Search results for: machine resistance training

Authors: Enny Suswati, Supangat Supangat

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Background. Ready-to-eat food products are becoming increasingly popular because consumers are increasingly busy, competitive, and changing lifestyles. Examples of ready-to-eat foods include crispy fried chicken. Escherichia coli is one of the most important causes of food-borne diseases and the most frequent antibiotic-resistant pathogen globally. This study assessed the prevalence and antibiotic resistance profile of E. coli from ready-to-eat crispy fried chicken in Jember city, Indonesia. Methodology. This cross-sectional study was conducted from November 2020 to April 2021 by collecting 81crispy fried chicken samples from 27 food stalls in campus area using a simple random sampling method. Isolation and determination of E. coli use were performed by conventional culture method. An antibiotic susceptibility test was conducted using Kirby Bauer disk diffusion method on the Mueller–Hinton agar. Result. Out of 81crispy fried chicken samples, 77 (95.06%) were positive for E. coli. High E. coli drug resistance was observed on ampicillin, amoxicillin (100%) followed by cefixime (98.72%), erythromycin (97.59%), sulfamethoxazole (93.59%), azithromicin (83.33%), cefotaxime (78.28%), choramphenicol (75.64%), and cefixime (74.36%). On the other hand, there was the highest susceptibility for ciprofloxacin (64.10%). The multiple antibiotic resistance indexes of E. coli isolates varied from 0.4 to 1. The predominant antimicrobial resistance profiles of E. coli were CfmCroAmlAmpAzmCtxSxtCE (n=17), CfmCroAmlCipAmpAzmCtxSxtCE (n=16), and CfmAmlAmpAzmCtxSxtCE (n=5), respectively. Multidrug resistance was also found in the isolates' 76/77 (98.70%). Conclusion. The resistance pattern CfmCroAmlAmpAzmCtxSxtCE was the most common among the E. coli isolates, with 17 showing it. The multiple antibiotic index (MAR index) ranged from 0.4 to 1. Hygienic measures should be rigorously implemented and monitoring resistance of E. coli is required to reduce the risks related to the emergence of multi-resistant bacteria

Keywords: antibacterial drug, ready to eat, crispy fried chicken, escherichia coli

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Authors: C. Schneider, M. M. Seizmeir, T. Suchanek, M. Hutter-Mironovova, M. Bdiwi, M. Putz

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In this paper, a suitable measurement setup is presented to conduct force and pressure measurements for transient contact cases at the example of lathe machine tending. Empirical measurements were executed on a selected collaborative robot’s behavior regarding allowable operating speeds under consideration of sensor- and workpiece-specific factors. Comparisons between the theoretic calculations proposed in ISO/TS 15066 and the practical measurement results reveal a basis for future research. With the created database, preliminary risk assessment and economic assessment procedures of collaborative machine tending cells can be facilitated.

Keywords: biomechanical thresholds, collaborative robots, force and pressure measurements, machine tending, transient contact

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Authors: Amiel Satvedi, Richard Pyne

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Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

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Authors: Kouzi Katia

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This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

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Authors: Menan M. Elsayed, Hussein A. Heshmat

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The aim of the study is to determine the effect of 100 mg/d Pregnenolone on biological variables after plyometric training for volleyball players. Methods: 15 male volleyball players participated in this study. Serum levels of testosterone, creatine phosphokinase (CPK), lactate, and glucose were measured before and post-exercise. Results: Testosterone was not altered, while creatine phosphokinase (CPK), lactate, and glucose levels significantly decreased. It is recommended to use Pregnenolone administration to decreased muscle damage and delayed fatigue for volleyball players after plyometric training. In conclusion, this study demonstrated that oral Pregnenolone administration of 100 mg/d might decrease muscle damage and delayed fatigue which may affect positively the volleyball players after a plyometric training bout.

