Search results for: equation modeling methods

Authors: Bahar Ayhan

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The present paper is concerned with the numerical modeling of the inelastic behavior of the anisotropically damaged ductile materials, which are based on a generalized macroscopic theory within the framework of continuum damage mechanics. Kinematic decomposition of the strain rates into elastic, plastic and damage parts is basis for accomplishing the structure of continuum theory. The evolution of the damage strain rate tensor is detailed with the consideration of anisotropic effects. Helmholtz free energy functions are constructed separately for the elastic and inelastic behaviors in order to be able to address the plastic and damage process. Additionally, the constitutive structure, which is based on the standard dissipative material approach, is elaborated with stress tensor, a yield criterion for plasticity and a fracture criterion for damage besides the potential functions of each inelastic phenomenon. The finite element method is used to approximate the linearized variational problem. Stress and strain outcomes are solved by using the numerical integration algorithm based on operator split methodology with a plastic and damage (multiplicator) variable separately. Numerical simulations are proposed in order to demonstrate the efficiency of the formulation by comparing the examples in the literature.

Keywords: anisotropic damage, finite element method, plasticity, coupling

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: Prasansha Kumari

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This research intends to identify and analyze the new trends of usage the traditional farming methods to modern paddy cultivation. Information gathered through conducting interviews with total of 200 farmers in selected paddy cultivation areas in Kurunegalla district. As well as this research utilized by case study and observation in Ulpotha Traditional Village, Galgamuwa of Sri Lanka. Secondary data collected from books, articles, relevant websites and other relevant documents. Collected data analyzed by descriptive research methodology. Outcomes are there is growing interest in usage the traditional farming methods to the small consumption level paddy lands that have emerged during the last few decades as well as the research revealed that traditional farming method has identified the ecofriendly farming practices to restrict long term side effects inherited from the modern methods. The study finds out the demand of traditional rice varieties has been growing among the community as health and nutrition purpose.

Keywords: traditional farming, organic, inorganic, paddy cultivation

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Authors: S. S. Ghodsi, M. H. Mehrabi, Zainah Ibrahim, Meldi Suhatril

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This research examines the performance of a hybrid passive control device for enhancing the seismic response of steel frame structures. The device design comprises a damper which employs a viscoelastic material to control both shear and axial strain. In the design, energy is dissipated through the shear strain of a two-layer system of viscoelastic pads which are located between steel plates. In addition, viscoelastic blocks have been included on either side of the main shear damper which obtains compressive strains in the viscoelastic blocks. These dampers not only dissipate energy but also increase the stiffness of the steel frame structure, and the degree to which they increase the stiffness may be controlled by the size and shape. In this research, the cyclical behavior of the damper was examined both experimentally and numerically with finite element modeling. Cyclic loading results of the finite element modeling reveal fundamental characteristics of this hybrid viscoelastic damper. The results indicate that incorporating a damper of the design can significantly improve the seismic performance of steel frame structures.

Keywords: cyclic loading, energy dissipation, hybrid damper, passive control system, viscoelastic damper

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Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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Authors: Regita P. Permata, Ulfa S. Nuraini

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Traveling Salesman Problem (TSP) is the most studied problem in combinatorial optimization. In simple language, TSP can be described as a problem of finding a minimum distance tour to a city, starting and ending in the same city, and exactly visiting another city. In product distribution, companies often get problems in determining the minimum distance that affects the time allocation. In this research, we aim to apply TSP heuristic methods to simulate nodes as city coordinates in product distribution. The heuristics used are sub tour reversal, nearest neighbor, farthest insertion, cheapest insertion, nearest insertion, and arbitrary insertion. We have done simulation nodes using Euclidean distances to compare the number of cities and processing time, thus we get optimum heuristic method. The results show that the optimum heuristic methods are farthest insertion and nearest insertion. These two methods can be recommended to solve product distribution problems in certain companies.

