Search results for: distance training

Authors: Nasibullina A., Leonov D.

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The ultrasonography method is actively used for the early diagnosis of various le-sions in the human body, including the mammary gland. The incidence of breast cancer has increased by more than 20%, and mortality by 14% since 2008. The correctness of the diagnosis often directly depends on the qualifications and expe-rience of a diagnostic medical sonographer. That is why special attention should be paid to the practical training of future specialists. Anatomical phantoms are ex-cellent teaching tools because they accurately imitate the characteristics of real hu-man tissues and organs. The purpose of this work is to create a breast phantom for practicing ultrasound diagnostic skills in grayscale and elastography imaging, as well as ultrasound-guided biopsy sampling. We used silicone-like compounds ranging from 3 to 17 on the Shore scale hardness units to simulate soft tissue and lesions. Impurities with experimentally selected concentrations were added to give the phantom the necessary attenuation and reflection parameters. We used 3D modeling programs and 3D printing with PLA plastic to create the casting mold. We developed a breast phantom with inclusions of varying shape, elasticity and echogenicity. After testing the created phantom in B-mode and elastography mode, we performed a survey asking 19 participants how realistic the sonograms of the phantom were. The results showed that the closest to real was the model of the cyst with 9.5 on the 0-10 similarity scale. Thus, the developed breast phantom can be used for ultrasonography, elastography, and ultrasound-guided biopsy training.

Keywords: breast ultrasound, mammary gland, mammography, training phantom, tissue-mimicking materials

Procedia PDF Downloads 88

Authors: Donna-Marie Phyllis Lanton

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Sarcopenia is a well-known geriatric syndrome characterized by the progressive and generalized loss of muscle quantity or quality. The incidence of sarcopenia increases with age and is associated with adverse outcomes such as the increased risk of falls, cognitive impairment, loss of independence, diminished quality of life, increased health costs, need for care in a skilled nursing facility, and increased mortality. Physical activity, including resistance training, is the most prevalent recommendation for treating and preventing sarcopenia. Residents (N = 23) of a skilled nursing facility in East Orlando, Florida, participated in a 90-day strength training program designed using the PARIHS framework to improve measures of muscle mass, muscle strength, physical performance, and quality of life. Residents engaged in both resistance and balance exercises for 1 hour two times a week. Baseline data were collected and compared to data at Days 30, 60, and 90. T tests indicated significant gains on all measures from baseline to 90 days: muscle mass increased by 1.2 (t[22] = 2.85, p = .009), grip strength increased by 4.02 (t[22] = 8.15, p < .001), balance increased by 2.13 (t[22] = 18.64, p < .001), gait speed increased by 1.83 (t[22] = 17.84, p < .001), chair speed increased 1.87 (t[22] = 16.36, p < .001), and quality of life score increased by 17.5 (t[22] = 19.26, p < .001). For residents with sarcopenia in skilled nursing facilities, a 90-day strength training program with resistance and balance exercises may provide an option for decreasing the incidence of sarcopenia among that population

Keywords: muscle mass, muscle strength, older adults, PARIHS framework

Procedia PDF Downloads 86

Authors: Sallama Resen, Celal Öztürk

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Distance estimation between tow nodes has wide scope of surveillance and tracking applications. This paper suggests a Bluetooth Low Energy (BLE) technology as a media for transceiver and receiver signal in small indoor areas. As an example, BLE communication technologies used in child safety domains. Local network is designed to detect child position in indoor school area consisting Mobile Beacons (MB), Access Points (AP) and Smart Phones (SP) where MBs stuck in children’s shoes as wearable sensors. This paper presents a technique that can detect mobile beacons’ position and help finding children’s location within dynamic environment. By means of bluetooth beacons that are attached to child’s shoes, the distance between the MB and teachers SP is estimated with an accuracy of less than one meter. From the simulation results, it is shown that high accuracy of position coordinates are achieved for multi-mobile beacons in different environments.

Keywords: bluetooth low energy, child safety, mobile beacons, received signal strength

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Authors: Jui-Chen Huang

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This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

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Authors: Ching-Ting Hsu, Wei-Hua Ho, Yi-Chun Chang

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Video object tracking is one of the popular research topics in computer graphics area. The trajectory can be applied in security, traffic control, even the sports training. The trajectory for sports training can be utilized to analyze the athlete’s performance without traditional sensors. There are many relevant works which utilize mean shift algorithm with background subtraction. This kind of the schemes should select a kernel function which may affect the accuracy and performance. In this paper, we consider the motion information in the pre-coded bitstream. The proposed algorithm extracts the trajectory by composing the motion vectors from the pre-coded bitstream. We gather the motion vectors from the overlap area of the object and calculate mean of the overlapped motion vectors. We implement and simulate our proposed algorithm in H.264 video codec. The performance is better than relevant works and keeps the accuracy of the object trajectory. The experimental results show that the proposed trajectory extraction can extract trajectory form the pre-coded bitstream in high accuracy and achieve higher performance other relevant works.

