Search results for: winkler model (beam on elastic foundation)

Authors: F. Benhamida, A. Graa, L. Benameur, I. Ziane

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The state estimation of the electrical power system operation state is very important for supervising task. With the nonlinearity of the AC power flow model, the state estimation problem (SEP) is a nonlinear mathematical problem with many local optima. This paper treat the mathematical model for the SEP and the monitoring of the nonlinear systems of great dimensions with an application on power electrical system, the modelling, the analysis and state estimation synthesis in order to supervise the power system behavior. in fact, it is very difficult, to see impossible, (for reasons of accessibility, techniques and/or of cost) to measure the excessive number of the variables of state in a large-sized system. It is thus important to develop software sensors being able to produce a reliable estimate of the variables necessary for the diagnosis and also for the control.

Keywords: power system, state estimation, robustness, observability

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Authors: B. F. Nteumagne, E. Pindza, E. Mare

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We apply Lie symmetries analysis to price and hedge options in the fractional Brownian framework. The reputation of Lie groups is well spread in the area of Mathematical sciences and lately, in Finance. In the presence of transactions costs and under fractional Brownian motions, analytical solutions become difficult to obtain. Lie symmetries analysis allows us to simplify the problem and obtain new analytical solution. In this paper, we investigate the use of symmetries to reduce the partial differential equation obtained and obtain the analytical solution. We then proposed a hedging procedure and calibration technique for these types of options, and test the model on real market data. We show the robustness of our methodology by its application to the pricing of digital options.

Keywords: fractional brownian model, symmetry, transaction cost, option pricing

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Authors: Sakshi Gupta, Anupam Agrawal, Ekta Singla

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An exoskeleton design for rehabilitation purpose encounters many challenges, including ergonomically acceptable wearing technology, architectural design human-motion compatibility, actuation type, human-robot interaction, etc. In this paper, a passive architecture for upper limb exoskeleton is proposed for assisting in rehabilitation tasks. Kinematic modelling is detailed for task-based kinematic synthesis of the wearable exoskeleton for self-feeding tasks. The exoskeleton architecture possesses expansion and torsional springs which are able to store and redistribute energy over the human arm joints. The elastic characteristics of the springs have been optimized to minimize the mechanical work of the human arm joints. The concept of hybrid combination of a 4-bar parallelogram linkage and a serial linkage were chosen, where the 4-bar parallelogram linkage with expansion spring acts as a rigid structure which is used to provide the rotational degree-of-freedom (DOF) required for lowering and raising of the arm. The single linkage with torsional spring allows for the rotational DOF required for elbow movement. The focus of the paper is kinematic modelling, analysis and task-based synthesis framework for the proposed architecture, keeping in considerations the essential tasks of self-feeding and self-exercising during rehabilitation of partially healthy person. Rehabilitation of primary functional movements (activities of daily life, i.e., ADL) is routine activities that people tend to every day such as cleaning, dressing, feeding. We are focusing on the feeding process to make people independent in respect of the feeding tasks. The tasks are focused to post-surgery patients under rehabilitation with less than 40% weakness. The challenges addressed in work are ensuring to emulate the natural movement of the human arm. Human motion data is extracted through motion-sensors for targeted tasks of feeding and specific exercises. Task-based synthesis procedure framework will be discussed for the proposed architecture. The results include the simulation of the architectural concept for tracking the human-arm movements while displaying the kinematic and static study parameters for standard human weight. D-H parameters are used for kinematic modelling of the hybrid-mechanism, and the model is used while performing task-based optimal synthesis utilizing evolutionary algorithm.