Keywords: Euclidean, heuristics, simulation, TSP

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Authors: Mahmoud Fouad, Mervat Badr, Marwa Ibrahim

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Micro-grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. Renewable power sources such as wind, solar and hydro offer high potential of benign power for future micro-grid systems. Micro-Grid (MG) is basically a low voltage (LV) or medium voltage (MV) distribution network which consists of a number of called distributed generators (DG’s); micro-sources such as photovoltaic array, fuel cell, wind turbine etc. energy storage systems and loads; operating as a single controllable system, that could be operated in both grid-connected and islanded mode. The capacity of the DG’s is sufficient to support all; or most, of the load connected to the micro-grid. This paper presents a micro-grid system based on wind and solar power sources and addresses issues related to operation, control, and stability of the system. Using Matlab/Simulink, the system is modeled and simulated to identify the relevant technical issues involved in the operation of a micro-grid system based on renewable power generation units.

Keywords: micro-grid system, photovoltaic, wind turbine, energy storage, distributed generation, modeling

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Authors: Alakija Temitope Olufunmilayo, Akinyemi, Yagba Joy

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Hepatitis is the inflammation of the liver tissue that can cause whiteness of the eyes (Jaundice), lack of appetite, vomiting, tiredness, abdominal pain, diarrhea. Hepatitis is acute if it resolves within 6 months and chronic if it last longer than 6 months. Acute hepatitis can resolve on its own, lead to chronic hepatitis or rarely result in acute liver failure. Chronic hepatitis may lead to scarring of the liver (Cirrhosis), liver failure and liver cancer. Modelling Hepatitis B may become necessary in order to reduce its spread. So, dynamic SIR model can be used. This model consists of a system of three coupled non-linear ordinary differential equation which does not have an explicit formula solution. It is an epidemiological model used to predict the dynamics of infectious disease by categorizing the population into three possible compartments. In this study, a five-compartment dynamic model of Hepatitis B disease was proposed and developed by adding control measure of sensitizing the public called awareness. All the mathematical and statistical formulation of the model, especially the general equilibrium of the model, was derived, including the nonlinear least square estimators. The initial parameters of the model were derived using nonlinear least square embedded in R code. The result study shows that the proportion of Hepatitis B patient in the study population is 1.4 per 1,000,000 populations. The estimated Hepatitis B induced death rate is 0.0108, meaning that 1.08% of the infected individuals die of the disease. The reproduction number of Hepatitis B diseases in Nigeria is 6.0, meaning that one individual can infect more than 6.0 people. The effect of sensitizing the public on the basic reproduction number is significant as the reproduction number is reduced. The study therefore recommends that programme should be designed by government and non-governmental organization to sensitize the entire Nigeria population in order to reduce cases of Hepatitis B disease among the citizens.

Keywords: hepatitis B, modelling, non-linear ordinary differential equation, sihar model, sensitization

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Authors: Johanna Aromaa

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This paper presents a development project aimed at enhancing student-teachers' awareness of the role of the body in teaching and learning. In this project, theory and practice are brought into dialogue through workshops of body work that utilize art-based and somatic methods. They are carried out in a special course for educating teachers in a Finnish University. Expected results from the project include: 1) the participants become aware of the multiple roles that the body has in educational encounters, and with it, develop a more holistic approach to teaching and learning, 2) the participants gain access to and learn to form bodily knowledge, 3) a working model on enhancing student-teachers' awareness of the role of bodily knowledge in teacher’s work is developed. Innovative methods as well as a radical rethinking of the nature of teaching and learning are needed if we are to appreciate knowing body in the future schools.

