Search results for: role model

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: Fatemeh Faramarzi, Hosein Mahjoob

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Building dams on rivers for utilization of water resources causes problems in hydrodynamic equilibrium and results in leaving all or part of the sediments carried by water in dam reservoir. This phenomenon has also significant impacts on water and sediment flow regime and in the long term can cause morphological changes in the environment surrounding the river, reducing the useful life of the reservoir which threatens sustainable development through inefficient management of water resources. In the past, empirical methods were used to predict the sedimentation amount in dam reservoirs and to estimate its efficient lifetime. But recently the mathematical and computational models are widely used in sedimentation studies in dam reservoirs as a suitable tool. These models usually solve the equations using finite element method. This study compares the results from tow software packages, GSTARS4 & HEC-6, in the prediction of the sedimentation amount in Dez dam, southern Iran. The model provides a one-dimensional, steady-state simulation of sediment deposition and erosion by solving the equations of momentum, flow and sediment continuity and sediment transport. GSTARS4 (Generalized Sediment Transport Model for Alluvial River Simulation) which is based on a one-dimensional mathematical model that simulates bed changes in both longitudinal and transverse directions by using flow tubes in a quasi-two-dimensional scheme to calibrate a period of 47 years and forecast the next 47 years of sedimentation in Dez Dam, Southern Iran. This dam is among the highest dams all over the world (with its 203 m height), and irrigates more than 125000 square hectares of downstream lands and plays a major role in flood control in the region. The input data including geometry, hydraulic and sedimentary data, starts from 1955 to 2003 on a daily basis. To predict future river discharge, in this research, the time series data were assumed to be repeated after 47 years. Finally, the obtained result was very satisfactory in the delta region so that the output from GSTARS4 was almost identical to the hydrographic profile in 2003. In the Dez dam due to the long (65 km) and a large tank, the vertical currents are dominant causing the calculations by the above-mentioned method to be inaccurate. To solve this problem, we used the empirical reduction method to calculate the sedimentation in the downstream area which led to very good answers. Thus, we demonstrated that by combining these two methods a very suitable model for sedimentation in Dez dam for the study period can be obtained. The present study demonstrated successfully that the outputs of both methods are the same.

Keywords: Dez Dam, prediction, sedimentation, water resources, computational models, finite element method, GSTARS4, HEC-6

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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: Firdaus Khairi Abdul Kadir, Nazihah Rusli, Noor Aisyah Abdul Aziz

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Islam is a comprehensive religion encompassing all aspects of society’s life such as social, economic, political, cultural and environmental. The environment is part of the manifestation of God’s greatness which has pearls of wisdom, bestowed upon human beings to make them realize that everything is in the hands of God (Allah SWT). However, the equilibrium of nature could be disturbed from the excessive exploitation by humans’ hands. As a caliph on this earth, it is the responsibility of human beings to look after the environment proactively. Besides, Islam calls for the execution of accountable development and respecting the principles of sustainability. Therefore, this study focuses on the role of human beings as caliphs on this earth who are responsible for nature and their acts in conserving and preserving the environment based on the approach of religious education. This study also used the research method of the survey library.

Keywords: environment, human beings, caliph, tauhid, Allah SWT

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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: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

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Australia is a country of some 7,700 million square kilometres with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban storm-water and treated wastewater. But till now it is not widely practiced in Australia, and particularly storm-water is neglected. In Australia, only 4% of storm-water and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As storm-water is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing storm-water recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of storm-water harvesting and reuse. Numerical modelling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes storm-water quantity to design the system components, and the hydraulic model helps to route the flow through storm-water infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a storm-water harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of storm-water harvesting and reuse such as available guidelines of storm-water harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of storm-water harvesting and reuse.

Keywords: storm-water management, storm-water harvesting and reuse, numerical modelling, geographic information system, decision support system, database

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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: Joanna Gerszon, Aleksandra Rodacka

