Search results for: student network

Authors: Betül Ersoy, Deniz Özalp Kizilay, Gül Gümüşer, Fatma Taneli

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Introduction: Peak bone mass is reached in late adolescence in females. Age at menarche influences estrogen exposure, which plays a vital role in bone metabolism. The relationship between age at menarche and bone mineral density (BMD) is still controversial. In this study, we investigated the relationship between age at menarche, BMD, socioeconomic status (SES) and body composition in female university student. Participant and methods: A total of 138 healthy girls at late adolescence period (mean age 20.13±0.93 years, range 18-22) were included in this university school-based cross-sectional study in the urban area western region of Turkey. Participants have been randomly selected to reflect the university students studying in all faculties. We asked relevant questions about socioeconomic status and age at menarche to female university students. Students were grouped into three SES as lower, middle and higher according to the educational and occupational levels of their parents using Hollingshead index. Height and weight were measured. Body Mass Index (BMI) (kg/m2 ) was calculated. Dual energy X-ray absorptiometry (DXA) was performed using the Lunar DPX series, and BMD and body composition were evaluated. Results: The mean age of menarche of female university student included in the study was 13.09.±1.3 years. There was no significant difference between the three socioeconomic groups in terms of height, body weight, age at menarche, BMD [BMD (gr/cm2 ) (L2-L4) and BMD (gr/cm2 ) (total body)], and body composition (lean tissue, fat tissue, total fat, and body fat) (p>0.05). While no correlation was found between the age at menarche and any parameter (p>0.05), a positive significant correlation was found between lean tissue and BMD L2-L4 (r=0.286, p=0.01). When the relationships were evaluated separately according to socioeconomic status, there was a significant correlation between BMDL2-L4 (r: 0.431, p=0.005) and lean tissue in females with low SES, while this relationship disappeared in females with middle and high SES. Conclusion: Age at menarche did not change according to socioeconomic status, nor did BMD and body composition in female at late adolescents. No relationship was found between age at menarche and BMD and body composition determined by DEXA in female university student who were close to reaching peak bone mass. The results suggested that especially BMDL2-L4 might increase as lean tissue increases.

Keywords: bone, osteoposis, menarche, dexa

Procedia PDF Downloads 74

Authors: Vivek Kumar Singh, Tripti Singh

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An ad hoc wireless network consists of mobile networks which creates an underlying architecture for communication without the help of traditional fixed-position routers. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol used for Mobile Ad hoc Network (MANET). Nevertheless, the architecture must maintain communication routes although the hosts are mobile and they have limited transmission range. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks, so that MANET requires different protocols. This paper presents the performance analysis of the routing protocols used various parameter-patterns with Two-ray model.

Keywords: AODV, packet transmission rate, pause time, ZRP, QualNet 6.1

Procedia PDF Downloads 827

Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

Procedia PDF Downloads 116

Authors: Alejandra Yanez, Teresa Benavides, Zita Lopez

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Even before COVID-19, one of the most important challenges that Higher Education faces today is the need for innovative educational methodologies and flexibility. We could all agree that one of the objectives of Higher Education is to provide students with a variety of intellectual and practical skills that, at the same time, will help them develop competitive advantages such as adaptation and critical thinking. Among the strategic objectives of Universidad de Monterrey (UDEM) has been to provide flexibility and satisfaction to students in the delivery modes of the academic offer. UDEM implemented a methodology that combines face to face with synchronous and asynchronous as delivery modes. UDEM goal, in this case, was to implement new technologies and different teaching methodologies that will improve the students learning experience. In this study, the experience of students during courses implemented in new delivery mode was compared with students in courses with traditional delivery modes. Students chose openly either way freely. After everything students around the world lived in 2020 and 2021, one can think that the face to face (traditional) delivery mode would be the one chosen by students. The results obtained in this study reveal that both delivery modes satisfy students and favor their learning process. We will show how the combination of delivery modes provides flexibility, so the proposal is that universities can include them in their academic offer as a response to the current student's learning interests and needs.

