Search results for: machine resistance training

Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: R. Frikha, H. Kamoun

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Background:Chronicmyeloidleukemia (CML), a hematologicaldisease, ischaracterized by t (9; 22) and relatedoncogene BCR-ABL formation. Although Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of CML, resistanceoccurs and possibly médiates by mutation in severalgenesindependently of the bcr-abl1 kinase mechanism. it has been reportedthat JAK2V617F/BCR-ABL double positivitymaybe a potential marker of resistance in CML. Aims: This studywasinvestigated the JAK2V617F mutation in TKI-resistant CML patients. Methods: A retrospectivestudywasconducted in the Hospital University of Sfax, south of Tunisia, including all CML TKI-resistant patients. A Sanger sequencingwasperformedusing a high-fidelity DNA polymerase. Results:Nineresistant CP-CML patients wereenrolled in thisstudy. The JAK2V617F mutation wasdetectedin 3 patients with TKI resistance. Conclusion:Despite the limit of ourstudy, ourfinding highlights the high frequency of JAK2V617F/BCR-ABL double positivity as an important marker of resistance. So; the combination of JAK and TKI inhibitorsmightbe effective and potentiallybeguided by molecular monitoring of minimal residual disease1.

Keywords: chronic myeloid leukemia, tyrosine kinase inhibitors, resistance, JAK2V617F, BCR-ABL

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Authors: Eno Jah Tabogo

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The aim of this research is to identify and examine current deficiencies in entrepreneurial training in improving the performance of small businesses in sub Saharan Africa economies. This research achieves this by examining the course content, training methods, and profiles of trainers and trainees of small business service providers in Sub Saharan Africa (SSA) to identify training deficiencies in improving small businesses. Data was for the analysis was collected from a sample of four entrepreneurial training providers in SSA. These four providers served an average of 1,500 trainees. Questionnaire was used to collect data via face to face and through telephone. Face validity was determined by distributing the questionnaire among a group of colleagues, followed by a group discussion to strengthen the validity of the questionnaire. Interviews were also held with managers of training programs. Content and descriptive statistics was used to analyse the data collected. The results indicated only 25% of the training content were entrepreneurial. In terms of service provided, both business, entrepreneurial, technical and after-care services were identified. It was also discovered that owners of training firms had no formal entrepreneurship background. The paper contributes by advocating for a comprehensive entrepreneurship-training program for successful small business enterprises. Recommendations that could help sustain emerging small business enterprises and direction for further research are presented.

Keywords: entrepreneurship, emerging markets, small business, training

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Authors: Dede Basturk, Metin Kaya, Halil Taskin, Nurtekin Erkmen

