Search results for: distributed network

Authors: Cynthia Zgheib, Yonna Sacre

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Pregnancy, this particular moment in the life of a woman, requires monitoring of eating behavior changes. However, the food choices during pregnancy should be varied and healthy, including the consumption of different food groups. Nutritional status is the process of acquisition and consumption of food. Therefore, a varied diet is associated with good nutritional status. This is why the nutrition education is a strategy commonly applied to improve maternal nutrition during pregnancy. Thus, it is crucial to assess 'The eating behavior and nutritional status of pregnant women living in Keserwan Lebanon.' In order to evaluate the association of different persona, socioeconomic and sociodemographic factors with the eating behavior and nutrition in the concerned study category, a cross-sectional descriptive study was conducted on a sample of 150 pregnant women aging between 18 and 40 years randomly selected from the hospitals and clinics located in Keserwan area and equally distributed between different cities and villages of the area according to altitude. The purpose of this study was to evaluate the eating behavior of the concerned population and to compare it to the recommendation of the food guide pyramid, their level of food awareness and finally to analyze their blood tests in order to detect any nutrients deficiency that they may face during the course of their pregnancy. Sociodemographic, lifestyle, eating behaviour, health, eating patterns, awareness, and food frequency questionnaire (FFQ) were collected through a validated questionnaire specifically adapted for the purpose of the study. Statistical analysis was carried out, and multivariate models were used in order to evaluate the association between several independent variables and the eating behaviour and nutritional status of Lebanese pregnant women The final analysis has shown that 48.7% of pregnant women were aged between 30 and 40 years old, 56% had a normal BMI between 18.5 and 24.9, thus age affects the eating behavior, so the older are the pregnant women, and the healthier is their eating behavior. In fact, 80.7% had acceptable food behavior which is based on an equilibrium between both quantity and quality of food, although the recommended foods are foods found in the food pyramid and available in the Lebanese diet. In addition, 68% had an acceptable level of awareness concerning the health importance of good eating habits, therefore, it is positively affecting their food choices. Moreover, 50 % have an acceptable nutritional status which is confirmed by their biological tests. Future governmental or national studies and programs could be settled aiming to increase the awareness about the good eating behaviors and nutritional status of Lebanese pregnant women.

Keywords: eating behavior, nutritional status, level of awareness, pregnant woman

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Authors: Shiri Elisheva Decktor, Sharon Hornstein

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Highway merges and unmarked junctions are key components in any urban road network, which can act as bottlenecks and create traffic disruption. Inefficient highway merges may trigger traffic instabilities such as stop-and-go waves, pose safety conditions and lead to longer journey times. These phenomena occur spontaneously if the average vehicle density exceeds a certain critical value. This study focuses on modeling the traffic using a microscopic traffic flow model. A hybrid traffic model, which combines human-driven and controlled vehicles is assumed. The controlled vehicles obey different driving policies when approaching the merge, or in the vicinity of other vehicles. We developed a co-simulation model in SUMO (Simulation of Urban Mobility), in which the human-driven cars are modeled using the IDM model, and the controlled cars are modeled using a dedicated controller. The scenario chosen for this study is a closed track with one merge and one exit, which could be later implemented using a scaled infrastructure on our lab setup. This will enable us to benchmark the results of this study obtained in simulation, to comparable results in similar conditions in the lab. The metrics chosen for the comparison of the performance of our algorithm on the overall traffic conditions include the average speed, wait time near the merge, and throughput after the merge, measured under different travel demand conditions (low, medium, and heavy traffic).

