hernandez Rodriguez, Cristian Esneider Penuela Cruz

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Magnesium is a biocompatible and biodegradable material that has gained increased interest for application in resorbable orthopedic implants. However, to date, much research is being conducted to overcome the main disadvantage: its low corrosion resistance. In this work, we report our findings on the development and application of TiO₂-MgO coatings to improve and modulate the corrosion resistance of magnesium pieces. The plasma electrolytic oxidation (PEO) technique was employed to obtain the TiO₂-MgO coatings. The effect of the experimental parameters on the modulation of the TiO₂:MgO ratio was investigated. The most critical parameters were the chemical composition of the precursor electrolytic solution and the current density. According to scanning electron microscopy (SEM) observations, the coatings were porous; however, they become more compact as the current density increases. XRD measurements showed that the coatings are formed by a composite consisting of TiO₂ and MgO oxides, whose ratio can be changed by the experimental conditions. TiO₂ had the anatase crystalline structure, while the MgO had the FCC crystalline structure. The corrosion resistance was evaluated through the corrosion current (Icorr) measured at room temperature by the polarization technique (Tafel). For doing it, Hank's solution was used in order to simulate the body fluids. Also, immersion tests were conducted. Tafel curves showed an improvement of the corrosion resistance at some coated magnesium pieces in contrast to control pieces (uncoated). Corrosion currents were lower, and the corrosion potential changed to positive values. It was observed that the experimental parameters allowed to modulate the protective capacity of the coatings by changing the TiO₂:MgO ratio. Coatings with a higher content of TiO₂ (measured by energy dispersive spectroscopy) showed higher corrosion resistance. Results showed that TiO₂-MgO coatings can be successfully applied to improve the corrosion resistance of Mg pieces in simulated body fluid; even more, the corrosion resistance can be tuned by changing the TiO₂:MgO ratio.

Keywords: biomaterials, PEO, corrosion resistance, magnesium

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Authors: Spencer C. Pratt

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Anxiety is an emotional response that many, if not all, elite athletes struggle with on a daily basis. Recently, attention has been drawn to the strong need for athletes to receive mental training in order to help remedy the situation. The conceptual paper explores the effectiveness of a mental training component, based on the anxiolytic effects of exercise by investigating the positive relationship between physical activity and mental health through a comprehensive literature review. The review synthesizes pertinent research regarding the need for mental skills training among elite athletes and the anxiolytic effects of exercise. The paper concludes that with clear positive results from further experimentation with a (moderate intensity) running regimen, a wide range of elite athletes experiencing anxiety problems may have a viable solution.

Keywords: anxiety, mental training component, anxiolytic effects, elite athletes, moderate intensity running, mental skills training, running regimen

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Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

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The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

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Authors: Bambang Suko Priyono, Tristiana Rijanti

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This study examines the influence of Psychological Capital Dimensions to Organizational Citizenship Behavior. There are four dimensions of Psychological Capital such as hope, optimism, resilience, and self-efficacy. It also tests the moderation effect of Resistance to Change in the relation between Psychological Capital’s dimensions and Organizational Citizenship Behavior, and the influence of Organizational Citizenship Behavior to employees’ performance. The data from the chosen 160 respondents from Public Service Institution is processed using multiple regression and interaction method. The study results in: 1) Hope positively significantly influences Organizational Citizenship Behavior, 2) Optimism positively significantly influences Organizational Citizenship Behavior, 3) Resilience positively significantly influences Organizational Citizenship Behavior, 4) Self-efficacy positively significantly influences Organizational Citizenship Behavior, 5) Resistance to change is moderating variable between hope and Organizational Citizenship Behavior, 6) Resistance to change is moderating variable between self-efficacy and Organizational Citizenship Behavior, 7) Organizational Citizenship Behavior positively significantly influences performance. On the contrary, resistance to change as a moderating variable is proven for hope and resilience.