Keywords: bodily knowledge, the body, somatic methods, teacher education

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Authors: Wesley A. Saltarelli, Nicolas R. Finkler, Adriana C. P. Miwa, Maria C. Calijuri, Davi G. F. Cunha

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The metabolism of the streams is an indicator of ecosystem disturbance due to the influences of the catchment on the structure of the water bodies. The study of the respiration and photosynthesis allows the estimation of energy fluxes through the food webs and the analysis of the autotrophic and heterotrophic processes. We aimed at evaluating the metabolism in streams located in the Brazilian savannah, Cerrado (Sao Carlos, SP), by determining and modeling the daily changes of dissolved oxygen (DO) in the water during one year. Three water bodies with minimal anthropogenic interference in their surroundings were selected, Espraiado (ES), Broa (BR) and Canchim (CA). Every two months, water temperature, pH and conductivity are measured with a multiparameter probe. Nitrogen and phosphorus forms are determined according to standard methods. Also, canopy cover percentages are estimated in situ with a spherical densitometer. Stream flows are quantified through the conservative tracer (NaCl) method. For the metabolism study, DO (PME-MiniDOT) and light (Odyssey Photosynthetic Active Radiation) sensors log data for at least three consecutive days every ten minutes. The reaeration coefficient (k2) is estimated through the method of the tracer gas (SF6). Finally, we model the variations in DO concentrations and calculate the rates of gross and net primary production (GPP and NPP) and respiration based on the one station method described in the literature. Three sampling were carried out in October and December 2015 and February 2016 (the next will be in April, June and August 2016). The results from the first two periods are already available. The mean water temperatures in the streams were 20.0 +/- 0.8C (Oct) and 20.7 +/- 0.5C (Dec). In general, electrical conductivity values were low (ES: 20.5 +/- 3.5uS/cm; BR 5.5 +/- 0.7uS/cm; CA 33 +/- 1.4 uS/cm). The mean pH values were 5.0 (BR), 5.7 (ES) and 6.4 (CA). The mean concentrations of total phosphorus were 8.0ug/L (BR), 66.6ug/L (ES) and 51.5ug/L (CA), whereas soluble reactive phosphorus concentrations were always below 21.0ug/L. The BR stream had the lowest concentration of total nitrogen (0.55mg/L) as compared to CA (0.77mg/L) and ES (1.57mg/L). The average discharges were 8.8 +/- 6L/s (ES), 11.4 +/- 3L/s and CA 2.4 +/- 0.5L/s. The average percentages of canopy cover were 72% (ES), 75% (BR) and 79% (CA). Significant daily changes were observed in the DO concentrations, reflecting predominantly heterotrophic conditions (respiration exceeded the gross primary production, with negative net primary production). The GPP varied from 0-0.4g/m2.d (in Oct and Dec) and the R varied from 0.9-22.7g/m2.d (Oct) and from 0.9-7g/m2.d (Dec). The predominance of heterotrophic conditions suggests increased vulnerability of the ecosystems to artificial inputs of organic matter that would demand oxygen. The investigation of the metabolism in the pristine streams can help defining natural reference conditions of trophic state.

Keywords: low-order streams, metabolism, net primary production, trophic state

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

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Authors: N. Messai, A. Boumali

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In this work, we aim to solve the two dimensional Kemmer equation including Dirac oscillator interaction term, in the background space-time generated by a cosmic string which is submitted to an uniform magnetic field. Eigenfunctions and eigenvalues of our problem have been found and the influence of the cosmic string space-time on the energy spectrum has been analyzed.

Keywords: Kemmer oscillator, cosmic string, Dirac oscillator, eigenfunctions

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Authors: Amandeep Singh Dhaliwal

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Networking solutions, particularly wireless local area networks have revolutionized the technological advancement. Wireless Local Area Networks (WLANs) have gained a lot of popularity as they provide location-independent network access between computing devices. There are a number of access methods used in Wireless Networks among which DCF and PCF are the fundamental access methods. This paper emphasizes on the impact of DCF and PCF access mechanisms on the performance of the IEEE 802.11a, 802.11b and 802.11g standards. On the basis of various parameters viz. throughput, delay, load etc performance is evaluated between these three standards using above mentioned access mechanisms. Analysis revealed a superior throughput performance with low delays for 802.11g standard as compared to 802.11 a/b standard using both DCF and PCF access methods.

