Search results for: academic learning integration

Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

Procedia PDF Downloads 82

Authors: Owen Cegielski, Kristi Maida, Danny Morales, Sylvia L. Mendez

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This study explores the challenges and threats US secondary educators experience in incorporating culturally relevant education (CRE) practices in their classrooms. CRE is a social justice pedagogical practice used to connect student’s cultural references to academic skills and content, to promote critical reflection, to facilitate cultural competence, and to critique discourses of power and oppression. Empirical evidence on CRE demonstrates positive student educational outcomes in terms of achievement, engagement, and motivation. Additionally, due to the direct focus on uplifting diverse cultures through the curriculum, students experience greater feelings of belonging, increased interest in the subject matter, and stronger racial/ethnic identities. When these teaching practices are in place, educators develop deeper relationships with their students and appreciate the multitude of gifts they (and their families) bring to the classroom environment. Yet, educators regularly report being unprepared to incorporate CRE in their daily teaching practice and identify substantive gaps in their knowledge and skills in this area. Often, they were not exposed to CRE in their educator preparation program, nor do they receive adequate support through school- or district-wide professional development programming. Through a descriptive phenomenological research design, 20 interviews were conducted with a diverse set of secondary school educators to explore the challenges and threats they experience in incorporating CRE practices in their classrooms. The guiding research question for this study is: What are the challenges and threats US secondary educators face when seeking to incorporate CRE practices in their classrooms? Interviews were grounded by the theory of challenge and threat states, which highlights the ways in which challenges and threats are appraised and how resources factor into emotional valence and perception, as well as the potential to meet the task at hand. Descriptive phenomenological data analysis strategies were utilized to develop an essential structure of the educators’ views of challenges and threats in regard to incorporating CRE practices in their secondary classrooms. The attitude of the phenomenological reduction method was adopted, and the data were analyzed through five steps: sense of the whole, meaning units, transformation, structure, and essential structure. The essential structure that emerged was while secondary educators display genuine interest in learning how to successfully incorporate CRE practices, they perceive it to be a challenge (and not a threat) due to lack of exposure which diminishes educator capacity, comfort, and confidence in employing CRE practices. These findings reveal the value of attending to emotional valence and perception of CRE in promoting this social justice pedagogical practice. Findings also reveal the importance of appropriately resourcing educators with CRE support to ensure they develop and utilize this practice.

Keywords: culturally relevant education, descriptive phenomenology, social justice practice, US secondary education

Procedia PDF Downloads 177

Authors: C. Pislaru, A. Shebani

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This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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Authors: Sushish Baral, Pratibha Joshi, Yaman Maharjan

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Glaucoma is a chronic eye condition that causes vision loss that is irreversible. Early detection and treatment are critical to prevent vision loss because it can be asymptomatic. For the identification of glaucoma, multiple deep learning algorithms are used. Transformer-based architectures, which use the self-attention mechanism to encode long-range dependencies and acquire extremely expressive representations, have recently become popular. Convolutional architectures, on the other hand, lack knowledge of long-range dependencies in the image due to their intrinsic inductive biases. The aforementioned statements inspire this thesis to look at transformer-based solutions and investigate the viability of adopting transformer-based network designs for glaucoma detection. Using retinal fundus images of the optic nerve head to develop a viable algorithm to assess the severity of glaucoma necessitates a large number of well-curated images. Initially, data is generated by augmenting ocular pictures. After that, the ocular images are pre-processed to make them ready for further processing. The system is trained using pre-processed images, and it classifies the input images as normal or glaucoma based on the features retrieved during training. The Vision Transformer (ViT) architecture is well suited to this situation, as it allows the self-attention mechanism to utilise structural modeling. Extensive experiments are run on the common dataset, and the results are thoroughly validated and visualized.

Keywords: glaucoma, vision transformer, convolutional architectures, retinal fundus images, self-attention, deep learning

Procedia PDF Downloads 182

Authors: Aline F. Marcon, Eduardo F. da Silva, Marina Bouzon

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The impact of lean management on environmental sustainability is the research line that receives the most attention from academicians. Therefore, the social dimension of sustainable development has so far received less attention. This paper aims to evaluate the impact of intra-plant lean manufacturing practices on social sustainability indicators extracted from the Global Reporting Initiative (GRI) parameters. The method is two-phased, including MCDM approach to uncover the most relevant practices regarding social performance and Interpretive Structural Modeling (ISM) method to reveal the structural relationship among lean practices. Professionals from the academic and industrial fields answered the questionnaires. From the results of this paper, it is possible to verify that practices such as “Safety Improvement Programs”, “Total Quality Management” and “Cross-functional Workforce” are the ones which have the most positive influence on the set of GRI social indicators.