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In the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, protein and peptide aggregation processes play a vital role in contributing to the formation of intracellular and extracellular protein deposits. One of the major components of these deposits is the oxidatively modified glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Therefore, the purpose of this research was to answer the question whether piceatannol, a stilbene derivative, counteracts and/or slows down oxidative stress-induced GAPDH aggregation. The study also aimed to determine if this natural occurring compound prevents unfavorable nuclear translocation of GAPDH in hippocampal cells. The isothermal titration calorimetry (ITC) analysis indicated that one molecule of GAPDH can bind up to 8 molecules of piceatannol (7.3 ± 0.9). As a consequence of piceatannol binding to the enzyme, the loss of activity was observed. Parallel with GAPDH inactivation the changes in zeta potential, and loss of free thiol groups were noted. Nevertheless, the ligand-protein binding does not influence the secondary structure of the GAPDH. Precise molecular docking analysis of the interactions inside the active center allowed to presume that these effects are due to piceatannol ability to assemble a covalent binding with nucleophilic cysteine residue (Cys149) which is directly involved in the catalytic reaction. Molecular docking also showed that simultaneously 11 molecules of ligand can be bound to dehydrogenase. Taking into consideration obtained data, the influence of piceatannol on level of GAPDH aggregation induced by excessive oxidative stress was examined. The applied methods (thioflavin-T binding-dependent fluorescence as well as microscopy methods - transmission electron microscopy, Congo Red staining) revealed that piceatannol significantly diminishes level of GAPDH aggregation. Finally, studies involving cellular model (Western blot analyses of nuclear and cytosolic fractions and confocal microscopy) indicated that piceatannol-GAPDH binding prevents GAPDH from nuclear translocation induced by excessive oxidative stress in hippocampal cells. In consequence, it counteracts cell apoptosis. These studies demonstrate that by binding with GAPDH, piceatannol blocks cysteine residue and counteracts its oxidative modifications, that induce oligomerization and GAPDH aggregation as well as it prevents hippocampal cells from apoptosis by retaining GAPDH in the cytoplasm. All these findings provide a new insight into the role of piceatannol interaction with GAPDH and present a potential therapeutic strategy for some neurological disorders related to GAPDH aggregation. This work was supported by the by National Science Centre, Poland (grant number 2017/25/N/NZ1/02849).

Keywords: glyceraldehyde-3-phosphate dehydrogenase, neurodegenerative disease, neuroprotection, piceatannol, protein aggregation

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Authors: Ramin Tafazzoli, Rahime Zamanfashami, Amir Mohagheghzadeh

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Entrepreneurship is the driving engine of countries’ economic development and has a determinant role in the economic, social and cultural improvement of the societies. Entrepreneurship and its impact on countries’ destiny, result in the planner and policy makers’ attempts to explore and extend it in various aspects. These days, all countries follow their social capital development and human resource quality improvement to achieve the strategic national objectives, economic growth, value creation, cultural dynamism, civil excellence and social solidarity, pursuing the sustainable development based on innovation, entrepreneurial technology , knowledge management and knowledge-focused in various levels and areas. Because of the rapid economic and cultural changes in recent decades and also the emerged need for reinforcing the knowledge-based structures and wealth generation via knowledge, a convenient infrastructure is strongly required for generating science and technology. Devoting attention to entrepreneurship and training and fostering the students who have the essential abilities and skills for creating a suitable business unit, is one of the duties of each university. New expectations necessitate that universities in the development trend by way of entrepreneurship, play a prominent role. Since, higher education has an important role in training and fostering the specialist human resource in the society, attention to the academic entrepreneurship help to develop this issue better. The higher education, relying on its core mission (training and researching) be expected to help the path where exploit and apply the created capabilities and also to cause the development in the society. In this term, the higher education play an essential role to expanse and extent the entrepreneurial concepts by establishing the entrepreneurship universities. Therefore, it is necessary to constitute and establish the entrepreneurship university to solve the problems and improve the development trend. The entrepreneurial courses follow the objectives such as: informing, creating culture, entrepreneurial morality, technical knowledge, entrepreneurial skills transferring, preparing the audiences or researching, job creation, business establishing and its preservation. According to the vision 1404 of Islamic republic of Iran in which the society has to include the advanced knowledge in the field of technology and science generation and also economic growth. In this essay, we investigate the entrepreneurship concepts, entrepreneurship university characteristics, entrepreneurship organizations values, entrepreneurship education process, meanwhile paying attention to that fact which the university can play an essential role in entrepreneurs training by education, culture and science. At the end, we present some suggestion and some solution for obstacles, emphasizing on the vision.