Keywords: biological variables, plyometric exercise program, pregnenolone, volleyball player

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Authors: Aleksandra Zysk, Pawel Badura

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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: classification, singing, spectral analysis, vocal emission, vocal register

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Authors: Hind Bouami

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Handling life-critical systems complexity requires to be equipped with appropriate technology and the right human agents’ functions such as knowledge, experience, and competence in problem’s prevention and solving. Human agents are involved in the management and control of human-machine system’s performance. Documenting human agent’s situation awareness is crucial to support human-machine designers’ decision-making. Knowledge about risks, critical parameters and factors that can impact and threaten automation system’s performance should be collected using preventive and retrospective approaches. This paper aims to document operators’ situation awareness through the analysis of automated organizations’ feedback. The analysis of automated hospital pharmacies feedbacks helps to identify and control critical parameters influencing human machine interaction in order to enhance system’s performance and security. Our human machine system evaluation approach has been deployed in Macon hospital center’s pharmacy which is equipped with automated drug dispensing systems since 2015. Automation’s specifications are related to technical aspects, human-machine interaction, and human aspects. The evaluation of drug delivery automation performance in Macon hospital center has shown that the performance of the automated activity depends on the performance of the automated solution chosen, and also on the control of systemic factors. In fact, 80.95% of automation specification related to the chosen Sinteco’s automated solution is met. The performance of the chosen automated solution is involved in 28.38% of automation specifications performance in Macon hospital center. The remaining systemic parameters involved in automation specifications performance need to be controlled.

Keywords: life-critical systems, situation awareness, human-machine interaction, decision-making

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Authors: Abdelghani Boudiaf

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The profusion of studies relating to the concept of organizational learning shows the importance that has been given to this concept in the management sciences. A few years ago, companies leaned towards ISO 9001 certification; this requires the implementation of the quality management system (QMS). In order for this objective to be achieved, companies must have a set of skills, which pushes them to develop learning through continuous training. The results of empirical research have shown that implementation of the QMS in the company promotes the development of learning. It should also be noted that several types of learning are developed in this sense. Given the nature of skills development is normative in the context of the quality demarche, companies are obliged to qualify and improve the skills of their human resources. Continuous training is the keystone to develop the necessary learning. To carry out continuous training, companies need to be able to identify their real needs by developing training plans based on well-defined engineering. The training process goes obviously through several stages. Initially, training has a general aspect, that is to say, it focuses on topics and actions of a general nature. Subsequently, this is done in a more targeted and more precise way to accompany the evolution of the QMS and also to make the changes decided each time (change of working method, change of practices, change of objectives, change of mentality, etc.). To answer our problematic we opted for the method of qualitative research. It should be noted that the case study method crosses several data collection techniques to explain and understand a phenomenon. Three cases of companies were studied as part of this research work using different data collection techniques related to this method.

Keywords: changing mentalities, continuing training, organizational learning, quality management system, skills development

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Authors: Yizhi Zhang, Xiaozan Wang, Mingming Guo, Pengpeng Li

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Introduction: The purpose of this study is to examine the effectiveness of after-school football training in improving the physical fitness of primary school students, so as to provide corresponding suggestions for carrying out after-school football training in primary schools. Methods: A total of 72 students from the experimental primary school of Mouping district, Yantai city, Shandong province, participated in this experiment. The experiment was conducted for two semesters. During the experiment period, the experimental group conducted one-hour football training after school from Monday to Thursday afternoon every week, and two hours of football training on Saturday morning every week. The control group conducted sports teaching and extracurricular activities as usual without other intervention. Before and after the experiment, both the experimental group and the control group underwent physical fitness tests according to the physical fitness test standards of Chinese students, including lung capacity, 50-meter run, one-minute skipping rope, sitting forward flexor, and one-minute sit-ups. The test results were all converted to the 100-point system according to the scoring standards. Results: (1) Before the experiment, there was no significant difference between the experimental group and the control group in various physical fitness indicators (p > 0.05). (2) After the experiment, the lung capacity score (T = 3.108, p < 0.05), the 50-meter run score (T = 6.593, p < 0.05), the skipping score (T = 9.227, p < 0.05), the sitting forward flexor score (T = 3.742, p < 0.05), and the sit-up score (T = 5.210, p < 0.05) of the experimental group were significantly higher than that of the control group. Conclusion: This study shows that the physical fitness of primary school students can be improved by football training in their spare time. It is suggested to carry out after-school football training activities in primary schools so as to effectively improve the physical fitness of pupils.

Keywords: after-school football training, physical fitness, primary school students, school sports

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Authors: Ahmad Akrad, Rabia Sehab, Fadi Alyoussef

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Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a fault detection method is suggested using residual errors generated by the root mean square (RMS) of phase currents. The application of this method is based on an asymmetric nonlinear model of Induction Machine considering the winding fault of the three axes frame state space. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults.