Keywords: organizational citizenship behavior, performance, psychological capital’s dimensions, and resistance to change

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Authors: Sanjeev Kumar, Swati Choudhary

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Background: A variety of studies warn that sedentary lifestyles can contribute to many preventable causes of death. This study was taken to determine the effects of two types of aerobic training programs on erythrocytes, leukocytes, hemoglobin concentration (Hb), platelets and hematocrit of sedentary people (N=60) with age group 20 to 30 years. Methods: All the subjects were randomly divided into three groups i.e. two experiments groups (aerobic dance & cardio fitness) and control group. Each group having 10 male and 10 females. Experimental groups undergone 60 minutes of training 5 times a week for 12 weeks whereas the control group did not participate in any training program except their daily routine. The aerobic dance group was chosen to perform exercise like step –touch, side-to-side, V-step and hand and body movements, etc. The cardio fitness group was chosen to perform exercises with modern fitness equipment like treadmill, elliptical trainer, stationary bike and rowing machine. Rating of perceived exertion (RPE) scale developed by Gunner Borg was used to monitor the intensity of the workout. Aerobic programs were encompassed of low-impact (0- 4 week & perceived exertion from 6 to 12), moderate-impact (4-8 week and perceived exertion from 12 to 16) and high-impact (8- 12 week & perceived exertion from 16 to 20). Results: To test the effectiveness of training programs paired t-test was used and significant difference (p<0.05) was observed in erythrocytes, hemoglobin concentration, platelets, hematocrit but no significant effects of training was found in leukocytes (p>0.05). Paired t-test also showed that no effect of time was seen in the control group in all the cases (p>0.05). Further analysis of covariance was used to know which program was more effective and it was seen that F value was found significant in the case of erythrocytes, hemoglobin concentration, platelets, and hematocrit as their associated p-value (p<0.05) is lesser than 0.05. As F value was found significant for hematological parameters, fishers least significant difference test was used and results of post hoc mean comparison indicated that experimental groups (aerobic dance group and cardio fitness group) had significant difference with control group in erythrocytes, hemoglobin concentration, platelets and hematocrit and insignificant difference was found between aerobic dance group & cardio fitness group in all the cases. Thus, it may be concluded that in general, both the aerobic training programs had adequate effects on all the hematological parameters except leukocytes.

Keywords: aerobic dance, cardio fitness, hematological variables, rating perceived exertion scale

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Authors: Pataraporn Kheawwan

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Preceptorship represents an important aspect in new nurse orientation. However, there was no formal preceptor training program developed for nurse preceptor in Thailand. The purposes of this study were to develop and evaluate formal preceptor training program for nurse preceptors in King Chulalongkorn Memorial Hospital, Thailand. A research and development study design was utilized in this study. Participants were 37 nurse preceptors. The program contents were delivered by e-learning material, class lecture, group discussion followed by simulation training. Knowledge of the participants was assessed pre and post program. Skill and critical thinking were assessed using Preceptor Skill and Decision Making Evaluation form at the end of program. Statistical significant difference in knowledge regarding preceptor role and coaching strategies between pre and post program were found. All participants had satisfied skill and decision making score after completed the program. Most of participants perceived benefits of preceptor training course. In conclusion, The results of this study reveal that the newly developed preceptorship course is an effective formal training course for nurse preceptors.

Keywords: preceptor, preceptorship, new nurse, clinical education

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Authors: Dhanashree Aole, V. Hariharan, Swati Surushe

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Corrosion can cause serious and expensive damage to the automobile components. Various proven techniques for controlling and preventing corrosion depend on the specific material to be protected. Electrochemical Impedance Spectroscopy (EIS) and salt spray tests are commonly used to assess the corrosion degradation mechanism of coatings on metallic surfaces. While, the only test which monitors the corrosion rate in real time is known as Linear Polarisation Resistance (LPR). In this study, electrochemical tests (EIS & LPR) and spray test are reviewed to assess the corrosion resistance and durability of different coatings. The main objective of this study is to correlate the test results obtained using linear polarization resistance (LPR) and Electrochemical Impedance Spectroscopy (EIS) with the results obtained using standard salt spray test. Another objective of this work is to evaluate the performance of various coating systems- CED, Epoxy, Powder coating, Autophoretic, and Zn-trivalent coating for vehicle underbody application. The corrosion resistance coating are assessed. From this study, a promising correlation between different corrosion testing techniques is noted. The most profound observation is that electrochemical tests gives quick estimation of corrosion resistance and can detect the degradation of coatings well before visible signs of damage appear. Furthermore, the corrosion resistances and salt spray life of the coatings investigated were found to be according to the order as follows- CED> powder coating > Autophoretic > epoxy coating > Zn- Trivalent plating.