Keywords: flexibility, new delivery modes, student satisfaction, academic offer

Procedia PDF Downloads 99

Authors: Liuhui Zhu, Peng Zeng

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The rural revitalization strategy means to take the country and the city on the same level, and achieve urban-rural integration and comprehensive development of rural areas. Beijing-Tianjin-Hebei rural areas have always been the weak links in the region, with prominently uneven development between urban and rural areas. The rural areas need to join the overall regional synergy. Based on the analysis of the characteristics and problems of rural development in the region from the perspective of production-living-ecology space, the paper proposes the township as the basic unit for rural revitalization according to the overall requirements of the rural revitalization strategy. The basic unit helps to realize resource arrangement, functional organization, and collaborative governance organized by the production-living-ecology spatial network. The paper summarizes the planning strategies for the basic unit. Through spatial cognition and spatial reconstruction, the three space is networked through the base, nodes, and connections to improve the comprehensive value of rural areas and achieve the multiple goals of rural revitalization.

Keywords: rural revitalization, Beijing-Tianjin-Hebei region, township level, production-living-ecology spatial network

Procedia PDF Downloads 193

Authors: Kaycee Bills

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Studies have demonstrated that middle and high school students with disabilities are more likely to experience bullying than other student groups. The high rates of bullying victimization observed among youth with disabilities can result in severe socio-emotional consequences. These socio-emotional consequences often manifest in detrimental impacts on the students’ personal relationships. Past studies have indicated that participating in extracurricular athletic activities can have several socio-emotional benefits for students with disabilities. Given the findings of past studies demonstrating the positive relationship between mental health and participation in sports among students with disabilities, it is possible that participating in athletics could have a moderating relationship on the severity of the impact that bullying has on a student’s relationships with family and friends. Using the National Crime Victimization Survey/School Crime Supplement (NCVS/SCS), this study employs an ordinal logistic regression to determine if participation in extracurricular athletic activities mitigates the damaging impact bullying has on the personal relationships with friends and family among students who have disabilities. This study identified statistically significant results suggesting that students with disabilities who participate in athletics reported reduced levels of negative personal relationships resulting from bullying compared to their peers who did not participate in athletics.

Keywords: disability, inclusion, bullying, relationships

Procedia PDF Downloads 181

Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

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Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: causality, defect causes, social network analysis, association rule mining

Procedia PDF Downloads 365

Authors: Salman Naseer, Usman Zafar, Iqra Zafar

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This study explores the implication of Vehicular Adhoc Network (VANET) - in the rural and urban scenarios that is one domain of Mobile Adhoc Network (MANET). VANET provides wireless communication between vehicle to vehicle and also roadside units. The Federal Commission Committee of United States of American has been allocated 75 MHz of the spectrum band in the 5.9 GHz frequency range for dedicated short-range communications (DSRC) that are specifically designed to enhance any road safety applications and entertainment/information applications. There are several vehicular related projects viz; California path, car 2 car communication consortium, the ETSI, and IEEE 1609 working group that have already been conducted to improve the overall road safety or traffic management. After the critical literature review, the selection of routing protocols is determined, and its performance was well thought-out in the urban and rural scenarios. Numerous routing protocols for VANET are applied to carry out current research. Its evaluation was conceded with the help of selected protocols through simulation via performance metric i.e. throughput and packet drop. Excel and Google graph API tools are used for plotting the graphs after the simulation results in order to compare the selected routing protocols which result with each other. In addition, the sum of the output from each scenario was computed to undoubtedly present the divergence in results. The findings of the current study present that DSR gives enhanced performance for low packet drop and high throughput as compared to AODV and DSDV in an urban congested area and in rural environments. On the other hand, in low-density area, VANET AODV gives better results as compared to DSR. The worth of the current study may be judged as the information exchanged between vehicles is useful for comfort, safety, and entertainment. Furthermore, the communication system performance depends on the way routing is done in the network and moreover, the routing of the data based on protocols implement in the network. The above-presented results lead to policy implication and develop our understanding of the broader spectrum of VANET.