Keywords: H.264, video bitstream, video object tracking, sports training

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Authors: Elriena Eksteen, Yolandi Willemse, Dawie D. J. Malan, Suria Ellis

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It is important to understand which competencies are needed for managerial and administrative effectiveness of school sport managers with regard to the design, delivery and direction of school sport programmes. The purpose of this study was to determine the competencies and training needs for secondary school sport managers in the North West Province. Data were gathered from 79 school sport managers in the North West Province by means of a validated self-compiled questionnaire. Descriptive statistics, factor analysis and a dependent t-test were used to compare which competencies school sport managers perceive as important in their work with the competencies they actually perform. Functional competencies and core competencies were both found to be important for managing school sport effectively. There were statistically significant differences between the perceived importance of competencies and the frequency with which competencies were actually performed. Respondents attached greater importance to functional and core competencies than the proportion of time spent actually performing them. Furthermore, results indicated the need to train teachers in managing sport finance, sport facilities and human resources, as well as presenting workshops in public relations, sport marketing and sport organisation.

Keywords: competencies, functional competencies, core competencies, school sport manager, training needs

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Authors: Maria Khan

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Framing good core Human Resource Management (HRM) functions like recruitment, selection, training and development, which if executed effectively, can become a strategic advantage for a company. HRM policies related to mid-level managers can depend on the type of top management. This may be due to the difference in perception of effective HRM policies of an expatriate and local leadership. This comparative case study assesses how local mid-level managers are managed in leading multinational telecom companies in Pakistan. Core HRM functions related to managers were analysed through field research based on semi-structured interviews with relevant Human Resource Managers. Results suggest that recruitment and selection practices are not too different and are in compliance with best HRM practices. However, there is a difference in the effective implementation of Training and Development policies. Changing global management trends and skill development dictate that MNCs continuously develop the local talent effectively for local and international success.

Keywords: recruitment, selection, training, development, core HRM, human resource management, subsidiary, international staffing, managers, MNC, expatriate

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Júlia Alarcon Pinto, Carlos João Schaffhausser, Gustavo Alarcon Pinto

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Introduction: The deaf people in Brazil communicate through the Brazilian Sign Language (LIBRAS), which is restricted to this minority and people that received training. However, there is a lack of prepared professionals in the health system to deal with these patients. Therefore, effective communication, health education, quality of support and assistance are compromised. It is of utmost importance to develop measures that ensure the inclusion of deaf parents and children since there are frequent doubts about sphincter training and an absence of tools to promote effective communication between doctors and their patients. Objective: Use of an efficient, rapid and cheap communication method to promote social inclusion and patient education of deaf parents and children during pediatrics appointments. Results; The application demonstrates how to express phrases and symptoms within seconds and this allows patients to fully understand the information provided during the appointment and are capable to evaluate the signs of readiness, learn the correct approaches with the child, what are the adequate instruments, possible obstacles and the importance to execute medical orientations in order to achieve success in the process. Consequently, patients feel more satisfied, secured and embraced by professionals in the health system care. Conclusion: It is of utmost importance to use efficient and cheap methods that support patient care and education in order to promote health and social inclusion.

Keywords: application, deaf patients, social inclusion, sphincter training

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Authors: Takashi Kaburagi, Takamasa Komura, Yosuke Kurihara

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Absolute pitch is the ability to identify a musical note without a reference tone. Training for absolute pitch often occurs in preschool education. It is necessary to clarify how well the trainee can make use of synesthesia in order to evaluate the effect of the training. To the best of our knowledge, there are no existing methods for objectively confirming whether the subject is using synesthesia. Therefore, in this study, we present a method to distinguish the use of color-auditory synesthesia from the separate use of color and audition during absolute pitch training. This method measures blood volume in the prefrontal cortex using functional Near-infrared spectroscopy (fNIRS) and assumes that the cognitive step has two parts, a non-linear step and a linear step. For the linear step, we assume a second order ordinary differential equation. For the non-linear part, it is extremely difficult, if not impossible, to create an inverse filter of such a complex system as the brain. Therefore, we apply a method based on a self-organizing map (SOM) and are guided by the available data. The presented method was tested using 15 subjects, and the estimation accuracy is reported.