Keywords: induction machine, asymmetric nonlinear model, fault diagnosis, inter-turn short-circuit fault, root mean square, current sensor fault, fault detection and isolation

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Authors: Thakur Pushpawati, Singh Vinita, Agrawal Sarita, Mohapatra Eli

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Polycystic ovary syndrome (PCOS) is a disease of endocrine and frequently encountered in women in their reproductive period, and it is characterized by clinical features of anovulation, clinical and biochemical features of hyperandrogenism, and PCOS morphology on ultrasonographic examination. In Indian scenario, only a few studies are available on the correlation of serum 25-dihydroxy vitamin D3 level and insulin level. The present study is a prospective case-control study and aims to estimate the concentration of serum 25-dihydroxy vitamin D3 and insulin resistance and determine the association of serum 25-dihydroxy vitamin D3 with insulin resistance in PCOS women of 18-40 years age group. In this study, the primary objective is to estimate the concentration of 25-dihydroxy vitamin D3, insulin, glycaemic status, calcium and phosphorus levels in 18-40 year age women with polycystic ovary syndrome and to compare these parameters with age and BMI matched healthy control of same age group women. The secondary objective is to determine the association between 25-dihydroxy vitamin D3 concentration and insulin resistance among PCOS cases in 18-40 years age group women. This study was carried on at outpatient Department of Obstetrics & Gynaecology, Aiims Raipur. It took one year from the date of approval. In case, 32 women were diagnosed (Diagnosed PCOS cases as per Rotterdoms criteria among women of 18-40 years of age), as control group 32 women of 18-40 years of age were diagnosed As a result, serum insulin level was elevated among PCOS women along with 25-dihydroxy vitamin D3 deficiency.Conclude up, PCOS is more common in the age group of 20-40 years. There is a strong correlation between vitamin D deficiency and insulin resistance among PCOS patients.

Keywords: vitamin D, insulin resistance, PCOS, reproductive age group

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Authors: Pedro Paulo Galindo Francisco, Eli Dhadad Junior

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This study addresses the Meese-Rogoff Puzzle by introducing the latest machine learning techniques as alternatives for predicting the exchange rates. Using RMSE as a comparison metric, Meese and Rogoff discovered that economic models are unable to outperform the random walk model as short-term exchange rate predictors. Decades after this study, no statistical prediction technique has proven effective in overcoming this obstacle; although there were positive results, they did not apply to all currencies and defined periods. Recent advancements in artificial intelligence technologies have paved the way for a new approach to exchange rate prediction. Leveraging this technology, we applied five machine learning techniques to attempt to overcome the Meese-Rogoff puzzle. We considered daily data for the real, yen, British pound, euro, and Chinese yuan against the US dollar over a time horizon from 2010 to 2023. Our results showed that none of the presented techniques were able to produce an RMSE lower than the Random Walk model. However, the performance of some models, particularly LSTM and N-BEATS were able to outperform the ARIMA model. The results also suggest that machine learning models have untapped potential and could represent an effective long-term possibility for overcoming the Meese-Rogoff puzzle.

Keywords: exchage rate, prediction, machine learning, deep learning

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Authors: O. Casasayas, M. Vigo, R. Navarro, P. Ragazzi, P. Alvarez, A. Perez-Bellmunt

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Introduction: The blood flow restriction training (BFR) is a method of muscle training that allows increasing the stress of muscle tissue to enhance the muscle cross-section and strength. This type of training has clear benefits in the rehabilitation field since it can improve muscle strength using low mechanical loads. The aim of this study is to know in which knee pathologies BFR has been used, what methodology was used and what were the obtained results. Study design: We performed a systematic literature search using strategies for the concepts of “blood flow restriction OR blood flow restriction training AND knee” in Medline. Articles were screened by authors and included if they used the blood flow restriction training in pathology of the knee. Results: The pathology more frequently treated by BFR was knee osteoarthritis and the variables most analyzed were strength and pain. The vascular occlusion used was 80% in the major part of studies. The groups of BFR obtained an increase of strength with less pain but not always the results are statistically significant. The evidence levels are poor in the high number of studies because in some cases there is not a control group or the evaluators were not blinded. Conclusion: The use of BFR is useful to improve muscle strength in knee pathology since it does not increase the pain, but more studies are needed to see (comprehend) if this type of treatment obtains better results than a conventional therapy. No studies have been found that compare the different occlusion effects in both the strength improvement and the pain reduction. Neither studies that analyse the effects of BFR on the muscle contractile parameters have been found.