Keywords: DCF, IEEE, PCF, WLAN

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Authors: Adeaga Ibiyemi Iyabo, Adeaga Oyetunde Adeoye

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Interestingly, mechanical drying methods has played a major role in the commercialization of agricultural and agricultural allied sectors. In the overall, drying enhances the favorable storability and preservation of agricultural produce which in turn promotes its producibility, marketability, salability, and profitability. Recent researches have shown that solar drying is easier, affordable, controllable, and of course, cleaner and purer than other means of drying methods. It is, therefore, needful to persistently appraise solar dryers with a view to improving on the existing advantages. In this paper, mathematical equations were formulated for solar dryer using mass conservation law, material balance law and least cost savings method. Computer codes were written in Visual Basic.Net. The developed computer software, which considered Ibadan, a strategic south-western geographical location in Nigeria, was used to investigate the relationship between variable orientation angle of flat plate collector on solar energy trapped, derived monthly heat load, available energy supplied by solar and fraction supplied by solar energy when 50000 Kg/Month of produce was dried over a year. At variable collector tilt angle of 10°.13°,15°,18°, 20°, the derived monthly heat load, available energy supplied by solar were 1211224.63MJ, 102121.34MJ, 0.111; 3299274.63MJ, 10121.34MJ, 0.132; 5999364.706MJ, 171222.859MJ, 0.286; 4211224.63MJ, 132121.34MJ, 0.121; 2200224.63MJ, 112121.34MJ, 0.104, respectively .These results showed that if optimum collector angle is not reached, those factors needed for efficient and cost reduction drying will be difficult to attain. Therefore, this software has revealed that off - optimum collector angle in commercial solar drying does not worth it, hence the importance of the software in decision making as to the optimum collector angle of orientation.

Keywords: energy, ibadan, heat - load, visual-basic.net

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Authors: Wanida Suwunniponth

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This research paper aimed to developing a causal relationship model of success factors of customer relationship management of tourism in Thailand and to investigating relationships among the potential factors that facilitate the success of customer relationship management (CRM). The research was conducted in both quantitative and qualitative methods, by utilizing both questionnaire and in-depth interview. The questionnaire was used in collecting the data from 250 management staff in the hotels located within Bangkok area. Sampling techniques used in this research included cluster sampling according to the service quality and simple random sampling. The data input was analyzed by use of descriptive analysis and System Equation Model (SEM). The research findings demonstrated important factors accentuated by most respondents towards the success of CRM, which were organization, people, information technology and the process of CRM. Moreover, the customer relationship management of tourism business in Thailand was found to be successful at a very significant level. The hypothesis testing showed that the hypothesis was accepted, as the factors concerning with organization, people and information technology played an influence on the process and the success of customer relationship management, whereas the process of customer relationship management factor manipulated its success. The findings suggested that tourism business in Thailand with the implementation of customer relationship management should opt in improvement approach in terms of managerial structure, corporate culture building with customer- centralized approach accentuated, and investment of information technology and customer analysis, in order to capacitate higher efficiency of customer relationship management process that would result in customer satisfaction and retention of service.

Keywords: customer relationship management, casual relationship model, tourism, Thailand

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Authors: Shaila Rana, Wasim Alhamdani

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Effective cybersecurity training is of the utmost importance, given the plethora of attacks that continue to increase in complexity and ubiquity. VR cybersecurity training remains a starkly understudied discipline. Studies that evaluated the effectiveness of VR cybersecurity training over traditional methods are required. An engaging and interactive platform can support knowledge retention of the training material. Consequently, an effective form of cybersecurity training is required to support a culture of cybersecurity awareness. Measurements of effectiveness varied throughout the studies, with surveys and observations being the two most utilized forms of evaluating effectiveness. Further research is needed to evaluate the effectiveness of VR cybersecurity training and traditional training. Additionally, research for evaluating if VR cybersecurity training is more effective than traditional methods is vital. This paper proposes a methodology to compare the two cybersecurity training methods and their effectiveness. The proposed framework includes developing both VR and traditional cybersecurity training methods and delivering them to at least 100 users. A quiz along with a survey will be administered and statistically analyzed to determine if there is a difference in knowledge retention and user satisfaction. The aim of this paper is to bring attention to the need to study VR cybersecurity training and its effectiveness compared to traditional training methods. This paper hopes to contribute to the cybersecurity training field by providing an effective way to train users for security awareness. If VR training is deemed more effective, this could create a new direction for cybersecurity training practices.