Keywords: passive mechanism, task-based synthesis, emulating human-motion, exoskeleton

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Authors: Leila Rashidian

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Temperature rise on Earth has had harmful effects on the Earth's surface and has led to change in precipitation patterns all around the world. The present research was aimed to study the process of climate change according to the data simulation in future and compare these parameters with current situation in the studied stations in Semnan province including Garmsar, Shahrood and Semnan. In this regard, LARS-WG software, HADCM₃ model and A₂ scenario were used for the 2010-2030 period. In this model, climatic parameters such as maximum and minimum temperature, precipitation and radiation were used daily. The obtained results indicated that there will be a 4.4% increase in precipitation in Semnan province compared with the observed data, and in general, there will be a 1.9% increase in temperature. This temperature rise has significant impact on precipitation patterns. Most of precipitation will be raining (torrential rains in some cases). According to the results, from west to east, the country will experience more temperature rise and will be warmer.

Keywords: climate change, Semnan province, Lars.WG model, climate parameters, HADCM₃ model

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Sari Elkahina, Zergoug Mourad, Benachenhou Kamel

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The main purpose of this paper is to perform a computations comparison of stress intensity factor 'SIF' evaluation in case of cracked thin plate with Aluminum alloy 7075-T6 and 2024-T3 used in aeronautics structure under uniaxial loading. This evaluation is based on finite element method with a virtual power principle through two techniques: the extrapolation and G−θ. The first one consists to extrapolate the nodal displacements near the cracked tip using a refined triangular mesh with T3 and T6 special elements, while the second, consists of determining the energy release rate G through G−θ method by potential energy derivation which corresponds numerically to the elastic solution post-processing of a cracked solid by a contour integration computation via Gauss points. The SIF obtained results from extrapolation and G−θ methods will be compared to an analytical solution in a particular case. To illustrate the influence of the meshing kind and the size of integration contour position simulations are presented and analyzed.

Keywords: crack tip, SIF, finite element method, concentration technique, displacement extrapolation, aluminum alloy 7075-T6 and 2024-T3, energy release rate G, G-θ method, Gauss point numerical integration

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Authors: Guanhua Zhou, Zhongqi Ma

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Submerged aquatic vegetation (SAV) in wetlands can absorb nitrogen and phosphorus effectively to prevent the eutrophication of water. It is feasible to monitor the distribution of SAV through remote sensing, but for the reason of weak vegetation signals affected by water body, traditional terrestrial vegetation indices are not applicable. This paper aims at constructing SAV index to enhance the vegetation signals and distinguish SAV from water body. The methodology is as follows: (1) select the bands sensitive to the vegetation parameters based on global sensitivity analysis of SAV canopy radiative transfer model; (2) take the soil line concept as reference, analyze the distribution of SAV and water reflectance simulated by SAV canopy model and semi-analytical water model in the two-dimensional space built by different sensitive bands; (3)select the band combinations which have better separation performance between SAV and water, and use them to build the SAVI indices in the form of normalized difference vegetation index(NDVI); (4)analyze the sensitivity of indices to the water and vegetation parameters, choose the one more sensitive to vegetation parameters. It is proved that index formed of the bands with central wavelengths in 705nm and 842nm has high sensitivity to chlorophyll content in leaves while it is less affected by water constituents. The model simulation shows a general negative, little correlation of SAV index with increasing water depth. Moreover, the index enhances capabilities in separating SAV from water compared to NDVI. The SAV index is expected to have potential in parameter inversion of wetland remote sensing.

Keywords: global sensitivity analysis, radiative transfer model, submerged aquatic vegetation, vegetation indices

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Authors: S. Khamtree, T. Ratanawilai, C. Nuntadusit

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Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 °C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (R²), Root Mean Square Error (RMSE) and Chi-square (χ²) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (R² = 0.9963) for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments.

