Search results for: unsupervised training

Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Angelina Tarabokija

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This study looks into how cognitive behavioral training (CBT) techniques affect collegiate track and field athletes' anxiety related to performance, with a focus on distance runners. The goal of the research is to discover whether consistent use of cognitive behavioral therapy (CBT) methods, such as progressive muscle relaxation, yoga (Y-CBT), visualization, relaxed breathing, and meditation, can reduce performance anxiety and improve sports performance. Six runners from the Rider Track & Field team, aged eighteen to twenty-three, participated in the quantitative research design used in the technique. Prior to employing CBT techniques every day for two weeks, including before competitions or on race day, participants conducted baseline assessments using the Sport Anxiety Scale-2 (SAS-2). The SAS-2 was used in post-competition evaluations to track alterations in performance anxiety. The findings show that participants' total trait anxiety levels significantly decreased after utilizing CBT techniques for one week. However, after two weeks, a few participants' anxiety levels slightly increased, pointing to the need for more research and regular practice. The study indicates that CBT approaches can effectively reduce performance anxiety and increase athletic performance in collegiate track and field athletes, despite constraints related to participant motivation and potential confounding variables. Future areas for research could entail examining the precise impacts of worry, interruption of attention, and bodily anxiety on performance, as well as adding more controls. Overall, by providing insights into evidence-based strategies to maximize mental states and athletic performance in collegiate athletes, this study advances the area of sports psychology.

Keywords: cognitive behavioral training, performance, athletes, anxiety, well-being, SAS-2, Sport, trait anxiety, somatic anxiety

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Authors: Mostafa Sarabzadeh, Masoumeh Helalizadeh, Seyyed Mahmoud Hejazi

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Multiple Sclerosis is considered as diseases related to central nerve system, the chronic and progressive disease impress on sensory and motor function of people. Due to equilibrium problems in this patients that related to disorder of nerve conduction transmission from central nerve system to organs and the nature of elastic bands that can make changes in neuromuscular junctions and momentary actions, the aim of this research is evaluate elastic training effect by reactionary ropes on nerve conduction velocity (in lower and upper limb) and functional balance in female patients with Multiple Sclerosis. The study was a semi-experimental study that was performed based on pre and post-test method, The statistical community consisted of 16 women with MS in the age mean 25-40yrs, at low and intermediate levels of disease EDSS 1-4 (Expanded Disability Status Scale) that were divided randomly into elastic and control groups, so the training program of experimental group lasted six weeks, 3 sessions per week of elastic exercises with reactionary ropes. Electroneurography parameters (nerve conduction velocity- latency) of Upper and lower nerves (Median, Tibial, Sural, Peroneal) along with balance were investigated respectively by the Electroneurography system (ENG) and Timed up and go (TUG) functional test two times in before and after the training period. After that, To analyze the data were used of Dependent and Independent T-test (with sig level p<0.05). The results showed significant increase in nerve conduction velocity of Sural (p=0.001), Peroneal (p=0.01), Median (p=0.03) except Tibial and also development Latency Time of Tibial (p= 0), Peroneal (p=0), Median (p=0) except Sural. The TUG test showed significant decreases in execution time too (p=0.001). Generally, based on what the obtained data can indicate, modern training with elastic bands can contribute to enhanced nerve conduction velocity and balance in neurosis patients (MS) so lead to reduce problems, promotion of mobility and finally more life expectancy in these patients.

Keywords: balance, elastic bands, multiple sclerosis, nerve conduction, velocity

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Authors: Lucy Horrobin, Rebecca Fores

