Search results for: velocity prediction program

Authors: Valerie Isaak

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Background: This study explores the effectiveness of refresher training sessions of an intervention program at reducing the employees’ risk of injury due to patient violence in a forensic psychiatric hospital. Methods: The original safety intervention program that consisted of a 3 days’ workshop was conducted in the maximum-security ward of a psychiatric hospital in Israel. Ever since the original intervention, annual refreshers were conducted, highlighting one of the safety elements covered in the original intervention. The study examines the effect of the intervention program along with the refreshers over a period of 10 years in four wards. Results: Analysis of the data demonstrates that beyond the initial reduction following the original intervention, refreshers seem to have an additional positive long-term effect, reducing both the number of violent incidents and the number of actual employee injuries in a forensic psychiatric hospital. Conclusions: We conclude that such an intervention program followed by refresher training would promote employees’ wellbeing. A healthy work environment is part of management’s commitment to improving employee wellbeing at the workplace.

Keywords: wellbeing, violence at work, intervention program refreshers, public sector mental healthcare

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Authors: Pramod Keshav Kolase, Atul K. Desai

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This paper presents the experimental investigation results of Ultrasonic Pulse Velocity (UPV) tests conducted on roller compacted concrete pavement (RCCP) material containing Class F fly ash of as mineral admixture and triangular polyester fiber as a secondary reinforcement. The each mix design series fly ash content is varied from 0% to 45 % and triangular polyester fiber 0% to 0.75% by volume fraction. In each series and for different ages of curing (i.e. 7, 28 and 90 days) forty-eight cube specimens are cast and tested for compressive strength and UPV. The UPV of fly ash was found to be lower for all mixtures at 7 days in comparison with control mix concrete. But at 28, 56 days and 90 days the UPV were significantly improved for all the mixes. Relationships between compressive strength of RCCP and UPV and Dynamic Elastic Modulus are proposed for all series mixes.

Keywords: compressive strength, dynamic elastic modulus, fly ash, fiber, roller compacted concrete, ultrasonic pulse velocity

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Authors: Lina Tenjo, Ilba Rodríguez

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The role of cultural identity in bilingual programs has been barely discussed in regards to SLA. This research focuses on providing relevant information that helps in having more knowledge about the experiences that an elementary student has during the second language learning process in a bilingual program within a multicultural context. This study explores the experience of 18 students in a dual language program, in a public elementary school in Northern Virginia, USA. It examines their dual language experience and the different ways this experience contributes to the formation of their cultural identity. The findings were studied with the purpose of determining the relationship between participants and certain aspects of cultural identity in a multicultural context. The reflections that originate from the voices of children are the key source that helps us to better understand the particular needs that young learners have during their participation in a DLP.

Keywords: acculturation, bilingual education, culture, dual language program, identity, second language acquisition

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Authors: Valerie Isaak

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This study examines the effectiveness of an intervention program aimed at enhancing a unit-level safety climate as a way to minimize the risk of employees being injured by patient violence. The intervention program conducted in maximum security units in one of the psychiatric hospitals in Israel included a three day workshop. Safety climate was examined before and after the implementation of the intervention. We also collected data regarding incidents involving patient violence. Six months after the intervention a significant improvement in employees’ perceptions regarding management’s commitment to safety were found as well as a marginally significant improvement in communication concerning safety issues. Our research shows that an intervention program aimed at enhancing a safety climate is associated with a decrease in the number of aggressive incidents. We conclude that such an intervention program is likely to return the sense of safety and reduce the scope of violence.

Keywords: violence, intervention, safety climate, performance, public sector

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Authors: M. Najafi, S. Bab, F. Rahimi Dehgolan

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The motion of an axially moving beam with rotating prismatic joint with a tip mass on the end is analyzed to investigate the nonlinear vibration and dynamic stability of the beam. The beam is moving with a harmonic axially and rotating velocity about a constant mean velocity. A time-dependent partial differential equation and boundary conditions with the aid of the Hamilton principle are derived to describe the beam lateral deflection. After the partial differential equation is discretized by the Galerkin method, the method of multiple scales is applied to obtain analytical solutions. Frequency response curves are plotted for the super harmonic resonances of the first and the second modes. The effects of non-linear term and mean velocity are investigated on the steady state response of the axially moving beam. The results are validated with numerical simulations.