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In total, 29 students studying in Selçuk University Physical Training and Sports School who are recreationally active participated voluntarilyin this study which was carried out in order to examine effects of Vertimax trainings on agility, quickness and acceleration. 3 groups took their parts in this study as Vertimax training group (N=10), Ordinary training group (N=10) and Control group (N=9). Measurements were carried out in performance laboratory of Selçuk University Physical Training and Sports School. A training program for quickness and agility was followed up for subjects 3 days a week (Monday, Wednesday, Friday) for 8 weeks. Subjects taking their parts in vertimax training group and ordinary training group participated in the training program for quickness and agility. Measurements were applied as pre-test and post-test. Subjects of vertimax training group followed the training program with vertimax device and subjects of ordinary training group followed the training program without vertimax device. As to control group who are recreationally active, they did not participate in any program. 4 gate photocells were used for measuring and measurement of distances was carried out in m. Furthermore, single gate photocell and honi were used for agility test. Measurements started with 15 minutes of warm-up. Acceleration, quickness and agility tests were applied on subjects. 3 measurements were made for each subject at 3 minutes resting intervals. The best rating of three measurements was recorded. 5 m quickness pre-test value of vertimax training groups has been determined as 1,11±0,06 s and post-test value has been determined as 1,06 ± 0,08 s (P<0,05). 5 m quickness pre-test value of ordinary training group has been determined as 1,11±0,06 s and post-test value has been determined as 1,07±0,07 s (P<0,05).5 m quickness pre-test value of control group has been determined as 1,13±0,08 s and post-test value has been determined as 1,10 ± 0,07 s (P>0,05). Upon examination of 10 m acceleration value before and after the training, 10 m acceleration pre-test value of vertimax training group has been determined as 1,82 ± 0,07 s and post-test value has been determined as 1,76±0,83 s (P>0,05). 10 m acceleration pre-test value of ordinary training group has been determined as 1,83±0,05 s and post-test value has been determined as 1,78 ± 0,08 s (P>0,05).10 m acceleration pre-test value of control group has been determined as 1,87±0,11 s and post-test value has been determined as 1,83 ± 0,09 s (P>0,05). Upon examination of 15 m acceleration value before and after the training, 15 m acceleration pre-test value of vertimax training group has been determined as 2,52±0,10 s and post-test value has been determined as 2,46 ± 0,11 s (P>0,05).15 m acceleration pre-test value of ordinary training group has been determined as 2,52±0,05 s and post-test value has been determined as 2,48 ± 0,06 s (P>0,05). 15 m acceleration pre-test value of control group has been determined as 2,55 ± 0,11 s and post-test value has been determined as 2,54 ± 0,08 s (P>0,05).Upon examination of agility performance before and after the training, agility pre-test value of vertimax training group has been determined as 9,50±0,47 s and post-test value has been determined as 9,66 ± 0,47 s (P>0,05). Agility pre-test value of ordinary training group has been determined as 9,99 ± 0,05 s and post-test value has been determined as 9,86 ± 0,40 s (P>0,05). Agility pre-test value of control group has been determined as 9,74 ± 0,45 s and post-test value has been determined as 9,92 ± 0,49 s (P>0,05). Consequently, it has been observed that quickness and acceleration features were developed significantly following 8 weeks of vertimax training program and agility features were not developed significantly. It is suggested that training practices used for the study may be used for situations which may require sudden moves and in order to attain the maximum speed in a short time. Nevertheless, it is also suggested that this training practice does not make contribution in development of moves which may require sudden direction changes. It is suggested that productiveness and innovation may come off in terms of training by using various practices of vertimax trainings.

Keywords: vertimax, training, quickness, agility, acceleration

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Authors: Dong-Hyun Kim, Wan-Ho Chung, Hak-Sung Kim

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In this work, non-destructive evaluation was conducted to measure the sheet resistance of silver nanowire coated film and find a damage of that film using terahertz (THz) wave. Pulse type THz instrument was used, and the measurement was performed under transmission and pitch-catch reflection modes with 30 degree of incidence angle. In the transmission mode, the intensity of the THz wave was gradually increased as the conductivity decreased. Meanwhile, the intensity of THz wave was decreased as the conductivity decreased in the pitch-catch reflection mode. To confirm the conductivity of the film, sheet resistance was measured by 4-point probe station. Interaction formula was drawn from a relation between the intensity and the sheet resistance. Through substituting sheet resistance to the formula and comparing the resultant value with measured maximum THz wave intensity, measurement of sheet resistance using THz wave was more suitable than that using 4-point probe station. In addition, the damage on the silver nanowire coated film was detected by applying the THz image system. Therefore, the reliability of the entire film can be also be ensured. In conclusion, real-time monitoring using the THz wave can be applied in the transparent electrodes with detecting the damaged area as well as measuring the sheet resistance.

Keywords: terahertz wave, sheet resistance, non-destructive evaluation, silver nanowire

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Authors: Nurtekin Erkmen, Turgut Kaplan, Halil Taskin, Ahmet Sanioglu, Gokhan Ipekoglu