Keywords: highway merges, traffic modeling, SUMO, driving policy

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Authors: Zohreh Khojasteh-Ghamari, Takashi Irohara

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One of the efficient ways in supply chain risk management is avoiding the interruption in Supply Chain (SC) before it occurs. Although the majority of the organizations focus on their first-tier suppliers to avoid risk in the SC, studies show that in only 60 percent of the disruption cases the reason is first tier suppliers. In the 40 percent of the SC disruptions, the reason is downstream SC, which is the second tier and lower. Due to the increasing complexity and interrelation of modern supply chains, the SC elements have become difficult to trace. Moreover, studies show that there is a vital need to better understand the integration of risk and visibility, especially in the context of multiple objectives. In this study, we propose a multi-objective programming model to avoid disruption in SC. The objective of this study is evaluating the effect of downstream SCV on managing supply chain risk. We propose a multi-objective mathematical programming model with the objective functions of minimizing the total cost and maximizing the downstream supply chain visibility (SCV). The decision variable is supplier selection. We assume there are several manufacturers and several candidate suppliers. For each manufacturer, our model proposes the best suppliers with the lowest cost and maximum visibility in downstream supply chain. We examine the applicability of the model by numerical examples. We also define several scenarios for datasets and observe the tendency. The results show that minimum visibility in downstream SC is needed to have a safe SC network.

Keywords: downstream supply chain, optimization, supply chain risk, supply chain visibility

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Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

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Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: photovoltaic, urban residences, technology forecasting, prospecting

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Authors: Bi Xiao Fang, Tan Bao Zhen

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Soft skills, core competencies, and generic competencies are exchangeable terminologies often used to represent a similar concept. In the Singapore context, such skills are currently being referred to as Critical Core Skills (CCS). In 2019, SkillsFuture Singapore (SSG) reviewed the Generic Skills and Competencies (GSC) framework that was first introduced in 2016, culminating in the development of the Critical Core Skills (CCS) framework comprising 16 soft skills classified into three clusters. The CCS framework is part of the Skills Framework, and whose stated purpose is to create a common skills language for individuals, employers and training providers. It is also developed with the objectives of building deep skills for a lean workforce, enhance business competitiveness and support employment and employability. This further helps to facilitate skills recognition and support the design of training programs for skills and career development. According to SSG, every job role requires a set of technical skills and a set of Critical Core Skills to perform well at work, whereby technical skills refer to skills required to perform key tasks of the job. There has been an increasing emphasis on soft skills for the future of work. A recent study involving approximately 80 organizations across 28 sectors in Singapore revealed that more enterprises are beginning to recognize that soft skills support their employees’ performance and business competitiveness. Though CCS is of high importance for the development of the workforce’s employability, there is little attention paid to the CCS use and profiling across occupations. A better understanding of how CCS is distributed across the economy will thus significantly enhance SSG’s career guidance services as well as training providers’ services to graduates and workers and guide organizations in their hiring for soft skills. This CCS profiling study sought to understand how CCS is demanded in different occupations. To achieve its research objectives, this study adopted a quantitative method to measure CCS use across different occupations in the Singaporean workforce. Based on the CCS framework developed by SSG, the research team adopted a formative approach to developing the CCS profiling tool to measure the importance of and self-efficacy in the use of CCS among the Singaporean workforce. Drawing on the survey results from 2500 participants, this study managed to profile them into seven occupation groups based on the different patterns of importance and confidence levels of the use of CCS. Each occupation group is labeled according to the most salient and demanded CCS. In the meantime, the CCS in each occupation group, which may need some further strengthening, were also identified. The profiling of CCS use has significant implications for different stakeholders, e.g., employers could leverage the profiling results to hire the staff with the soft skills demanded by the job.