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Background: Muay Thai is an increasingly popular combat sport worldwide. Further academic research in the sport will contribute to its professional development. This research sought to produce normative data in relation to the physical and physiological characteristics of professional Muay Thai boxers, as, currently no such data exists. The ultimate aim being to inform appropriate training programs and to facilitate coaching. Methods: N = 9 professional, adult, male Muay Thai boxers were assessed for the following anthropometric, physical and physiological characteristics, using validated methods of assessment: body fat, hamstring flexibility, maximal dynamic upper body strength, lower limb peak power, upper body muscular endurance and aerobic capacity. Raw data scores were analysed for mean, range and SD and where applicable were expressed relative to body mass (BM). Results: Results showed similar characteristics to those found in other combat sports. Low percentages of body fat (mean±SD) 8.54 ± 1.16 allow for optimal power to weight ratios. Highly developed aerobic capacity (mean ±SD) 61.56 ± 5.13 ml.min.kg facilitate recovery and power maintenance throughout bouts. Lower limb peak power output values of (mean ± SD) 12.60 ± 2.09 W/kg indicate that Muay Thai boxers are amongst the most powerful of combat sport athletes. However, maximal dynamic upper body strength scores of (mean±SD) 1.14 kg/kg ± 0.18 were in only the 60th percentile of normative data for the general population and muscular endurance scores (mean±SD) 31.55 ± 11.95 and flexibility scores (mean±SD) 19.55 ± 11.89 cm expressed wide standard deviation. These results might suggest that these characteristics are insignificant in Muay Thai or under-developed, perhaps due to deficient training programs. Implications: This research provides the first normative data of physical and physiological characteristics of Muay Thai boxers. The findings of this study would aid trainers and coaches when designing effective evidence-based training programs. Furthermore, it provides a foundation for further research relating to physiology in Muay Thai. Areas of further study could be determining the physiological demands of a full rules bout and the effects of evidence-based training programs on performance.

Keywords: fitness testing, Muay Thai, physiology, strength and conditioning

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Authors: Zulkiflee Abd Latif, Sitinor Atikah Nordin, Alawi Sulaiman

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Different tree species possess different and various benefits. Arenga Pinnata tree species own several potential uses that is valuable for the economy and the country. Mapping vegetation using remote sensing technique involves various process, techniques and consideration. Using satellite imagery, this method enables the access of inaccessible area and with the availability of near infra-red band; it is useful in vegetation analysis, especially in identifying tree species. Pixel-based and object-based classification technique is used as a method in this study. Pixel-based classification technique used in this study divided into unsupervised and supervised classification. Object based classification technique becomes more popular another alternative method in classification process. Using spectral, texture, color and other information, to classify the target make object-based classification is a promising technique for classification. Classification of Arenga Pinnata trees is overlaid with elevation, slope and aspect, soil and river data and several other data to give information regarding the tree character and living environment. This paper will present the utilization of remote sensing technique in order to map Arenga Pinnata tree species

Keywords: Arenga Pinnata, pixel-based classification, object-based classification, remote sensing

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

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Authors: Fuad M. Alkoot

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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

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Authors: Jeff A. Tysinger, Dawn P. Tysinger

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The aim of this paper is to theoretically apply Bowen’s understanding of triangulation and triads to school psychology intern supervision so that it can assist in the conceptualization of the dynamics of intern supervision and provide some key methods to address common issues. The school psychology internship is the capstone experience for the school psychologist in training. It involves three key participants whose relationships will determine the success of the internship.  To understand the potential effect, Bowen’s family systems theory can be applied to the supervision relationship. He describes a way to resolve stress between two people by triangulating or binging in a third person. He applies this to a nuclear family, but school psychology intern supervision requires the marriage of an intern, field supervisor, and university supervisor; thus, setting all up for possible triangulation. The consequences of triangulation can apply to standards and requirements, direct supervision, and intern evaluation. Strategies from family systems theory to decrease the negative impact of supervision triangulation.

Keywords: family systems theory, intern supervision, school psychology training, triangulation

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Authors: Bashiru Olayinka Adisa, Najeem Lateef

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The integrated knowledge in the application of mechanical engineering, microprocessor and electronic sensor technologies is becoming the basic skill of a modern engineer in machinery based processes. To meet this objective, we have developed a cross-disciplinary industrial training to teach essential hard technical and soft project skills to the mechanical engineering students in mid-curriculum. Ten groups of students were selected to participate in a 150 hour program. The students were required to design and build a robot with ability to follow tracks and pick/place target blocks in specific locations. The students were trained to integrate the knowledge of computer aid design, electronics, sensor theories and motor technology to fabricate a workable robot as a major outcome of this course. On completion of the project, students competed for top robot honors by demonstrating their robots' movements and performance in pick/place to a panel of judges.