Keywords: AODV, DSDV, DSR, Adhoc network

Procedia PDF Downloads 285

Authors: M. A. Mulatu, L. C. Chang, Y. S. Han

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Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.

Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration

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Authors: Phillip Garrad, Saritha Unnikrishnan

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The recent popularity of connected and autonomous vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks have been instigated by both researchers or white-coat hackers and cyber-criminals. As Connected Vehicles move towards full autonomy, the impact of these cyber-attacks also grows. The current research details challenges faced in cybersecurity testing of CAV, including access and cost of the representative test setup. Other challenges faced are lack of experts in the field. Possible solutions to how these challenges can be overcome are reviewed and discussed. From these findings, a software simulated CAV network is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects in penetration testing in other industries. There is an attempt to introduce similar AI models to the software simulation. The expectation from this implementation is to see similar improvements in runtime and efficiency for the CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing

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Authors: Fawaz A. Binsarra, Halim Boussabaine

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The notion of complexity science has been attracting the interest of researchers and professionals due to the need of enhancing the efficiency of understanding complex systems dynamic and structure of interactions. In addition, complexity analysis has been used as an approach to investigate complex systems that contains a large number of components interacts with each other to accomplish specific outcomes and emerges specific behavior. The design process is considered as a complex action that involves large number interacted components, which are ranked as design tasks, design team, and the components of the design process. Those three main aspects of the building design process consist of several components that interact with each other as a dynamic system with complex information flow. In this paper, the goal is to uncover the complex structure of information interactions in building design process. The Investigating of Royal Institute of British Architects Plan Of Work 2013 information interactions as a case study to uncover the structure and building design process complexity using network analysis software to model the information interaction will significantly enhance the efficiency of the building design process outcomes.

Keywords: complexity, process, building desgin, Riba, design complexity, network, network analysis

Procedia PDF Downloads 525

Authors: Nathaniel Evans, Jessica Boersma, Kenneth Kass

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With technology and STEM fields growing every day, there is a significant projected shortfall in qualified cybersecurity workers. As such, it is essential to develop a cybersecurity curriculum that builds skills and cultivates interest in cybersecurity early on. With new jobs being created every day and an already significant gap in the job market, it is vital that educators are pro-active in introducing a cybersecurity curriculum where students are able to learn new skills and engage in an age-appropriate cyber curriculum. Within this growing world of cybersecurity, students should engage in age-appropriate technology and cybersecurity curriculum, starting with elementary school (k-5), extending through high school, and ultimately into college. Such practice will provide students with the confidence, skills, and, ultimately, the opportunity to work in the burgeoning information security field. This paper examines educational methods, pedagogical practices, current cybersecurity curricula, and other educational resources and conducts analysis for false assumptions and developmental appropriateness. It also examines and identifies common mistakes with current cyber curriculum and lessons and discuss strategies for improvement. Throughout the lessons that were reviewed, many common mistakes continued to pop up. These mistakes included age appropriateness, technology resources that were available, and consistency of student’s skill levels. Many of these lessons were written for the wrong grade levels. The ones written for the elementary level all had activities that assumed that every student in the class could read at grade level and also had background knowledge of the cyber activity at hand, which is not always the case. Another major mistake was that these lessons assumed that all schools had any kind of technology resource available to them. Some schools are 1:1, and others are only allotted three computers in their classroom where the students have to share. While coming up with a cyber-curriculum, it has to be kept in mind that not all schools are the same, not every classroom is the same. There are many students who are not reading at their grade level or have not had exposure to the digital world. We need to start slow and ease children into the cyber world. Once they have a better understanding, it will be easier to move forward with these lessons and get the students engaged. With a better understanding of common mistakes that are being made, a more robust curriculum and lessons can be created that no only spark a student’s interest in this much-needed career field but encourage learning while keeping our students safe from cyber-attacks.