Keywords: Linear Polarization Resistance (LPR), Electrochemical Impedance Spectroscopy (EIS), salt spray test, sacrificial and barrier coatings

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Authors: Michael Wagner, Philipp Steinbauer, Andrea Katharina Lietz, Alexander Hoffelner, Johannes Fessler

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Background: Cardiopulmonary resuscitations are stressful situations in which vital decisions must be made within seconds. Lack of routine due to the infrequency of pediatric emergencies can lead to serious medical and communication errors. Virtual reality can fundamentally change the way simulation training is conducted in the future. It appears to be a useful learning tool for technical and non-technical skills. It is important to investigate the use of VR in providing a strong sense of presence within simulations. Methods: In this randomized study, we will enroll doctors and medical students from the Medical University of Vienna, who will receive learning material regarding the resuscitation of a one-year-old child. The study will be conducted in three phases. In the first phase, 20 physicians and 20 medical students from the Medical University of Vienna will be included. They will perform simulation-based training with a standardized scenario of a critically ill child with a hypovolemic shock. The main goal of this phase is to establish a baseline for the following two phases to generate comparative values regarding cognitive load and stress. In phase 2 and 3, the same participants will perform the same scenario in a VR setting. In both settings, on three set points of progression, one of three predefined events is triggered. For each event, three different stress levels (easy, medium, difficult) will be defined. Stress and cognitive load will be analyzed using the NASA Task Load Index, eye-tracking parameters, and heart rate. Subsequently, these values will be compared between VR training and traditional simulation-based training. Hypothesis: We hypothesize that the VR training and the traditional training groups will not differ in physiological response (cognitive load, heart rate, and heart rate variability). We further assume that virtual reality training can be used as cost-efficient additional training. Objectives: The aim of this study is to measure cognitive load and stress level during a real-life simulation training and compare it with VR training in order to show that VR training evokes the same physiological response and cognitive load as real-life simulation training.

Keywords: virtual reality, cognitive load, simulation, adaptive virtual reality training

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Authors: Sayed-Mahdi Hashemi-Dehkordi, Ian Baker

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This paper investigates the benefits of implementing distance learning in training courses for the oil and gas industries to reduce lean. Due to the remote locations of many oil and gas operations, scheduling and organizing in-person training classes for employees in these sectors is challenging. Furthermore, considering that employees often work in periodic shifts such as day, night, and resting periods, arranging in-class training courses requires significant time and transportation. To explore the effectiveness of distance learning compared to in-class learning, a set of questionnaires was administered to employees of a far on-shore refinery unit in Iran, where both in-class and distance classes were conducted. The survey results revealed that over 72% of the participants agreed that distance learning saved them a significant amount of time by rating it 4 to 5 points out of 5 on a Likert scale. Additionally, nearly 67% of the participants acknowledged that distance learning considerably reduced transportation requirements, while approximately 64% agreed that it helped in resolving scheduling issues. Introducing and encouraging the use of distance learning in the training environments of oil and gas industries can lead to notable time and transportation savings for employees, ultimately reducing lean in a positive manner.