Keywords: employability, skills profiling, skills measurement, soft skills

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Authors: Faozia A. S. Abuhtana, Yahia S. Abujnah, Said O. Gnann

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Ultra High Temperature (UHT) processed milk is widely distributed and preferred in numerous countries all over the world due its relatively high quality and long shelf life. Because of the notable high consumption rate of UHT in Libya in addition to negligible studies related to such product on the local level, this study was designed to assess the shelf life of locally produced as well as imported reconstituted sterilized whole milk samples marketed in Tripoli, Libya . Four locally produced vs. three imported brands were used in this study. All samples were stored at room temperature (25± 2C ) for 8 month long period, and subjected to physical, chemical, microbiological and sensory tests. These tests included : measurement of pH, specific gravity, percent acidity, and determination of fat, protein and melamine content. Microbiological tests included total aerobic count, total psychotropic bacteria, total spore forming bacteria and total coliform counts. Results indicated no detection of microbial growth of any type during the study period, in addition to no detection of melamine in all samples. On the other hand, a gradual decline in pH accompanied with gradual increase in % acidity of both locally produced and imported samples was observed. Such changes in both pH and % acidity reached their lowest and highest values respectively during the 24th week of storage. For instance pH values were (6.40, 6.55, 6.55, 6.15) and (6.30, 6.50, 6.20) for local and imported brands respectively. On the other hand, % acidity reached (0.185, 0181, 0170, 0183) and (0180, 0.180, 0.171) at the 24th week for local and imported brands respectively. Similar pattern of decline was also observed in specific gravity, fat and protein content in some local and imported samples especially at later stages of the study. In both cases, some of the recorded pH values, % acidity, sp. gravity and fat content were in violation of the accepted limits set by Libyan standard no. 356 for sterilized milk. Such changes in pH, % acidity and other UHT sterilized milk constituents during storage were coincided with a gradual decrease in the degree of acceptance of the stored milk samples of both types as shown by sensory scores recorded by the panelists. In either case degree of acceptance was significantly low at late stages of storage and most milk samples became relatively unacceptable after the 18th and 20th week for both untrained and trained panelists respectively.

Keywords: UHT milk, shelf life, quality, gravity, bacteria

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Authors: Felipa de Mello-Sampayo

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The aim of this study is to undertake, from patient’s perspective, the timing and probability of using teledermatology, comparing it with a conventional referral system. The dynamic stochastic model’s main value-added consists of the concrete application to patients waiting for dermatology surgical intervention. Patients with low health level uncertainty must use teledermatology treatment as soon as possible, which is precisely when the teledermatology is least valuable. The results of the model were then tested empirically with the teledermatology network covering the area served by the Hospital Garcia da Horta, Portugal, links the primary care centers of 24 health districts with the hospital’s dermatology department via the corporate intranet of the Portuguese healthcare system. Health level volatility can be understood as the hazard of developing skin cancer and the trend of health level as the bias of developing skin lesions. The results of the survival analysis suggest that the theoretical model can explain the use of teledermatology. It depends negatively on the volatility of patients' health, and positively on the trend of health, i.e., the lower the risk of developing skin cancer and the younger the patients, the more presurgical teledermatology one expects to occur. Presurgical teledermatology also depends positively on out-of-pocket expenses and negatively on the opportunity costs of teledermatology, i.e., the lower the benefit missed by using teledermatology, the more presurgical teledermatology one expects to occur.

Keywords: teledermatology, wait time, uncertainty, opportunity cost, survival analysis

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Authors: Introducing Principles of Land Surveying by Assigning a Practical Project