Keywords: absolute pitch, functional near-infrared spectroscopy, prefrontal cortex, synesthesia

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Authors: Musaab Riyadh, Norwati Mustapha, Dina Riyadh

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Trajectory similarity can be defined as the cost of transforming one trajectory into another based on certain similarity method. It is the core of numerous mining tasks such as clustering, classification, and indexing. Various approaches have been suggested to measure similarity based on the geometric and dynamic properties of trajectory, the overlapping between trajectory segments, and the confined area between entire trajectories. In this article, an evaluation of these approaches has been done based on computational cost, usage memory, accuracy, and the amount of data which is needed in advance to determine its suitability to stream mining applications. The evaluation results show that the stream mining applications support similarity methods which have low computational cost and memory, single scan on data, and free of mathematical complexity due to the high-speed generation of data.

Keywords: global distance measure, local distance measure, semantic trajectory, spatial dimension, stream data mining

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Authors: Asawari Ajay Avhad

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The Soil and Water Assessment Tool (SWAT) is a hydrological model designed to predict the complex interactions within natural and human-altered watersheds. This research applies the SWAT model to the Ulhas River basin, a small watershed undergoing urbanization and characterized by bowl-like topography. Three simulation scenarios (LC17, LC22, and LC27) are investigated, each representing different land use and land cover (LULC) configurations, to assess the impact of urbanization on runoff. The LULC for the year 2027 is generated using the MOLUSCE Plugin of QGIS, incorporating various spatial factors such as DEM, Distance from Road, Distance from River, Slope, and distance from settlements. Future climate data is simulated within the SWAT model using historical data spanning 30 years. A susceptibility map for runoff across the basin is created, classifying runoff into five susceptibility levels ranging from very low to very high. Sub-basins corresponding to major urban settlements are identified as highly susceptible to runoff. With consideration of future climate projections, a slight increase in runoff is forecasted. The reliability of the methodology was validated through the identification of sub-basins known for experiencing severe flood events, which were determined to be highly susceptible to runoff. The susceptibility map successfully pinpointed these sub-basins with a track record of extreme flood occurrences, thus reinforcing the credibility of the assessment methodology. This study suggests that the methodology employed could serve as a valuable tool in flood management planning.

Keywords: future land use impact, flood management, run off prediction, ArcSWAT

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Authors: Gintarė Sauliutė, Gintaras Svecevičius

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Landfill leachates contain a number of persistent pollutants, including heavy metals. They have the ability to spread in ecosystems and accumulate in fish which most of them are classified as top-consumers of trophic chains. Fish are freely swimming organisms; but perhaps, due to their species-specific ecological and behavioral properties, they often prefer the most suitable biotopes and therefore, did not avoid harmful substances or environments. That is why it is necessary to evaluate the persistent pollutant dispersion in hydroecosystem using fish tissue metal concentration. In hydroecosystems of hybrid type (e.g. river-pond-river) the distance from the pollution source could be a perfect indicator of such a kind of metal distribution. The studies were carried out in the Kairiai landfill neighboring hybrid-type ecosystem which is located 5 km east of the Šiauliai City. Fish tissue (gills, liver, and muscle) metal concentration measurements were performed on two types of ecologically-different fishes according to their feeding characteristics: benthophagous (Gibel carp, roach) and predatory (Northern pike, perch). A number of mathematical models (linear, non-linear, using log and other transformations) have been applied in order to identify the most satisfactorily description of the interdependence between fish tissue metal concentration and the distance from the pollution source. However, the only one log-multiple regression model revealed the pattern that the distance from the pollution source is closely and positively correlated with metal concentration in all predatory fish tissues studied (gills, liver, and muscle).

Keywords: bioaccumulation in fish, heavy metals, hydroecosystem, landfill leachate, mathematical model

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Authors: Long Chen

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With the proliferation of E-Learning, collaborative learning becomes more and more popular in various teaching and learning occasions. Studies over the years have proved that actively participating in classroom discussion can enhance student's learning experience, consolidating their knowledge and understanding of the class content. Collaborative learning can also allow students to share their resources and knowledge by exchanging, absorbing, and observing one another's opinions and ideas. Community Question Answering (CQA) services are particularly suitable paradigms for collaborative learning, since it is essentially an online collaborative learning platform where one can get information from multiple sources for he/her to choose from. However, current CQA services have only achieved limited success in collaborative learning due to the uncertainty of answers' quality. In this paper, we predict the quality of answers in a CQA service, i.e. Yahoo! Answers, for the use of online education and distance learning, which would enable a student to find relevant answers and potential answerers more effectively and efficiently, and thus greatly increase students' user experience in CQA services. Our experiment reveals that the quality of answers is influenced by a series of factors such as asking time, relations between users, and his/her experience in the past. We also show that by modelling user's profile with our proposed personalized features, student's satisfaction towards the provided answers could be accurately estimated.