Keywords: super harmonic resonances, non-linear vibration, axially moving beam, Galerkin method

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

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Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: palm oil, fatty acid, NIRS, regression

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Authors: Sara D. Garduno-Diaz, Lorena Loriato

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Food selection is one of the main modifiable risk factors for the avoidance of several detrimental health conditions. Excessive and regular sugar intake has been identified as highly unfavorable, yet a highly occurring practice. A proposed approach to modify this eating practice is the online program developed here. The program targets a modification of mindset and lifestyle habits around food, through a four week raw-vegan guided eating program. While the focus of the program is to set up sustainable changes in sugar intake reduction, it also aims to promote a plant-based eating style. Three pilot sessions have been run with participants from seven different countries. Participants are guided through the program via a combination of daily e-mails, a 24-hour support platform, and by-weekly remote live sessions. Meal preparation techniques, as well as cooking instructions, are provided, following set menus developed by a team of professional chefs and nutritionists. Goal setting, as well as alternatives to specific food-related challenges, is addressed. While the program is intended for both women and men, the majority of participants to date have been female. Feedback has been positive, with changes in eating habits have included an elimination of added sugars, an increase in home cooking and vegetable intake, and a reduction in foods of animal origin. Difficulties in following the program have been reported as unavailability of certain ingredients depending on the country of residence of the participants, social and cultural hurdles, and time restrictions. Nevertheless, the results obtained to date indicate this to be a highly interactive program with the potential to be scaled up and applied to various populations as a public health measure on the way to better health.

Keywords: eating habits, food addiction, nutrition education, plant-based, remote practice

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Authors: Narupon Kunbootsri, J. Kraipoj, K. Phandech, P. Sirasaporn

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Physiotherapy is one of the treatments for frozen shoulder but there was no data about the treatment of physiotherapy. Moreover, it is question about onset of symptom before physiotherapy program and obtaining physical modalities and delayed start physiotherapy program lead to delayed improvement. Thus the aim of this study was to investigate physiotherapy program for frozen shoulder on pain score, onset of symptom and obtaining physical modalities. A retrospective study design was conducted. 182 medical records of patients with frozen shoulder were reviewed. These frozen shoulders were treated at physiotherapy unit, department of Rehabilitation last 3 years (January, 2014- December, 2016). The data consist of onset of symptom, pain score and obtaining physical modalities were recorded. There was a statistically significant improve in pain score, pretreatment score mean 7.24±1.52 and the last follow up pain score mean 3.88± 1.0 [mean difference 3.18 with 95%CI were [2.45- 3.92]. In addition, the onset of symptoms was 145 days before obtaining physiotherapy program. The physical modalities used frequently were hot pack 14.8% and ultrasound diathermy 13.7%. In conclusion, the retrospective study show physiotherapy program including, hot pack and ultrasound diathermy seem to be useful for frozen shoulder in term of pain score. But onset of symptom is too long to start physiotherapy programs.

Keywords: frozen shoulder, physiotherapy, pain score, onset of symptom, physical modality

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Authors: Alma M. Corpuz

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This study evaluated the supplemental feeding program for 59 undernourished pupils in an elementary school located in one of the depressed communities in Tarlac City, Philippines in SY 2013-2014. Pupils were fed for one month with heavy breakfast and afternoon snacks. They were also given vitamins daily. Findings revealed that most of the pupils regained normal Body Mass Indices (BMIs) during a routine weighing in the school opening. In addition, results revealed that the academic performance of the pupils in the 4th Quarter, after the feeding program, was higher compared to the 3rd Quarter period. The researchers recommended that school extension programs should prioritize activities to address malnutrition among pupils to help them perform well in academics. In addition, feeding programs must include heavy meal plans like what was implemented in this project. The feeding program must also include giving of milk and vitamins to ensure significant improvement in their nutrition. It is also important that feacalysis and deworming be performed before the feeding program and proper handwashing be integrated into the feeding activity.