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A practical project is used in an engineering surveying course to expose sophomore and junior civil engineering students to several important issues related to the use of basic principles of land surveying. The project, which is the design of a two-lane rural highway to connect between two arbitrary points, requires students to draw the profile of the proposed highway along with the existing ground level. Areas of all cross-sections are then computed to enable quantity computations between them. Lastly, Mass-Haul Diagram is drawn with all important parts and features shown on it for clarity. At the beginning, students faced challenges getting started on the project. They had to spend time and effort thinking of the best way to proceed and how the work would flow. It was even more challenging when they had to visualize images of cut, fill and mixed cross sections in three dimensions before they can draw them to complete the necessary computations. These difficulties were then somewhat overcome with the help of the instructor and thorough discussions among team members and/or between different teams. The method of assessment used in this study was a well-prepared-end-of-semester questionnaire distributed to students after the completion of the project and the final exam. The survey contained a wide spectrum of questions from students' learning experience when this course development was implemented to students' satisfaction of the class instructions provided to them and the instructor's competency in presenting the material and helping with the project. It also covered the adequacy of the project to show a sample of a real-life civil engineering application and if there is any excitement added by implementing this idea. At the end of the questionnaire, students had the chance to provide their constructive comments and suggestions for future improvements of the land surveying course. Outcomes will be presented graphically and in a tabular format. Graphs provide visual explanation of the results and tables, on the other hand, summarize numerical values for each student along with some descriptive statistics, such as the mean, standard deviation, and coefficient of variation for each student and each question as well. In addition to gaining experience in teamwork, communications, and customer relations, students felt the benefit of assigning such a project. They noticed the beauty of the practical side of civil engineering work and how theories are utilized in real-life engineering applications. It was even recommended by students that such a project be exercised every time this course is offered so future students can have the same learning opportunity they had.

Keywords: land surveying, highway project, assessment, evaluation, descriptive statistics

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Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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Authors: S. Neelima, P. S. Subramanyam

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A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.

Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction

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Authors: Bi Zhao

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Neural network technology has greatly improved the output of machine translation in terms of both fluency and accuracy, which greatly increases its appeal for young users. The present exploratory study aims to find out how the Chinese undergraduates perceive and use machine translation in their daily life. A survey is conducted to collect data from 100 undergraduate students from multiple Chinese universities and with varied academic backgrounds, including arts, business, science, engineering, and medicine. The survey questions inquire about their use (including frequency, scenarios, purposes, and preferences) of and attitudes (including trust, quality assessment, justifications, and ethics) toward machine translation. Interviews and tasks of evaluating machine translation output are also employed in combination with the survey on a sample of selected respondents. The results indicate that Chinese undergraduate students use machine translation on a daily basis for a wide range of purposes in academic, communicative, and entertainment scenarios. Most of them have preferred machine translation tools, but the availability of machine translation tools within a certain scenario, such as the embedded machine translation tool on the webpage, is also the determining factor in their choice. The results also reveal that despite the reportedly limited trust in the accuracy of machine translation output, most students lack the ability to critically analyze and evaluate such output. Furthermore, the evidence is revealed of the inadequate awareness of ethical responsibility as machine translation users among Chinese undergraduate students.

Keywords: Chinese undergraduates, machine translation, trust, usage

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Authors: M. Kosacka, I. Kudelska

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Vehicle is one of the most influential and complex product worldwide, which affects people’s life, state of the environment and condition of the economy (all aspects of sustainable development concept) during each stage of lifecycle. With the increase of vehicles’ number, there is growing potential for management of End of Life Vehicle (ELV), which is hazardous waste. From one point of view, the ELV should be managed to ensure risk elimination, but from another point, it should be treated as a source of valuable materials and spare parts. In order to obtain materials and spare parts, there are established recycling networks, which are an example of sustainable policy realization at the national level. The basic object in the polish recycling network is dismantling facility. The output material streams in dismantling stations include waste, which very often generate costs and spare parts, that have the biggest potential for revenues creation. Both outputs are stored into warehouses, according to the law. In accordance to the revenue creation and sustainability potential, it has been placed a strong emphasis on storage process. We present the concept of storage method, which takes into account the specific of the dismantling facility in order to support decision-making process with regard to the principles of sustainable development. The method was developed on the basis of case study of one of the greatest dismantling facility in Poland.

