Search results for: index model

Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

Procedia PDF Downloads 43

Authors: F. Atheer, Al-Saoudi, Robin Kalfat, Riadh Al-Mahaidi

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Over the last two decades, externally bonded fiber reinforced polymer (FRP) composites bonded to concrete substrates has become a popular method for strengthening reinforced concrete (RC) highway and railway bridges. Such structures are exposed to severe cyclic loading throughout their lifetime often resulting in fatigue damage to structural components and a reduction in the service life of the structure. Since experimental and numerical results on the fatigue performance of FRP-to-concrete joints are still limited, the current research focuses on assessing the fatigue performance of externally bonded FRP-to-concrete joints using a direct shear test. Some early results indicate that the stress ratio and the applied cyclic stress level have a direct influence on the fatigue life of the externally bonded FRP. In addition, a calibrated finite element model is developed to provide further insight into the influence of certain parameters such as: concrete strength, FRP thickness, number of cycles, frequency and stiffness on the fatigue life of the FRP-to-concrete joints.

Keywords: FRP, concrete bond, control, fatigue, finite element model

Procedia PDF Downloads 436

Authors: D. Calogine, O. Chau, S. Dotti, O. Ramiarinjanahary, P. Rasoavonjy, F. Tovondahiniriko

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Mafate is a natural circus in the north-western part of Reunion Island, without an electrical grid and road network. A micro-grid concept is being experimented in this area, composed of a photovoltaic production combined with electrochemical batteries, in order to meet the local population for self-consumption of electricity demands. This work develops a discrete model as well as a stochastic model in order to reach an optimal equilibrium between production and consumptions for a cluster of houses. The management of the energy power leads to a large linearized programming system, where the time interval of interest is 24 hours The experimental data are solar production, storage energy, and the parameters of the different electrical devices and batteries. The unknown variables to evaluate are the consumptions of the various electrical services, the energy drawn from and stored in the batteries, and the inhabitants’ planning wishes. The objective is to fit the solar production to the electrical consumption of the inhabitants, with an optimal use of the energies in the batteries by satisfying as widely as possible the users' planning requirements. In the discrete model, the different parameters and solutions of the linear programming system are deterministic scalars. Whereas in the stochastic approach, the data parameters and the linear programming solutions become random variables, then the distributions of which could be imposed or established by estimation from samples of real observations or from samples of optimal discrete equilibrium solutions.

Keywords: photovoltaic production, power consumption, battery storage resources, random variables, stochastic modeling, estimations of probability distributions, mixed integer linear programming, smart micro-grid, self-consumption of electricity.

Procedia PDF Downloads 96

Authors: Mehdi Habibagahi, Shami Nejadi, Ata Aminfar

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A significant degradation factor that impacts the durability of concrete structures is the alkali-silica reaction. Engineers are frequently charged with the challenges of conducting a thorough safety assessment of concrete structures that have been impacted by ASR. The alkali-silica reaction has a major influence on the structural capacities of structures. In most cases, the reduction in compressive strength, tensile strength, and modulus of elasticity is expressed as a function of free expansion and crack widths. Predicting the effect of ASR on flexural strength is also relevant. In this paper, a nonlinear three-dimensional (3D) finite-element model was proposed to describe the flexural strength degradation induced byASR.Initial strains, initial stresses, initial cracks, and deterioration of material characteristics were all considered ASR factors in this model. The effects of ASR on structural performance were evaluated by focusing on initial flexural stiffness, force–deformation curve, and load-carrying capacity. Degradation of concrete mechanical properties was correlated with ASR growth using material test data conducted at Tech Lab, UTS, and implemented into the FEM for various expansions. The finite element study revealed a better understanding of the ASR-affected RC beam's failure mechanism and capacity reduction as a function of ASR expansion. Furthermore, in this study, decreasing of the residual mechanical properties due to ASRisreviewed, using as input data for the FEM model. Finally, analysis techniques and a comparison of the analysis and the experiment results are discussed. Verification is also provided through analyses of reinforced concrete beams with behavior governed by either flexural or shear mechanisms.