Keywords: wasted, severely wasted, body mass index, supplemental feeding

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Authors: D. I. George Amalarethinam, A. Emima

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Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

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Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

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Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Triphonia Ngailo

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Rainfall is a major climatic parameter affecting many sectors such as health, agriculture and water resources. Its quantitative prediction remains a challenge to weather forecasters although numerical weather prediction models are increasingly being used for rainfall prediction. The performance of six convective parameterization schemes, namely the Kain-Fritsch scheme, the Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D scheme, the Grell-Fretas scheme, the New Tiedke scheme of the weather research and forecast (WRF) model regarding quantitative rainfall prediction over Uganda is investigated using the root mean square error for the March-May (MAM) 2013 season. The MAM 2013 seasonal rainfall amount ranged from 200 mm to 900 mm over Uganda with northern region receiving comparatively lower rainfall amount (200–500 mm); western Uganda (270–550 mm); eastern Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A spatial variation in simulated rainfall amount by different convective parameterization schemes was noted with the Kain-Fritsch scheme over estimating the rainfall amount over northern Uganda (300–750 mm) but also presented comparable rainfall amounts over the eastern Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny, and the Grell-3D underestimated the rainfall amount over most parts of the country especially the eastern region (300–600 mm). The Grell-Fretas captured rainfall amount over the northern region (250–450 mm) but also underestimated rainfall over the lake Victoria Basin (150–300 mm) while the New Tiedke generally underestimated rainfall amount over many areas of Uganda. For deterministic rainfall prediction, the Grell-Fretas is recommended for rainfall prediction over northern Uganda while the Kain-Fritsch scheme is recommended over eastern region.

Keywords: convective parameterization schemes, March-May 2013 rainfall season, spatial variation of parameterization schemes over Uganda, WRF model

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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Authors: Tauhidur Rahman, Kasturi Bhuyan

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In the present paper, Ground Response Analysis at the Rukni irrigation project has been thoroughly investigated. Surface level seismic hazard is mainly used by the practical Engineers for designing the important structures. Surface level seismic hazard can be obtained accounting the soil factor. Structures on soft soil will show more ground shaking than the structure located on a hard soil. The Surface level ground motion depends on the type of soil. Density and shear wave velocity is different for different types of soil. The intensity of the soil amplification depends on the density and shear wave velocity of the soil. Rukni irrigation project is located in the North Eastern region of India, near the Dauki fault (550 Km length) which has already produced earthquakes of magnitude (Mw= 8.5) in the past. There is a probability of a similar type of earthquake occuring in the future. There are several faults also located around the project site. There are 765 recorded strong ground motion time histories available for the region. These data are used to determine the soil amplification factor by incorporation of the engineering properties of soil. With this in view, three of soil bore holes have been studied at the project site up to a depth of 30 m. It has been observed that in Soil bore hole 1, the shear wave velocity vary from 99.44 m/s to 239.28 m/s. For Soil Bore Hole No 2 and 3, shear wave velocity vary from 93.24 m/s to 241.39 m/s and 93.24m/s to 243.01 m/s. In the present work, surface level seismic hazard at the project site has been calculated based on the Probabilistic seismic hazard approach accounting the soil factor.