Keywords: entrepreneurship, entrepreneur university, higher education, university

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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: Abdulrahman Nami Almutairi

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In the face of escalating climate change concerns, the concept of smart cities emerges as a promising approach to mitigate carbon emissions and move towards carbon neutrality. This paper provides a comprehensive review of the role of Natural Gas in achieving carbon neutrality. Natural gas has often been seen as a transitional fuel in the context of reducing carbon emissions. Its main role stems from being cleaner than coal and oil when burned for electricity generation and industrial processes. The urgent need to address this global issue has prompted a global shift towards cleaner energy sources and sustainable practices. In this endeavor, natural gas has emerged as a pivotal player, hailed for its potential to mitigate carbon emissions, and facilitate the transition to a low-carbon economy. With its lower carbon intensity compared to conventional fossil fuels, natural gas presents itself as a promising alternative for meeting energy demands while reducing environmental impact. As the world stands at a critical juncture in the fight against climate change, exploring the potential of natural gas as a transitional fuel offers insights into pathways towards a more sustainable and resilient future. By critically evaluating its opportunities and challenges, we can harness the potential of natural gas as a transitional fuel while advancing towards a cleaner, more resilient energy system. Through collaborative efforts and informed decision-making, we can pave the way for a future where energy is not only abundant but also environmentally sustainable and socially equitable.

Keywords: natural gas, clean fuel, carbon emissions, global warming, environmental protection

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Authors: Tamas Bezsenyi, Noemi Katona

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Fighting Human Trafficking is a highly important issue worldwide that states need to deal with in international politics. In the EU combatting human trafficking is emphasized in international policy making and also in the work of international law enforcement, thus in the work of the EUROPOL. While the EU Directive against Human Trafficking prescribes how states should fight this transnational crime and also how victims should be assisted, the EUROPOL focuses on the effective cooperation between national law enforcement agencies. However, despite the aims of the common fight, human trafficking is regulated differently in the punitive law of various nation states. This deeply defines the work and possibilities of national law enforcement organizations. Among the manifold differences in this paper, we focus on the role of regulating asset recovery. We highlight that money, and the regulation and practice how the law enforcement deals with income gained from criminal activities, play essential role in combatting human trafficking. While doing research on the investigation of transnational human trafficking by the Hungarian Law Enforcement Agencies, we have found that the unfortunate regulation of asset recovery determines the lower effectiveness of eliminating criminal organizations. While i.e. in the Netherlands confiscation of property takes place in an early stage of the criminal procedure, in Hungary it can be conducted only if money laundering is also assumed. Our presentation builds on the comparison of criminal procedures which we analyse based on criminal files and interviews with coworkers of the National Bureau of Investigation.

Keywords: human trafficking, law enforcement, asset recovery, organized crime

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Authors: Lizel Bertie, Kim Johnston

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Parental emotion regulation plays a central role in the socialisation of emotion, especially when teaching young children to cope with negative emotions. Despite evidence which shows non-supportive parental responses to children’s expression of negative emotions has implications for the social and emotional development of the child, few studies have investigated risk factors which impact parental emotion socialisation processes. The current study aimed to explore the extent to which parental stress contributes to both difficulties in parental emotion regulation and non-supportive parental responses to children’s expression of negative emotions. In addition, the study examined whether parental use of expressive suppression as an emotion regulation strategy facilitates the influence of parental stress on non-supportive responses by testing the relations in a mediation model. A sample of 140 Australian adults, who identified as parents with children aged 5 to 10 years, completed an online questionnaire. The measures explored recent symptoms of depression, anxiety, and stress, the use of expressive suppression as an emotion regulation strategy, and hypothetical parental responses to scenarios related to children’s expression of negative emotions. A mediated regression indicated that parents who reported higher levels of stress also reported higher levels of expressive suppression as an emotion regulation strategy and increased use of non-supportive responses in relation to young children’s expression of negative emotions. These findings suggest that parents who experience heightened symptoms of stress are more likely to both suppress their emotions in parent-child interaction and engage in non-supportive responses. Furthermore, higher use of expressive suppression strongly predicted the use of non-supportive responses, despite the presence of parental stress. Contrary to expectation, no indirect effect of stress on non-supportive responses was observed via expressive suppression. The findings from the study suggest that parental stress may become a more salient manifestation of psychological distress in a sub-clinical population of parents while contributing to impaired parental responses. As such, the study offers support for targeting overarching factors such as difficulties in parental emotion regulation and stress management, not only as an intervention for parental psychological distress, but also the detection and prevention of maladaptive parenting practices.