Keywords: blood flow restriction training, knee, arthroscopy knee, physical therapy

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Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya

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Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.

Keywords: ANN, CNN, supervised learning, machine learning, deep learning

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Authors: Ambuj Kumar Gautam, V. Vasu

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This paper introduces a head movement based Human Machine Interface (HMI) that uses the right and left movements of head to control a robot motion. Here we present an approach for making an effective technique for real-time face orientation information system, to control a robot which can be efficiently used for Electrical Powered Wheelchair (EPW). Basically this project aims at application related to HMI. The system (machine) identifies the orientation of the face movement with respect to the pixel values of image in a certain areas. Initially we take an image and divide that whole image into three parts on the basis of its number of columns. On the basis of orientation of face, maximum pixel value of approximate same range of (R, G, and B value of a pixel) lie in one of divided parts of image. This information we transfer to the microcontroller through serial communication port and control the motion of robot like forward motion, left and right turn and stop in real time by using head movements.

Keywords: electrical powered wheelchair (EPW), human machine interface (HMI), robotics, microcontroller

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Authors: Recep Keşli, Cengiz Demir, Onur Türkyılmaz

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Objective: The aim of this study was to determine the prevalence of Mycoplasma hominis and Ureaplasma urealyticum as the causative agents in men with non-gonococcal urethtritis, and anti-bacterial resistance rates. Methods: The Study was carried out in the two Medical Microbiology Laboratories belonging to: Konya Education and Research Hospital and ANS Practice and Research Hospital, Afyon Kocatepe University, between January 2012 and December 2015. Urethral samples were obtained from patients by using a swab. Mycoplasma hominis and Ureaplasma urealyticum were detected by using Mycoplasma IST-2 kit (bio-Mérieux, Marcy l'Étoile, France). Neisseria gonorrhoea was excluded by Gram staining and culture methods. Results: Of all the one hundred and eighty-eight male patients with urethritis, forty M. hominis and forty two U. urealyticum were detected. Resistance rates of M. hominis strains against to doxycycline, ofloxacin, erythromycin, tetracycline, ciprofloxacin, azithromycin, clarithromycin, and pristinamycin were found as 5 %, 65 %, 25 %, 5 %, 80 %, 20 %, 20 %, 20 %, 5 %, respectively. Resistance rates of U. urealyticum strains against to doxycycline, ofloxacin, erythromycin, tetracycline, ciprofloxacin, azithromycin, clarithromycin, and pristinamycin were found as 4.7 %, 66.6 %, 23.8 %, 4.75 %, 81 %, 19 %, 19 %, 4.7 % respectively. No resistance was detected against to josamycin, for both the strains. Conclusions: It was concluded that; ciprofloxacin and ofloxacin had the weakest; josamycin, doxycycline, and tetracycline had the strongest in vitro anti-bacterial activity, for treatment of the NGU. So josamycin, doxycycline, and tetracycline should be preferred as the first choice of anti-bacterial agents, for treatment of the patients with non-gonococcal male urethritis.

Keywords: antimicrobial resistance, Mycoplasma hominis, non-gonococcal urethritis, Ureaplasma urealyticum

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Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

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MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

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Authors: Bert H. Jacobson, Taylor Monaghan, John Sellers