Keywords: dismantling, end of life vehicles, sustainability, storage

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Authors: Zhuohan Li, Jing Yang, Yaoyuan Cui

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The gut-brain axis (GBA), a communication network between gut microbiota and the brain, benefits for investigation of brain diseases. Currently, organ chips are considered one of the potential tools for GBA research. However, most of the available GBA chips have limitations in replicating the three-dimensional (3D) growth environment of cells and lack the required cell types for barrier function. In the present study, a microfluidic chip was developed for GBA interaction. Blood-brain barrier (BBB) module was prepared with HBMEC, HBVP, U87 cells and decellularized matrix (dECM). Intestinal epithelial barrier (IEB) was prepared with Caco-2 and vascular endothelial cells and dECM. GBA microfluidic device was integrated with IEB and BBB modules using 3D printing interconnecting microchannel scaffolds. BBB and IEB interaction on this GBA chip were evaluated with lipopolysaccharide (LPS) exposure. The present GBA chip achieved multicellular three-dimensional cultivation. Compared with the co-culture cell model in the transwell, fluorescein was absorbed more slowly by 5.16-fold (IEB module) and 4.69-fold (BBB module) on the GBA chip. Accumulation of Rhodamine 123 and Hoechst33342 was dramatically decreased. The efflux function of transporters on IEB and BBB was significantly increased on the GBA chip. After lipopolysaccharide (LPS) disrupted the IEB, and then BBB dysfunction was further observed, which confirmed the interaction between IEB and BBB modules. These results demonstrated that this GBA chip may offer a promising tool for gut-brain interaction study.

Keywords: decellularized matrix, gut-brain axis, organ-on-chip, three-dimensional printing.

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Authors: Bircan Demiral

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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.

Keywords: cognitive radio network, OFDM, power allocation, water filling

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Ping-Hung Chen, Han-Liang Lin

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Taiwan has formed diverse settlement patterns in different time and space backgrounds. Various socio-network links are created between individuals, families, communities, and societies, and different living cultures are also derived. But rapid urbanization and social structural change have caused the creation of densely-packed assembly housing complexes and made neighborhood community upward developed. This, among others, seemed to have affected neighborhood relationship and also created social problems. To understand the complex relations and socio-spatial structure of the community, it is important to use mixed methods. This research employs the theory of space syntax to analyze the layout and structural indicators of the selected communities in Tainan city. On the other hand, this research does the survey about residents' interactions and the sense of community by questionnaire of the selected communities. Then the mean values of the syntax measures from each community were correlated with the results of the questionnaire using a Pearson correlation to examine how elements in physical design affect the sense of community and neighborhood relationship. In Taiwan, most urban morphology research methods are qualitative study. This paper tries to use space syntax to find out the correlation between the community layout and the neighborhood relationship. The result of this study could be used in future studies or improve the quality of residential communities in Taiwan.

Keywords: community layout, neighborhood relationship, space syntax, mixed-method

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Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: Noel Busch-Armendariz, Caitlin Sulley

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Introduction: This study investigated the development of college experiences, COVID-19 pandemic experiences, alcohol use, and sexual violence. The longitudinal study includes 656 college students living in the same dormitory. Students' alcohol use and social network structure were investigated to better understand the relationship with sexual violence risk. Basic Methodologies: Over two years, students repeated five web-based surveys, including a pre-college survey and surveys during four consecutive semesters. Questions were added in the fourth wave to assess students’ experiences of the COVID-19 pandemic, administered from November-January 2021, including mental and behavioral health. Analyses include the impact of COVID on living arrangements, drinking behaviors, and daily life; experiences of COVID symptoms, testing, and diagnosis, responses to COVID such as social distancing, quarantining, not working, increased health care needs; experience of fear, worry, stigma, emotional well-being, loneliness, and mental health; experiences of financial loss, lack of basic supplies, receiving emotional and financial support, and comparison with academic disengagement. Concluding Statement: Findings and discussion will include strategies to strengthen mental and behavioral health programs and policies.