Keywords: electronics, sensor theories and motor, robot, technology

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Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

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In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

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Authors: Nasir Mustafa

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One of the prerequisites required for an efficient diagnosis in a medical practice is to have a strong command of both functional and clinical anatomy. In this study, we introduce a new collaborative approach to the effective teaching of the knee and hip joints. In the present teaching model, anatomists, orthopedists and physical therapists present the anatomy of the hip and knee joints in small groups. Courses for the hip and knee joints were scheduled during the early stages of the medical curriculum. Students of nursing and physical therapy were grouped together to sensitize to the importance of a collaborative effort. The study results clearly demonstrate that nursing students and physical therapy students appreciated this teaching approach. The collaborative approach further proved to be a suitable method to teach both functional and clinical anatomy of the hip and knee joints. Aside from this training, a collaborative approach between medical students and physical therapy students was also successful for a healthcare organization.

Keywords: hip and knee joint anatomy, collaborative, Anatomy teaching, Nursing students, Physiotherapy students

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Authors: Sehrish Khan

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The present study investigated the attitude of university students towards semester system and teachers with a specific objective of finding problems faced by students in semester system. 10 focus group discussions were conducted among students in five Universities of Hazara Division of KPK regarding their knowledge and attitudes about semester system and problems they faced due to this system and teacher’s attitude. The key findings were the problems like favoritism, gender biased ness, racial biased ness, biased ness in marking, relative marking, harassment, using students for personal tasks and authoritarian attitude from teachers’ side and the heavy tasks in less time which are causing stress among students. It was recommended that proper training and monitoring system should be maintained for evaluation of teachers to minimize the corruption in this sacred profession and maximize the optimal functioning. The information gathered in this research can be used to develop training modules for University teachers.

Keywords: university teachers, favoritism, biasedness, harassment

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Authors: Hana Aljumayi, Mohammed Issa

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The aim of this study was to investigate the effect of the training program for professional athletes at the Saudi Archery Federation on the electrical activity of the muscles involved in pulling the bowstring, maximum muscle strength (MVC) and to identify the relationship between the electrical activity of these muscles and accuracy in shooting among female archers. The researcher used a descriptive approach that was suitable for the nature of the study, and a sample of nine female archers was selected using purposive sampling. An EMG device was used to measure signal amplitude, signal frequency, spectral energy signal, and MVC. The results showed statistically significant differences in signal amplitude among muscles, with F(8,1)=5.91 and a significance level of 0.02. There were also statistically significant differences between muscles in terms of signal frequency, with F(8,1)=8.23 and a significance level of 0.02. Bonferroni test results indicated statistically significant differences between measurements at a significance level of 0.05, with anterior measurements showing an average difference of 16.4 compared to other measurements. Furthermore, there was a significant negative correlation between signal amplitude in the calf muscle and accuracy in shooting (r=-0.78) at a significance level of 0.02. There was also a significant positive correlation between signal frequency in the calf muscle and accuracy in shooting (r=0.72) at a significance level of 0.04. In conclusion, it appears that the training program for archery athletes focused more on skill development than physical aspects such as muscle activity and strength development. However, it did have a statistically significant effect on signal amplitude but not on signal frequency or MVC development in muscles involved in pulling the bowstring.

Keywords: electrical activity of muscles, archery sport, shooting accuracy, muscles

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Authors: H. M. Haytham, E. A. Azza, E.S. Mohamed, E. G. Nesreen

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Thoracotomy is a great surgery that has serious pulmonary complications, so purpose of this study was to determine the response of diaphragmatic excursion to inspiratory muscle trainer post thoracotomy. Thirty patients of both sexes (16 men and 14 women) with age ranged from 20 to 40 years old had done thoracotomy participated in this study. The practical work was done in cardiothoracic department, Kasr-El-Aini hospital at faculty of medicine for individuals 3 days Post operatively. Patients were assigned into two groups: group A (study group) included 15 patients (8 men and 7 women) who received inspiratory muscle training by using inspiratory muscle trainer for 20 minutes and routine chest physiotherapy (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Group B (control group) included 15 patients (8 men and 7 women) who received the routine chest physiotherapy only (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Ultrasonography was used to evaluate the changes in diaphragmatic excursion before and after training program. Statistical analysis revealed a significant increase in diaphragmatic excursion in the study group (59.52%) more than control group (18.66%) after using inspiratory muscle trainer post operatively in patients post thoracotomy. It was concluded that the inspiratory muscle training device increases diaphragmatic excursion in patients post thoracotomy through improving inspiratory muscle strength and improving mechanics of breathing and using of inspiratory muscle trainer as a method of physical therapy rehabilitation to reduce post-operative pulmonary complications post thoracotomy.