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The aim of this study was to determine the effects of an 8 week soccerspecific technical training with limited vision perception on postural control and technical parameters in 10-12 aged soccer players. Subjects in this study were 24 male young soccer players (age: 11.00 ± 0.56 years, height: 150.5 ± 4.23 cm, body weight: 41.49 ± 7.56 kg). Subjects were randomly divided as two groups: Training and control. Balance performance was measured by Biodex Balance System (BBS). Short pass, speed dribbling, 20 m speed with ball, ball control, juggling tests were used to measure soccer players’ technical performances with a ball. Subjects performed soccer training 3 times per week for 8 weeks. In each session, training group with limited vision perception and control group with normal vision perception committed soccer-specific technical drills for 20 min. Data analyzed with t-test for independent samples and Mann-Whitney U between groups and paired t-test and Wilcoxon test between pre-posttests. No significant difference was found balance scores and with eyes open and eyes closed and LOS test between training and control groups after training (p>0.05). After eight week of training there are no significant difference in balance score with eyes open for both training and control groups (p>0.05). Balance scores decreased in training and control groups after the training (p<0.05). The completion time of LOS test shortened in both training and control groups after training (p<0.05). The training developed speed dribbling performance of training group (p<0.05). On the other hand, soccer players’ performance in training and control groups increased in 20 m speed with a ball after eight week training (p<0.05). In conclusion; the results of this study indicate that soccer-specific training with limited vision perception may not improves balance performance in 10-12 aged soccer players, but it develops speed dribbling performance.

Keywords: Young soccer players, vision perception, postural control, technical

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Authors: Kherafa Abdennasser

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The application of Information and Communication Technologies (ICT) to the training area led to the creation of this new reality called E-learning. That last one is described like the marriage of multi- media (sound, image and text) and of the internet (diffusion on line, interactivity). Distance learning became an important totality for training and that last pass in particular by the setup of a distance learning platform. In our memory, we will use an open source platform named Dokeos for the management of a distance training of GPS called e-GPS. The learner is followed in all his training. In this system, trainers and learners communicate individually or in group, the administrator setup and make sure of this system maintenance.

Keywords: ICT, E-learning, learning plate-forme, Dokeos, GPS

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Magdy Abouzeid, Nancy Abouzeid, Afaf Salem

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Background: The elite child athletes are one who has superior athletic talent. Monofin (a single surface swim fin) swimming already proved to be the most efficient method of swimming for human being. This is a novel descriptive study examining myocardial function indices in prepubertal monofin children. The aim of the present study was to determine the influence of long-term monofin training (LTMT), 36 weeks, 6 times per week, 90 min per unit on Myocardial function adaptation in elite child monofin athletes. Methods: 14 elite monofin children aged 11.95 years (± 1.09 yr) took part for (LTMT). All subjects underwent two-dimension, M-mode, and Doppler echocardiography before and after training to evaluate cardiac dimensions and function; septal and posterior wall thickness. Statistical methods of SPSS, means ± SD and paired t test, % of improvement were used. Findings: There was significant difference (p<0.01) and % improvement for all echocardiography parameter after (LTMT). Inter ventricular septal thickness in diastole and in systole increased by 27.9 % and 42.75 %. Left ventricular end systolic dimension and diastole increased by 16.81 % and 42.7 % respectively. Posterior wall thickness in systole very highly increased by 283.3 % and in diastole increased by 51.78 %. Left ventricular mass in diastole and in systole increased by 44.8 % and 40.1 % respectively. Stroke volume (SV) and resting heart rate (HR) significant changed (sv) 25 %, (HR) 14.7 %. Interpretation: the unique swim fin tool and create propulsion and overcome resistance. Further researches are needed to determine the effects of monofin training on right ventricular in child athletes.

Keywords: prepubertal, monofin training, heart athlete's, elite child athlete, echocardiography

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Authors: Chechen Liao, Chin Yi Yang

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Although several factors that affect learning to program have been identified over the years, there continues to be no indication of any consensus in understanding why some students learn to program easily and quickly while others have difficulty. Seldom have researchers considered the problem of how to help the students enhance the programming learning outcome. The research had been conducted at a high school in Taiwan. Students participating in the study consist of 330 tenth grade students enrolled in the Basic Computer Concepts course with the same instructor. Two types of training methods-instruction-oriented and exploration-oriented were conducted. The result of this research shows that the instruction-oriented training method has better learning performance than exploration-oriented training method.