Keywords: Community Question Answering, Collaborative Learning, Log File, Co-Training

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

Procedia PDF Downloads 140

Authors: Priscila Vitorino, Jeeziane Rezende, Edison Pereira, Adrielly Silva, Weimar Barroso

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Body composition insight during physical activity is relevant to follow up sports income since it can be important and actuate in velocity, resistance, potency, and has an effect on force and agility. The purpose of this study was to identify anthropometric profile, evaluate and correlate body mass index and bioimpedance behavior during the days of Caminhada Ecológica de Goiás - Brasil. A longitudinal study was performed with 25 male participants, with an average age of 45.6±9.1 years. All patients were actives. Body composition was evaluated by body mass index (BMI) measurement and bioimpedance procedures. Both were collected 20 days before walking beginning (A0) and in the four days along the same (A1, A2, A3 e A4). Data were collected in the end of each walking day at athletes accommodations. Final distance during walking route was 308 km in five days, with an average of 62km/day and 7,6 km/hour, and an average temperature of 30°C. Data are represented with mean and standard deviation. ANOVA (Bonferroni pos test) was used to compare frequent measurements between the days. Pearson's correlation test was used to correlate BMI with lean mass, fat mass, and water. BMI decreased from A0 to A1, A2 and A3 (p < 0,01) and increased on A4 (p < 0,01). No changes were observed concerning fat percentage (p=0,60), lean mass (p=0,10) and body water composition (p=0,09). A positive and moderate correlation between BMI and fat percentage was observed; an inverse and moderate correlation between BMI, lean mass and body water composition occurred. Total body mass increased during high intensity and long term walking distance. However, the values of body fat, lean mass and water were maintained.

Keywords: aerobic exercise, body composition, metabolism, sports

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Authors: Anuradha Banerjee

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Energy aware operation is one of the visionary goals in the area of robotics because operability of robots is greatly dependent upon their residual energy. Practically, the tasks allocated to robots carry different priority and often an upper limit of time stamp is imposed within which the task needs to be completed. If a robot is unable to complete one particular task given to it the task is reallocated to some other robot. The collection of robots is controlled by a Central Monitoring Unit (CMU). Selection of the new robot is performed by a fuzzy controller called Task Reallocator (TRAC). It accepts the parameters like residual energy of robots, possibility that the task will be successfully completed by the new robot within stipulated time, distance of the new robot (where the task is reallocated) from distance of the old one (where the task was going on) etc. The proposed methodology increases the probability of completing globally assigned tasks and saves huge amount of energy as far as the collection of robots is concerned.

Keywords: energy-efficiency, fuzzy-controller, priority, reallocation, task

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Authors: Strahinja Kovačević, Jelena Vladić, Senka Vidović, Zoran Zeković, Lidija Jevrić, Sanja Podunavac Kuzmanović

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Supercritical extracts of highly valuated medicinal plant Satureja montana were prepared by application of supercritical carbon dioxide extraction in the carbon dioxide pressure range from 125 to 350 bar and temperature range from 40 to 60°C. Using GC/MS method of analysis chemical profiles (aromatic constituents) of S. montana extracts were obtained. Self-training artificial neural networks were applied to predict the retention time of the analyzed terpenes in GC/MS system. The best ANN model obtained was multilayer perceptron (MLP 11-11-1). Hidden activation was tanh and output activation was identity with Broyden–Fletcher–Goldfarb–Shanno training algorithm. Correlation measures of the obtained network were the following: R(training) = 0.9975, R(test) = 0.9971 and R(validation) = 0.9999. The comparison of the experimental and predicted retention times of the analyzed compounds showed very high correlation (R = 0.9913) and significant predictive power of the established neural network.

Keywords: ANN regression, GC/MS, Satureja montana, terpenes

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Authors: Olga Orynycz, Andrzej Wasiak

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Mathematical model describing energetic efficiency (defined as a ratio of energy obtained in the form of biofuel to the sum of energy inputs necessary to facilitate production) of agricultural subsystem as a function of technological parameters was developed. Production technology is characterized by parameters of machinery, topological characteristics of the plantation as well as transportation routes inside and outside of plantation. The relationship between the energetic efficiency of agricultural and industrial subsystems is also derived. Due to the assumed large area of the individual field, the operations last for several days increasing inter-fields routes because of several returns. The total distance driven outside of the fields is, however, small as compared to the distance driven inside of the fields. This results in small energy consumption during inter-fields transport that, however, causes a substantial decrease of the energetic effectiveness of the whole system.