Keywords: diaphragmatic excursion, inspiratory muscle trainer, ultrasonography, thoracotomy

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Authors: Anupama Sekhar, Preeti Saryan, Vinita Gowda

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Plants, due to their sedentary lifestyle, have evolved mechanisms to synthesize a huge diversity of complex, specialized chemical metabolites, a majority of them being volatile organic compounds (VOCs). These VOCs are heavily involved in their biotic and abiotic interactions. Since chemical composition could be under the same selection processes as other morphological characters, we test if VOCs can be used to taxonomically distinguish species in the well-studied, fragrant ginger genus -Hedychium (Zingiberaceae). We propose that variations in the volatile profiles are suggestive of adaptation to divergent environments, and their presence could be explained by either phylogenetic conservatism or ecological factors. In this study, we investigate the volatile chemistry within Hedychium, which is endemic to Asian palaeotropics. We used an unsupervised clustering approach which clearly distinguished most taxa, and we used ancestral state reconstruction to estimate phylogenetic signals and chemical trait evolution in the genus. We propose that taxonomically, the chemical composition could aid in species identification, especially in species complexes where taxa are not morphologically distinguishable, and extensive, targeted chemical libraries will help in this effort.

Keywords: chemotaxonomy, dynamic headspace sampling, floral fragrance, floral volatile evolution, gingers, Hedychium

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Authors: A. Alrasheed, I. Connerton

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Daily provision of high quality food and hygiene to patients is a challenging goal of the healthcare. In Saudi Arabia, matters related to food safety and hygiene are regulated by the Ministry of Health (MOH) and the Saudi Food and Drugs Authority (SFDA). The purpose of this research is to discuss the food safety management inconsistencies and flaws, in particular the ones related to Hazard Analysis and Critical Control Points (HACCP) in Riyadh’s MOH hospitals. As required by law, written HACCP regulations must be implemented, and food handlers need to receive the training accordingly. However, in Saudi hospitals, this is not a requirement, and the food handlers do not need to hold training certificates in food safety or HACCP. Nowadays, the matter of food safety and hygiene have become increasingly important since the decision makers want to align these regulations with the majority of the world and to implement HACCP fully and for this purpose, the SFDA was established. 

Keywords: food safety, patients, hospitals, HACCP, Saudi Arabia

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Bennani Zoubir Nada, El Hiri Abderrazak, El Hajri Aimad

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In context of economic and health crisis, sustainable entrepreneurship has become one of the best solutions to economic recovery. This study is about the third program of the Moroccan national human development initiative in her third phase which began in 2019 and continuous until 2023, and which deals with income improvement and social inclusion of young people, under the high patronage of his majesty the king of Morocco. What is the approach of this program and how entrepreneurship training of young people can be a pillar to generate income and create jobs? Starting on the effectuation theory, we adopted an exploratory qualitative approach through semi-structured interviews with national human development initiative stakeholders in the area of Meknes-Morocco, which allowed us the state of progress of this program. We carried out a survey based on a grid of questions to collect information that we processed using NVIVO software. The most relevant results are that people eligible are jobless young people, who are between 18 and 35 years old, who reside in Meknes and surroundings and who have a project idea. They are trained by experts in entrepreneurship and management through targeted and diversified courses. To ensure the sustainability of projects, the project organisers have provided measures to ensure the sustainability of the companies through continuous monitoring and evaluation as well as support during all phases from the project idea to the realisation and progress.

Keywords: sustainable entrepreneurship, training, social inclusion, national human development initiative in Morocco (INDH), youth entrepreneurship, the effectuation theory

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Authors: Martha Salinas, Valkyria Bernal

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Creativity is a possible response to the profound social, economic, and global changes society is living and education is the source to develop this kind of capacity. However, institutional pressures often prevent teachers from engaging in creative teaching practices and make innovation not the main curricular focus when building learning scenarios and experiences. This study proposes and validates the use of a prototype of Educative Video – Capsules from the perspective of teacher training, presenting the different stages of design, the content plan, as well as the influences of its components and characteristics from the perspective of creativity. The paper presents literature findings of the factors that influence the innovative behavior of teachers, the beliefs of teachers about creativity and its nature, as well as the creative pedagogies that have generated better results. The results show that the disposition of teachers towards creative pedagogies improves significantly with the use of a tool that is based on the principles of microlearning and is developed in a non-academic, autonomous, and non-imposed family environment as traditional teacher training processes usually occur.

