Search results for: teaching learning model
16594 Algorithm Research on Traffic Sign Detection Based on Improved EfficientDet
Authors: Ma Lei-Lei, Zhou You
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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.Keywords: convolutional neural network, transformer, feature pyramid networks, loss function
Procedia PDF Downloads 9816593 Association Between Short-term NOx Exposure and Asthma Exacerbations in East London: A Time Series Regression Model
Authors: Hajar Hajmohammadi, Paul Pfeffer, Anna De Simoni, Jim Cole, Chris Griffiths, Sally Hull, Benjamin Heydecker
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Background: There is strong interest in the relationship between short-term air pollution exposure and human health. Most studies in this field focus on serious health effects such as death or hospital admission, but air pollution exposure affects many people with less severe impacts, such as exacerbations of respiratory conditions. A lack of quantitative analysis and inconsistent findings suggest improved methodology is needed to understand these effectsmore fully. Method: We developed a time series regression model to quantify the relationship between daily NOₓ concentration and Asthma exacerbations requiring oral steroids from primary care settings. Explanatory variables include daily NOₓ concentration measurements extracted from 8 available background and roadside monitoring stations in east London and daily ambient temperature extracted for London City Airport, located in east London. Lags of NOx concentrations up to 21 days (3 weeks) were used in the model. The dependent variable was the daily number of oral steroid courses prescribed for GP registered patients with asthma in east London. A mixed distribution model was then fitted to the significant lags of the regression model. Result: Results of the time series modelling showed a significant relationship between NOₓconcentrations on each day and the number of oral steroid courses prescribed in the following three weeks. In addition, the model using only roadside stations performs better than the model with a mixture of roadside and background stations.Keywords: air pollution, time series modeling, public health, road transport
Procedia PDF Downloads 14416592 Deep Reinforcement Learning-Based Computation Offloading for 5G Vehicle-Aware Multi-Access Edge Computing Network
Authors: Ziying Wu, Danfeng Yan
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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network
Procedia PDF Downloads 11816591 Influence of Psychosocial Factors on Physical Activity Level among Individuals with Asthma
Authors: Awotidebe Taofeek, Oyinsuyi Oluwafunmbi
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Psychosocial factors play a significant role in physical activity participation in diseased conditions and the general population. However, little is known about the role of exercise self-efficacy (ESE), exercise perceived barriers (EPB), and social support (SOS) in patients with asthma. This study investigated the influence of psychosocial factors on physical activity participation in patients with asthma in ile-ife. This cross-sectional study involved 130 patients with asthma. They were recruited from the Chest Clinic of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife using purposive sampling technique. Ethical approval was obtained from the Ethics and Research Committee of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife, Nigeria. Socio-demographic characteristics of respondents were recorded. Information on ESE, EPB, and SOS were obtained using Exercise Self-Efficacy, Exercise Benefit, and Barrier and Medical Outcome Social Support Scales respectively. Physical activity level was assessed in the last 7 days using international physical activity questionnaire. Descriptive and inferential statistics were used to analyze the data. Alpha level was set at p<0.5. The mean age of the respondents was 25.15 ± 9.38, and a majority, 110 (84.60%), engaged in low physical activity, 69(53%) had low exercise self-efficacy. However, less than two-third 80 (62.20%) reported high social support, with the majority of 95 (73.10%) reported high exercise perceived barriers. The means of ESE for male and femalerespondents were 29.01 ± 20.62 and 24.35 ± 17.36, respectively. The means of SOS formale and female respondents were 49.52 ± 22.22 and 61.87 ± 22.66, respectively. Themeans of EPB for male and female respondents were 53.37 ± 10.23 and 57.43 ± 9.65, respectively. The respondents were comparable in exercise self-efficacy and physicalactivity level (p>0.05). However, there were significant differences in social support (t=-2.791; p=0.006) and exercise perceived barriers (t=-2.108, p=0.037).Theresultsshowthattherewasasignificantrelationshipbetweenexerciseperceivedbarriersandlowphysicalactivitylevel(r=-0.216;p=0.023).TherewasasignificantassociationbetweenExerciseself-efficacyandmarried individuals(OR=0.967;95%CI=0.936-0.998;p= 0.037). Similarly, However,thereweresignificantassociationsbetweensocialsupport Andagegroup35-54years(OR=1.036;95%CI=1.007-1.067;p=0.014),females(OR= 1.024;95%CI=1.006;p=0.009)andmarriedindividuals(OR=1.049;95%CI=1.020-1.079. p=0.001).Therewasasignificantassociationbetweenexerciseperceivedbarriersand females(OR=1.043;95%CI=1.002-1.085;p=0.040).However, thereweresignificant associationsbetweenexerciseperceivedbarriersandoccupationgroup;civilservants (OR=1.092;95%CI=1.009-1.182;p=0.028),retiree(OR=1.092;95%CI=1.040-1.469;p= 0.016)andstudents(OR=1.110;95%CI=1.040;p=0.002). Inconclusion,agreaterpercentageofpatientswithasthmahadlowphysicalactivityleveland it was associatedwithhighexerciseperceivedbarriers,whileexerciseself-efficacyandsocialsupportwerenot.Keywords: asthma, psychosocial factors, physical activity, physical fitness
Procedia PDF Downloads 12516590 Level Set Based Extraction and Update of Lake Contours Using Multi-Temporal Satellite Images
Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu
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The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.Keywords: level set model, multi-temporal image, lake contour extraction, contour update
Procedia PDF Downloads 36616589 Agricultural Extension Workers’ Education in Indonesia - Roles of Distance Education
Authors: Adhi Susilo