Keywords: biofuel, energetic efficiency, EROEI, mathematical modelling, production system

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Authors: Zhaojun Wang, Zongdi Sun, Qinqin Cui, Xingwan Ren

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Based on multivariate statistical analysis theory, this paper uses the principal component analysis method, Mahalanobis distance analysis method and fitting method to establish the photovoltaic health model to evaluate the health of photovoltaic panels. First of all, according to weather conditions, the photovoltaic panel variable data are classified into five categories: sunny, cloudy, rainy, foggy, overcast. The health of photovoltaic panels in these five types of weather is studied. Secondly, a scatterplot of the relationship between the amount of electricity produced by each kind of weather and other variables was plotted. It was found that the amount of electricity generated by photovoltaic panels has a significant nonlinear relationship with time. The fitting method was used to fit the relationship between the amount of weather generated and the time, and the nonlinear equation was obtained. Then, using the principal component analysis method to analyze the independent variables under five kinds of weather conditions, according to the Kaiser-Meyer-Olkin test, it was found that three types of weather such as overcast, foggy, and sunny meet the conditions for factor analysis, while cloudy and rainy weather do not satisfy the conditions for factor analysis. Therefore, through the principal component analysis method, the main components of overcast weather are temperature, AQI, and pm2.5. The main component of foggy weather is temperature, and the main components of sunny weather are temperature, AQI, and pm2.5. Cloudy and rainy weather require analysis of all of their variables, namely temperature, AQI, pm2.5, solar radiation intensity and time. Finally, taking the variable values in sunny weather as observed values, taking the main components of cloudy, foggy, overcast and rainy weather as sample data, the Mahalanobis distances between observed value and these sample values are obtained. A comparative analysis was carried out to compare the degree of deviation of the Mahalanobis distance to determine the health of the photovoltaic panels under different weather conditions. It was found that the weather conditions in which the Mahalanobis distance fluctuations ranged from small to large were: foggy, cloudy, overcast and rainy.

Keywords: fitting, principal component analysis, Mahalanobis distance, SPSS, MATLAB

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Authors: Kenneth Uzochukwu Ezugwu

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The quest for adequate teacher education is a serious task for the educational system in Nigeria because teachers are the major translators of education programmes in the classroom. The production of well trained teachers will enhance quality of the products of the school system. It is in this respect that the national policy on education posited that no educational system can rise above the quality of teachers. It is in the light of the above that this paper discusses and brought to the fore certain issues as the re-introduction of teacher training colleges, competitive entry requirement into teacher education and continuous on-the-job training as areas of needed innovation.

Keywords: curriculum innovation, issues, perspectives, teacher education

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Authors: Seyed Abolhasan Naeini, Elham Ghanbari Alamooti

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Static stability of soil slopes using numerical simulation by a finite element code, ABAQUS, has been investigated, and safety factors of the slopes achieved in the case of static load of a 10-storey building. The embankments have the same soil condition but different loading distance from the slope heel. The numerical method for estimating safety factors is 'Strength Reduction Method' (SRM). Mohr-Coulomb criterion used in the numerical simulations. Two steps used for measuring the safety factors of the slopes: first is under gravity loading, and the second is under static loading of a building near the slope heel. These safety factors measured from SRM, are compared with the values from Limit Equilibrium Method, LEM. Results show that there is good agreement between SRM and LEM. Also, it is seen that by increasing the distance from slope heel, safety factors increases.

Keywords: limit equilibrium method, static stability, soil slopes, strength reduction method