Keywords: educational innovation, resistance to innovation, creativity, creative pedagogy

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Authors: Sara Nasiri Semnani, Alireza Ramzani

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Background and Aims: Sodium bicarbonate is a supplementation that used to reduce fatigue and increase power output in short-term training. On the other hand, the Ischemic Reperfusion Preconditioning (IRPC) is an appropriate stimulus to increase the submaximal contractile response. Materials and methods: 9 female student-athletes in double-blind randomized crossover design were three mode, sodium bicarbonate + IRPC, sodium bicarbonate and placebo+ IRPC. Participants moved forward single arm dumbbell hand with a weight of 2 kg can be carried out most frequently. Results: The results showed that plasma lactate concentration and records of sodium bicarbonate + IRPC and sodium bicarbonate conditions were significantly different compared to placebo + IRPC (Respectively p=0.001, p=0/02). Conclusion: According to the research findings, bicarbonate supplementation in IRPC training condition increased force and delay fatigue in submaximal dynamic contraction.

Keywords: ischemic reperfusion, preconditioning, sodium bicarbonate, submaximal dynamic force

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: Nana Weng

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Localization in the aspect of human resource means more diversity and more opportunities. The main purpose of this article is to identify the perception of local employees and intermediate managers (non-Japanese) and figure out exploratory factors which have been contributing and blocking the level of localization in the aspect of human resource management by using EFA (Exploratory Factors Analysis). Questionnaires will be designed for local employees and managers to inquire about the perceptions of regulations and implementation regarding recruitment, training and development, promotion and rewarding. The study finds that Japanese firms have worked well in the process of localization, especially in hiring and training local staffs in Taiwan. The significance of this study lies in paying more attention to the perception of local employees and intermediate managers regarding localization rather than interviews results from Japanese expatriates or top HR managers who are in charging of localization policy-making.

Keywords: Japanese firms in Taiwan, localization of human resources, exploratory factors analysis, local employees and intermediate managers

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Authors: Philippe Judlin, Olivier Morel

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Background: In France, the resident curriculum (RC) in Obstetrics and Gynecology (OBGYN) takes five years. In the course of the last 15 years, this RC has undergone major changes, characterized mainly by successive reductions of work hours. The program used to comprise long and frequent shifts, huge workload, poor supervision and erratic theoretical teaching. A decade ago, the French Ministry of Heath recommended a limitation of shift duration up to 24 hours and a minimum of 11 hours off duty between shifts. Last year, in order to comply with European Union directives, new recommendations have further limited residents’ work hours to 48 hours per week. Methods: Assessment of the residency program adjustments recently made to accommodate the recommendations while improving the training quality in resorting to new methods. Results: The challenge facing program directors was to provide an all-encompassing curriculum to OBGYN residents despite fewer work hours. Program has been dramatically redesigned, and several measures have been put in place: -The resident rotation system has been redesigned. Residents used to make 6-month rotations between 10-12 Departments of OBGYN or Surgery. Fewer Departments, those providing the best teaching, have been kept in the new RC. -Extensive inhouse supervision has been implemented for all kinds of clinical activities. Effectual supervision of residents has proved to be an effective tool to improve the quality of training. -The tutorship system, with academic members individually overseeing residents during their curriculum, has been perfected. It allows a better follow-up of residents’ progresses during the 5-year program. -The set up of an extensive program of lectures encompassing all maters in Obstetrics & Gynecology. These mandatory lectures are available online in a dedicated website. Therefore, face-to-face lectures have been limited in order to fit in the 48-hour limit. -The use of simulation has been significantly increased in obstetrics, materno-fetal medicine and surgery (stressing especially laparoscopic training). -Residents’ feedback has been taken into account in the setup of the new RC. Conclusion: This extensive overhaul of the Obstetrics and Gynecology RC has been in place since last year only. Nevertheless, the new program seems to adequately take into account the new recommendations while providing a better and more consistent teaching to the OBGYN residents.