Keywords: COVID, mental health, substance abuse, college students, sexual misconducts

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Authors: Robel Wondimu Alemayehu, Sihwa Jung, Manwoo Park, Young K. Ju

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Following the aftermath of the 1994 Northridge earthquake, intensive research on beam to column connections is conducted, leading to the current design basis. The current design codes require the use of either a prequalified connection or a connection that passes the requirements of large-scale cyclic qualification test prior to use in intermediate or special moment frames. The second alternative is expensive both in terms of money and time. On the other hand, the maximum beam depth in most of the prequalified connections is limited to 900mm due to the reduced rotation capacity of deeper beams. However, for long span beams the need to use deeper beams may arise. In this study, a beam to column connection detail suitable for deep beams is presented. The connection detail comprises of thicker-tapered beam flange adjacent to the beam to column connection. Within the thicker-tapered flange region, two reduced beam sections are provided with the objective of forming two plastic hinges within the tapered-thicker flange region. In addition, the length, width, and thickness of the tapered-thicker flange region are proportioned in such a way that a third plastic hinge forms at the end of the tapered-thicker flange region. As a result, the total rotation demand is distributed over three plastic zones. Making it suitable for deeper beams that have lower rotation capacity at one plastic hinge. The effectiveness of this connection detail is studied through finite element analysis. For the study, a beam that has a depth of 1200mm is used. Additionally, comparison with welded unreinforced flange-welded web (WUF-W) moment connection and reduced beam section moment connection is made. The results show that the rotation capacity of a WUF-W moment connection is increased from 2.0% to 2.2% by applying the proposed moment connection detail. Furthermore, the maximum moment capacity, energy dissipation capacity and stiffness of the WUF-W moment connection is increased up to 58%, 49%, and 32% respectively. In contrast, applying the reduced beam section detail to the same WUF-W moment connection reduced the rotation capacity from 2.0% to 1.50% plus the maximum moment capacity and stiffness of the connection is reduced by 22% and 6% respectively. The proposed connection develops three plastic hinge regions as intended and it shows improved performance compared to both WUF-W moment connection and reduced beam section moment connection. Moreover, the achieved rotation capacity satisfies the minimum required for use in intermediate moment frames.

Keywords: connections, finite element analysis, seismic design, steel intermediate moment frame

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Authors: Robert Joseph M. Licup

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The deployment of the fifth-generation (5G) mobile system through mmWave frequencies is the new solution in the requirement to provide higher bandwidth readily available for all users. The usage pattern of the mobile users has moved towards either the work from home or online classes set-up because of the pandemic. Previous mobile technologies can no longer meet the high speed, and bandwidth requirement needed, given the drastic shift of transactions to the home. The millimeter-wave (mmWave) underutilized frequency is utilized by the fifth-generation (5G) cellular networks that support multi-gigabit-per-second (Gbps) transmission. However, due to its short wavelengths, high path loss, directivity, blockage sensitivity, and narrow beamwidth are some of the technical challenges that need to be addressed. Different tools, technologies, and scenarios are explored to support network design, accurate channel modeling, implementation, and deployment effectively. However, there is a big challenge on how the consumer will adopt this solution and maximize the benefits offered by the 5G Technology. This research proposes to study the intricacies of technology diffusion, individual attitude, behaviors, and how technology adoption will be attained. The agent based simulation model shaped by the actual applications, technology solution, and related literature was used to arrive at a computational model. The research examines the different attributes, factors, and intricacies that can affect each identified agent towards technology adoption.

Keywords: agent-based model, AnyLogic, 5G O21, 5G mmWave solutions, technology adoption

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Authors: Abdul Mannan Akhtar

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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: data mining, k-means, road traffic accidents, Waze, Weka

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

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Authors: Nazanin Naderi, Milton Smith