Keywords: Ground Response Analysis, shear wave velocity, soil amplification, surface level seismic hazard

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Gopikrishnan, Bharathiraja, Boopalan, Jensin Joshua

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The Pitot static tube has proven their values and practicability in measuring velocity of fluids for many years. With the aim of extensive usage of such Pitot tube systems, one of the major enabling technologies is to use the design and fabricate a high sensitive pitot tube for the purpose of calibration of the subsonic wind tunnel. Calibration of wind tunnel is carried out by using different instruments to measure variety of parameters. Using too many instruments inside the tunnel may not only affect the fluid flow but also lead to drag or losses. So, it is essential to replace the different system with a single system that would give all the required information. This model of high sensitive Pitot tube has been designed to ease the calibration process. It minimizes the use of different instruments and this single system is capable of calibrating the wind tunnel test section. This Pitot static tube is completely digitalized and so that the velocity data`s can be collected directly from the instrument. Since the turbulence factors are dependent on velocity, the data’s that are collected from the pitot static tube are then processed and the level of turbulence in the fluid flow is calculated. It is also capable of measuring the pressure distribution inside the wind tunnel and the flow angularity of the fluid. Thus, the well-designed high sensitive Pitot static tube is utilized in calibrating the tunnel and also for the measurement of turbulence.

Keywords: pitot static tube, turbulence, wind tunnel, velocity

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Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

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Authors: Maryam Zarra-Nezhad, Ali Moazami-Goodarzi, Joona Muotka, Nina Sajaniemi

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This study examines the extent to which the impact of a universal intervention program, i.e., POMPedaSens, on children’s early social-emotional learning (SEL) is different depending on early childhood education (ECE) teaches stress at work. The POMPedaSens program aims to promote children’s (5–6-year-olds) SEL by supporting ECE teachers’ engagement and emotional availability. The intervention effectiveness has been monitored using an 8-month randomized controlled trial design with an intervention (IG; 26 teachers and 195 children) and a waiting control group (CG; 36 teachers and 198 children) that provided the data before and after the program implementation. The ECE teachers in the IG are trained to implement the intervention program in their early childhood education and care groups. Latent change score analysis suggests that the program increases children’s prosocial behavior in the IG when teachers show a low level of stress. No significant results were found for the IG regarding a change in antisocial behavior. However, when teachers showed a high level of stress, an increase in prosocial behavior and a decrease in antisocial behavior were only found for children in the CG. The results suggest a promising application of the POMPedaSens program for promoting prosocial behavior in early childhood when teachers have low stress. The intervention will likely need a longer time to display the moderating effect of ECE teachers’ well-being on children’s antisocial behavior change.

Keywords: early childhood, social-emotional learning, universal intervention program, professional development, teachers' stress

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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The utilization of Large Eddy Simulation (LES) has been extensive in turbulence research. LES concentrates on resolving the significant grid-scale motions while representing smaller scales through subfilter-scale (SFS) models. The deconvolution model, among the available SFS models, has proven successful in LES of engineering and geophysical flows. Nevertheless, the thorough investigation of how sub-filter scale dynamics and filter anisotropy affect SFS modeling accuracy remains lacking. The outcomes of LES are significantly influenced by filter selection and grid anisotropy, factors that have not been adequately addressed in earlier studies. This study examines two crucial aspects of LES: Firstly, the accuracy of direct deconvolution models (DDM) is evaluated concerning sub-filter scale (SFS) dynamics across varying filter-to-grid ratios (FGR) in isotropic turbulence. Various invertible filters are employed, including Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The importance of FGR becomes evident as it plays a critical role in controlling errors for precise SFS stress prediction. When FGR is set to 1, the DDM models struggle to faithfully reconstruct SFS stress due to inadequate resolution of SFS dynamics. Notably, prediction accuracy improves when FGR is set to 2, leading to accurate reconstruction of SFS stress, except for cases involving Helmholtz I and II filters. Remarkably high precision, nearly 100%, is achieved at an FGR of 4 for all DDM models. Furthermore, the study extends to filter anisotropy and its impact on SFS dynamics and LES accuracy. By utilizing the dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with anisotropic filters, aspect ratios (AR) ranging from 1 to 16 are examined in LES filters. The results emphasize the DDM’s proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. Notably high correlation coefficients exceeding 90% are observed in the a priori study for the DDM’s reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as filter anisotropy increases. In the a posteriori analysis, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, including velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strainrate tensors, and SFS stress. It is evident that as filter anisotropy intensifies, the results of DSM and DMM deteriorate, while the DDM consistently delivers satisfactory outcomes across all filter-anisotropy scenarios. These findings underscore the potential of the DDM framework as a valuable tool for advancing the development of sophisticated SFS models for LES in turbulence research.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Raksit Nanthatanti, Jarruwat Charoensuk, S. Hirai, Manop Masomtop