Keywords: indicators, ISM, lean, social, sustainability

Procedia PDF Downloads 137

Authors: Vanessa Kummer, Maik Meusel

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Real estate demand estimates are typically derived from transaction data. However, in regions with excess demand, transactions are driven by supply and therefore do not indicate what people are actually looking for. To estimate the demand for housing in Switzerland, search subscriptions from all important Swiss real estate platforms are used. These data do, however, suffer from missing information—for example, many users do not specify how many rooms they would like or what price they would be willing to pay. In economic analyses, it is often the case that only complete data is used. Usually, however, the proportion of complete data is rather small which leads to most information being neglected. Also, the data might have a strong distortion if it is complete. In addition, the reason that data is missing might itself also contain information, which is however ignored with that approach. An interesting issue is, therefore, if for economic analyses such as the one at hand, there is an added value by using the whole data set with the imputed missing values compared to using the usually small percentage of complete data (baseline). Also, it is interesting to see how different algorithms affect that result. The imputation of the missing data is done using unsupervised learning. Out of the numerous unsupervised learning approaches, the most common ones, such as clustering, principal component analysis, or neural networks techniques are applied. By training the model iteratively on the imputed data and, thereby, including the information of all data into the model, the distortion of the first training set—the complete data—vanishes. In a next step, the performances of the algorithms are measured. This is done by randomly creating missing values in subsets of the data, estimating those values with the relevant algorithms and several parameter combinations, and comparing the estimates to the actual data. After having found the optimal parameter set for each algorithm, the missing values are being imputed. Using the resulting data sets, the next step is to estimate the willingness to pay for real estate. This is done by fitting price distributions for real estate properties with certain characteristics, such as the region or the number of rooms. Based on these distributions, survival functions are computed to obtain the functional relationship between characteristics and selling probabilities. Comparing the survival functions shows that estimates which are based on imputed data sets do not differ significantly from each other; however, the demand estimate that is derived from the baseline data does. This indicates that the baseline data set does not include all available information and is therefore not representative for the entire sample. Also, demand estimates derived from the whole data set are much more accurate than the baseline estimation. Thus, in order to obtain optimal results, it is important to make use of all available data, even though it involves additional procedures such as data imputation.

Keywords: demand estimate, missing-data imputation, real estate, unsupervised learning

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Authors: Flavia Schuler Gomes, Cristina Brito Dias, Emily Schuler

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One of the emerging themes in modern society is migration. What in the past was a route mostly traveled by men, is currently carried out by women and even children. In this sense, the objective of this research was to understand the experiences and repercussions of the migration in the life of young Brazilians who went to Switzerland. The specific objectives were: to know the causes and consequences of migration; how was the adaptation in the country in emotional and educational terms; as how the interviewees feel the impact of living with two cultures simultaneously. The research had a qualitative methodology. The participants were eight young men and women, between the ages of 18 and 25, who migrated to Switzerland as a child. The instrument used was interview technique of life history. The collected data were analyzed through the thematic content analysis. The results indicate that the young people migrated to accompany their mothers; in terms of nationality, two participants feel completely Swiss, and six believe they share Swiss and Brazilian aspects. None of the participants followed an academic career, having secondary education.

Keywords: adaptation, children, culture, migration

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Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: Seyyed Abdollah Hojjati

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Review in the areas of secondary education; it is a kind of comparative requires very careful scrutiny in educational structure of different countries,In upcoming review of the basic structure of our educational system in Islamic republic of Iran with somedeveloped countries in the world, Analyzing of strengthsand weaknesses in main areas, A simple review of the above methods do not consider this particular community, Modifythe desired result can be expressed in the secondary school curriculum and academic guidance of under graduate students in a skill-driven and creativity growth, It not just improves the health and dynamism of this period and increases the secondary teachers' authority and the relationship between teacher and student in this course will be meaningful and attractive, But with reduced of false prosperity and guaranteed institutes and quizzes, areas will be provided for students to enjoy the feeling ofthe psychological comfort and to have the highest growth of creativity .