Keywords: empirical models, rubberwood, moisture ratio, hot air drying

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

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Authors: Elham Taghizadeh, Mostafa Abedzadeh, Mostafa Setak

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Logistics network is expected that opened facilities work continuously for a long time horizon without any failure; but in real world problems, facilities may face disruptions. This paper studies a reliable joint inventory location problem to optimize cost of facility locations, customers’ assignment, and inventory management decisions when facilities face failure risks and doesn’t work. In our model we assume when a facility is out of work, its customers may be reassigned to other operational facilities otherwise they must endure high penalty costs associated with losing service. For defining the model closer to real world problems, the model is proposed based on p-median problem and the facilities are considered to have limited capacities. We define a new binary variable (Z_is) for showing that customers are not assigned to any facilities. Our problem involve a bi-objective model; the first one minimizes the sum of facility construction costs and expected inventory holding costs, the second one function that mention for the first one is minimizes maximum expected customer costs under normal and failure scenarios. For solving this model we use NSGAII and MOSS algorithms have been applied to find the pareto- archive solution. Also Response Surface Methodology (RSM) is applied for optimizing the NSGAII Algorithm Parameters. We compare performance of two algorithms with three metrics and the results show NSGAII is more suitable for our model.

Keywords: joint inventory-location problem, facility location, NSGAII, MOSS

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Authors: Khalid Hassan Abdesamed, Kalsom Abd Wahab

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Economic development and growth are significantly linked to the consistent and sustainable sector of small and medium enterprises (SMEs). Banks are the frontrunners in financing and advising SMEs. The main objective of the study is to assess the tendency of SMEs to use the Islamic bank. Model was developed using quantitative method with a hypothetical-deductive testing approach. Model (N = 364) used primary data on the tendency of SMEs to use Islamic banks gathered from questionnaire. It is found by Mann-Whitney test that the tendency to use Islamic bank varies between those firms which consider formal financing with the ones relying on informal financing with the latter tends more to use Islamic bank. This study can serve academic researchers, policy makers, and developing countries as a model of SMEs’ desirability to Islamic banking.

Keywords: formal financing, informal financing, Islamic bank, SMEs

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Hamidrza Joodaki

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The most complex issue in urban land use planning is site selection that needs to assess the verity of elements and factors. Multi Criteria Decision Making (MCDM) methods are the best approach to deal with complex problems. In this paper, combination of the analytical hierarchy process (AHP) model and FUZZY logic was used as MCDM methods to select the best site for gas station in the 4th gas zone of Tehran. The first and the most important step in FUZZY-AHP model is selection of criteria and sub-criteria. Population, accessibility, proximity and natural disasters were considered as the main criteria in this study. After choosing the criteria, they were weighted based on AHP by EXPERT CHOICE software, and FUZZY logic was used to enhance accuracy and to approach the reality. After these steps, criteria layers were produced and weighted based on FUZZY-AHP model in GIS. Finally, through ARC GIS software, the layers were integrated and the 4th gas zone in TEHRAN was selected as the best site to locate gas station.

Keywords: multiple criteria decision making (MCDM), analytic hierarchy process (AHP), FUZZY logic, geographic information system (GIS)

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Authors: Pedram Saadati, Zahra Nazari

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In the last decade, the role and importance of knowledge-based technological businesses in the insurance industry has greatly increased, and due to the weakness of previous studies in Iran, the current research deals with the design of the InsurTech empowerment model. In order to obtain the conceptual model of the research, a hybrid framework has been used. The statistical population of the research in the qualitative part were experts, and in the quantitative part, the InsurTech activists. The tools of data collection in the qualitative part were in-depth and semi-structured interviews and structured self-interaction matrix, and in the quantitative part, a researcher-made questionnaire. In the qualitative part, 55 indicators, 20 components and 8 concepts (dimensions) were obtained by the content analysis method, then the relationships of the concepts with each other and the levels of the components were investigated. In the quantitative part, the information was analyzed using the descriptive analytical method in the way of path analysis and confirmatory factor analysis. The proposed model consists of eight dimensions of supporter capability, supervisor of insurance innovation ecosystem, managerial, financial, technological, marketing, opportunity identification, innovative InsurTech capabilities. The results of statistical tests in identifying the relationships of the concepts with each other have been examined in detail and suggestions have been presented in the conclusion section.