Keywords: education, laparoscopy, residency, simulation

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Authors: Tanimola Kazeem Abiodun

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In Nigeria, both formal education and distance learning opportunities are used in teacher training. Practical courses aim to improve the skills of teacher candidates in a school environment. Teacher candidates attend kindergarten classes under the supervision of a teacher. In this context, the guiding skills of teachers gain importance in terms of shaping candidates’ perceptions about teaching profession. In this study, the teachers’ perceptions related to the guiding skills within the practical courses were determined. Also, the perceptions and applications related to guiding skills were compared. A Likert scale questionnaire and an open-ended question were used to determine perceptions and applications. 120 questionnaires were taken into consideration and analyses of data were performed by using percentage distribution and QSR Nvivo 8 program. In this study, statements related to teachers’ perceptions about the guiding skills were asked and it is determined that almost all the teachers agreed about the importance of these statements. On the other hand, how these guidance skills are applied by teachers is also queried with an open-ended question. Finally, thoughts and applications related to guidance skills were compared to each other. Based on this comparison, it is seen that there are some differences between the thoughts and applications especially related with time management, planning, feedbacks, curriculum, workload, rules and guidance. It can be said that some guidance skills cannot be controlled only by teachers. For example, candidates’ motivation, attention, population and educational environment are also determinative factors for effective guidance. In summary, it is necessary to have prior conditions for teachers to apply these idealized guidance skills for training more successful candidates to pre-school education era. At this point, organization of practical courses by the faculties gains importance and in this context it is crucial for faculties to revise their applications based on more detailed researches.

Keywords: teacher training, guiding skills, education, practical courses

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Authors: S. M. Ishtiaque, V. K. Yadav, S. D. Joshi, J. K. Chatterjee

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The DIAMETRIC FAULTS system has been developed that captures a bi-directional image of yarn continuously in sequentially manner and provides the detailed classification of faults. A novel mathematical framework developed on the acquired bi-directional images forms the basis of fault classification in four broad categories, namely, Thick1, Thick2, Thin and Normal Yarn. A discretised version of Radon transformation has been used to convert the bi-directional images into one-dimensional signals. Images were divided into training and test sample sets. Karhunen–Loève Transformation (KLT) basis is computed for the signals from the images in training set for each fault class taking top six highest energy eigen vectors. The fault class of the test image is identified by taking the Euclidean distance of its signal from its projection on the KLT basis for each sample realization and fault class in the training set. Euclidean distance applied using various techniques is used for classifying an unknown fault class. An accuracy of about 90% is achieved in detecting the correct fault class using the various techniques. The four broad fault classes were further sub classified in four sub groups based on the user set boundary limits for fault length and fault volume. The fault cross-sectional area and the fault length defines the total volume of fault. A distinct distribution of faults is found in terms of their volume and physical dimensions which can be used for monitoring the yarn faults. It has been shown from the configurational based characterization and classification that the spun yarn faults arising out of mass variation, exhibit distinct characteristics in terms of their contours, sizes and shapes apart from their frequency of occurrences.

Keywords: Euclidean distance, fault classification, KLT, Radon Transform

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Authors: Meaghan Bowman

Abstract:

Soldiers are taught about the importance of effective communication with repetition of the phrase, “Communication is key.” They receive training in preparing for, and carrying out, interactions between foreign and domestic leaders to gain crucial information about a mission. These interactions are known as Key Leader Engagements (KLEs). For the training of KLEs, doctrine mandates the skills needed to conduct these “engagements” such as how to: behave appropriately, identify key leaders, and employ effective strategies. Army officers in training learn how to confront leaders, what information to gain, and how to ask questions respectfully. Unfortunately, soldiers rarely learn how to formulate questions optimally. Since less complex questions are easier to understand, we hypothesize that semantic complexity affects content understanding, and that age and education levels may have an effect on one’s ability to form paraphrases and judge their quality. In this study, we looked at paraphrases of queries as well as judgments of both the paraphrases’ naturalness and their semantic similarity to the query. Queries were divided into three complexity categories based on the number of relations (the first number) and the number of knowledge graph edges (the second number). Two crowd-sourced tasks were completed by Amazon volunteer participants, also known as turkers, to answer the research questions: (i) Are more complex queries harder to paraphrase and judge and (ii) Do age and education level affect the ability to understand complex queries. We ran statistical tests as follows: MANOVA for query understanding and two-way ANOVA to understand the relationship between query complexity and education and age. A probe of the number of given-level queries selected for paraphrasing by crowd-sourced workers in seven age ranges yielded promising results. We found significant evidence that age plays a role and marginally significant evidence that education level plays a role. These preliminary tests, with output p-values of 0.0002 and 0.068, respectively, suggest the importance of content understanding in a communication skill set. This basic ability to communicate, which may differ by age and education, permits reproduction and quality assessment and is crucial in training soldiers for effective participation in KLEs.