Keywords: comparative, curriculum of secondary education, curriculum, Iran, developed countries

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Authors: Ioanna Garefi, Irene Kalemaki

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Education is not solely about preparing young people for the world of work but also about equipping them with competences that will enable them to become socially proactive, empowered, responsible, and engaged citizens who will collectively contribute to and benefit from an inclusive and sustainable future. Hence, progress assessment towards competence development is an ongoing process where continuous efforts are needed. This paper abstract presents the work of the H2020 NEMESIS project that aims to investigate, experiment and co-create together with schools a model for introducing and embedding social innovation education (SIE henceforth) in European primary and secondary schools. All in all, during the 2018-2019 academic year, 8 schools from 5 European countries involving 56 teachers, 1030 students, and 80 external stakeholders, experimented with different methodologies for embedding SIE in their contexts. This paper captures briefly the impact of these efforts towards the cultivation and progression of students’ social innovation (SI henceforth) competences. As part of the model, 14 SI competences, whose progress was evaluated, have been introduced falling under 3 interrelated categories: competences for identifying opportunities for social and collective value creation, competences for developing collaborations and building meaningful relations and competences for taking action both on an individual and collective level. Methodologically wise, the evaluation strategy employed was informed by a realist approach, enabling the researchers to go beyond synthesizing 'what happened' and towards understanding 'why it happened', delving into ‘what works, for whom and in what circumstances’. The reason for choosing such an approach was because it goes beyond attempting to answer the basic yes or no question of evaluation and focus on an ‘explanatory quest’ tracing the limits of when and where intervention is effective. A rich mix of sources of evidence have been employed, from focus groups with 80 people from the 5 EU countries to an online survey to 206 students, classroom observations, students’ narratives granting them with the opportunity to freely express their opinions, short stories letting students express their feelings through their imagination and also, drawings so that younger children can express their perception of reality. All these evidences offered insights on the impact of SIE on the development of students’ competences. Research findings showed that students progressed in all 14 SI competences through their involvement in the different activities. This positive progression is attributed to the model’s three core principles: 1) the student-centered approach, rendering students active and self-determined producers of their own learning, 2) the co-creation process fostering intergenerational interactions, empowering thus students by making their voices heard and valued and also, 3) the transformative social action whereby through their projects, students are able to witness the impact they are bringing about with their actions. Concluding, these initial findings, together with the forthcoming evaluation research to a pool of 30 schools around Europe, have the potential to raise the dynamics of the under-investigated field of SIE and encourage its embeddedness in more schools around Europe.

Keywords: competence development, education, social innovation, students

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Authors: Chanchan Liu

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In the process of urbanization in China, the rapid development of urban construction has been achieved, but a large number of rural buildings still continue the construction mode many years ago. This paper mainly analyzes the rural residential buildings in the hot summer and cold winter regions analyze the active and passive technologies of the buildings. It explored the feasibility of realizing the sustainable development of rural buildings in an economically reasonable range, using mainly passive technologies, innovative building design methods, reducing the buildings’ demand for conventional energy, and supplementing them with renewable energy sources. On this basis, appropriate technology and regional characteristics are proposed to keep the rural architecture retain its characteristics in the development process. It is hoped that this exploration can provide reference and help for the development of rural buildings in the hot summer and cold winter regions.

Keywords: the rural building, active technology, passive technology, sustainable development

Procedia PDF Downloads 207

Authors: Banan Aljumaiah

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In recent years, the construction industry has leveraged the information revolution, which makes it possible to view the entire construction process of new buildings before they are built with the advent of Building Information Modelling (BIM). Although BIM is an integration of the building model with the data and documents about the building, however, its implementation is limited to individual buildings missing the large picture of the city infrastructure. This limitation of BIM led to the birth of City Information Modelling. Three years ago, Eastern Province Municipality (EPM) in Saudi Arabia mandated that all major projects be delivered with collaborative 3D BIM. After three years of implementation, EPM started to implement City Information Modelling (CIM) as a part of the Smart City Plan to link infrastructure and public services and modelling how people move around and interact with the city. This paper demonstrates a local case study of BIM implementation in EPM and its future as a part of project management automation; the paper also highlights the ambitious plan of EPM to transform CIM towards building smart cities.