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Intense resistance-type activity generally elicits delayed onset muscle soreness (DOMS) in individuals unaccustomed to such action. DOMS is a combination of contractile tissue microtrauma, osmotic pressure changes, alteration calcium regulation, and inflammation. Elevated muscle-specific enzyme creatine kinase (CK) is a marker of striated muscle damage. Avian immunoglobulin (IgY) mediates inflammation and may thereby reduce post-exercise DOMS. Purpose: The aim of this study was to compare the effect of oral IgY and placebo (Pl) on CK, serum relevels, and perceived pain following induced DOMS. Methods: Healthy college-aged females (N=16) were randomly divided into an experimental group (IgY) and a control group (PL). CK serum levels were recorded followed by 14 days of supplementation of either IgY or Pl at the following doses: days 1-2 =4.5 g, days 3-5 =9.0 g, and days 6-14 =13.5 g. Following the 14 d, lower limb DOMS was induced using two methods of resistance training. After 48 hours, subjects reported for a second blood draw. Results: One-way ANOVA resulted in the IgY group posting significantly less (p < 0.05) serum CK than the PL group. Furthermore, the IgY group experienced significantly less post-test perceived soreness than the Pl group. Conclusion: IgY supplementation lessens muscle CK levels and perceived muscle soreness following exercise, possibly due to an anti-inflammatory effect. It was suggested that IgY may serve as a buffer for DOMS thereby allowing the participant to continue vigorous exercise without discomfort.

Keywords: muscle, soreness, damage, serum

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Authors: Suvimon Wajeetongratana, Sittichai Thammasane

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This research objective was to study the development training that affecting the work performance of Suan Sunandha Rajabhat University manpower. The sample of 200 manpower was used to collect data for the survey. The statistics for data analysis were frequency percentage, mean value, standard deviation and hypothesis testing using independent samples (t-test). The study indicated that the development training has the most affect to employees in the high level and the second was coaching by the senior follow by the orientation in case of changing jobs task or changing positions. Interms of manpower work performance have three performance areas are quality of the job is better than the original. Moreover the results of hypothesis testing found that the difference personal information including gender, age, education, income per month have difference effectiveness of attitudes and also found the develop training is correlated with the performance of employees in the same direction.

Keywords: development training, employees job satisfaction, work performance, Sunandha Rajabhat University

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Authors: Tony Ikponmwosa Obaseki

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The paper studied Colleges of education environments with specific insight at available technologies in college libraries with the objective of ascertaining the services rendered and the impact of information services on teacher trainings in the overall development and benefit of the educational ecosystem. Problems were situated and assumptions formulated made to guide the study proper. Twelve (12) Colleges of education environment from the six geopolitical zones in Nigeria were comparatively studied, using twelve (12) librarians and six hundred (600) randomly selected training teachers. Analysis and presentation of findings will be done using well stated scientific procedures.

Keywords: library, technologies, digital library, colleges of education, teacher training, education ecosystem

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: B. Sayaheen

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The translator’s competence is one of the topics that has received a great deal of research in the field of translation studies because such competencies are still debatable and not yet agreed upon. Besides, scholars tackle this topic from different points of view. Approaches to teaching these competencies have gone through some developments. This paper aims at investigating these developments, exploring the major turning points and shifts in the developments of teaching methods in translator training. The significance of these turning points and the external or internal causes will also be discussed. Based on the past and present status of teaching approaches in translator training, this paper tries to predict the future of these approaches. This paper is mainly concerned with developments of teaching approaches in the West since the 1980s to the present. The reason behind choosing this specific period is not because translator training started in the 1980s but because most criticism of the teacher-centered approach started at that time. The implications of this research stem from the fact that it identifies the turning points and the causes that led teachers to adopt student-centered approaches rather than teacher-centered approaches and then to incorporate technology and the Internet in translator training. These reasons were classified as external or internal reasons. Translation programs in the West and in other cultures can benefit from this study. Translation programs in the West can notice that teaching translation is geared toward incorporating more technologies. If these programs already use technology and the Internet to teach translation, they might benefit from the assumed future direction of teaching translation. On the other hand, some non-Western countries, and to be specific some professors, are still applying the teacher-centered approach. Moreover, these programs should include technology and the Internet in their teaching approaches to meet the drastic changes in the translation process, which seems to rely more on software and technologies to accomplish the translator’s tasks. Finally, translator training has borrowed many of its approaches from other disciplines, mainly language teaching. The teaching approaches in translator training have gone through some developments, from teacher-centered to student-centered and then toward the integration of technologies and the Internet. Both internal and external causes have played a crucial role in these developments. These borrowed approaches should be comprehensively evaluated in order to see if they achieve the goals of translator training. Such evaluation may lead us to come up with new teaching approaches developed specifically for translator training. While considering these methods and designing new approaches, we need to keep an eye on the future needs of the market.