Keywords: engagement, key leader, paraphrasing, query complexity, understanding

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

Abstract:

Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

Keywords: clustering, unsupervised learning, pattern recognition, categorical datasets, knowledge discovery, k-means

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Authors: Kathleen L. Seifert

Abstract:

Students with special needs are expected to achieve the same academic standards as their general education peers, yet many students with special needs are pulled-out of general content instruction. Because of this, many students with special needs are denied content knowledge from a content expert and instead receive content instruction in a more restrictive setting. Collaborative teaching, where a general education and special education teacher work alongside each other in the same classroom, has become increasingly popular as a means to meet the diverse needs of students in America’s public schools. The idea behind co-teaching is noble; to ensure students with special needs receive content area instruction from a content expert while also receiving the necessary supports to be successful. However, in spite of this noble effort, the effects of co-teaching are not always positive. The reasons why have produced several hypotheses, one of which has to do with lack of proper training and implementation of effective evidence-based co-teaching practices. In order to examine the effects of co-teacher training, eleven teaching pairs from a small mid-western school district in the United States participated in a study. The purpose of the study was to examine the effects of co-teacher training on middle and high school student achievement in Math and Language Arts. A local university instructor provided teachers with training in co-teaching via a three-day workshop. In addition, co-teaching pairs were given the opportunity for direct observation and feedback using the Co-teaching Core Competencies Observation Checklist throughout the academic year. Data are in the process of being collected on both the students enrolled in the co-taught classes as well as on the teachers themselves. Student data compared achievement on standardized assessments and classroom performance across three domains: 1. General education students compared to students with special needs in co-taught classrooms, 2. Students with special needs in classrooms with and without co-teaching, 3. Students in classrooms where teachers were given observation and feedback compared to teachers who refused the observation and feedback. Teacher data compared the perceptions of the co-teaching initiative between teacher pairs who received direct observation and feedback from those who did not. The findings from the study will be shared with the school district and used for program improvement.

Keywords: collabortive teaching, collaboration, co-teaching, professional development

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Authors: Daniel M. Wolff, Patricia Gray, Rafael de la Parra Venegas

Abstract:

An unsupervised machine listening system is constructed and applied to a dataset of 17,195 30-second marine hydrophone recordings. The system is then heuristically supplemented with anecdotal listening, contextual recording information, and supervised learning techniques to reduce the number of false positives. Features for classification are assembled by extracting the following data from each of the audio files: the spectral centroid, root-mean-squared values for each frequency band of a 10-octave filter bank, and mel-frequency cepstral coefficients in 5-second frames. In this way both time- and frequency-domain information are contained in the features to be passed to a clustering algorithm. Classification is performed using the k-means algorithm and then a k-nearest neighbors search. Different values of k are experimented with, in addition to different combinations of the available feature sets. Hypothesized class labels are 'primarily anthrophony' and 'primarily biophony', where the best class result conforming to the former label has 104 members after heuristic pruning. This demonstrates how a large audio dataset has been made more tractable with machine learning techniques, forming the foundation of a framework designed to acoustically monitor and gauge biological and anthropogenic activity in a marine environment.

Keywords: anthrophony, hydrophone, k-means, machine learning

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Authors: Dzhavidan Zeinalov, Bugra Sen, Firangiz Aslanova

Abstract:

Most text-to-speech models cannot operate well in low-resource languages and require a great amount of high-quality training data to be considered good enough. Yet, with the improvements made in ASR systems, it is now much easier than ever to collect data for the design of custom text-to-speech models. In this work, our work on using the ASR model to collect data to build a viable text-to-speech system for one of the leading financial institutions of Azerbaijan will be outlined. NVIDIA’s implementation of the Tacotron 2 model was utilized along with the HiFiGAN vocoder. As for the training, the model was first trained with high-quality audio data collected from the Internet, then fine-tuned on the bank’s single speaker call center data. The results were then evaluated by 50 different listeners and got a mean opinion score of 4.17, displaying that our method is indeed viable. With this, we have successfully designed the first text-to-speech model in Azerbaijani and publicly shared 12 hours of audiobook data for everyone to use.

Keywords: Azerbaijani language, HiFiGAN, Tacotron 2, text-to-speech, transfer learning, whisper

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