Keywords: BIM, BIM to CIM

Procedia PDF Downloads 132

Authors: Monica Sanchez

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What responsibility does urban planning have on climate changes? How does the territory give us answers of resilience? Historically, urban plans have civilized territories: waters are channeled, grounds are sealed, foreign species are incorporated, native ones are extinguished, and/or enclosed spaces are heated or cooled. Socially this facilitates coexistence, but in turn brings negative environmental consequences. The past fifty years, mankind has tried to redirect these consequences through different strategies. Research studies produced strategies designed to alleviate climate change. Exploring the nature of territories has been incorporated in urban planning to discover natures response. The case to be studied is Santiago, Chile: for its combined impacts of climate change and the significant response by this city on climate governance in the last decades. Warmer areas in Santiago are seen in the areas of high-density buildings such as the commune of Recoleta, while the coldest are characterized by the predominance of low residential densities as the commune of Providencia. These two communes are separated and complemented by an undulating body that comes from the Andes mountains called San Cristobal Hill. What if the hill were taken into account when making roads, zoning and buildings? Was it difficult to prolong in the urban plans the hill characteristics to the city solving the intersection with other natural areas? Apparently it was, because the projected-profile informs us that the planned strategies used correspond to the same operations used in the flat areas of Santiago. This research focuses on: explaining the geographic relationships between city-hill; explaining the planning process around the hill with a morphological analysis; evaluating how the hill has been considered the in the city in the plans that intended to cushion the environmental impacts and studying what is missing on the hill and city to strengthen their integration. Therefore, the research will have different scales of understanding: addressing territorial scale -understanding the vegetation, topography and hydrology; a city scale -analyzing urban plans that Santiago has dealt with the environment and city; and a local scale -studying the integration and public spaces and coverage- norms of the adjacent communes. The expected outcome is to decipher possible deficits and capabilities of the current urban plans for climate change. It is anticipated that the hill and valley is now trying to reconcile after such a long separation. Yet it seems that never will prevail all the Rules of Nature, but the Urban Rules. The plans will require pruning, irrigation, control of invasive alien species and public safety standards, but will be rejoining a dose of nature with the building environment -this will protect us better from it from the time that we feared from it and knew little about it. Today we know a little more, enough to adapt to the process. Although nature is not perceived and we ignore it, it has a remarkable ability to respond.

Keywords: resilience, climate change, urban plans, land use, hills and cities, heat islands, morphology

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Authors: Jasraj Meena, Malay Kumar, Manu Vardhan

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Cloud computing is a new technology in industry and academia. The technology has grown and matured in last half decade and proven their significant role in changing environment of IT infrastructure where cloud services and resources are offered over the network. Cloud technology enables users to use services and resources without being concerned about the technical implications of technology. There are substantial research work has been performed for the usage of cloud computing in educational institutes and majority of them provides cloud services over high-end blade servers or other high-end CPUs. However, this paper proposes a new stack called “CiCKAStack” which provide cloud services over unutilized computing resources, named as commodity computers. “CiCKAStack” provides IaaS and PaaS using underlying commodity computers. This will not only increasing the utilization of existing computing resources but also provide organize file system, on demand computing resource and design and development environment.

Keywords: commodity computers, cloud-computing, KVM, CloudStack, AppScale

Procedia PDF Downloads 261

Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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Authors: Hafid Smaili, Wilfred Rouwhorst, Paul Frost

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The trend of recent accident and incident cases worldwide show that the state-of-the-art automation and operations, for current and future demanding operational environments, does not provide the desired level of operational safety under crew peak workload conditions, specifically in complex situations such as loss-of-control in-flight (LOC-I). Today, the short term focus is on preparing crews to recognise and handle LOC-I situations through upset recovery training. This paper describes the cockpit integration aspects and piloted assessment of both a manually assisted and automatic upset detection and recovery system that has been developed and demonstrated within the European Advanced Cockpit for Reduction Of StreSs and workload (ACROSS) programme. The proposed system is a function that continuously monitors and intervenes when the aircraft enters an upset and provides either manually pilot-assisted guidance or takes over full control of the aircraft to recover from an upset. In order to mitigate the highly physical and psychological impact during aircraft upset events, the system provides new cockpit functionalities to support the pilot in recovering from any upset both manually assisted and automatically. A piloted simulator assessment was made in Oct-Nov 2015 using ten pilots in a representative civil large transport fly-by-wire aircraft in terms of the preference of the tested upset detection and recovery system configurations to reduce pilot workload, increase situational awareness and safe interaction with the manually assisted or automated modes. The piloted simulator evaluation of the upset detection and recovery system showed that the functionalities of the system are able to support pilots during an upset. The experiment showed that pilots are willing to rely on the guidance provided by the system during an upset. Thereby, it is important for pilots to see and understand what the aircraft is doing and trying to do especially in automatic modes. Comparing the manually assisted and the automatic recovery modes, the pilot’s opinion was that an automatic recovery reduces the workload so that they could perform a proper screening of the primary flight display. The results further show that the manually assisted recoveries, with recovery guidance cues on the cockpit primary flight display, reduced workload for severe upsets compared to today’s situation. The level of situation awareness was improved for automatic upset recoveries where the pilot could monitor what the system was trying to accomplish compared to automatic recovery modes without any guidance. An improvement in situation awareness was also noticeable with the manually assisted upset recovery functionalities as compared to the current non-assisted recovery procedures. This study shows that automatic upset detection and recovery functionalities are likely to positively impact the operational safety by means of reduced workload, improved situation awareness and crew stress reduction. It is thus believed that future developments for upset recovery guidance and loss-of-control prevention should focus on automatic recovery solutions.