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Since worldwide demand for renewable energy is increasing rapidly because of the climate problem and the limitation of fossil fuels, technologies of alternative energy sources have been developed and the electric power network now includes renewable energy resources such as wind energy. Because of the huge advantages that wind energy has, like reduction in natural gas use, price pressure, emissions of greenhouse gases and other atmospheric pollutants, electric sector water consumption and many other contributions to the nation’s economy like job creation it has got too much attention these days from different parts of the world especially in the United States which is trying to provide 20% of the nation’s energy from wind by 2030. This study is trying to evaluate the effect of splitting wind farms on power output. We are trying to find if we can get more output by installing wind turbines in different sites rather than installing all wind turbines in one site. Five potential sites in Texas have been selected as a case study and two years wind data has been gathered for these sites. Wind data are analyzed and effect of correlation between sites on power output has been evaluated. Standard deviation and autocorrelation effect has also been considered for this study. The paper has been organized as follows: After the introduction the second section gives a brief overview of wind analysis. The third section addresses the case study and evaluates correlation between sites, auto correlation of sites and standard deviation of power output. In section four we describe the results.

Keywords: auto correlation, correlation between sites, splitting wind farms, power output, standard deviation

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Authors: S. Mamoucha, J. Rahul, N. Christodoulakis

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Introduction: Nature has been the source of medicinal agents since the dawn of the human existence on Earth. Currently, millions of people, in the developing world, rely on medicinal plants for primary health care, income generation and lifespan improvement. In Greece, more than 5500 plant taxa are reported while about 250 of them are considered to be of great pharmaceutical importance. Among the plants used for medical purposes, Vitex agnus-castus L. (Verbenaceae) is known since ancient times. It is a small tree or shrub, widely distributed in the Mediterranean basin up to the Central Asia. It is also known as chaste tree or monks pepper. Theophrastus mentioned the shrub several times, as ‘agnos’ in his ‘Enquiry into Plants’. Dioscorides mentioned the use of V. agnus-castus for the stimulation of lactation in nursing mothers and the treatment of several female disorders. The plant has important medicinal properties and a long tradition in folk medicine as an antimicrobial, diuretic, digestive and insecticidal agent. Materials and methods: Leaves were cleaned, detached, fixed, sectioned and investigated with light and Scanning Electron Microscopy (SEM). Histochemical tests were executed as well. Specific histochemical reagents (osmium tetroxide, H2SO4, vanillin/HCl, antimony trichloride, Wagner’ s reagent, Dittmar’ s reagent, potassium bichromate, nitroso reaction, ferric chloride and di methoxy benzaldehyde) were used for the sub cellular localization of secondary metabolites. Results: Light microscopical investigations of the elongated leaves of V. agnus-castus revealed three layers of palisade parenchyma, just below the single layered adaxial epidermis. The spongy parenchyma is rather loose. Adaxial epidermal cells are larger in magnitude, compared to those of the abaxial epidermis. Four different types of capitate, secreting trichomes, were localized among the abaxial epidermal cells. Stomata were observed at the abaxial epidermis as well. SEM revealed the interesting arrangement of trichomes. Histochemical treatment on fresh and plastic embedded tissue sections revealed the nature and the sites of secondary metabolites accumulation (flavonoids, steroids, terpenes). Acknowledgment: This work was supported by IKY - State Scholarship Foundation, Athens, Greece.

Keywords: Vitex agnus-castus, leaf anatomy, histochemical reagents, secondary metabolites

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Authors: M. Ekiert, T. Uhl, A. Mlyniec