Keywords: distance learning, in-class learning, lean, oil and gas, scheduling, time, training programs, transportation

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Authors: Christine Y. Yeh, Brian D. Piening, Sarah M. Totten, Kimberly Kukurba, Wenyu Zhou, Kevin P. F. Contrepois, Gucci J. Gu, Sharon Pitteri, Michael Snyder

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Three million deaths worldwide are attributed to obesity. However, the biomolecular mechanisms that describe the link between adiposity and subsequent disease states are poorly understood. Insulin resistance characterizes approximately half of obese individuals and is a major cause of obesity-mediated diseases such as Type II diabetes, hypertension and other cardiovascular diseases. This study makes use of longitudinal quantitative and high-throughput multi-omics (genomics, epigenomics, transcriptomics, glycoproteomics etc.) methodologies on blood samples to develop multigenic and multi-analyte signatures associated with weight gain and insulin resistance. Participants of this study underwent a 30-day period of weight gain via excessive caloric intake followed by a 60-day period of restricted dieting and return to baseline weight. Blood samples were taken at three different time points per patient: baseline, peak-weight and post weight loss. Patients were characterized as either insulin resistant (IR) or insulin sensitive (IS) before having their samples processed via longitudinal multi-omic technologies. This comparative study revealed a wealth of biomolecular changes associated with weight gain after using methods in machine learning, clustering, network analysis etc. Pathways of interest included those involved in lipid remodeling, acute inflammatory response and glucose metabolism. Some of these biomolecules returned to baseline levels as the patient returned to normal weight whilst some remained elevated. IR patients exhibited key differences in inflammatory response regulation in comparison to IS patients at all time points. These signatures suggest differential metabolism and inflammatory pathways between IR and IS patients. Biomolecular differences associated with weight gain and insulin resistance were identified on various levels: in gene expression, epigenetic change, transcriptional regulation and glycosylation. This study was not only able to contribute to new biology that could be of use in preventing or predicting obesity-mediated diseases, but also matured novel biomedical informatics technologies to produce and process data on many comprehensive omics levels.

Keywords: insulin resistance, multi-omics, next generation sequencing, proteogenomics, type ii diabetes

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Authors: Usman Abubakar, Xiaoyuan Wang, Sayyed Haleem Shah, Sadiq Ur Rahman, Rabiu Saleh Zakariyya

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High-speed Permanent magnet synchronous machine (HSPMSM) uses in different industrial applications like blowers, compressors as a result of its superb performance. Nevertheless, the over-temperature rise of both winding and PM is one of their substantial problem for a high-power HSPMSM, which affects its lifespan and performance. According to the literature, HSPMSM with a Hybrid cooling configuration has a much lower temperature rise than non-hybrid cooling. This paper presents the design 185kW, 26K rpm with two different cooling configurations, i.e., hybrid cooling configuration (forced air and housing spiral water jacket) and non-hybrid (forced air cooling assisted with winding’s potting material and sleeve’s material) to enhance the heat dissipation of winding and PM respectively. Firstly, the machine’s electromagnetic design is conducted by the finite element method to accurately account for machine losses. Then machine’s cooling configurations are introduced, and their effectiveness is validated by lumped parameter thermal network (LPTN). Investigation shows that using potting, sleeve materials to assist non-hybrid cooling configuration makes the machine’s winding and PM temperature closer to hybrid cooling configuration. Therefore, the machine with non-hybrid cooling is prototyped and tested due to its simplicity, lower energy consumption and can still maintain the lifespan and performance of the HSPMSM.

Keywords: airflow network, axial ventilation, high-speed PMSM, thermal network

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: Jahanzaib

Abstract:

The rural economy can be uplifted through agricultural extension education for female as the majority is uneducated. The present study was carried out in five districts (Bahawalpur, Lodhran, Raheem Yar Khan, Bahawalnagr, and Vehari) of southern Punjab, Pakistan. The ten females were selected from each district, poor economic background for agricultural training. The training was provided free of cost, through Punjab skills development program. After six month training, the trainees were awarded with certificates and a tool kit. After completion of training data was recorded and analyzed, the results indicate that, female trainees were in a better economic position than the females of nearby districts without training. From this study, we can conclude that agricultural education for female can not only improve the economy of the individual family but also improve the agriculture of Pakistan on the sustainable basis as the majority of workers are female in rural areas of Pakistan.