Keywords: learning performance, programming learning, TDD, training method

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Authors: Jung-Min Yang

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Corrective control enables us to change the stable state behavior of an asynchronous sequential machine without modifying inner logic of the machine. This paper addresses corrective control for asynchronous machines with switching capability. The considered asynchronous machine consists of a set of different submachines and switches to each machine according to a constant switching sequence. The control goal is to design a corrective controller such that the closed-loop system can match the behavior of a reference model. The reachability of the switched asynchronous machine is described by a logic calculation of the reachability of submachines. The design procedure of the proposed corrective controller is outlined, and the applicability of the proposed scheme is validated in an example.

Keywords: switched asynchronous sequential machines, corrective control, state feedback, switching sequences

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Authors: Eizadi Mojtaba

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This study aimed to evaluate the effect of 8 weeks aerobic training on serum osteocalsin as an osteoblasts hormone and cortisol in adult men with asthma. For this purpose, twenty four non-trained adult men with mild to moderate asthma were participated in study voluntarily and divided into exercise (aerobic training, 8 weeks/3 times per week) and control groups by randomly. Pre and post training of serum osteocalsin and cortisol were measured of two groups. Student’s paired ‘t’ test was applied to compare the pre and post training values. A p-value of less than 0.05 was considered to be statistically significant. There were no statistically significant differences with regard to all anthropometrical and biochemical markers between the exercise and control groups at baseline ( P > 0.05 ). Exercise training resulted in a significant increase in serum osteocalsin and decrease in cortisol ( P > 0.05 ), but not in control group. Based on these data, we concluded that aerobic training can be improved Processes of bone formation in asthma patients.

Keywords: osteoblasts, asthma, aerobic exercise, sedentary

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Authors: R. Loukil, M. Chtourou, T. Damak

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This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.

Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state

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Authors: Cheikh Bamba Dione, Alla Lo, Elhadji Mamadou Nguer, Siley O. Ba

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In this paper, we propose two neural machine translation (NMT) systems (French-to-Wolof and Wolof-to-French) based on sequence-to-sequence with attention and transformer architectures. We trained our models on a parallel French-Wolof corpus of about 83k sentence pairs. Because of the low-resource setting, we experimented with advanced methods for handling data sparsity, including subword segmentation, back translation, and the copied corpus method. We evaluate the models using the BLEU score and find that transformer outperforms the classic seq2seq model in all settings, in addition to being less sensitive to noise. In general, the best scores are achieved when training the models on word-level-based units. For subword-level models, using back translation proves to be slightly beneficial in low-resource (WO) to high-resource (FR) language translation for the transformer (but not for the seq2seq) models. A slight improvement can also be observed when injecting copied monolingual text in the target language. Moreover, combining the copied method data with back translation leads to a substantial improvement of the translation quality.

Keywords: backtranslation, low-resource language, neural machine translation, sequence-to-sequence, transformer, Wolof

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: A. Nusrath Unissa, Sameer Hassan, Luke Elizabeth Hanna

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Altered drug binding may be an important factor in isoniazid (INH) resistance, rather than major changes in the enzyme’s activity as a catalase or peroxidase (KatG). The identification of structural or functional defects in the mutant KatGs responsible for INH resistance remains as an area to be explored. In this connection, the differences in the binding affinity between wild-type (WT) and mutants of KatG were investigated, through the generation of three mutants of KatG, Ser315Thr [S315T], Ser315Asn [S315N], Ser315Arg [S315R] and a WT [S315]) with the help of software-MODELLER. The mutants were docked with INH using the software-GOLD. The affinity is lower for WT than mutant, suggesting the tight binding of INH with the mutant protein compared to WT type. These models provide the in silico evidence for the binding interaction of KatG with INH and implicate the basis for rationalization of INH resistance in naturally occurring KatG mutant strains of Mycobacterium tuberculosis.