Keywords: assumptions, cybersecurity, k-12, teacher

Procedia PDF Downloads 165

Authors: Dariush Jafari, S. Mostafa Nowee

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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: thermodynamic modeling, ANN, solubility, ternary electrolyte system

Procedia PDF Downloads 384

Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

Procedia PDF Downloads 415

Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

Procedia PDF Downloads 135

Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

Procedia PDF Downloads 381

Authors: Diba Arjmandi

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The notion of power and gender domination is one of the inseparable aspects of themes in postmodern literature. The reason of its importance has been discussed frequently since the rise of Michel Foucault and his vantage point toward the circulation of power and the transgression of forces. The language and society act as the basic grounds for the study, as all human beings are bound to the set of rules and norms which shape them in the acceptable way in the macrocosm. How different genders in different positions behave and show reactions to the provocation of social forces and superiority of one another, is of great interest to writers and literary critics. Mamet’s works are noticeable for their controversial but timely themes which illustrate the human conflict with the community and greed for power. Many critics like Christopher Bigsby and Harold Bloom have been discussing Mamet and his ideas during recent years. This paper is the study of Oleanna, Mamet’s masterpiece about teacher-student relationship and the circulation of power between a man and woman. He shows the very breakable boundaries in domination of a gender and the downfall of speech as the consequence of transgression and freedom. The failure of the language the teacher uses and the abuses of his own words by a student who seeks superiority and knowledge are the main subjects of discussion. Supported by the ideas of Foucault, the language Mamet uses to represent his characters becomes the fundamental element of this survey. As a result, language becomes both the means of achievement and also downfall.

Keywords: domination, foucault, language, mamet, oleanna, power, transgression

Procedia PDF Downloads 485

Authors: Min-Woo Kim, Ok-Kyun Na, Jun-Ho Byun, Jong-Hwan Park, Seung-Hwa Yang, Joon-Hong Park, Young-Chul Park

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This study is focused on the comparative analysis and improvement to grasp the flow characteristic of the Anti-Splash Device located under the P/V Valve and new concept design models using the CFD analysis and Artificial Neural Network. The P/V valve located upper deck to solve the pressure rising and vacuum condition of inner tank of the liquid cargo ships occurred oil outflow accident by transverse and longitudinal sloshing force. Anti-Splash Device is fitted to improve and prevent this problem in the shipbuilding industry. But the oil outflow accidents are still reported by ship owners. Thus, four types of new design model are presented by study. Then, comparative analysis is conducted with new models and existing model. Mostly the key criterion of this problem is flux in the outlet of the Anti-Splash Device. Therefore, the flow and velocity are grasped by transient analysis. And then it decided optimum model and design parameters to develop model. Later, it needs to develop an Anti-Splash Device by Flow Test to get certification and verification using experiment equipment.

Keywords: anti-splash device, P/V valve, sloshing, artificial neural network

Procedia PDF Downloads 588

Authors: Ali A. Alshahrani

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This study aims to identify Saudi English as a Foreign Language (EFL) students' perspectives towards using the English language in their studies. The study explores students' self-confident and its association with students' actual performance in English courses in their different academic programs. A multimodal methodology was used to fulfill the research purpose and answer the research questions. A 25-item survey questionnaire and final examination grades were used to collect data. Two hundred forty-one students agreed to participate in the study. They completed the questionnaire and agreed to release their final grades to be a part of the collected data. The data were coded and analyzed by SPSS software. The findings indicated a significant difference in students' performance in English courses between participants' academic programs on the one hand. Students' self-confidence in their English language skills, on the other hand, was not significantly different between participants' academic programs. Data analysis also revealed no correlational relationship between students' self-confidence level and their language skills and their performance. The study raises more questions about other vital factors such as course instructors' views of the materials, faculty members of the target department, family belief in the usefulness of the program, potential employers. These views and beliefs shape the student's preparation process and, therefore, should be explored further.

Keywords: English language intensive program, language proficiency, performance, self-confidence

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Authors: Lucia Antonela Mitidieri

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This research analyzes the application of a model of settlements management based on networks of territorial integration that advocates planning as a cyclical and participatory process that engages early on with civic society, the private sector and the state. Through qualitative methods such as participant observation, interviews with snowball technique and an active research on territories, concrete results of community empowerment are obtained from the promotion of productive enterprises and community spaces of encounter and exchange. Studying the cultural and organizational dimensions of empowerment allows building indicators such as increase of capacities or community cohesion that can lead to support local governments in achieving sustainable urban development for a reduction of urban poverty.