Keywords: aircraft accidents, automatic flight control, loss-of-control, upset recovery

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Authors: Aisha Iddrisu

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The proliferation of cyberviolence in the wave of increased social media consumption calls for immediate attention both at the local and global levels. With over 4.70 billion social media users worldwide and 8.8 social media users in Ghana, various forms of violence have become the order of the day in most countries and communities. Cyber violence is defined as producing, retrieving, and sharing of hurtful or dangerous online content to cause emotional, psychological, or physical harm. The urgency and severity of cyber violence have led to the enactment of laws in various countries though lots still need to be done, especially in Ghana. In Ghana, studies on cyber violence have not been extensively dealt with. Existing studies concentrate only on one form or the other form of cyber violence, thus cybercrime and cyber bullying. Also, most studies in Africa have not explored cyber violence forms using empirical theories and the few that existed were qualitatively researched, whereas others examine the effect of cyber violence rather than examining why those who involve in it behave the way they behave. It is against this backdrop that this study aims to examine various cyber violence behaviour among social media users in Ghana by applying the theory of Self-control and Social control theory. This study is important for the following reasons. The outcome of this research will help at both national and international level of policymaking by adding to the knowledge of understanding cyberviolence and why people engage in various forms of cyberviolence. It will also help expose other ways by which such behaviours are enforced thereby serving as a guide in the enactment of the rightful rules and laws to curb such behaviours. It will add to literature on consequences of new media. This study seeks to confirm or reject to the following research hypotheses. H1 Social media usage has direct significant effect of cyberviolence behaviours. H2 Ineffective parental management has direct significant positive relation to Low self-control. H3 Low self-control has direct significant positive effect on cyber violence behaviours among social, H4 Differential association has significant positive effect on cyberviolence behaviour among social media users in Ghana. H5 Definitions have a significant positive effect on cyberviolence behaviour among social media users in Ghana. H6 Imitation has a significant positive effect on cyberviolence behaviour among social media users in Ghana. H7 Differential reinforcement has a significant positive effect on cyberviolence behaviour among social media users in Ghana. H8 Differential association has a significant positive effect on definitions. H9 Differential association has a significant positive effect on imitation. H10 Differential association has a significant positive effect on differential reinforcement. H11 Differential association has significant indirect positive effects on cyberviolence through the learning process.

Keywords: cyberviolence, social media users, self-control theory, social learning theory

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Authors: Fatemeh Safdari, Amirnaser Shamkhali, Gholamabbas Parsafar

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Carbon nanostructures are of great importance in academic research and industry, which can be mentioned to chemical sensors, catalytic processes, pharmaceutical and environmental issues. Common point in all of these applications is the occurrence of adsorption of molecules on these structures. Important carbon nanostructures in this case are mainly nanotubes and graphene. To modify pure graphene, recently, many experimental and theoretical studies have carried out to investigate of metal adsorption on graphene. In this work, the adsorption of CO molecules on pure graphene and on metal adatom on graphene surface has been simulated based on density functional theory (DFT). All calculations were performed by PBE functional and Troullier-Martins pseudopotentials. Density of states (DOS) for graphene-CO, graphen and CO around the Fermi energy has been moved and very small mixing occured which implies the physisorption of CO on the bare graphen surface. While, the results have showed that CO adsorption on transition-metal adatom on graphene surface is chemisorption.