Keywords: Mycobacterium tuberculosis, KatG, INH resistance, mutants, modelling, docking

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Authors: H. Malachova, A. Oulehlova, D. Rezac

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Crisis preparedness training is the best possible strategy for identifying weak points, understanding vulnerability, and finding possible strategies for mitigation of blackout consequences. Training represents an effective tool for developing abilities and skills to cope with crisis situations. This article builds on the results of the research carried out in the field of preparation, realization, process, and impacts of training on subjects of energy sector critical infrastructure as a part of crisis preparedness. The research has revealed that the subjects of energy sector critical infrastructure have not realized training and therefore are not prepared for the restoration of the energy supply and black start after blackout regardless of the fact that most subjects state blackout and subsequent black start as key dangers. Training, together with mutual communication and processed crisis documentation, represent a basis for successful solutions for dealing with emergency situations. This text presents the suggested model of SIMEX simulator as a tool which supports managing crisis situations, containing training environment. Training models, possibilities of constructive simulation making use of non-aggregated as well as aggregated entities and tools of communication channels of individual simulator nodes have been introduced by the article.

Keywords: communication, energetic critical infrastructure, training, simulation

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Authors: Asieh Abbassi Daloii, Fatemeh Fani, Ahmad Abdi

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Objective: The aim of this study was to determine the effect of 8 weeks endurance training and L-NAME on apelin in adipose tissue, glucose and insulin in elderly male’s rats. Methods: For this purpose, 24 vistar elderly rats with average 20 months old purchased from Razi Institute and transferred to Research Center were randomly divided into four groups: 1. control, 2. training, 3.training and L-NAME and 4. L-NAME. Training protocol performed for 8 weeks and 5 days a week with 75-80 VO2 max. All rats were killed 72 hours after the final training session and after 24 hours of fasting adipose tissue samples were collected and kept in -80. Also, Data was analyzed with One way ANOVA and Tucky in p < 0/05. Results: The results showed that the inhibition of nitric oxide on apelin in adipose tissue of adult male rats after eight weeks of endurance training increased significantly compared to the control group (p < 0.00). Also, the results showed no significant difference between the levels of insulin and glucose groups. Conclusion: It is likely that the increased apelin in adipose tissue in mice independent of insulin and glucose.

Keywords: endurance training, L-NAME, apelin in adipose tissue, elderly male rats

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Authors: Behnam Hasanzadeh, Asieh Abbassi Daloii, Ailin Ebrahimi

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The present study aims to investigate the effect of six weeks of progressive aerobic training and aqueous extract of Crataegus monogyna on VEGF variations and plasma angiopoetin-1/2 (ANG- 1/2) in male Wistar rats. Materials and methods: A number of 30 male Wistar rats, 4-6 months old, were randomly divided into four groups: control Crataegus monogyna (N=8), training Crataegus monogyna (N=8), control saline (N=6), and training saline (N=8). The aerobic training program included running on the treadmill at the speed of 34 meters per minute for 60 minutes per day. The training was conducted for six weeks, five days a week. Following each training session, both experimental and control subjects of Crataegus monogyna groups were orally fed with 0.5 mg Crataegus monogyna extract per gram of body weight. The normal saline group was given the same amount of normal saline solution (NS). Eventually, 72 hours after the last training session, blood samples were taken from inferior verna cava. Results: the results showed that progressive endurance training caused insignificant reductions in plasma VEGF concentration in the training group, Crataegus monogyna group and training-Crataegus monogyna group comparing the control group. Plasma ANG-1 concentration reduced in the training, Crataegus monogyna and training-Crataegus monogyna groups while plasma ANG-2 concentration significantly increased in the Crataegus monogyna group (P=0.022) comparing with the control group. The results showed that the ratio of plasma ANG-2 to ANG-1 significantly increased in the Crataegus monogyna group (P=0.028) comparing with the control group. Conclusion: the findings suggest that combination of aerobic training and Crataegus monogyna extract has no synergistic effect on anti-angiogenesis indicators and Crataegus monogyna extract had a stronger effect on anti-angiogenesis indicators.