Keywords: emotion regulation, emotion socialisation, expressive suppression, non-supportive responses, parental stress

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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: Vishant Gahlaut, A Mercy Latha, Sanjay Kumar Ghosh

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Multi-stage depressed collectors (MDC) are used as an efficiency enhancement technique in traveling wave tubes the high-energy electron beam, after its interaction with the RF signal, gets velocity sorted and collected at various depressed electrodes of the MDC. The ultimate goal is to identify an optimum thermal management scheme (cooling mechanism) that could extract the heat efficiently from the electrodes. Careful thermal analysis, incorporating the cooling mechanism is required to ensure that the maximum temperature does not exceed the safe limits. A simple analytical model for quick prediction of the thermal has been developed. The model has been developed for the worst-case un-modulated DC condition, where all the thermal power is dissipated in the last electrode (typically, fourth electrode in the case of the four-stage depressed collector). It considers the thermal contact resistances at various braze joints accounting for the practical non-uniformities. Analytical results obtained from the model have been validated with simulated and experimental results.

Keywords: multi-stage depressed collector, TWTs, thermal contact resistance, thermal management

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Authors: Baratali Monfarediraz

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Humans’ identity is not only under the influence of a certain society or social structure but also it is influenced by an international identity. This article is a research on role of education in the manifestation of universally accepted values such as, advancement of science, improvement in the quality of education, preservation of the natural environment, preservation, and spread of peace, exchange of knowledge and technology, equal educational opportunities, benefiting from a universal morality and etc. Therefore, the relation between universal beliefs and values and educational approaches and programs is the first thing to pay attention to. Studies indicate that the first step in achieving the above mentioned goals is offering learning strategies. Therefore the importance of educational approaches and programs as a tool for the transference of ideas, experiences and thoughts becomes quite clear. Proper education gives everyone the opportunity of acquiring knowledge while creating tendency toward social activities paves the way for achieving the universal values.

Keywords: globalization, universal values, education, universal goal, values, society

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Authors: M. Alam, P. Seshaiyer

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The rupture predictability of intracranial aneurysm is one of the most important parameters for physicians in surgical treatment. As most of the intracranial aneurysms are asymptomatic, still the rupture potential of both symptomatic and asymptomatic lesions is relatively unknown. Moreover, an intracranial aneurysm constrained by a nerve tissue might be a common scenario for a physician to deal with during the treatment process. Here, we perform a computational modeling of nerve tissue constrained intracranial saccular aneurysm to show a protective role of constrained tissue on the aneurysm. A comparative parametric study of the model also performs taking long constraint, medium constraint, short constraint, point contact, narrow neck aneurysm, wide neck aneurysm as parameters for the analysis. Results show that contact constraint aneurysm generates less stress near the fundus compared to no constraint aneurysm, hence works as a protective wall for the aneurysm not to be ruptured.

Keywords: rupture potential, intracranial saccular aneurysm, anisotropic hyper-elastic material, finite element analysis

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Authors: Yong-Nam Kwon

Abstract:

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

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

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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: Simran Kaur, Paul J. Van Geel

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A coupled Thermal-Mechanical-Biological (TMB) model was developed for the analysis of impacts of temperatures on waste stabilization at a Municipal Solid Waste (MSW) landfill in Quebec, Canada using COMSOL Multiphysics, a finite element-based software. For waste placed in landfills in Northern climates during winter months, it can take months or even years before the waste approaches ideal temperatures for biodegradation to occur. Therefore, the proposed model links biodegradation induced strain in MSW to waste temperatures and corresponding heat generation rates as a result of anaerobic degradation. This provides a link between the thermal-biological and mechanical behavior of MSW. The thermal properties of MSW are further linked to density which is tracked and updated in the mechanical component of the model, providing a mechanical-thermal link. The settlement of MSW is modelled based on the concept of viscoelasticity. The specific viscoelastic model used is a single Kelvin – Voight viscoelastic body in which the finite element response is controlled by the elastic material parameters – Young’s Modulus and Poisson’s ratio. The numerical model was validated with 10 years of temperature and settlement data collected from a landfill in Ste. Sophie, Quebec. The coupled TMB modelling framework, which simulates placement of waste lifts as they are placed progressively in the landfill, allows for optimization of several thermal and mechanical parameters throughout the depth of the waste profile and helps in better understanding of temperature dependence of MSW stabilization. The model is able to illustrate how waste placed in the winter months can delay biodegradation-induced settlement and generation of landfill gas. A delay in waste stabilization will impact the utilization of the approved airspace prior to the placement of a final cover and impact post-closure maintenance. The model provides a valuable tool to assess different waste placement strategies in order to increase airspace utilization within landfills operating under different climates, in addition to understanding conditions for increased gas generation for recovery as a green and renewable energy source.

Keywords: coupled model, finite element modeling, landfill, municipal solid waste, waste stabilization

Procedia PDF Downloads 127