Keywords: insurTech, knowledge-base, empowerment model, factor analysis, insurance

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Authors: Sara Mostofian

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The nuclear industry is a technology that can fulfill future energy needs but requires special attention to ensure safety and reliability while minimizing any environmental impact. To meet these expectations, the nuclear industry is exploring different reactor technologies for power production. Several designs are under development and the technical viability of these new designs is the subject of many ongoing studies. One of these studies considers the radioactive emissions and radioactive waste generated during the life of a nuclear power production plant to allow a successful license process. For all the modern technologies, a good understanding of the radioactivity generated in the process systems of the plant is essential. Some of that understanding may be gleaned from the performance of some prototype reactors of similar design that operated decades ago. This paper presents how, with that understanding, a model can be developed to estimate the emissions as well as the radioactive waste during the normal operation of a nuclear power plant. The model would predict the radioactive material concentrations in different waste streams. Using this information, the radioactive emission and waste generated during the life of these new technologies can be estimated during the early stages of the design of the plant.

Keywords: SMRs, activity transport, model, radioactive waste

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Authors: Chayanika Rout, Debjani Chakraborty, Adrijit Goswami

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Our work presents an inventory model which illustrates imperfect production and imperfect inspection processes for deteriorating items. A cost-minimizing model is studied considering two types of inspection errors, namely, Type I error of falsely screening out a proportion of non-defects, thereby passing them on for rework and Type II error of falsely not screening out a proportion of defects, thus selling those to customers which incurs a penalty cost. The screened items are reworked; however, no returns are entertained due to deteriorating nature of the items. In more practical situations, certain parameters such as the demand rate and the deterioration rate of inventory cannot be accurately determined, and therefore, they are assumed to be triangular fuzzy numbers in our model. We calculate the optimal lot size that must be produced in order to minimize the total inventory cost for both the crisp and the fuzzy models. A numerical example is also considered to exemplify the procedure which is followed by the analysis of sensitivity of various parameters on the decision variable and the objective function.

Keywords: deteriorating items, EPQ, imperfect quality, rework, type I and type II inspection errors

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Authors: Yogesh Shukla

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Many attempts have been made to study temperature distribution problem in human tissues under normal environmental and physiological conditions at constant arterial blood temperature. But very few attempts have been made to investigate temperature distribution in human tissues under different arterial blood temperature. In view of above, a finite element model has been developed to unsteady temperature distribution in dermal region in human body. The model has been developed for one dimension unsteady state case. The variation in parameters like thermal conductivity, blood mass flow and metabolic activity with respect to position and time has been incorporated in the model. Appropriate boundary conditions have been framed. The central difference approach has been used in space variable and trapezoidal rule has been employed a long time variable. Numerical results have been obtained to study relationship among temperature and time.

Keywords: rate of metabolism, blood mass flow rate, thermal conductivity, heat generation, finite element method

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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Authors: Issa S. Oweis, Gary Gartenberg, Luma J. Oweis

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The site for a residential apartment building overlies an abandoned iron mine in granitic gneiss in northern New Jersey. The mine stope is about 137 m (450 long) and dipping over 344m (800 feet) at 450 to 500. As the building footprint straddles, the mine site needed remediation. The remediation scheme consisted of compaction grouting a minimum 10 m (30 ft.) depth of the mine stope in rock to establish a buttress for the hanging wall and allow support of the building foundation. The rock strength parameters (friction and cohesion) were established based on Hoek Geologic Strength Index (GSI). The derived strength parameters were used in the wedge analysis to simulate rock cave-in. It was concluded that a cave-in would be unlikely. Verification holes confirmed the effectiveness of grouting. Although post grouting micro gravity survey depicted a few anomalies, no anomalies were found to exist by further drilling and excavation.