Keywords: community spaces, empowerment, network urbanism, participatory process

Procedia PDF Downloads 330

Authors: Al Huuskonen, Clio Lake, K. M. Naude, Polina Petlitsyna, Sorsha Henning, Julia Wimmers-Klick

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This project presents the outcomes of a community-based participatory action initiative aimed at advocating for equitable healthcare and human rights for trans, two-spirit, and gender-diverse individuals, building upon the University of British Columbia (UBC) Trans Coalition's ongoing efforts. Participatory Action Research (PAR) was chosen as the research method with the goal of improving trans rights on the UBC campus, particularly regarding equitable access to healthcare. PAR involves active community contribution throughout the research process, which in this case was done by way of liaising with student resource groups and advocacy leaders. The goals of this project were as follows: a) identify gaps in gender-affirming healthcare for UBC students by consulting the community and collaborating with UBC services, b) develop an information package outlining provincial and university-based health insurance for gender-affirming care (including hormone therapy and surgeries), FAQs, and resources for UBC's trans students, c) make this package available to UBC students and other national transgender advocacy organizations. The initiative successfully expanded the UBC AMS Student Health and Dental Plan to include gender-affirming procedural coverage, developed a care access guide for students, and advocated for improved health records inclusivity, mechanisms for trans students to report negative care experiences, and increased access to gender-affirming primary care through the on-campus health clinic. Collaboration with other universities' pride organizations and Trans Care BC yielded positive outcomes through broader coalition building and resource sharing. Ongoing efforts are underway to update provincial policies, particularly through expanding coverage under fair pharma care and addressing the compounding effects of the primary care crisis for trans individuals. The project's tangible results include improved trans rights on campus, especially in terms of healthcare access. Expanding healthcare coverage through student care benefits thousands of students, making the ability to undergo important affirming procedures more affordable. Providing students with information on extended coverage options and communication with their doctors further removes barriers to care and positively impacts student wellbeing. This initiative demonstrates the effectiveness of community-based participatory action in advancing equitable healthcare for trans and gender-diverse individuals and serves as a model for other institutions and organizations striving to promote inclusivity and advocate for marginalized populations' rights.

Keywords: equitable healthcare, trans and gender-diverse individuals, inclusivity, participatory action research project

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Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

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In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

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Authors: Hongyun Li, Zhibin Jiang

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The travel of passengers in the urban rail transit network is influenced by changes in network structure and operational status, and the response of individual travel preferences to these changes also varies. Firstly, the influence of the suspension of urban rail transit line sections on passenger travel along the line is analyzed. Secondly, passenger travel trajectories containing multi-dimensional semantics are described based on network UD data. Next, passenger panel data based on spatio-temporal sequences is constructed to achieve frequent passenger clustering. Then, the Graph Convolutional Network (GCN) is used to model and identify the changes in travel modes of different types of frequent passengers. Finally, taking Shanghai Metro Line 11 as an example, the travel behavior patterns of frequent passengers after the Huaqiao section shutdown during the COVID-19 epidemic are analyzed. The results showed that after the section shutdown, most passengers would transfer to the nearest Anting station for boarding, while some passengers would transfer to other stations for boarding or cancel their travels directly. Among the passengers who transferred to Anting station for boarding, most of passengers maintained the original normalized travel mode, a small number of passengers waited for a few days before transferring to Anting station for boarding, and only a few number of passengers stopped traveling at Anting station or transferred to other stations after a few days of boarding on Anting station. The results can provide a basis for understanding urban rail transit passenger travel patterns and improving the accuracy of passenger flow prediction in abnormal operation scenarios.