Keywords: turning points, developments, translator training, market, The West

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Authors: Oleg Reva, Ilya Korotetskiy, Marina Lankina, Murat Kulmanov, Aleksandr Ilin

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Molecular docking approaches are widely used for design of new antibiotics and modeling of antibacterial activities of numerous ligands which bind specifically to active centers of indispensable enzymes and/or key signaling proteins of pathogens. Widespread drug resistance among pathogenic microorganisms calls for development of new antibiotics specifically targeting important metabolic and information pathways. A generally recognized problem is that almost all molecular targets have been identified already and it is getting more and more difficult to design innovative antibacterial compounds to combat the drug resistance. A promising way to overcome the drug resistance problem is an induction of reversion of drug resistance by supplementary medicines to improve the efficacy of the conventional antibiotics. In contrast to well established computer-based drug design, modeling of drug resistance reversion still is in its infancy. In this work, we proposed an approach to identification of compensatory genetic variants reducing the fitness cost associated with the acquisition of drug resistance by pathogenic bacteria. The approach was based on an analysis of the population genetic of Mycobacterium tuberculosis and on results of experimental modeling of the drug resistance reversion induced by a new anti-tuberculosis drug FS-1. The latter drug is an iodine-containing nanomolecular complex that passed clinical trials and was admitted as a new medicine against MDR-TB in Kazakhstan. Isolates of M. tuberculosis obtained on different stages of the clinical trials and also from laboratory animals infected with MDR-TB strain were characterized by antibiotic resistance, and their genomes were sequenced by the paired-end Illumina HiSeq 2000 technology. A steady increase in sensitivity to conventional anti-tuberculosis antibiotics in series of isolated treated with FS-1 was registered despite the fact that the canonical drug resistance mutations identified in the genomes of these isolates remained intact. It was hypothesized that the drug resistance phenotype in M. tuberculosis requires an adjustment of activities of many genes to compensate the fitness cost of the drug resistance mutations. FS-1 cased an aggravation of the fitness cost and removal of the drug-resistant variants of M. tuberculosis from the population. This process caused a significant increase in genetic heterogeneity of the Mtb population that was not observed in the positive and negative controls (infected laboratory animals left untreated and treated solely with the antibiotics). A large-scale search for linkage disequilibrium associations between the drug resistance mutations and genetic variants in other genomic loci allowed identification of target proteins, which could be influenced by supplementary drugs to increase the fitness cost of the drug resistance and deprive the drug-resistant bacterial variants of their competitiveness in the population. The approach will be used to improve the efficacy of FS-1 and also for computer-based design of new drugs to combat drug-resistant infections.

Keywords: complete genome sequencing, computational modeling, drug resistance reversion, Mycobacterium tuberculosis

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Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: Yujeong Shin, Seong Jin Cho, Jin Ho Kim

Abstract:

In the textile-weaving machine, the reed is the core component to separate thousands of strands of yarn and to produce the fabric in a continuous high-speed movement. In addition, the reed affects the quality of the fiber. Therefore, the wire forming analysis of the main raw materials of the reed needs to be considered. Roll-forming is a key technology among the manufacturing process of reed wire using textile machine. A simulation of roll-forming line in accordance with the reduction rate is performed using LS-DYNA. The upper roller, fixed roller and reed wire are modeled by finite element. The roller is set to be rigid body and the wire of SUS430 is set to be flexible body. We predict the variation of the cross-sectional shape of the wire depending on the reduction ratio.

Keywords: textile machine, reed, rolling, reduction ratio, wire

Procedia PDF Downloads 375

Authors: D. Leibman, D. Wolf, A. Gal-On

Abstract:

Viral diseases of tomato crops result in heavy yield losses and may even jeopardize the production of these crops. Classical tomato breeding for disease resistance against Tomato yellow leaf curl virus (TYLCV), leads to partial resistance associated with a number of recessive genes. To author’s best knowledge Pepino mosaic virus (PepMV) genetic resistance is not yet available. The generation of viral resistance by means of genetic engineering was reported and implemented for many crops, including tomato. Transgenic resistance against viruses is based, in most cases, on Post Transcriptional Gene Silencing (PTGS), an endogenous mechanism which destroys the virus genome. In this work, we developed immunity against PepMV and TYLCV in a tomato based on a PTGS mechanism. Tomato plants were transformed with a hairpin-construct-expressed transgene-derived double-strand-RNA (tr-dsRNA). In the case of PepMV, the binary construct harbored three consecutive fragments of the replicase gene from three different PepMV strains (Italian, Spanish and American), to provide resistance against a range of virus strains. In the case of TYLCV, the binary vector included three consecutive fragments of the IR, V2 and C2 viral genes constructed in a hairpin configuration. Selected transgenic lines (T0) showed a high accumulation of transgene siRNA of 21-24 bases, and T1 transgenic lines showed complete immunity to PepMV and TYLCV. Graft inoculation displayed immunity of the transgenic scion against PepMV and TYLCV. The study presents the engineering of resistance in tomato against two serious diseases, which will help in the production of high-quality tomato. However, unfortunately, these resistant plants have not been implemented due to public ignorance and opposition against breeding by genetic engineering.