Keywords: grout, stope, rock, properties

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Authors: Delia Enyedi

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Throughout film history, the regular return of 3D cinema has been discussed in connection to crises caused by the advent of television or the competition of the Internet. In addition, the three waves of stereoscopic 3D (from 1952 up to 1983) and its current digital version have been blamed for adding a challenging technical distraction to the viewing experience. By discussing the films Dial M for Murder (1954) and Goodbye to Language (2014), the paper aims to analyze the response of recognized auteurs to the use of 3D techniques in filmmaking. For Alfred Hitchcock, the solution to attaining perceptual immersion paradoxically resided in restraining the signature effect of 3D, namely protrusion. In Jean-Luc Godard’s vision, 3D techniques allowed him to explore perceptual absorption by means of depth of field, for which he had long advocated as being central to cinema. Thus, both directors contribute to the foundation of an auteur aesthetic in 3D filmmaking.

Keywords: Alfred Hitchcock, authorship, 3D filmmaking, Jean-Luc Godard, perceptual absorption, perceptual immersion

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Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction

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Authors: Peter Adly Hamdy Fahmy

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The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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Authors: Yong-Nam Kwon

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In the present study, we have designed the hydro-mechanical forming in which AZ31 sheet was drawn to a kind of preform step following gas blow forming for accurate geometry. In order to judge a formability enhancement of AZ31 sheet, model geometry came from a practical automotive part which had quite depth with complicated curvatures, which was proven that a single sheet forming could not gave a successful part. Experimentally, we succeeded to make the model part with accurate dimension. The optimum forming conditions for respective forming steps were considered most important technical features of this hydro-mechanical and would be discussed in details. Also, the effort to avoid detrimental abnormal grain growth was given and discussed for a practical application.

Keywords: hydro-mechanical forming, AZ31, abnormal grain growth, model geometry

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Sanjeev Kumar Sharma, Arnab Mondal, Ranjit Kumar Upadhyay

Abstract:

Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. We consider a FitzHugh-Rinzel (FH-R) model and studied the different dynamics of the model by considering the parameter c as the predominant parameter. The model exhibits different types of neuronal responses such as regular spiking, mixed-mode bursting oscillations (MMBOs), elliptic bursting, etc. Based on the bifurcation diagram, we consider the three regimes (MMBOs, elliptic bursting, and quiescent state). An analytical treatment for the occurrence of the supercritical Hopf bifurcation is studied. Further, we extend our study to a network of a hundred neurons by considering the bi-directional synaptic coupling between them. In this article, we investigate the alternation of spiking propagation and bursting phenomena of an uncoupled and coupled FH-R neurons. We explore that the complete graph of heterogenous desynchronized neurons can exhibit different types of bursting oscillations for certain coupling strength. For higher coupling strength, all the neurons in the network show complete synchronization.

Keywords: excitable neuron model, spiking-bursting, stability and bifurcation, synchronization networks

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Authors: A. Szekrényes

Abstract:

This paper revisits the free vibration problem of delaminated composite beams. It is shown that during the vibration of composite beams the delaminated parts are subjected to the parametric excitation. This can lead to the dynamic buckling during the motion of the structure. The equation of motion includes time-dependent stiffness and so it leads to a system of Mathieu-Hill differential equations. The free vibration analysis of beams is carried out in the usual way by using beam finite elements. The dynamic buckling problem is investigated locally, and the critical buckling forces are determined by the modified harmonic balance method by using an imposed time function of the motion. The stability diagrams are created, and the numerical predictions are compared to experimental results. The most important findings are the critical amplitudes at which delamination buckling takes place, the stability diagrams representing the instability of the system, and the realistic mode shape prediction in contrast with the unrealistic results of models available in the literature.

Keywords: delamination, free vibration, parametric excitation, sweep excitation

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Authors: Tamriko Pavliashvili

Abstract:

Marriage is such an important institution of family law, which is an indicator of the development of society. Although a family can be created by the birth of a child between an unmarried couple, marriage is still the main basis for the creation of a family, during which the rights and duties imposed require legal regulation. At present, in the conditions of globalization, there are different types of marriage, although, in the main countries, it is still a union of a woman and a man, which involves voluntary cohabitation and assuming and fulfilling the norms and responsibilities established on the basis of the law. Modern society is at the stage where there is a need to create a family, and therefore marriage provides the best opportunity for relationships and existence between people. The mentioned paper about the state institution - of marriage gives us the opportunity to get more information about the existing habits and legal norms from ancient times to the modern period in Georgia, and also through comparison, we will see what the differences and commonalities were and are in the marriage law of the countries of the world and Georgia.