Keywords: virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training

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Authors: Helen Nelly Naiga, Christopher Garimoi Orach

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Introduction: Long-acting reversible contraceptive (LARC) methods are highly effective. However, LARC use in Uganda is low (13%). We assessed the factors associated with the use of long-acting reversible contraceptives among women of reproductive age (15-49 yrs) in Jinja District. Methods: We conducted a facility-based cross-sectional study. A total of 314 women aged 15–49 years attending public health facilities (1 hospital and 3 health center IV) in Jinja district, were randomly selected. A total of 6 key informants and 6 in-depth interviews were conducted. Logistic regression analysis was conducted using Stata version 14. Qualitative data were analysed using thematic analysis. Results: The study found that 40.45% of the respondents had ever used LARC. The commonest LARC method used was implanting (38.22%). The factors significantly associated with use of LARC were employment (AOR =2.91; 95% CI (1.05-8.08), access to LARC methods (AOR =4.48; 95% CI (1.24-16.21), husband support (AOR =4.90; 95% CI (1.56-15.41), and experience of no side effects (AOR =3.48; 95% CI (1.00-12.19). Conclusion and recommendations: The study showed that 4 in 10 women of reproductive age in Jinja District were using LARC. The factors associated with LARC use were employment, husband support, access to LARC methods, and the lack of side effects. There is a need to strengthen client education, improve accessibility to LARC methods at all levels of health centers, improve male partner’s decision-making in LARC use and manage the side effects effectively.

Keywords: family planning, implants, intrauterine device, long-acting reversible contraceptives (LARC)

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Authors: Vladimira Hornackova, Jana Kottasova, Zuzana Vanova, Anna Jungrova

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Present study deals with drama education in preschool education. The research made in this field brings a qualitative comparative survey with the aim to find out the use of methods and techniques of drama education in preschool education at university or secondary school graduate preschool teachers. The research uses a content analysis and an unstandardized questionnaire for preschool teachers and obtained data are processed with the help of descriptive methods and correlations. The results allow a comparison of aspects applied through drama in preschool education. The research brings impulses for education improvement in kindergartens and inspiration for university study programs of drama education in the professional training of preschool teachers.

Keywords: drama education, preschool education, preschool teacher, research

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Authors: Yumeng He

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The purpose of this paper is to establish the “extenics” of children music education, the “extenics” thought and methods are introduced into the children music education field. Discussions are made from the perspective of children music education on how to generate new music cognitive from music cognitive, how to generate new music education from music education and how to generate music learning from music learning. The research methods including the extensibility of music art, extensibility of music education, extensibility of music capability and extensibility of music learning. Results of this study indicate that the thought and research methods of children’s extended music education not only have developed the “extenics” concept and ideological methods, meanwhile, the brand-new thought and innovative research perspective have been employed in discussing the children music education. As indicated in research, the children’s extended music education has extended the horizon of children music education, and has endowed the children music education field with a new thought and research method.