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This paper addresses the roles of distance education in the agricultural extension workers’ education. Agriculture plays an important role in both poverty reduction and economic growth. The technology of agriculture in the developing world should change continuously to keep pace with rising populations and rapidly changing social, economic, and environmental conditions. Therefore, agricultural extension workers should have several competencies in order to carry out their duties properly. One of the essential competencies that they must possess is the professional competency that is directly related to their duties in carrying out extension activities. Such competency can be acquired through studying at Universitas Terbuka (UT). With its distance learning system, agricultural extension workers can study at UT without leaving their duties. This paper presenting sociological analysis and lessons learnt from the specific context of Indonesia. Diversities in geographic, demographic, social cultural and economic conditions of the country provide specific challenges for its distance education practice and the process of social transformation to which distance education can contribute. Extension officers used distance education for personal benefits and increased professional productivity. An increase in awareness is important for the further adoption of distance learning for extension purposes. Organizations in both the public and private sector must work to increase knowledge of ICTs for the benefit of stakeholders. The use of ICTs can increase productivity for extensions officers and expand educational opportunities for learners. The use of distance education by extension to disseminate educational materials around the world is widespread. Increasing awareness and use of distance learning can lead to more productive relationships between extension officers and agricultural stakeholders.Keywords: agricultural extension, demographic and geographic condition, distance education, ICTs
Procedia PDF Downloads 51516588 Clinician's Perspective of Common Factors of Change in Family Therapy: A Cross-National Exploration
Authors: Hassan Karimi, Fred Piercy, Ruoxi Chen, Ana L. Jaramillo-Sierra, Wei-Ning Chang, Manjushree Palit, Catherine Martosudarmo, Angelito Antonio
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Background: The two psychotherapy camps, the randomized clinical trials (RCTs) and the common factors model, have competitively claimed specific explanations for therapy effectiveness. Recently, scholars called for empirical evidence to show the role of common factors in therapeutic outcome in marriage and family therapy. Purpose: This cross-national study aims to explore how clinicians, across different nations and theoretical orientations, attribute the contribution of common factors to therapy outcome. Method: A brief common factors questionnaire (CFQ-with a Cronbach’s Alpha, 0.77) was developed and administered in seven nations. A series of statistical analyses (paired-samples t-test, independent sample t-test, ANOVA) were conducted: to compare clinicians perceived contribution of total common factors versus model-specific factors, to compare each pair of common factors’ categories, and to compare clinicians from collectivistic nations versus clinicians from individualistic nation. Results: Clinicians across seven nations attributed 86% to common factors versus 14% to model-specific factors. Clinicians attributed 34% of therapeutic change to client’s factors, 26% to therapist’s factors, 26% to relationship factors, and 14% to model-specific techniques. The ANOVA test indicated each of the three categories of common factors (client 34%, therapist 26%, relationship 26%) showed higher contribution in therapeutic outcome than the category of model specific factors (techniques 14%). Clinicians with psychology degree attributed more contribution to model-specific factors than clinicians with MFT and counseling degrees who attributed more contribution to client factors. Clinicians from collectivistic nations attributed larger contributions to therapist’s factors (M=28.96, SD=12.75) than the US clinicians (M=23.22, SD=7.73). The US clinicians attributed a larger contribution to client’s factors (M=39.02, SD=1504) than clinicians from the collectivistic nations (M=28.71, SD=15.74). Conclusion: The findings indicate clinicians across the globe attributed more than two thirds of therapeutic change to CFs, which emphasize the training of the common factors model in the field. CFs, like model-specific factors, vary in their contribution to therapy outcome in relation to specific client, therapist, problem, treatment model, and sociocultural context. Sociocultural expectations and norms should be considered as a context in which both CFs and model-specific factors function toward therapeutic goals. Clinicians need to foster a cultural competency specifically regarding the divergent ways that CFs can be activated due to specific sociocultural values.Keywords: common factors, model-specific factors, cross-national survey, therapist cultural competency, enhancing therapist efficacy
Procedia PDF Downloads 28716587 A Closed-Loop Design Model for Sustainable Manufacturing by Integrating Forward Design and Reverse Design
Authors: Yuan-Jye Tseng, Yi-Shiuan Chen
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In this paper, a new concept of closed-loop design model is presented. The closed-loop design model is developed by integrating forward design and reverse design. Based on this new concept, a closed-loop design model for sustainable manufacturing by integrated evaluation of forward design, reverse design, and green manufacturing using a fuzzy analytic network process is developed. In the design stage of a product, with a given product requirement and objective, there can be different ways to design the detailed components and specifications. Therefore, there can be different design cases to achieve the same product requirement and objective. Thus, in the design evaluation stage, it is required to analyze and evaluate the different design cases. The purpose of this research is to develop a model for evaluating the design cases by integrated evaluation of forward design, reverse design, and green manufacturing models. A fuzzy analytic network process model is presented for integrated evaluation of the criteria in the three models. The comparison matrices for evaluating the criteria in the three groups are established. The total relational values among the three groups represent the total relational effects. In application, a super matrix can be created and the total relational values can be used to evaluate the design cases for decision-making to select the final design case. An example product is demonstrated in this presentation. It shows that the model is useful for integrated evaluation of forward design, reverse design, and green manufacturing to achieve a closed-loop design for sustainable manufacturing objective.Keywords: design evaluation, forward design, reverse design, closed-loop design, supply chain management, closed-loop supply chain, fuzzy analytic network process