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Tendons are the biological soft tissue structures composed of collagen, proteoglycan, glycoproteins, water and cells of extracellular matrix (ECM). Tendons, which primary function is to transfer force generated by the muscles to the bones causing joints movement, are exposed to many micro and macro damages. In fact, tendons and ligaments trauma are one of the most numerous injuries of human musculoskeletal system, causing for many people (particularly for athletes and physically active people), recurring disorders, chronic pain or even inability of movement. The number of tendons reconstruction and transplantation procedures is increasing every year. Therefore, studies on soft tissues storage conditions (influencing i.e. tissue aging) seem to be an extremely important issue. In this study, an atomic-scale investigation on the kinetics of decomposition of two selected tendon components – collagen type I (which forms a 60-85% of a tendon dry mass) and elastin protein (which combine with ECM creates elastic fibers of connective tissues) is presented. A molecular model of collagen and elastin was developed based on crystal structure of triple-helical collagen-like 1QSU peptide and P15502 human elastin protein, respectively. Each model employed 4 linear strands collagen/elastin strands per unit cell, distributed in 2x2 matrix arrangement, placed in simulation box filled with water molecules. A decomposition phenomena was simulated with molecular dynamics (MD) method using ReaxFF force field and periodic boundary conditions. A set of NVT-MD runs was performed for 1000K temperature range in order to obtained temperature-depended rate of production of decomposition by-products. Based on calculated reaction rates activation energies and pre-exponential factors, required to formulate Arrhenius equations describing kinetics of decomposition of tested soft tissue components, were calculated. Moreover, by adjusting a model developed for collagen, system scalability and correct implementation of the periodic boundary conditions were evaluated. An obtained results provide a deeper insight into decomposition of selected tendon components. A developed methodology may also be easily transferred to other connective tissue elements and therefore might be used for further studies on soft tissues aging.

Keywords: decomposition, molecular dynamics, soft tissue, tendons

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Authors: Sekkal Nawel

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The Web of Things (WoT), integration of smart technologies from the Internet or network to Web architecture or application, is becoming more complex, larger, and dynamic. The WoT is associated with various elements such as sensors, devices, networks, protocols, data, functionalities, and architectures to perform services for stakeholders. These services operate in the context of the interaction of stakeholders and the WoT elements. Such context is becoming a key information source from which data are of various nature and uncertain, thus leading to complex situations. In this paper, we take interest in the development of intelligent Web services. The key ingredients of this “intelligent” notion are the context diversity, the necessity of a semantic representation to manage complex situations and the capacity to reason with uncertain data. In this perspective, we introduce a multi-layered architecture based on a generic intelligent Web service model dealing with various contexts, which proactively predict future situations and reactively respond to real-time situations in order to support decision-making. For semantic context data representation, we use PR-OWL, which is a probabilistic ontology based on Multi-Entity Bayesian Networks (MEBN). PR-OWL is flexible enough to represent complex, dynamic, and uncertain contexts, the key requirements of the development for the intelligent Web services. A case study was carried out using the proposed architecture for intelligent plant watering to show the role of proactive and reactive contextual reasoning in terms of WoT.

Keywords: smart web service, the web of things, context reasoning, proactive, reactive, multi-entity bayesian networks, PR-OWL

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Authors: Veepaul Kaur Mann Balwinder Singh

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The COVID-19 had an intense impact on several countries across the world. National governments have imposed widespread restrictions to prevent the growth of this pandemic. The new health competitive scenario induced by the COVID-19 crisis raised many issues on how business activities should be reorganized due to the difficulties of physical interactions with distributors, suppliers and customers. The pandemic has particularly affected the whole selling process because of the relevant issues that emerged in managing physical sale channels and interactions with one another, both in the Business-to-Consumer and in the Business-to-Business markets. Recent research about the appropriate actions and strategies that could help firms overcome the crisis has highlighted the key role of digital expertise that may ensure connections and, thus, help business activities run smoothly. This could be true, especially with the occurrence of strong limitations on physical interactions during the COVID-19 pandemic. The catastrophe changes life publically and economically. People are living alone for following the social distancing norms. In that set-up, Digital Marketing is playing an important role in civilization. Anyone can buy any item, pay bills, transfer money and compare items through Digital Marketing without physical interactions. After COVID-19, people will be more aware of health safety and trust. So, through Digital Marketing, organizations can approach customers and provide good service environments. In such a situation, the online network becomes the most important encouraging for online customers to get in contact with the firm and carry out online selling and purchasing activities around the world.

Keywords: COVID-19, business, digital marketing, online customer

Procedia PDF Downloads 45