Keywords: comprehensive evaluations, extension thought, extension cognition music education, extensibility

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Authors: Raj K. Gupta, X. Gary Tan, Andrzej Przekwas

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Bomb blasts from Improvised Explosive Devices (IEDs) account for vast majority of terrorist attacks worldwide. Injuries caused by IEDs result from a combination of the primary blast wave, penetrating fragments, and human body accelerations and impacts. This paper presents a multiscale computational model of coupled blast physics, whole human body biodynamics and injury biomechanics of sensitive organs. The disparity of the involved space- and time-scales is used to conduct sequential modeling of an IED explosion event, CFD simulation of blast loads on the human body and FEM modeling of body biodynamics and injury biomechanics. The paper presents simulation results for blast-induced brain injury coupling macro-scale brain biomechanics and micro-scale response of sensitive neuro-axonal structures. Validation results on animal models and physical surrogates are discussed. Results of our model can be used to 'replicate' filed blast loadings in laboratory controlled experiments using animal models and in vitro neuro-cultures.

Keywords: blast waves, improvised explosive devices, injury biomechanics, mathematical models, traumatic brain injury

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Authors: Abdelmalek Ouannou, Adil Brouri, Laila Kadi, Tarik

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Switched reluctance motor (SRM) has a major interest in a large domain as in electric vehicle driving because of its wide range of speed operation, high performances, low cost, and robustness to run under degraded conditions. The purpose of the paper is to develop a new analytical approach for modeling SRM parameters. Then, an identification scheme is proposed to obtain the SRM parameters. Since the SRM is featured by a highly nonlinear behavior, modeling these devices is difficult. Then, it is convenient to develop an accurate model describing the SRM. Furthermore, it is always operated in the magnetically saturated mode to maximize the energy transfer. Accordingly, it is shown that the SRM can be accurately described by a generalized polynomial Hammerstein model, i.e., the parallel connection of several Hammerstein models having polynomial nonlinearity. Presently an analytical identification method is developed using a chirp excitation signal. Afterward, the parameters of the obtained model have been determined using Finite Element Method analysis. Finally, in order to show the effectiveness of the proposed method, a comparison between the true and estimate models has been performed. The obtained results show that the output responses are very close.

Keywords: switched reluctance motor, swept-sine signal, generalized Hammerstein model, nonlinear system

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Authors: M. Reza Hashemi, Chris Small, Scott Hayward

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The Northeast Coast of the US faces damaging effects of coastal flooding and winds due to Atlantic tropical and extratropical storms each year. Historically, several large storm events have produced substantial levels of damage to the region; most notably of which were the Great Atlantic Hurricane of 1938, Hurricane Carol, Hurricane Bob, and recently Hurricane Sandy (2012). The objective of this study was to develop an integrated modeling system that could be used as a forecasting/hindcasting tool to evaluate and communicate the risk coastal communities face from these coastal storms. This modeling system utilizes the ADvanced CIRCulation (ADCIRC) model for storm surge predictions and the Simulating Waves Nearshore (SWAN) model for the wave environment. These models were coupled, passing information to each other and computing over the same unstructured domain, allowing for the most accurate representation of the physical storm processes. The coupled SWAN-ADCIRC model was validated and has been set up to perform real-time forecast simulations (as well as hindcast). Modeled storm parameters were then passed to a coastal risk assessment tool. This tool, which is generic and universally applicable, generates spatial structural damage estimate maps on an individual structure basis for an area of interest. The required inputs for the coastal risk model included a detailed information about the individual structures, inundation levels, and wave heights for the selected region. Additionally, calculation of wind damage to structures was incorporated. The integrated coastal risk assessment system was then tested and applied to Charlestown, a small vulnerable coastal town along the southern shore of Rhode Island. The modeling system was applied to Hurricane Sandy and a synthetic storm. In both storm cases, effect of natural dunes on coastal risk was investigated. The resulting damage maps for the area (Charlestown) clearly showed that the dune eroded scenarios affected more structures, and increased the estimated damage. The system was also tested in forecast mode for a large Nor’Easters: Stella (March 2017). The results showed a good performance of the coupled model in forecast mode when compared to observations. Finally, a nearshore model XBeach was then nested within this regional grid (ADCIRC-SWAN) to simulate nearshore sediment transport processes and coastal erosion. Hurricane Irene (2011) was used to validate XBeach, on the basis of a unique beach profile dataset at the region. XBeach showed a relatively good performance, being able to estimate eroded volumes along the beach transects with a mean error of 16%. The validated model was then used to analyze the effectiveness of several erosion mitigation methods that were recommended in a recent study of coastal erosion in New England: beach nourishment, coastal bank (engineered core), and submerged breakwater as well as artificial surfing reef. It was shown that beach nourishment and coastal banks perform better to mitigate shoreline retreat and coastal erosion.