Procedia PDF Downloads 67616586 Modeling Corruption Dynamics Within Bono and Ahafo Police Service in Ghana
Authors: Adam Ahmed Hosney
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The existence of a culture of corruption within an institution, such as the police, could be a sign of failure from various angles. There is a general perception among Ghanaians that the most corrupt institution is the police service. The purpose of this study is to formulate and analyze a nonlinear mathematical model to investigate corruption as an epidemic within the Ghana police service, this study revealed the basic reproduction number for corruption extinction and corruption survival. The threshold conditions for all kinds of equilibrium points are obtained using linearization methods and Lyapunov functional methods, and they demonstrate local asymptotic stability for both corrupt endemic and corrupt free equilibrium states. The model was analyzed qualitatively, and the solution was derived. The model appears to be positively invariant and attractive. Therefore, the region exhibits positive invariance. Thus, it is adequate to think about the dynamics of the model. For the purpose of illustrating the solution, the graphic result was presented and discussed. Results show that corruption will die out within the police service if the government shows no tolerance for those involved in corrupt practices. Study findings indicate that leaders should be trustworthy, demonstrate a complete and viable commitment to addressing corruption, and make it a priority to provide mass education to all citizens as well as using religious leaders to fight corruption since most Ghanaians are religious and trust their leaders.Keywords: mathematical model, differential equation, dynamical system, simulation
Procedia PDF Downloads 2716585 Specific Frequency of Globular Clusters in Different Galaxy Types
Authors: Ahmed H. Abdullah, Pavel Kroupa
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Globular clusters (GC) are important objects for tracing the early evolution of a galaxy. We study the correlation between the cluster population and the global properties of the host galaxy. We found that the correlation between cluster population (NGC) and the baryonic mass (Mb) of the host galaxy are best described as 10 −5.6038Mb. In order to understand the origin of the U -shape relation between the GC specific frequency (SN) and Mb (caused by the high value of SN for dwarfs galaxies and giant ellipticals and a minimum SN for intermediate mass galaxies≈ 1010M), we derive a theoretical model for the specific frequency (SNth). The theoretical model for SNth is based on the slope of the power-law embedded cluster mass function (β) and different time scale (Δt) of the forming galaxy. Our results show a good agreement between the observation and the model at a certain β and Δt. The model seems able to reproduce higher value of SNth of β = 1.5 at the midst formation time scale.Keywords: galaxies: dwarf, globular cluster: specific frequency, number of globular clusters, formation time scale
Procedia PDF Downloads 32616584 Design of a Small and Medium Enterprise Growth Prediction Model Based on Web Mining
Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj
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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.Keywords: data mining, SME growth, success factors, web mining
Procedia PDF Downloads 26716583 A Comparative Study of Automotive / Transportation Design Programs and University: Industry Cooperation Models in Higher Education
Authors: Efe Çukur
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This study aims to discuss and compare i) widespread and generic design, particularly industrial design education in relation to the specific needs of the automotive/transportation industry, and ii) an automotive/transportation design education model within and under to provide the conditions of design education and automotive industry, especially in Turkey and T.R.N.C. The automotive industry is the 11th largest in the world ($1.51 trillion). One of the most important departments in this industry, along with sales, marketing and engineering, is the design department. The automotive industry is known as the locomotive industry, but there is a non-automotive design department on the academic side of Turkey. This suggestion; includes the presentation of a program proposal that meets the needs of the industry for Turkey and T.R.N.C., the second largest automobile manufacturing country in Europe. On the education side, industrial design education has become a generic title. Automotive design studios are divided into several subgroups. Even in the higher graduate education, the automotive design departments get their subgroups like exterior design and interior design. Transportation design, which is a subfield of industrial design, is offered as higher education in transportation design departments, particularly in America and Europe. In these departments, the curriculum is shaped to the needs of the sectors. Higher education transportation design programs began in the mid-20th century. Until those high education programs...Until these high education programs, the industry has adapted architectures and engineers for designer workloads. Still today transportation design graduates are not the majority of the design studios. The content of the study is an in-depth comparison of these institutions and how the requirements, demands of the industry are met in this regard and revealed. Some of the institutions are selected from Europe and US. To be analyzed under the headings of staff, courses, syllabus, University-Industry collaboration, and location selection. The study includes short, mid, and long term proposals and a hypothesis for discussion. In short, the study will not only provide a wide comparative scope of information on generic and specialized aspects of design education in different countries but also propose a higher education model for automotive / transportation design with solid data of requirements, methodology, and structure regarding learning outcomes, and especially industry cooperation.Keywords: design education, automotive - transportation design programs, transportation design, automotive industry in Turkey /T.R.N.C., automotive design education in Turkey /T.R.N.C.