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Authors: Eleanor F. Willard

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The attrition rate on distance learning courses can be high. This research examines how online students often react when faced with poor results. Using q methodology, it was found that the emotional response level and the type of social support sought by students were key influences on their attitude to failure. As educational and psychological researchers, we are adept at measuring learning and achievement, but examining attitudes towards barriers to learning are not so well researched. The distance learning student has differing needs from onsite learners and, as the attrition rate is notoriously high in the online student population, examining learners’ attitude towards adversity and barriers is important. Self-report measures such as questionnaires are useful in terms of ascertaining levels of constructs such as resilience and academic confidence. Interviewing, too, can gain in depth detail of the opinions of such a population, but only in individuals. The aim of this research was to ascertain what the feelings and attitudes of online students were when faced with a setback. This was achieved using q methodology due to its use of both quantitative and qualitative methodology and its suitability for exploratory research. The emphasis with this methodology is the attitudes, not the individuals. The work was focused upon a population of distance learning students who attended a school on site for one week as part of their studies. They were engaged in a psychology masters conversion course and, as such, were graduate students. The Q sort had 30 items taken from the Academic Resilience Scale (ARS-30). The scale items represent three constructs; perseverance, reflecting (including adaptive help-seeking) and negative affect. These are widely acknowledged as being relevant concepts underpinning psychological resilience. The q sort was conducted with 19 students in total. This is done by participants arranging statement cards regarding how similar to themselves they believe each statement to be. This was done after reading a vignette describing an experience of academic failure. Commonalities and differences between the sorts from all participants are then analyzed in terms of correlations and response patterns. Following data collection, the participants' responses were initially analyzed and the key perspectives (factors) to emerge were labelled ‘persevering individuals’ and ‘emotional networkers’. The differences between the two perspectives centre around the level of emotion felt when faced with barriers and the extent that students enlist the help of others inside and outside of the university. The dominant factor to emerge from the sorts of ‘persevering individuals’ demonstrated that many distance learners are tenacious. However, for other students, the level of emotional and social support is pivotal in helping them complete their studies when facing adversity. This was demonstrated by the ‘emotional networkers’ perspective. This research forms a starting point for further work on engaging and retaining online students at university and can potentially provide insight into how universities can lower attrition rates on distance learning courses.

Keywords: academic resilience, distance learning, online learning, q methodology

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Authors: Nastaran Ahmadpour Samani, Shahram Talebi

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Added mass is an important quantity in analysis of the motion of a submerged object ,which can be calculated by solving the equation of potential flow around the object . Here, we consider systems in which a square object is submerged in a channel of fluid and moves parallel to the wall. The corresponding added mass at a given distance from the wall d and for the object size s (which is the side of square object) is calculated via lattice Blotzmann simulation . By changing d and s separately, their effect on the added mass is studied systematically. The simulation results reveal that for the systems in which d > 4s, the distance does not influence the added mass any more. The added mass increases when the object approaches the wall and reaches its maximum value as it moves on the wall (d -- > 0). In this case, the added mass is about 73% larger than which of the case d=4s. In addition, it is observed that the added mass increases by increasing of the object size s and vice versa.

Keywords: Lattice Boltzmann simulation , added mass, square, variable size

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Authors: Ali Mahamat

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This paper explores the application of Functional Communication Training (FCT) as an intervention to decrease maladaptive behaviors among individuals diagnosed with Intellectual Disability (ID) and Autism Spectrum Disorders (ASD) within an extensive support needs residential program. Evidence suggests that FCT can be ef ective in promoting positive behavioral changes and enhancing communication skills in this population. The prevalence of maladaptive behaviors in individuals with ID and ASD is a significant concern for caregivers and professionals in residential programs. These behaviors can include aggression, self-injury, and disruptive activities, which can impede the individual's quality of life. Functional Communication Training (FCT) has been identified as a potential solution to these challenges, providing individuals with the communication skills needed to express their needs and desires effectively. Method: A quasi-experimental design was used to investigate the effectiveness of FCT in a residential setting for individuals with ID and ASD. Participants included individuals with varying degrees of ID and ASD who exhibited maladaptive behaviors. A baseline was established for each participant's behavior before introducing FCT as an intervention. The FCT intervention involved teaching the individuals alternative, functionally equivalent communication behaviors to replace maladaptive behaviors. The training was implemented in the participants' natural environment and was incorporated into their daily routines. The intervention period lasted for six months, with follow-ups conducted at three months and six months post-intervention.Results indicated a significant decrease in maladaptive behaviors for individuals who received the FCT intervention. In addition, an enhancement in communication skills was observed, with the majority of participants demonstrating an increased ability to express their needs and desires appropriately. The findings of this study provide support for the effectiveness of FCT in reducing maladaptive behaviors in individuals with ID and ASD in a residential setting. Moreover, the study highlights the importance of incorporating functional communication skills training in the daily routines of these individuals. By providing these individuals with an effective means of communication, FCT not only reduces the occurrence of maladaptive behaviors but also improves the quality of life for these individuals. However, future research should explore the long-term effects of FCT and consider the influence of individual differences on the effectiveness of the intervention.