Keywords: adsorption, density functional theory, graphene, metal adatom

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Authors: J. Hash, J. Converse, L. Gibson

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Plant medicines are of growing interest for addressing mental health concerns. Ayahuasca, a traditional plant-based medicine, has established itself as a powerful way of processing trauma and precipitating healing and mood stabilization. Eye Movement Desensitization and Reprocessing (EMDR) is another treatment modality that aids in the rapid processing and resolution of trauma. We investigated group EMDR therapy, G-TEP, as a preparatory practice before Ayahuasca ceremonies to determine if the combination of these modalities supports participants in their journeys of letting go of past experiences negatively impacting mental health, thereby accentuating the healing of the plant medicine. We surveyed 96 participants (51 experimental G-TEP, 45 control grounding prior to their ceremony; age M=38.6, SD=9.1; F=57, M=34; white=39, Hispanic/Latinx=23, multiracial=11, Asian/Pacific Islander=10, other=7) in a pre-post, mixed methods design. Participants were surveyed for demographic characteristics, symptoms of PTSD and cPTSD (International Trauma Questionnaire (ITQ), depression (Beck Depression Inventory, BDI), and stress (Perceived Stress Scale, PSS) before the ceremony and at the end of the ceremony weekend. Open-ended questions also inquired about their expectations of the ceremony and results at the end. No baseline differences existed between the control and experimental participants. Overall, participants reported a decrease in meeting the threshold for PTSD symptoms (p<0.01); surprisingly, the control group reported significantly fewer thresholds met for symptoms of affective dysregulation, 2(1)=6.776, p<.01, negative self-concept, 2 (1)=7.122, p<.01, and disturbance in relationships, 2 (1)=9.804, p<.01, on subscales of the ITQ as compared to the experimental group. All participants also experienced a significant decrease in scores on the BDI, t(94)=8.995, p<.001, and PSS, t(91)=6.892, p<.001. Similar to patterns of PTSD symptoms, the control group reported significantly lower scores on the BDI, t(65.115)=-2.587, p<.01, and a trend toward lower PSS, t(90)=-1.775, p=.079 (this was significant with a one-sided test at p<.05), compared to the experimental group following the ceremony. Qualitative interviews among participants revealed a potential explanation for these relatively higher levels of depression and stress in the experimental group following the ceremony. Many participants reported needing more time to process their experience to gain an understanding of the effects of the Ayahuasca medicine. Others reported a sense of hopefulness and understanding of the sources of their trauma and the necessary steps to heal moving forward. This suggests increased introspection and openness to processing trauma, therefore making them more receptive to their emotions. The integration process of an Ayahuasca ceremony is a week- to months-long process that was not accessible in this stage of research, yet it is an integral process to understanding the full effects of the Ayahuasca medicine following the closure of a ceremony. Our future research aims to assess participants weeks into their integration process to determine the effectiveness of EMDR, and if the higher levels of depression and stress indicate the initial reaction to greater awareness of trauma and receptivity to healing.

Keywords: ayahuasca, EMDR, PTSD, mental health

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Authors: Bennabhaktula Lavanya

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The study of women, their societal roles, and their importance has been a subject of intense discussion and scholarly inquiry. Researchers have diligently endeavoured to understand the influence of women in the domains of society, economy, culture, and politics, as well as the broader ramifications for society. Women's history aims to improve existing historical accounts by analyzing political institutions, economic events, social frameworks, cultural trends, and primary sources that have historically underprivileged women. The extensive research undertaken has resulted in the formation and recognition of women's history as a valid and unique subject of study within history. The Present paper analyses the academic discipline of Women's History and investigates its changing patterns. Tries to address the challenge of transforming the prevailing historical tradition by using innovative methods and frameworks and analyses the interests, experiences, and achievements of women in order to recreate their perceptions and priorities. The paper also examines the principles of Women's History, Gender Studies, and Feminist History and varying perspectives on women.

Keywords: history, perspectives, research, women

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Authors: Halima Zaman

Abstract:

This paper identifies real-life challenges faced by non-English-speaking learners. The author focuses on challenges both inside and outside the classroom. A qualitative approach has been applied to conduct the study with two different groups of ESOL (English to Speakers of Other Languages) learners. The author pays attention to the reasons behind the difficulties in controlling the learners’ focus within the classroom. Learners’ lifestyles, motivations, and previous educational backgrounds have been considered while determining the challenges they face within the classroom. Some existing challenges of teaching English to adults have been discussed in this paper; however, the primary focus is to observe those two groups of learners to identify their challenges. In this paper, the author has applied the academic knowledge of her Master of Arts in English Language teaching program to support and strengthen the observation of this case study. The paper ends with a number of recommendations that can be beneficial for newcomers to ESOL teaching and a scope of further exploratory research.