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In this study, the effect of channel geometry and operating circumstances on a liquid cooling plate for Lithium-ion Battery modules has been investigated Inlet temperature, water velocity, and channel count were the main factors. According to the passage, enhancing the number of cooling channels[2,3,4,6channelperbases] will affect water flow distribution caused by varying the velocity inlet inside the cooling block[0.5,1.0,1.5,2.0 m/sec] and intake temperatures[25,30,35,40oC], The findings indicate that the battery’s temperature drops as the number of channels increases. The maximum battery's operating temperature [45 oC] rises, but ∆t is needed to be less than 5 oC [v≤1m/sec]. Maximum temperature and local temperature difference of the battery change significantly with the change of the velocity inlet in the cooling channel and its thermal conductivity. The results of the simulation will help to increase cooling efficiency on the cooling system for Li-ion Battery based on a Mini channel in a liquid-cooling configuration

Keywords: cooling efficiency, channel count, lithium-ion battery, operating

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Authors: Ahmed Amin Mousa, M. Abd El Salam

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The current study presents a proposed program for acquisition the skills and techniques needed to produce concept cartoon. The proposed program has been prepared for non-specialist students who have never used neither graphics nor animating software. It was presented to postgraduates in Faculty of Education for Early Childhood, Cairo University, during the spring term of the 2014-2015 academic year. The program works in three different aspects: Drawing and images editing, sound manipulation, and creating animation. In addition, the researchers have prepared a questionnaire for measuring the quality of the concept cartoons produced by the students. The questionnaire was used as a pre-test and post-test, and at the end of the study, a significant difference was determined in favour of post-test results.

Keywords: cartoon, concept cartoon, kindergarten, animation

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Authors: Amr AbdelAzim Ali, G. A. Elsheikh, Moutaz M. Hegazy

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Reaction wheels (RWs) are generally used as main actuator in the attitude control system (ACS) of spacecraft (SC) for fast orientation and high pointing accuracy. In order to achieve the required accuracy for the RWs model, the main characteristics of the RWs that necessitate analysis during the ACS design phase include: technical features, sequence of operating and RW control logic are included in function (behavior) model. A mathematical model is developed including the various errors source. The errors in control torque including relative, absolute, and error due to time delay. While the errors in angular velocity due to differences between average and real speed, resolution error, loose in installation of angular sensor, and synchronization errors. The friction torque is presented in the model include the different feature of friction phenomena: steady velocity friction, static friction and break-away torque, and frictional lag. The model response is compared with the experimental torque and frequency-response characteristics of tested RWs. Based on the created RW model, some criteria of optimization based control torque allocation problem can be recommended like: avoiding the zero speed crossing, bias angular velocity, or preventing wheel from running on the same angular velocity.

Keywords: friction torque, reaction wheels modeling, software in the loop, spacecraft attitude control

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Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

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Authors: Jagdish Prasad Maurya, Sanjay Kumar Pandey

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Inadequate understanding of the complex nature of flow features in tornado vortex is a major problem in modelling tornadoes. Tornadoes are violent atmospheric phenomenon that appear all over the world. Modelling tornadoes aim to reduce the loss of the human lives and material damage caused by the tornadoes. Dynamics of tornado is investigated by a numerical technique, the improved version of the projection method. In this paper, authors solve the problem for axisymmetric tornado vortex by the said method that uses a finite difference approach for getting an accurate and stable solution. The conclusions drawn are that large radial inflow velocity occurs near the ground that leads to increase the tangential velocity. The increased velocity phenomenon occurs close to the boundary and absolute maximum wind is obtained near the vortex core. The results validate previous numerical and theoretical models.