Keywords: ADCIRC, coastal flooding, storm surge, coastal risk assessment, living shorelines

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Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

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Authors: H. Bonakdari, I. Ebtehaj

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The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), bridge pier, scour depth, nonlinear regression (NLR)

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Authors: Thanin Sitthiwirattham, Jiraporn Reunsumrit

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We study the existence of positive solutions to the three points difference summation boundary value problem. We show the existence of at least one positive solution if f is either superlinear or sublinear by applying the fixed point theorem due to Krasnoselskii in cones.

Keywords: positive solution, boundary value problem, fixed point theorem, cone

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

Abstract:

Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: Xuguo Zhang, Jimmy Fung, Kenneth Leung, Alexis Lau

Abstract:

Fine particulate matter concentrations have been decreasing in the past few years while the ozone concentrations are posing an increasing trend in the Greater Bay Area (GBA) of China. A series of control policies have been released to mitigate the country-wide air pollution, however, how to effectively evaluate the exercised control measures and efficiently reveal potential projected mitigation pathways are still limited. By refining an enhanced air-quality-modeling system, this study provides an account of the air quality assessments from 2019 to 2025 to appraise the air quality results and improvement under designed scenarios for assessing the optimum scope for tightening the Air Quality Objectives (AQOs). The results show that it is doable to tighten the 24-hour AQO for SO2 from the World Health Objective air quality guidelines Interim Targets Level-1 (IT-1) (125μg/m3) to IT-2 level (50μg/m3) with the current number of exceedance allowed (three) remains unchanged. It is also possible to tighten the annual AQO for PM2.5 from IT-1 (35 μg/m3) to IT 2 (25 μg/m3), and its 24-hr AQO from IT-1 (75 μg/m3) to IT 2 (50 μg/m3) with the number of exceedances allowed increased from current nine to 35. Regional cooperation under the development of the GBA cooperation are still needed to be focused and strengthen due to the cross-boundary transport characteristics of the air pollution.

Keywords: air quality attainment, Hong Kong, mitigation policy, chemical transport modeling, sensitivity analysis

Procedia PDF Downloads 67

Authors: Shank Kulkarni, Alireza Tabarraei

Abstract:

The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

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Authors: Chongyang Ye, Rong Liu

Abstract:

Compression textiles such as compression stockings (CSs) have been extensively applied for the prevention and treatment of chronic venous insufficiency of lower extremities. The involvement of multiple mechanical factors such as interface pressure, frictional force, and elastic materials make the interactions between lower limb and CSs to be complex. Determination of Poisson’s ratio and elastic moduli of CS materials are critical for constructing finite element (FE) modeling to numerically simulate a complex interactive system of CS and lower limb. In this study, a mixed approach, including an analytic model based on the orthotropic Hooke’s Law and experimental study (uniaxial tension testing and pure shear testing), has been proposed to determine Young’s modulus, Poisson’s ratio, and shear modulus of CS fabrics. The results indicated a linear relationship existing between the stress and strain properties of the studied CS samples under controlled stretch ratios (< 100%). The newly proposed method and the determined key mechanical properties of elastic orthotropic CS fabrics facilitate FE modeling for analyzing in-depth the effects of compression material design on their resultant biomechanical function in compression therapy.

Keywords: elastic compression stockings, Young’s modulus, Poisson’s ratio, shear modulus, mechanical analysis

Procedia PDF Downloads 103