Procedia PDF Downloads 9316582 Using Structural Equation Modeling to Analyze the Impact of Remote Work on Job Satisfaction
Authors: Florian Pfeffel, Valentin Nickolai, Christian Louis Kühner
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Digitalization has disrupted the traditional workplace environment by allowing many employees to work from anywhere at any time. This trend of working from home was further accelerated due to the COVID-19 crisis, which forced companies to rethink their workplace models. While in many companies, this shift happened out of pure necessity; many employees were left more satisfied with their job due to the opportunity to work from home. This study focuses on employees’ job satisfaction in the service sector in dependence on the different work models, which are defined as a “work from home” model, the traditional “work in office” model, and a hybrid model. Using structural equation modeling (SEM), these three work models have been analyzed based on 13 influencing factors on job satisfaction that have been further summarized in the three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, a survey has been conducted with n = 684 employees in the service sector. Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees who work entirely remotely or have a hybrid work model are significantly more satisfied with their job, with a job satisfaction score of 5.0 respectively on a scale from 1 (very dissatisfied) to 7 (very satisfied), than employees do not have the option to work from home with a score of 4.6. This comes as a result of the lower identification with the work in the model without any remote working. Furthermore, the responses indicate that it is important to consider the individual preferences of each employee when it comes to the work model to achieve overall higher job satisfaction. Thus, it can be argued that companies can profit off of more motivation and higher productivity by considering the individual work model preferences, therefore, increasing the identification with the respective work.Keywords: home-office, identification with work, job satisfaction, new work, remote work, structural equation modeling
Procedia PDF Downloads 8216581 Towards Developing A Rural South African Child Into An Engineering Graduates With Conceptual And Critical Thinking Skills
Authors: Betty Kibirige
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Students entering the University of Zululand (UNIZULU) Science Faculty mostly come with skills that allow them to prepare for exams and pass them in order to satisfy requirements for entry into a tertiary Institution. Some students hail from deep rural schools with limited facilities, while others come from well-resourced schools. Personal experience has shown that it may take a student the whole time at a tertiary institution following the same skills as those acquired in high school as a sure means of entering the next level in their development, namely a postgraduate program. While it is apparent that at this point in human history, it is totally impossible to teach all the possible content in any one subject, many academics approach teaching and learning from the traditional point of view. It therefore became apparent to explore ways of developing a graduate that will be able to approach life with skills that allows them to navigate knowledge by applying conceptual and critical thinking skills. Recently, the Science Faculty at the University of Zululand introduced two Engineering programs. In an endeavour to approach the development of the Engineering graduate in this institution to be able to tackle problem-solving in the present-day excessive information availability, it became necessary to study and review approaches used by various academics in order to settle for a possible best approach to the challenge at hand. This paper focuses on the development of a deep rural child in a graduate with conceptual and critical thinking skills as major attributes possessed upon graduation. For this purpose, various approaches were studied. A combination of these approaches was repackaged to form an approach that may appear novel to UNIZULU and the rural child, especially for the Engineering discipline. The approach was checked by offering quiz questions to students participating in an engineering module, observing test scores in the targeted module and make comparative studies. Test results are discussed in the article. It was concluded that students’ graduate attributes could be tailored subconsciously to indeed include conceptual and critical thinking skills, but through more than one approach depending mainly on the student's high school background.Keywords: graduate attributes, conceptual skills, critical thinking skills, traditional approach
Procedia PDF Downloads 24216580 Scenario-Based Analysis of Electric Vehicle Penetration in Road Transportation in Laos
Authors: Bouneua Khamphilavanh, Toshihiko Masui
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The penetration of EV (electric vehicle) technology in Lao road transportation, in this study, was analyzed by using the AIM/CGE [Laos] model. The computable general equilibrium (CGE) model was developed by the Asia-Pacific Integrated Model (AIM) team. In line with the increase of the number of road vehicles, the energy demand in the transport sector has been gradually increased which resulted in a large amount of budget spent for importing fossil fuels during the last decade, and a high carbon dioxide emission from the transport sector, hence the aim of this research is to analyze the impact of EVs penetration on economic and CO₂ emission in short-term, middle-term, and long-term. By the year 2050, the expected gross domestic product (GDP) value, due to Laos will spend more budget for importing the EV, will be gradually lost up to one percent. The cumulative CO₂ emission from 2020 to 2050 in BAU case will be 12,000 GgCO₂eq, and those in the EV mitigation case will be 9,300 GgCO₂eq, which accounting for likely 77% cumulative CO₂ emission reduction in the road transport sector by introducing the EV technology.Keywords: GDP, CO₂ mitigation, CGE model, EV technology, transport
Procedia PDF Downloads 27816579 Automated Building Internal Layout Design Incorporating Post-Earthquake Evacuation Considerations
Authors: Sajjad Hassanpour, Vicente A. González, Yang Zou, Jiamou Liu