Keywords: angiopoetin-1/2, VEGF, Crataegus monogyna extract, aerobic training

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: Rodrigo Aguiar, Adelino Ferreira

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Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

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Authors: Neda Zamani

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The present study aimed to investigate the effectiveness of training courses and their limitations using the CIPP model. The investigations were done on Isfahan Refinery as a case study. From a purpose point of view, the present paper is included among applied research and from a data gathering point of view, it is included among descriptive research of the field type survey. The population of the study included participants in training courses, their supervisors and experts of the training department. Probability-proportional-to-size (PPS) was used as the sampling method. The sample size for participants in training courses included 195 individuals, 30 supervisors and 11 individuals from the training experts’ group. To collect data, a questionnaire designed by the researcher and a semi-structured interview was used. The content validity of the data was confirmed by training management experts and the reliability was calculated through 0.92 Cronbach’s alpha. To analyze the data in descriptive statistics aspect (tables, frequency, frequency percentage and mean) were applied, and inferential statistics (Mann Whitney and Wilcoxon tests, Kruskal-Wallis test to determine the significance of the opinion of the groups) have been applied. Results of the study indicated that all groups, i.e., participants, supervisors and training experts, absolutely believe in the importance of training courses; however, participants in training courses regard content, teacher, atmosphere and facilities, training process, managing process and product as to be in a relatively appropriate level. The supervisors also regard output to be at a relatively appropriate level, but training experts regard content, teacher and managing processes as to be in an appropriate and higher than average level.

Keywords: training courses, limitations of training effectiveness, CIPP model, Isfahan oil refinery company

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Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim

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As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.

Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction

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Authors: Laleh Behboudi Tabrizi, Melika Naserzare

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Accumulating experimental and epidemiologic data smoker individuals are more prone to systemic inflammation than non-smokers. In this study we aimed to determine serum TNF-α and C-reactive protein (CRP) as pro-inflammatory cytokines in response to 3 months aerobic training in smoker men. A total 30 middle-aged healthy smokers selected for participate in this study and were divided into either control or exercise groups. The subjects in exercise group were completed a 3 months aerobic training program for 3 sessions per week at 60 – 80 % of maximal heart rate. Those in control group did nit participated in exercise training. Pre and post-training of CRP and TNF-α were measured in two groups. Student’s t-tests for paired samples were performed to determine whether there were signigcant within-group changes in the outcomes. P value of <0.05 was accepted as significant. No significant differences were found in anthropometrical and biochemical markers between two groups at baseline. Aerobic training program resulted in a significant decrease in anthropometrical markers and serum TNF-α but not in serum CRP in exercise group. All variables remained without changes in control groups. Based on these finding, it is concluded that aerobic training can be improve inflammatory cytokine with emphasis on TNF-α in smokers.

Keywords: cigarette, cytokine, chronic training, inflammation

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Authors: Erin C. Rodenburg, Jennifer McWhirter, Andrew Papadopoulos

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Support workers for adults with developmental disabilities promote the care and wellbeing of a historically underserved population. Poor employment training and low work satisfaction for these disability support workers are linked to low productivity, poor quality of care, turnover, and intention to leave employment. Therefore, to improve the lives of those within disability support homes, both client and caregiver, it is vital to determine where improvements to training and support for those providing direct care can be made. The current study aims to explore disability support worker’s perceptions of the training received in their employment at the residential homes, how it prepared them for their role, and where there is room for improvement with the aim of developing recommendations for an improved training experience. Responses were collected from 85 disability support workers across 40 Ontario group homes. Findings suggest most disability support workers within the 40 support homes feel adequately trained in their responsibilities of employment. For those who did not feel adequately trained, the main issues expressed were a lack of standardization in training, a need for more continuous training, and a move away from trial and error in performing tasks to support clients with developmental disabilities.

Keywords: developmental disabilities, disability workers, support homes, training

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

Abstract:

In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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Authors: M. Zaitoun, S. Cumming, A. Purcell

Abstract:

This study aims to determine if audiologists' experience characteristics in ABR (Auditory Brainstem Response) reading is associated with their performance in interpreting ABR results. Fifteen ABR traces with varying degrees of hearing level were presented twice, making a total of 30. Audiologists were asked to determine the hearing threshold for each of the cases after completing a brief survey regarding their experience and training in ABR administration. Sixty-one audiologists completed all tasks. Correlations between audiologists’ performance measures and experience variables suggested significant associations (p < 0.05) between training period in ABR testing and audiologists’ performance in terms of both sensitivity and accuracy. In addition, the number of years conducting ABR testing correlated with specificity. No other correlations approached significance. While there are relatively few significant correlations between ABR performance and experience, accuracy in ABR reading is associated with audiologists’ length of experience and period of training. To improve audiologists’ performance in reading ABR results, an emphasis on the importance of training should be raised and standardized levels and period for audiologists training in ABR testing should also be set.