Keywords: urban rail transit, section shutdown, frequent passenger, travel behavior pattern

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Authors: Tianle Yang

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As a common mental disorder, depression is a leading cause of various diseases worldwide. Early detection and treatment of depression can dramatically promote remission and prevent relapse. However, conventional ways of depression diagnosis require considerable human effort and cause economic burden, while still being prone to misdiagnosis. On the other hand, recent studies report that physical characteristics are major contributors to the diagnosis of depression, which inspires us to mine the internal relationship by neural networks instead of relying on clinical experiences. In this paper, neural networks are constructed to predict depression from physical characteristics. Two initialization methods are examined - Xaiver and Kaiming initialization. Experimental results show that a 3-layers neural network with Kaiming initialization achieves 83% accuracy.

Keywords: depression, neural network, Xavier initialization, Kaiming initialization

Procedia PDF Downloads 127

Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: artificial neural networks, digital image processing, pattern recognition, phytosanitary

Procedia PDF Downloads 326

Authors: William C. Dean

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In the pedagogical sequence of the four- and five-year architectural programs at Alfred State, the fourth-year Urban Design Studio constitutes the first course where students directly explore design issues in the urban context. It is the first large-scale, community-based service learning project for most of the participating students. The students learn key lessons that include the benefits of working both individually and in groups of different sizes toward a common goal, accepting - and responding creatively too - criticism from stakeholders at different points in the project, and recognizing the role that local politics and activism can play in planning for community development. Above all, students are exposed to the importance of good planning in relation to preservation and community revitalization. The purpose of this paper is to discuss the use of community-based service-learning projects in undergraduate architectural education to promote student civic engagement as a means of helping communities visualize potential solutions for revitalizing their neighborhoods and business districts. A series of case studies will be presented in terms of challenges that were encountered, opportunities for student engagement and leadership, and the feasibility of sustainable community development resulting from those projects. The reader will be encouraged to consider how they can recognize needs within their own communities that could benefit from the assistance of architecture students and faculty.

Keywords: urban design, service-learning, civic engagement, community revitalization

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Authors: Afif Saleh Abugharsa

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The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

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Authors: Humeyra Bolakar Tosun

Abstract:

The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model.

Keywords: railway load carrying, neural network, modelling transport, transportation

Procedia PDF Downloads 142

Authors: John M. Lyne, K. Andrea Scott

Abstract:

In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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Authors: Jeremy Bekker, Guy Salazar

Abstract:

Introduction: Nature-exposure interventions on university campuses may serve as an effective addition to overburdened counseling and student support centers. Nature-exposure interventions can work as a preventative well-being enhancement measure on campuses, which can be used adjacently with existing health resources. Specifically, this paper analyzes how spending time in nature impacts psychological well-being, cognitive functioning, and physical health. The poster covers the core findings and recommendations of this paper, which has been previously published in the BYU undergraduate psychology journal Intuition. Research Goals and Method: The goal of this paper was to outline the potential benefits of nature exposure for students’ physical health, mental well-being, and academic success. Another objective of this paper was to outline potential research-based interventions that use campus green spaces to improve student outcomes. Given that the core objective of this paper was to identify and establish research-based nature exposure interventions that could be used on college campuses, a broad literature review focused on these areas. Specifically, the databases Scopus and PsycINFO were used to screen for research focused on psychological well-being, physical health, cognitive functioning, and nature exposure interventions. Outcomes: Nature exposure has been shown to help increase positive affect, life satisfaction, happiness, coping ability and subjective well-being. Further, nature exposure has been shown to decrease negative affect, lower mental distress, reduce cognitive load, and decrease negative psychological symptoms. Finally, nature exposure has been shown to lead to better physical health. Findings and Recommendations: Potential interventions include adding green space to university buildings and grounds, dedicating already natural environments as nature restoration areas, and providing means for outdoor excursions. Potential limitations and suggested areas for future research are also addressed. Many campuses already contain green spaces, defined as any part of an environment that is predominately made of natural elements, and these green spaces comprise an untapped resource that is relatively cheap and simple.

Keywords: nature exposure, preventative care, undergraduate mental health, well-being intervention

Procedia PDF Downloads 211