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Earthquakes pose a significant threat to both structural and non-structural elements in buildings, putting human lives at risk. Effective post-earthquake evacuation is critical for ensuring the safety of building occupants. However, current design practices often neglect the integration of post-earthquake evacuation considerations into the early-stage architectural design process. To address this gap, this paper presents a novel automated internal architectural layout generation tool that optimizes post-earthquake evacuation performance. The tool takes an initial plain floor plan as input, along with specific requirements from the user/architect, such as minimum room dimensions, corridor width, and exit lengths. Based on these inputs, firstly, the tool randomly generates different architectural layouts. Secondly, the human post-earthquake evacuation behaviour will be thoroughly assessed for each generated layout using the advanced Agent-Based Building Earthquake Evacuation Simulation (AB2E2S) model. The AB2E2S prototype is a post-earthquake evacuation simulation tool that incorporates variables related to earthquake intensity, architectural layout, and human factors. It leverages a hierarchical agent-based simulation approach, incorporating reinforcement learning to mimic human behaviour during evacuation. The model evaluates different layout options and provides feedback on evacuation flow, time, and possible casualties due to earthquake non-structural damage. By integrating the AB2E2S model into the automated layout generation tool, architects and designers can obtain optimized architectural layouts that prioritize post-earthquake evacuation performance. Through the use of the tool, architects and designers can explore various design alternatives, considering different minimum room requirements, corridor widths, and exit lengths. This approach ensures that evacuation considerations are embedded in the early stages of the design process. In conclusion, this research presents an innovative automated internal architectural layout generation tool that integrates post-earthquake evacuation simulation. By incorporating evacuation considerations into the early-stage design process, architects and designers can optimize building layouts for improved post-earthquake evacuation performance. This tool empowers professionals to create resilient designs that prioritize the safety of building occupants in the face of seismic events.Keywords: agent-based simulation, automation in design, architectural layout, post-earthquake evacuation behavior
Procedia PDF Downloads 10416578 Classification of Emotions in Emergency Call Center Conversations
Authors: Magdalena Igras, Joanna Grzybowska, Mariusz Ziółko
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The study of emotions expressed in emergency phone call is presented, covering both statistical analysis of emotions configurations and an attempt to automatically classify emotions. An emergency call is a situation usually accompanied by intense, authentic emotions. They influence (and may inhibit) the communication between caller and responder. In order to support responders in their responsible and psychically exhaustive work, we studied when and in which combinations emotions appeared in calls. A corpus of 45 hours of conversations (about 3300 calls) from emergency call center was collected. Each recording was manually tagged with labels of emotions valence (positive, negative or neutral), type (sadness, tiredness, anxiety, surprise, stress, anger, fury, calm, relief, compassion, satisfaction, amusement, joy) and arousal (weak, typical, varying, high) on the basis of perceptual judgment of two annotators. As we concluded, basic emotions tend to appear in specific configurations depending on the overall situational context and attitude of speaker. After performing statistical analysis we distinguished four main types of emotional behavior of callers: worry/helplessness (sadness, tiredness, compassion), alarm (anxiety, intense stress), mistake or neutral request for information (calm, surprise, sometimes with amusement) and pretension/insisting (anger, fury). The frequency of profiles was respectively: 51%, 21%, 18% and 8% of recordings. A model of presenting the complex emotional profiles on the two-dimensional (tension-insecurity) plane was introduced. In the stage of acoustic analysis, a set of prosodic parameters, as well as Mel-Frequency Cepstral Coefficients (MFCC) were used. Using these parameters, complex emotional states were modeled with machine learning techniques including Gaussian mixture models, decision trees and discriminant analysis. Results of classification with several methods will be presented and compared with the state of the art results obtained for classification of basic emotions. Future work will include optimization of the algorithm to perform in real time in order to track changes of emotions during a conversation.Keywords: acoustic analysis, complex emotions, emotion recognition, machine learning
Procedia PDF Downloads 39816577 The Role of Building Information Modeling as a Design Teaching Method in Architecture, Engineering and Construction Schools in Brazil
Authors: Aline V. Arroteia, Gustavo G. Do Amaral, Simone Z. Kikuti, Norberto C. S. Moura, Silvio B. Melhado
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Despite the significant advances made by the construction industry in recent years, the crystalized absence of integration between the design and construction phases is still an evident and costly problem in building construction. Globally, the construction industry has sought to adopt collaborative practices through new technologies to mitigate impacts of this fragmented process and to optimize its production. In this new technological business environment, professionals are required to develop new methodologies based on the notion of collaboration and integration of information throughout the building lifecycle. This scenario also represents the industry’s reality in developing nations, and the increasing need for overall efficiency has demanded new educational alternatives at the undergraduate and post-graduate levels. In countries like Brazil, it is the common understanding that Architecture, Engineering and Building Construction educational programs are being required to review the traditional design pedagogical processes to promote a comprehensive notion about integration and simultaneity