Keywords: ESOL, challenges, classroom, motivation, adult learners, teaching

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Authors: Jonathan Gong

Abstract:

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

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Mahmood Dehqan, Peyman Peyvasteh

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In recent years there has been a growing interest in issues concerning the impact of sociocultural theory (SCT) of learning on different aspects of second/foreign language learning. This study aimed to find the possible effects of sociocultural teaching techniques on reading strategy of EFL learners. Indeed, the present research compared the impact of peer and teacher scaffolding on EFL learners’ reading strategy use across two proficiency levels. To this end, a pre-test post-test quasi-experimental research design was used and two instruments were utilized to collect the data: Nelson English language test and reading strategy questionnaire. Ninety five university students participated in this study were divided into two groups of teacher and peer scaffolding. Teacher scaffolding group received scaffolded help from the teacher based on three mechanisms of effective help within ZPD: graduated, contingent, dialogic. In contrast, learners of peer scaffolding group were unleashed from the teacher-fronted classroom as they were asked to carry out the reading comprehension tasks with the feedback they provided for each other. Results obtained from ANOVA revealed that teacher scaffolding group outperformed the peer scaffolding group in terms of reading strategy use. It means teacher’s scaffolded help provided within the learners’ ZPD led to better reading strategy improvement compared with the peer scaffolded help. However, the interaction effect between proficiency factor and teaching technique was non-significant, leading to the conclusion that strategy use of the learners was not affected by their proficiency level in either teacher or peer scaffolding groups.

Keywords: peer scaffolding, proficiency level, reading strategy, sociocultural theory, teacher scaffolding

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Authors: D. Ponnamma, E. Alper, P. Sharma, M. A. AlMaadeed

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Integrating efficient energy harvesting materials into soft, flexible and eco-friendly substrates could yield significant breakthroughs in wearable and flexible electronics. Here we present a tri phasic filler combination of one-dimensional titanium dioxide nanotubes, two-dimensional reduced graphene oxide, and three-dimensional strontium titanate, introduced into a semi crystalline polymer, Poly(vinylidene fluoride-co-hexafluoropropylene). Simple mixing method is adopted for the composite fabrication after ensuring a high interaction among the various fillers. The films prepared were mainly tested for the piezoelectric responses and the mechanical stretchability. The results show that the piezoelectric constant has increased while changing the total filler concentration. We propose an integration of these materials in fabricating energy conversion devices useful in flexible and wearable electronics.

Keywords: dielectric property, hydrothermal growth, piezoelectricity, polymer nanocomposites

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Authors: Shimaa Nagro, Russell Campion

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Mobile devices are becoming ever more widely available, with growing functionality, and they are increasingly used as enabling technology to give students access to educational material anytime and anywhere. However, the design of educational material's user interfaces for mobile devices is beset by many unresolved research problems such as those arising from constraints associated with mobile devices or from issues linked to effective learning. The proposed research aims to produce: (i) a method framework for the design and evaluation of educational material’s interfaces to be delivered on mobile devices, in multimedia form based on Human Computer Interaction strategies; and (ii) a software tool implemented as a fast-track alternative to use the method framework in full. The investigation will combine qualitative and quantitative methods, including interviews and questionnaires for data collection and three case studies for validating the method framework. The method framework is a framework to enable an educational designer to effectively and efficiently create educational multimedia interfaces to be used on mobile devices by following a particular methodology that contains practical and usable tools and techniques. It is a method framework that accepts any educational material in its final lesson plan and deals with this plan as a static element, it will not suggest any changes in any information given in the lesson plan but it will help the instructor to design his final lesson plan in a multimedia format to be presented in mobile devices.

Keywords: mobile learning, M-Learn, HCI, educational multimedia, interface design

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Authors: Henrique C. C. Andrade, Ana Beatriz C. G. Silva, Fernando Luiz B. Ribeiro, Samir Maghous, Jose Claudio F. Telles, Eduardo M. R. Fairbairn

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The present paper aims at developing a parallel computational model for numerical simulation of poromechanics analyses of heterogeneous reservoirs. In the context of macroscopic poroelastoplasticity, the hydromechanical coupling between the skeleton deformation and the fluid pressure is addressed by means of two constitutive equations. The first state equation relates the stress to skeleton strain and pore pressure, while the second state equation relates the Lagrangian porosity change to skeleton volume strain and pore pressure. A specific algorithm for local plastic integration using a tangent operator is devised. A modified Cam-clay type yield surface with associated plastic flow rule is adopted to account for both contractive and dilative behavior.