Keywords: ABR, audiology, performance, training, experience

Procedia PDF Downloads 166

Authors: David Robert Irvine

Abstract:

In the dental restoration sector, there has been a shift to using zirconia. With the ever increasing need to decrease lead times to deliver restorations faster the zirconia is machined in its pre-sintered state instead of grinding the very hard sintered state. As with all machining, there is tool wear and while investigating the tooling used to machine pre-sintered zirconia it became apparent that the wear rate is based more on material build up and abrasion than it is on plastic deformation like conventional metal machining. It also came to light that the tool material can currently not be selected based on wear resistance, as there is no data. Different works have analysed the effect of the individual wear mechanism separately using similar if not the same material. In this work, the testing method used to analyse the wear was a modified from ISO 8688:1989 to use the pre-sintered zirconia and the cutting conditions used in dental to machine it. This understanding was developed through a series of tests based in machining operations, to give the best representation of the multiple wear factors that can occur in machining of pre-sintered zirconia such as 3 body abrasion, material build up, surface welding, plastic deformation, tool vibration and thermal cracking. From the testing, it found that carbide grades with low trans-granular rupture toughness would fail due to abrasion while those with high trans-granular rupture toughness failed due to edge chipping from build up or thermal properties. The results gained can assist the development of these tools and the restorative dental process. This work was completed with the aim of assisting in the selection of tool material for future tools along with a deeper understanding of the properties that assist in abrasive wear resistance and material build up.

Keywords: abrasive wear, cemented carbide, pre-sintered zirconia, tool wear

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Authors: Amir H. Bayat, Mohammad R. Alipour, Saeed Khamneh

Abstract:

As the respiration via nose is important physiologically, many studies have been done about nasal breathing that switches to oronasal breathing during exercise. The aim of this study was to assess the role of anterior nasal resistance as one of the effective factors on this switching. Twelve young, healthy, non-athletic and non-smoker male volunteers with normal BMI were selected after physical examination and participated in exercise protocol, including measurement of the ventilation, work load and oronasal switching point (OSP) during exercise, and anterior rhinomanometry at rest. The protocol was an incremental exercise with 25 watt increase in work load per minute up to OSP occurrence. There was a significant negative correlation between resting total anterior nasal resistance with OSP, work load and ventilation (p<0.05, r= -0.709). Resting total anterior nasal resistance can be considered as an important factor on OSP occurrence. So, the reducing the resistance of nasal passage may increase nasal respiration tolerance for longer time during exercise.

Keywords: anterior nasal resistance, exercise, OSP, ventilation, work load

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Authors: Francis Ojo Ologunagba, Monday Olatunbosun Ale, Lewis A. Olutayo

Abstract:

The economic successes of commercial development of agricultural product processing depend upon the adaptability of each processing stage to mechanization. In maize processing, one of its post-harvest operations that is still facing a major challenge is dehusking. Therefore, a maize dehusking machine that could replace the prevalent traditional method of dehusking maize in developing countries, especially Nigeria was designed, constructed and tested at the Department of Agricultural and Bio-Environmental Engineering Technology, Rufus Giwa Polytechnic, Owo. The basic features of the machine are feeding unit (hopper), housing frame, dehusking unit, drive mechanism and discharge outlets. The machine was tested with maize of 50mm average diameter at 13% moisture content and 2.5mm machine roller clearance. Test results showed appreciable performance with the dehusking efficiency of 92% and throughput capacity of 200 Kg/hr at a machine speed of 400rpm. The estimated production cost of the machine at the time of construction is forty-five thousand, one hundred and eighty nairas (₦45,180) excluding the cost of the electric motor. It is therefore recommended for small and medium-scale maize farmers and processors in Nigeria.

Keywords: construction, dehusking, design, efficiency, maize

Procedia PDF Downloads 323