Keywords: computational fluid dynamics, mathematical model, Navier-Stokes equations, tornado

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Authors: John Narh

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There is high rate of deforestation in Ghana due to agricultural expansion, illegal mining and illegal logging. While it is attempting to address the illegalities, Ghana has also initiated a reforestation program known as the Modified Taungya System (MTS). Within the MTS framework, farmers are allocated degraded forestland and provided with tree seedlings to practice agroforestry until the trees form canopy. Yet, the political, ecological and economic models that inform the selection of tree species, the motivations of participating farmers as well as the factors that accounts for differential access to the land and performance of farmers engaged in the program lie underexplored. Using a sequential explanatory mixed methods approach in five forest-fringe communities in the Eastern Region of Ghana, the study reveals that economic factors and Ghana’s commitment to international conventions on the environment underpin the selection of tree species for the MTS program. Social network and access to remittances play critical roles in having access to, and enhances poor farmers’ chances in the program respectively. Farmers are more motivated by the access to degraded forestland to cultivate food crops than having a share in the trees that they plant. As such, in communities where participating farmers are not informed about their benefit in the tree that they plant, the program is largely unsuccessful.

Keywords: translocality, deforestation, forest management, social network

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Authors: Anatoliy Kharkhurin

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This presentation picks up on a widely discussed topic in both multilingualism and creativity research that comes from pedagogical considerations. The research conducted by the author over last 10 years has delivered a solid argument that speaking more than one language facilitates an individual’s creative capacities. The author has expanded the scope of his research and implemented these findings in education. After reviewing the empirical evidence concerning a relationship between multilingual practice and creative behavior, he proposes a new program that includes teaching strategies from both fields, a unified Bilingual Creative Education program. The program is grounded in several conceptual premises. Specifically, it aims at facilitation of the overall linguistic, intellectual and creative competences of young children regardless of their intellectual and creative predispositions thereby meeting the recommendations of a number of governmental policies. It is designed for both migrants who speak their native language and attempt to acquire the language of the migration country and autochthones who want to acquire a foreign language simultaneously with their mother tongue. The purpose of the program is to introduce students to a school curriculum in two languages and to foster four defining aspects of creativity, novelty, utility, aesthetics and authenticity. To accomplish this goal, the program utilizes the holistic approach which combines cognitive, personal and environmental factors in education. The presentation discusses the empirical findings for the implementation of the program.

Keywords: bilingualism, creativity, education, autochthones

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Authors: R. E. Fat-Helbary, A. A. Abdel-latief, M. S. Arfa, Alaa Mostafa

Abstract:

The Egyptian Government proposed a general plan, aiming at constructing new settlements for Nubian in south Aswan in different places around Nasser Lake, one of these settlements in Kurkur area. The Nubian habitations in Wadi Kurkur are located around 30 km southwest of Aswan City. This area are affecting by near distance earthquakes from Kalabsha faults system. The shallow seismic refraction technique was conducted at the study area, to evaluate the soil and rock material quality and geotechnical parameters, in addition to the detection of the subsurface ground model under the study area. The P and S-wave velocities were calculated. The surface layer has P-wave, velocity ranges from 900 m/sec to 1625 m/sec and S-wave velocity ranges from 650 m/sec to 1400 m/sec. On the other hand the bedrock has P-wave velocity ranges from 1300 m/sec to 1980 m/sec and S-wave velocity ranges from 1050 m/sec to1725 m/sec. Measuring Vp and Vs velocities together with bulk density are calculated and used to extract the mechanical properties and geotechnical parameters of the foundation material at the study area. Output of this study is very important for solving the problems, which associated with the construction of various civil engineering purposes, for land use planning and for earthquakes resistant structure design.

Keywords: shallow seismic refraction technique, Kurkur area, p and s-wave velocities, geotechnical parameters, bulk density, Kalabsha faults

Procedia PDF Downloads 408

Authors: Kisan Sarda, Bhavika Shingote

Abstract:

This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

Procedia PDF Downloads 358

Authors: Assad Maalouf, Lunjin Lu, James Lynott

Abstract:

We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

Procedia PDF Downloads 160