Keywords: finite element method, poromechanics, poroplasticity, reservoir analysis

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Authors: Hao Xiaohong, Wu Zongxiang, Chen Xuefeng

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With the high power density and high integration of electronic devices, their heat flux has been increasing rapidly. Therefore, an effective cooling technology is essential for the reliability and efficient operation of electronic devices. Liquid cooling is studied increasingly widely for its higher heat transfer efficiency. Serpentine channels are superior in the augmentation of single-phase convective heat transfer because of their better channel velocity distribution. In this paper, eight different frame sizes water-cooled serpentine channel heat sinks are designed to study the heat transfer and pressure drop characteristics. With water as the working fluid, experiment setup is established and the results showed the effect of different channel width, fin thickness and number of channels on thermal resistance and pressure drop.

Keywords: heat transfer, experiment, serpentine heat sink, pressure drop

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Authors: Behailu Bezabih Ayele

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Illustrative expressions in art education and in overall learning are being given increasing attention in the transmission of knowledge. The objective of this paper, therefore, is to present an analysis of graffiti on school desks-a way of smuggling knowledge on the edge of classroom education and learning. The methodological approach focuses on the systematic collection and selection of desk graffiti. Four schools are chosen to reflect socioeconomic status and gender composition. The analysis focused on the categorization of graffiti by genre. This was followed by an analysis of the style, intensity as well as content of the messages in terms of overall social impacts. The paper grounds the analysis by reviewing the literature on modern education and art education in the Ethiopian context, as well as the place of desk graffiti. The findings generally show that the school desks and the school environment, by and large, have managed to serve as vessels through which formal and informal knowledge is acquired, transmitted, engrained into the students and transformed into messages by the students. The desks have also apparently served as a springboard to maximize the interfaces between several ideas and disciplines and communications. However, the very fact that the desks serve as massive channels of expression and knowledge transmission also points to a lack of breadth availability of channels of expression, perhaps confounding the ability of classrooms as means of outlet of expression and documentation for the students. This points to the need for efforts in education policy and funding of artistic endeavors for young students.

Keywords: artistic expression, desk graffiti, education, school children, Ethiopia

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Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

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Authors: Tarek Saadawi, Rosario Gennaro, Jonathan Akeley

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There is rapidly growing demand for professionals to fill positions in Cybersecurity. This is recognized as a national priority both by government agencies and the private sector. Cybersecurity is a very wide technical area which encompasses all measures that can be taken in an electronic system to prevent criminal or unauthorized use of data and resources. This requires defending computers, servers, networks, and their users from any kind of malicious attacks. The need to address this challenge has been recognized globally but is particularly acute in the New York metropolitan area, home to some of the largest financial institutions in the world, which are prime targets of cyberattacks. In New York State alone, there are currently around 57,000 jobs in the Cybersecurity industry, with more than 23,000 unfilled positions. The Cybersecurity Program at City College is a collaboration between the Departments of Computer Science and Electrical Engineering. In Fall 2020, The City College of New York matriculated its first students in theCybersecurity Master of Science program. The program was designed to fill gaps in the previous offerings and evolved out ofan established partnership with Facebook on Cybersecurity Education. City College has designed a program where courses, curricula, syllabi, materials, labs, etc., are developed in cooperation and coordination with industry whenever possible, ensuring that students graduating from the program will have the necessary background to seamlessly segue into industry jobs. The Cybersecurity Program has created multiple pathways for prospective students to obtain the necessary prerequisites to apply in order to build a more diverse student population. The program can also be pursued on a part-time basis which makes it available to working professionals. Since City College’s Cybersecurity M.S. program was established to equip students with the advanced technical skills needed to thrive in a high-demand, rapidly-evolving field, it incorporates a range of pedagogical formats. From its outset, the Cybersecurity program has sought to provide both the theoretical foundations necessary for meaningful work in the field along with labs and applied learning projects aligned with skillsets required by industry. The efforts have involved collaboration with outside organizations and with visiting professors designing new courses on topics such as Adversarial AI, Data Privacy, Secure Cloud Computing, and blockchain. Although the program was initially designed with a single asynchronous course in the curriculum with the rest of the classes designed to be offered in-person, the advent of the COVID-19 pandemic necessitated a move to fullyonline learning. The shift to online learning has provided lessons for future development by providing examples of some inherent advantages to the medium in addition to its drawbacks. This talk will address the structure of the newly-implemented Cybersecurity Master’s Program and discuss the innovations, challenges, and possible future directions.

Keywords: cybersecurity, new york, city college, graduate degree, master of science

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