between the phases of the project. In this context, the coherent inclusion of computation design to all segments of the educational programs of construction related professionals represents a significant research topic that, in fact, can affect the industry practice. Thus, the main objective of the present study was to comparatively measure the effectiveness of the Building Information Modeling courses offered by the University of Sao Paulo, the most important academic institution in Brazil, at the Schools of Architecture and Civil Engineering and the courses offered in well recognized BIM research institutions, such as the School of Design in the College of Architecture of the Georgia Institute of Technology, USA, to evaluate the dissemination of BIM knowledge amongst students in post graduate level. The qualitative research methodology was developed based on the analysis of the program and activities proposed by two BIM courses offered in each of the above-mentioned institutions, which were used as case studies. The data collection instruments were a student questionnaire, semi-structured interviews, participatory evaluation and pedagogical practices. The found results have detected a broad heterogeneity of the students regarding their professional experience, hours dedicated to training, and especially in relation to their general knowledge of BIM technology and its applications. The research observed that BIM is mostly understood as an operational tool and not as methodological project development approach, relevant to the whole building life cycle. The present research offers in its conclusion an assessment about the importance of the incorporation of BIM, with efficiency and in its totality, as a teaching method in undergraduate and graduate courses in the Brazilian architecture, engineering and building construction schools.Keywords: building information modeling (BIM), BIM education, BIM process, design teaching
Procedia PDF Downloads 15416576 A Machine Learning-Based Analysis of Autism Prevalence Rates across US States against Multiple Potential Explanatory Variables
Authors: Ronit Chakraborty, Sugata Banerji
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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling
Procedia PDF Downloads 10316575 Bankruptcy Prediction Analysis on Mining Sector Companies in Indonesia
Authors: Devina Aprilia Gunawan, Tasya Aspiranti, Inugrah Ratia Pratiwi
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This research aims to classify the mining sector companies based on Altman’s Z-score model, and providing an analysis based on the Altman’s Z-score model’s financial ratios to provide a picture about the financial condition in mining sector companies in Indonesia and their viability in the future, and to find out the partial and simultaneous impact of each of the financial ratio variables in the Altman’s Z-score model, namely (WC/TA), (RE/TA), (EBIT/TA), (MVE/TL), and (S/TA), toward the financial condition represented by the Z-score itself. Among 38 mining sector companies listed in Indonesia Stock Exchange (IDX), 28 companies are selected as research sample according to the purposive sampling criteria.The results of this research showed that during 3 years research period at 2010-2012, the amount of the companies that was predicted to be healthy in each year was less than half of the total sample companies and not even reach up to 50%. The multiple regression analysis result showed that all of the research hypotheses are accepted, which means that (WC/TA), (RE/TA), (EBIT/TA), (MVE/TL), and (S/TA), both partially and simultaneously had an impact towards company’s financial condition.Keywords: Altman’s Z-score model, financial condition, mining companies, Indonesia
Procedia PDF Downloads 52916574 Evaluating the Needs of PhD Students in Preparation of a Genre-Based English for Academic Purposes Course
Authors: Heba I. Bakry
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Academic writing in the tertiary education has always been a challenge to EFL learners. This proposed study aims at investigating the academic English language needs for PhD students and candidates studying humanities and social sciences at Cairo University. The research problem arises from the fact that most of them study English as a Foreign Language (EFL) or for specific purposes (ESP) in their undergraduate years. They are hardly familiarized with the different academic genres, despite the fact that they use academic resources written in English, and they are required to publish a paper internationally. Upon understanding the conventions and constraints of academic writing, postgraduates will have the opportunity to interact with the international academic spheres conveniently. There is, thus, a need to be acquainted with the generally accepted features of the academic genres, such as academic papers and their part-genres, such as writing abstracts, in addition to other occluded genres, such as personal statements and recommendation letters. The lack of practicing many of these genres is caused by the fact that there are clear differences between the rhetoric and conventions of the students' native language, i.e., Arabic, and the target language they are learning in the academic context, i.e., English. Moreover, apart from the general culture represented ethno-linguistically, the learners' 'small' culture represented in a national setting like Cairo University is more defining than their general cultural affiliations that are associated with their nationality, race, or religion, for instance. The main research question of this proposed study is: What is the effect of teaching a genre-based EAP course on the research writing competence of PhD candidates? To reach an answer to this question, the study will attempt to answer the following sub-questions: 1. What are the Egyptian PhD candidates' EAP perceived needs? 2. What are the requisite academic research skills for Egyptian scholars? The study intends to assess the students’ needs, as a step to design and evaluate an EAP course that is based on explaining and scrutinizing a variety of academic genres. Adopting a diagnostic approach, the needs assessment uses quantitative data collected through questionnaires, and qualitative data assembled from semi-structured interviews with the students and their teachers, in addition to non-participant observations of a convenience sample.Keywords: course design, English for academic purposes, genre-based, needs assessment