Keywords: functional communication training, intellectual disability, autism spectrum disorders, maladaptive behavior, residential program

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Authors: Hamide Azimi Lolaty, Fateme Alsadat Ghanipoor, Azar Ramzani, Reza Ali Mohammadpoor, Alireza Babaei

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Background and Objective: Despite the merits behind orthognathic surgery, self-care training in such patients seems logical. The current research was performed pursuing the goal of outlining the effect of training mindfulness-based self-care on Self-Esteem (SE) and Body Image Concern (BIC) of orthognathic surgery candidate patients. Material and Methods: The present study was performed using a semi-experimental method with pre-and post-design in the control and intervention groups. The eligible patients to enter the Babol-based Shahid Beheshti Orthognathic Surgery Clinic were conveniently divided into two 25-person groups. The variables of Self-Esteem and Body Image Concern were measured before and after executing the eight 90-minute training sessions and in the follow-up period done three months after executing the intervention using Cooper Smith’s Self-Esteem Inventory (CSEI) and Body Image Concern Inventory (BICI). The data were analyzed using ANOVA and the independent t-test and using SPSS-26, the data were analyzed at a 0.05 level. Results: As a result of the intervention, the intervention group’s SE score critically changed on average from 25.4±7.31 in the pre-intervention to 31.16±7.05 in the post-intervention and to 40.45±3.51 in the follow-up period (P=0.01), the intervention group’s BIC score changed on average from 60.28±16.47 in the pre-intervention to 47.15±80.47 in the post-intervention and to 32.20 ± 10.73 in the follow-up period. This difference was meaningful (P=0.001). But due to time and the intervention interaction, the control group underwent this significant reduction with a delay. The study revealed the scores of the SE as 32± 6.84 and that of the BIC as 43.32±10.64 in the control group didn’t result in any meaningful statistical difference (P<0.05). Conclusion: Training mindfulness-based self-care exerts an effect on the SE and BIC of the patients undergoing orthognathic surgery. Therefore, it’s recommended to train mindfulness-based self-care for orthognathic surgery candidate patients.

Keywords: self-care, mindfulness, self-esteem, body image concern, orthognathic surgery

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Authors: M. Ghasemi, S.Fazelifar

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Abstract Aim: Over-weight is not desirable and has implications for health and in the case of athletes affects performance. Exercise is a strategy used to counteract overweight owing to create a negative energy balance by increasing energy expenditure and influencing appetite regulating hormones. Interestingly, recent studies have revealed inhibitory effects of exercise on the hunger associated with these hormones in healthy subjects Neuropeptide Y(NPY) is a 36 amino acid protein that is a powerful stimulant appetite. NPY is an important central orexigenic hormone predominantly produced by the hypothalamus, and recently found to be secreted in adipose tissue. This neurotransmitter is secreted in the brain and autonomic nervous system. On the other hand, research has shown that thyme in addition to various properties, also affects the appetite. The purpose of this study was to determine Effects of eight weeks endurance training and thyme consumption on neuropeptide Y in untrained men. Methodology: 36 Healthy untrained men (mean body weight 78.25±3.2 kg, height 176±6.8 cm, age 34.32±4.54 years and BMI 29.1±4.3 kg/m2) voluntarily participated in this study . Subjects were randomly divided into four groups: 1. control, 2. Endurance training, 3. Thyme 4. Endurance training + Thyme. Amount of 10cc Blood sampling were obtained pre-test and post-test (after 8 weeks). The taken blood samples were centrifuged at 1500 × g for 15 min then plasma was stored at -20 °C until analysis. Endurance training consisted three session per week with 60% -75% of reserve heart rate for eight weeks. Exclusion criteria were history of gastrointestinal, endocrine, cardiovascular or psychological disease, and consuming any supplementation, alcohol and tobacco products. Descriptive statistics including means, standard deviations, and ranges were calculated for all measures. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p<0/05 accepted. Results: Results showed that aerobic training significantly reduced body weight, body mass index, percent body fat, but significant increase observed in maximal oxygen consumption level (p ≤ 0/05). The neuropeptide Y levels were significantly increased after exercise. Analysis of data determined that there was no significant difference between the four groups. Conclusion: Appetite control plays a critical role in the competition between energy consumption and energy expenditure. The results of this study showed that endurance training and thyme consumption can be cause improvement in physiological parameters such as increasing aerobic capacity, reduction of fat mass and improve body composition in untrained men.