Keywords: agricultural extension education, sustainable rural development, agriculture, rural development in Pakistan

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Authors: Kyle Saltmarsh

Abstract:

Acoustic testing possesses many benefits due to its non-destructive nature and practicality. There hence exists many scenarios in which using acoustic testing for condition testing shows powerful feasibility. A wealth of information is contained within the acoustic and vibration characteristics of structures, allowing the development meaningful features for the classification of their respective condition. In this paper, methods, results, and discussions are presented on the use of non-destructive acoustic testing coupled with acoustic feature extraction and machine learning techniques for the condition testing of manufactured circular steel plates subjected to varied levels of damage.

Keywords: plates, deformation, acoustic features, machine learning

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

Abstract:

Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Joe Voshall, Leigha Shoup

Abstract:

In 2022, the Ohio Peace Officer Training Council and the Attorney General required officers to complete a minimum of 24 hours of continued professional training for the year. Much of the training was based on Mental Health or similarly related topics. This includes Officer Wellness and Officer Mental Health. It is becoming clearer that the stigma of Officer / First Responder Mental Health is a topic that is becoming more prevalently faced. To assist officers and first responders in facing mental health issues, we are developing new training. This training will aid in recognizing mental health-related issues in officers/first responders and citizens, as well as further using the same information to better respond and interact with one another and the public. In general, society has many varying views of mental health, much of which is largely over-sensationalized by television, movies, and other forms of entertainment. There has also been a stigma in law enforcement / first responders related to mental health and being weak as a result of on-the-job-related trauma-induced struggles. It is our hope this new training will assist officers and first responders in not only positively facing and addressing their mental health but using their own experience and education to recognize signs and symptoms of mental health within individuals in the community. Further, we hope that through this recognition, officers and first responders can use their experiences and more in-depth understanding to better interact within the field and with the public. Through recognition and better understanding of mental health issues and more positive interaction with the public, additional achievements are likely to result. This includes in the removal of bias and stigma for everyone.

Keywords: law enforcement, mental health, officer related mental health, trauma

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Authors: Rizwana Amin, Afshan Afroze Bhatti

Abstract:

The study was a quasi-experimental pre-post test design including two groups. Data was collected from 127 students through non-probability random sampling from Bahaudin Zakariya University Multan. The groups were given pre-test using perceived stress scale and information about academic achievement was taken by self-report. After screening, 27 participants didn’t meet the criterion. Remaining 100 participants were divided into two groups (experimental and control). Further, 4 students of experimental group denied taking intervention. Then 46 understudies were separated into three subgroups (16, 15 and 15 in each) for training. The experimental groups were given the stress management training, each of experimental group attended one 3-hour training sessions separately while the control group was only given pre-post assessment. The data were analyzed using ANCOVA method (analysis of covariance) t–test. Results of the study indicate that stress training will lead to increased emotional intelligence and academic achievement of students.

Keywords: stress, stress management, academic achievement, students

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Authors: María Laura Guevara Campos

Abstract:

The increasing number of vending machines makes it easy for people to find them more frequently in stores, universities, workplaces, and even hospitals. These machines usually offer products with high contents of sugar and fat, which, if consumed regularly, can result in serious health threats, as overweight and obesity. Additionally, the energy consumption of these machines tends to be high, which has an impact on the environment as well. In order to promote the consumption of healthy food, a vending machine was designed to give the customer the opportunity to choose between a customized fruit salad and a customized fruit juice, both of them prepared instantly with the ingredients selected by the customer. The main parameters considered to design the machine were: the storage of the preferred fruits in a salad and/or in a juice according to a survey, the size of the machine, the use of ecologic recipients, and the overall energy consumption. The methodology used for the design was the one proposed by the German Association of Engineers for mechatronics systems, which breaks the design process in several stages, from the elaboration of a list of requirements through the establishment of the working principles and the design concepts to the final design of the machine, which was done in a 3D modelling software. Finally, with the design of this machine, the aim is to contribute to the development and implementation of healthier vending machines that offer freshly-made products, which is not being widely attended at present.

Keywords: design, design methodology, mechatronics systems, vending machines

Procedia PDF Downloads 121