Procedia PDF Downloads 24416573 Preparing Undergraduate Nursing and Midwifery Students for Culturally Competent Health Care: A Qualitative Study
Authors: Olayide Ogunsiji, Glenda McDonald
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Engendering cultural competence in nursing and midwifery students is germane to reducing disparities in contemporary health care settings, increasingly patronized by people from diverse background. Professional standards for registration in Australia require nurses and midwives to be culturally competent. Nursing and midwifery academics worldwide are responsible for preparing students for clinical practice, yet limited attention is paid to exploring how students are being prepared to care for a culturally diverse population. This paper provides insight into the perceptions of academics about how they are preparing undergraduate nursing and midwifery students for culturally competent health care. Academics were drawn from a tertiary educational institution in metropolitan Australia. They responded to a generic email indicating their interest in participating in the study. A total of nine academics who have taught undergraduate nursing and midwifery students in a unit that focused on health and illness perspectives for culturally diverse communities; and provided written consent to participate were included. These academics were engaged in a qualitative digitally-recorded semi-structured face-to-face or telephone interviews which lasted for about 45-60 minutes. Interview data were transcribed verbatim. Through constant comparison, three themes emerged: experiences of the teachers, strategies used for preparing students and challenges in preparing students. The participants spoke about their experiences of teaching in the unit and with the students. They faced challenges related to physical and relational space. They utilised a number of didactic approaches in teaching the unit and critiqued the adequacy of the content in preparing students for practice. This study demonstrated that didactic classroom approaches need to be supported with clinical practice and cultural immersion for a meaningful preparation of nursing and midwifery students to care for culturally diverse populations.Keywords: cultural competence, nursing students, preparation, undergraduate
Procedia PDF Downloads 15516572 Model and Neural Control of the Depth of Anesthesia during Surgery
Authors: Javier Fernandez, Mayte Medina, Rafael Fernandez de Canete, Nuria Alcain, Juan Carlos Ramos-Diaz
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At present, the experimentation of anesthetic drugs on patients requires a regulation protocol, and the response of each patient to several doses of entry drug must be well known. Therefore, the development of pharmacological dose control systems is a promising field of research in anesthesiology. In this paper, it has been developed a non-linear compartmental the pharmacokinetic-pharmacodynamical model which describes the anesthesia depth effect in a sufficiently reliable way over a set of patients with the depth effect quantified by the Bi-Spectral Index. Afterwards, an Artificial Neural Network (ANN) predictive controller has been designed based on the depth of anesthesia model so as to keep the patient in the optimum condition while he undergoes surgical treatment. For the purpose of quantifying the efficiency of the neural predictive controller, a classical proportional-integral-derivative controller has also been developed to compare both strategies. Results show the superior performance of predictive neural controller during BiSpectral Index reference tracking.Keywords: anesthesia, bi-spectral index, neural network control, pharmacokinetic-pharmacodynamical model
Procedia PDF Downloads 33716571 Developing a Model for Information Giving Behavior in Virtual Communities
Authors: Pui-Lai To, Chechen Liao, Tzu-Ling Lin
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Virtual communities have created a range of new social spaces in which to meet and interact with one another. Both as a stand-alone model or as a supplement to sustain competitive advantage for normal business models, building virtual communities has been hailed as one of the major strategic innovations of the new economy. However for a virtual community to evolve, the biggest challenge is how to make members actively give information or provide advice. Even in busy virtual communities, usually, only a small fraction of members post information actively. In order to investigate the determinants of information giving willingness of those contributors who usually actively provide their opinions, we proposed a model to understand the reasons for contribution in communities. The study will definitely serve as a basis for the future growth of information giving in virtual communities.Keywords: information giving, social identity, trust, virtual community
Procedia PDF Downloads 32216570 Numerical Simulations on Feasibility of Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization
Authors: Taiki Baba, Tomoaki Hashimoto
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The random dither quantization method enables us to achieve much better performance than the simple uniform quantization method for the design of quantized control systems. Motivated by this fact, the stochastic model predictive control method in which a performance index is minimized subject to probabilistic constraints imposed on the state variables of systems has been proposed for linear feedback control systems with random dither quantization. In other words, a method for solving optimal control problems subject to probabilistic state constraints for linear discrete-time control systems with random dither quantization has been already established. To our best knowledge, however, the feasibility of such a kind of optimal control problems has not yet been studied. Our objective in this paper is to investigate the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization. To this end, we provide the results of numerical simulations that verify the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization.Keywords: model predictive control, stochastic systems, probabilistic constraints, random dither quantization
Procedia PDF Downloads 28216569 A Comparative Evaluation of the SIR and SEIZ Epidemiological Models to Describe the Diffusion Characteristics of COVID-19 Polarizing Viewpoints on Online
Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal
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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion
Procedia PDF Downloads 6216568 Effects of Unfamiliar Orthography on the Lexical Encoding of Novel Phonological Features
Authors: Asmaa Shehata
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Prior research indicates that second language (L2) learners encounter difficulty in the distinguishing novel L2 contrasting sounds that are not contrastive in their native languages. L2 orthographic information, however, is found to play a positive role in the acquisition of non-native phoneme contrasts. While most studies have mainly involved a familiar written script (i.e., the Roman script), the influence of a foreign, unfamiliar script is still unknown. Therefore, the present study asks: Does unfamiliar L2 script play a role in creating distinct phonological representations of novel contrasting phonemes? It is predicted that subjects’ performance in the unfamiliar orthography group will outperform their counterparts’ performance in the control group. Thus, training that entails orthographic inputs can yield a significant improvement in L2 adult learners’ identification and lexical encoding of novel L2 consonant contrasts. Results are discussed in terms of their implications for the type of input introduced to L2 learners to improve their language learning.Keywords: Arabic, consonant contrasts, foreign script, lexical encoding, orthography, word learning
Procedia PDF Downloads 25616567 Dynamics of Adiabatic Rapid Passage in an Open Rabi Dimer Model
Authors: Justin Zhengjie Tan, Yang Zhao
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Adiabatic Rapid Passage, a popular method of achieving population inversion, is studied in a Rabi dimer model in the presence of noise which acts as a dissipative environment. The integration of the multi-Davydov D2 Ansatz into the time-dependent variational framework enables us to model the intricate quantum system accurately. By influencing the system with a driving field strength resonant with the energy spacing, the probability of adiabatic rapid passage, which is modelled after the Landau Zener model, can be derived along with several other observables, such as the photon population. The effects of a dissipative environment can be reproduced by coupling the system to a common phonon mode. By manipulating the strength and frequency of the driving field, along with the coupling strength of the phonon mode to the qubits, we are able to control the qubits and photon dynamics and subsequently increase the probability of Adiabatic Rapid Passage happening.Keywords: quantum electrodynamics, adiabatic rapid passage, Landau-Zener transitions, dissipative environment
Procedia PDF Downloads 8716566 Adsorption of Cd2+ from Aqueous Solutions Using Chitosan Obtained from a Mixture of Littorina littorea and Achatinoidea Shells
Authors: E. D. Paul, O. F. Paul, J. E. Toryila, A. J. Salifu, C. E. Gimba
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Adsorption of Cd2+ ions from aqueous solution by Chitosan, a natural polymer, obtained from a mixture of the exoskeletons of Littorina littorea (Periwinkle) and Achatinoidea (Snail) was studied at varying adsorbent dose, contact time, metal ion concentrations, temperature and pH using batch adsorption method. The equilibrium adsorption isotherms were determined between 298 K and 345 K. The adsorption data were adjusted to Langmuir, Freundlich and the pseudo second order kinetic models. It was found that the Langmuir isotherm model most fitted the experimental data, with a maximum monolayer adsorption of 35.1 mgkg⁻¹ at 308 K. The entropy and enthalpy of adsorption were -0.1121 kJmol⁻¹K⁻¹ and -11.43 kJmol⁻¹ respectively. The Freundlich adsorption model, gave Kf and n values consistent with good adsorption. The pseudo-second order reaction model gave a straight line plot with rate constant of 1.291x 10⁻³ kgmg⁻¹ min⁻¹. The qe value was 21.98 mgkg⁻¹, indicating that the adsorption of Cadmium ion by the chitosan composite followed the pseudo-second order kinetic model.Keywords: adsorption, chitosan, littorina littorea, achatinoidea, natural polymer
Procedia PDF Downloads 40316565 Developing a Green Strategic Management Model with regarding HSE-MS
Authors: Amin Padash, Gholam Reza Nabi Bid Hendi, Hassan Hoveidi
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Purpose: The aim of this research is developing a model for green management based on Health, Safety and Environmental Management System. An HSE-MS can be a powerful tool for organizations to both improve their environmental, health and safety performance, and enhance their business efficiency to green management. Model: The model is developed in this study can be used for industries as guidelines for implementing green management issue by considering Health, Safety and Environmental Management System. Case Study: The Pars Special Economic / Energy Zone Organization on behalf of Iran’s Petroleum Ministry and National Iranian Oil Company (NIOC) manages and develops the South and North oil and gas fields in the region. Methodology: This research according to objective is applied and based on implementing is descriptive and also prescription. We used technique MCDM (Multiple Criteria Decision-Making) for determining the priorities of the factors. Based on process approach the model consists of the following steps and components: first factors involved in green issues are determined. Based on them a framework is considered. Then with using MCDM (Multiple Criteria Decision-Making) algorithms (TOPSIS) the priority of basic variables are determined. The authors believe that the proposed model and results of this research can aid industries managers to implement green subjects according to Health, Safety and Environmental Management System in a more efficient and effective manner. Finding and conclusion: Basic factors involved in green issues and their weights can be the main finding. Model and relation between factors are the other finding of this research. The case is considered Petrochemical Company for promoting the system of ecological industry thinking.Keywords: Fuzzy-AHP method , green management, health, safety and environmental management system, MCDM technique, TOPSIS
Procedia PDF Downloads 411