Keywords: marriage, family law, the union of man and woman, church law, concubinage, registered marriage, impeding circumstances, positive and negative conditions of marriage

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Authors: Rassoli Aisa, Abrishami Movahhed Arezu, Faturaee Nasser, Seddighi Amir Saeed, Shafigh Mohammad

Abstract:

Cardiovascular diseases are one of the most common causes of mortality in developed countries. Coronary artery abnormalities and carotid artery stenosis, also known as silent death, are among these diseases. One of the treatment methods for these diseases is to create a deviatory pathway to conduct blood into the heart through a bypass surgery. The saphenous vein is usually used in this surgery to create the deviatory pathway. Unfortunately, a re-surgery will be necessary after some years due to ignoring the disagreement of mechanical properties of graft tissue and/or applied prostheses with those of host tissue. The objective of the present study is to clarify the viscoelastic behavior of human saphenous tissue. The stress relaxation tests in circumferential and longitudinal direction were done in this vein by exerting 20% and 50% strains. Considering the stress relaxation curves obtained from stress relaxation tests and the coefficients of the standard solid model, it was demonstrated that the saphenous vein has a non-linear viscoelastic behavior. Thereafter, the fitting with Fung’s quasilinear viscoelastic (QLV) model was performed based on stress relaxation time curves. Finally, the coefficients of Fung’s QLV model, which models the behavior of saphenous tissue very well, were presented.

Keywords: Viscoelastic behavior, stress relaxation test, uniaxial tensile test, Fung’s quasilinear viscoelastic (QLV) model, strain rate

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Authors: Mohsen Goodarzi, George Berghorn

Abstract:

Despite the rapid growth in the number of green building and community development projects, the long-term performance of these projects has not yet been sufficiently evaluated from the users’ points of view. This is partially due to the lack of post-occupancy evaluation tools available for this type of project. In this study, a post-construction evaluation model is developed to evaluate the relationship between the perceived performance and satisfaction of residents in LEED-certified residential buildings and communities. To develop this evaluation model, a primary five-factor model was developed based on the existing models and residential satisfaction theories. Each factor of the model included several measures that were adopted from LEED certification systems such as LEED-BD+C New Construction, LEED-BD+C Multifamily Midrise, LEED-ND, as well as the UC Berkeley’s Center for the Built Environment survey tool. The model included four predictor variables (factors), including perceived building performance (8 measures), perceived infrastructure performance (9 measures), perceived neighborhood design (6 measures), and perceived economic performance (4 measures), and one dependent variable (factor), which was residential satisfaction (6 measures). An online survey was then conducted to collect the data from the residents of LEED-certified residential communities (n=192) and the validity of the model was tested through Confirmatory Factor Analysis (CFA). After modifying the CFA model, 26 measures, out of the initial 33 measures, were retained to enter into a Structural Equation Model (SEM) and to find the relationships between the perceived buildings performance, infrastructure performance, neighborhood design, economic performance and residential Satisfaction. The results of the SEM showed that the perceived building performance was the most influential factor in determining residential satisfaction in LEED-certified communities, followed by the perceived neighborhood design. On the other hand, perceived infrastructure performance and perceived economic performance did not show any significant relationship with residential satisfaction in these communities. This study can benefit green building researchers by providing a model for the evaluation of the long-term performance of these projects. It can also provide opportunities for green building practitioners to determine priorities for future residential development projects.

Keywords: green building, residential satisfaction, perceived performance, confirmatory factor analysis, structural equation modeling

Procedia PDF Downloads 225