Keywords: Endurance training, neuropeptide Y, thyme, untrained men

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Authors: Vineeta Sirohi

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The development of critical skills and competencies becomes imperative for young people to cope with the unpredicted challenges of the time and prepare for work and life. Recognizing that education has a critical role in reaching sustainability goals as emphasized by 2030 agenda for sustainability development, educating youth in global competence, meta-cognitive competencies, and skills from the initial stages of formal education are vital. Further, educating for global competence would help in developing work readiness and boost employability. Vocational education and training in India as envisaged in various policy documents remain marginalized in practice as compared to general education. The country is still far away from the national policy goal of tracking 25% of the secondary students at grade eleven and twelve under the vocational stream. In recent years, the importance of skill development has been recognized in the present context of globalization and change in the demographic structure of the Indian population. As a result, it has become a national policy priority and taken up with renewed focus by the government, which has set the target of skilling 500 million people by 2022. This paper provides an overview of the policies, practices, and current status of vocational education and training in India supported by statistics from the National Sample Survey, the official statistics of India. The national policy documents and annual reports of the organizations actively involved in vocational education and training have also been examined to capture relevant data and information. It has also highlighted major initiatives taken by the government to promote skill development. The data indicates that in the age group 15-59 years, only 2.2 percent reported having received formal vocational training, and 8.6 percent have received non-formal vocational training, whereas 88.3 percent did not receive any vocational training. At present, the coverage of vocational education is abysmal as less than 5 percent of the students are covered by the vocational education programme. Besides, launching various schemes to address the mismatch of skills supply and demand, the government through its National Policy on Skill Development and Entrepreneurship 2015 proposes to bring about inclusivity by bridging the gender, social and sectoral divide, ensuring that the skilling needs of socially disadvantaged and marginalized groups are appropriately addressed. It is fundamental that the curriculum is aligned with the demands of the labor market, incorporating more of the entrepreneur skills. Creating nonfarm employment opportunities for educated youth will be a challenge for the country in the near future. Hence, there is a need to formulate specific skill development programs for this sector and also programs for upgrading their skills to enhance their employability. There is a need to promote female participation in work and in non-traditional courses. Moreover, rigorous research and development of a robust information base for skills are required to inform policy decisions on vocational education and training.

Keywords: policy, skill, training, vocational education

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Authors: A. Moghadasein, M. Ghasemi, S. Fazelifar

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Aim: Chemerin is a novel adipokine that play an important role in regulating lipid metabolism and abiogenesis. Chemerin is dependent on autocrine and paracrine signals for the differentiation and maturation of fat cells; it also regulates glucose uptake in fat cells and stimulates lipolysis. It has been reported that in adipocytes, chemerin enhances the insulin-stimulated glucose and causes the phosphorylation of tyrosine in Insulin receptor substrate. According to the studies, Chemerin may increase insulin sensitivity in adipose tissue and is largely associated with Body mass index, triglycerides, and blood pressure in those with normal glucose tolerance. There is limited information available regarding the effect of exercise training on serum chemerin concentrations. The purpose of this study was to investigate the effect of endurance training on serum chemerin levels and lipids of plasma in overweight women. Methodology: This study was a quasi-experimental research with a pre-post test design. After required examination and verification of high pressure by the physician, 22 obese subjects (age: 35.64±5.55 yr, weight: 75.62±9.30 kg, body mass index: 32.4±1.6 kg/m2) were randomly assigned to aerobic training (n= 12) and control (n= 12) groups. Participants completed a questionnaire indicating the lack of sports history during the past six months, the lack of anti-hypertension drugs use, hormone therapy, cardiovascular problems, and complete stoppage of menstrual cycle. Aerobic training was performed 3 times weekly for 8 weeks. Resting levels of chemerin plasma, metabolic parameters were measured prior to and after the intervention. The control group did not participate in any training program. In this study, ethical considerations included the complete description of the objectives to the study participants, ensuring the confidentiality of their information. Kolmogorov-Smirnov and Levin test were used for determining the normal distribution of data and homogeneity of variances, respectively. Analyze of variance with repeated measure were used to investigate the changes in the intra-group and the differences in inter-group of variables. Statistical operations were performed using SPSS 16 and the significance level of the tests was considered at P < 0.05. Results: After an 8 week aerobic training, levels of chemerin plasma were significantly decreased in aerobic trained group when compared with their control groups (p < 0.05).Concurrently, levels of HDL-c were significantly decreased (p < 0.05) whereas, levels of cholesterol, TG and LDL-c, showed no significant changes (p > 0.05). No significant correlations between chemerin levels and weight loss were observed in subjects with overweight women. Conclusion: The present study demonstrated, 8 weeks aerobic training, reduced serum chemerin concentrations in overweight women. Whereas, aerobic training exercise programmers affected the lipid profile response of obese subjects differently. However further research is warranted in order to unravel the molecular mechanism for the range of responses and the role of serum chemerin.

Keywords: chemerin, aerobic training, lipid profile, obese women

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Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

Procedia PDF Downloads 406