Keywords: PepMV, PTGS, TYLCV, tr-dsRNA

Procedia PDF Downloads 133

Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

Abstract:

Minimizing the number of tardy jobs is an important factor to consider while making scheduling decisions. This is because on-time shipments are vital for lowering cost and increasing customers’ satisfaction. This paper addresses the single machine scheduling problem with the objective of minimizing the number of tardy jobs. The only known information is the lower and upper bounds for processing times, and deterministic job due dates. A dominance relation is established, and an algorithm is proposed. Several heuristics are generated from the proposed algorithm. Computational analysis indicates that the performance of one of the heuristics is very close to the optimal solution, i.e., on average, less than 1.5 % from the optimal solution.

Keywords: single machine scheduling, number of tardy jobs, heuristi, lower and upper bounds

Procedia PDF Downloads 555

Authors: Suwarno, D. Jongudomkarn

Abstract:

Family Health Assessment (FHA) is a key process to identify the family health needs, family health problems, and family health history. Assessing the family health is not only from the assessment tool but also from health care provider especially Nurse. Nurses’ have duties to assess the family as holistic view and they have to increase their capacities (knowledge, skills and experiences) in FHA. Thus, the continuing nursing education-training program on using the KKU FHA Tool was aimed to enhance the participant nurses’ capacities in (FHA) based on such tool. The aim of this study was to evaluate the KKU FHA Tool training program on PCU nurses’ capacity before and after training program in Primary Care Unit Bantul, Yogyakarta. The Quasi-Experiment with one group pre-, post-test design as a research design with convenient sampling technique and one group pre- post test formula for Nurses who work in Six PCU Bantul, Yogyakarta as much as fourteen respondents. The research processes were used training program with module, video and handbook KKU FHA Tool, KKU FHA tool form and capacities questionnaires. It was analyzed by descriptive data, Kolmogorov-Smirnov and Paired Sample t-test. The overall comparing analysis of paired sample t-test revealed that the mean values of pre-test were 3.35 with SD 0.417, post-test was 3.86 with SD 0.154 and post-test in later two weeks was 4.00 with SD 0.243. It was found that the p value of among the pre-test, the intermediate post-test and the post–test in later two weeks were 0.000. The p value of the intermediate post-test and post-test in later two weeks was 0.053. KKU FHA Tool training program in PCU Bantul Yogyakarta was enhanced the participant nurses’ capacities significantly. In conclusion, we are recommending KKU FHA Tool forms have to develop and implement with qualitative research as complementary data in PCU Bantul Yogyakarta by Focus Group Discussion.

Keywords: family health assessment, KKU FHA tool, training program, nurses capacities

Procedia PDF Downloads 378

Authors: N. Sateesh, C. S. P. Rao, K. Satyanarayana, C. Rajashekar

Abstract:

This paper proposes a development of a CAD/CAM system for complex profiles of various machine members using a synthetic curve i.e. B-spline. Conventional methods in designing and manufacturing of complex profiles are tedious and time consuming. Even programming those on a computer numerical control (CNC) machine can be a difficult job because of the complexity of the profiles. The system developed provides graphical and numerical representation B-spline profile for any given input. In this paper, the system is applicable to represent a cam profile with B-spline and attempt is made to improve the follower motion.

Keywords: plate-cams, cam profile, b-spline, computer numerical control (CNC), computer aided design and computer aided manufacturing (CAD/CAM), R-D-R-D (rise-dwell-return-dwell)

Procedia PDF Downloads 611

Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

Abstract:

In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

Procedia PDF Downloads 168