Keywords: alkali-silica reaction, analysis, assessment, finite element, nonlinear analysis, reinforced concrete

Procedia PDF Downloads 150

Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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Authors: Jaehyun Choi, Hyunjung Kim, Namho Kim

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Earthwork is one of the critical civil construction operations that require large-quantities of resources due to its intensive dependency upon construction equipment. Therefore, efficient construction equipment management can highly contribute to productivity improvements and cost savings. Earthwork operation utilizes various combinations of construction equipment in order to meet project requirements such as time and cost. Identification of site condition and construction methods should be performed in advance in order to develop a proper execution plan. The factors to be considered include capacity of equipment assigned, the method of construction, the size of the site, and the surrounding condition. In addition, optimal combination of various construction equipment should be selected. However, in real world practice, equipment utilization plan is performed based on experience and intuition of management. The researchers evaluated the efficiency of various alternatives of construction equipment combinations by utilizing the process simulation model, validated the model from a case study project, and presented a methodology to find optimized plan among alternatives.

Keywords: earthwork operation, construction equipment, process simulation, optimization

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Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

Procedia PDF Downloads 263

Authors: Chu Shi Wei

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Supported employment in Malaysia is in the early stages of development. The development of supported employment in Malaysia is an important step towards the inclusion of individuals with disabilities who have previously lacked the necessary support for employment in the open labour market as they were confined to sheltered workshops. There is a paradigm shift from sheltered to supported employment as the sheltered workshop is based on the medical model of disability, which focuses on the disability of the individual and segregated training institutions. The paradigm shift revolves around the social model of disability, which emphasizes the abilities of the individual and the removal of the barriers in the environment by the provision of support. This study explores the development of supported employment by utilizing a mixed methods approach which consists of collecting quantitative data through a survey and interviewing participants to collect qualitative data. Job coaches from six employment sectors participated in the survey and interview. The findings of the study indicate that the role of job coaches is integral to the development of supported employment. The role of job coaches includes job matching, on-the-job training, and developing natural supports to foster greater diversity and inclusion in the workplace.

Keywords: supported employment, disabilities, diversity, development

Procedia PDF Downloads 55

Authors: Kidus Dawit Gedamu

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Addis Ababa City Road Authority is responsible for managing and setting performance evaluation of the city’s road network using the International Roughness Index (IRI). This helps the authority to conduct pavement condition assessments of asphalt roads each year to determine the health status or Level of service (LOS) of the roadway network and plan program improvements such as maintenance, resurfacing and rehabilitation. For a lower IRI limit economical and acceptable maintenance strategy may be selected among a number of maintenance alternatives. The Highway Development and Management (HDM-4) tool can do such measures to help decide which option is the best by evaluating the economic and structural conditions. This paper specifically addresses flexible pavement, including two principal arterial streets under the administration of the Addis Ababa City Roads Authority. The roads include the road from Megenagna Interchange to Ayat Square and from Ayat Square to Tafo RA. First, it was assessed the procedures followed by the city's road authority to develop the appropriate road maintenance strategies. Questionnaire surveys and interviews are used to collect information from the city's road maintenance departments. Second, the project analysis was performed for functional and economic comparison of different maintenance alternatives using HDM-4.

Keywords: appropriate maintenance strategy, cost stream, road deterioration, maintenance alternative

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Authors: Lusine S. Stepanyan, Elina V. Asriyan.

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It is known, that the efficiency of management depend on individual characteristics of manager. In case, was shown the role of personal position in the efficiency of management. Current research is aimed at reveal psychological and psychophysiological basis efficiency of management and finding ways of increasing the productivity of management that is most essential and topical problems of modern society. To understand the investigated phenomenon it was applied a complex approach. The Eysenk questionnaire was used for determining the level of aggression, frustration, anxiety and rigidity. The test of egocentric associations was used for determining the level of egocentrism. The test of COS (communicativeness and organizational skills) was used for diagnosing the level of communicativeness. The integral index of job satisfaction was used for diagnosis the efficiency of management activity. Then, the relationship between the above mentioned mental state, communicativeness, self-esteem, job satisfaction, locus of control, and egocentrism was investigated. The obtained results have shown the positive correlation between the egocentrism and frustration, anxiety and also the negative correlation with job satisfaction and communicativeness. Intergroup analyses has revealed the significant differences by communicativeness and the internality’ level. The revealed results can be used for diagnosis of efficiency of management.

Keywords: egocentrism, locus control, mental state, job satisfaction, professional activity

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Authors: Ahmad Mohsin, Irfan Raza Naqvi, Syda Fatima Usamn

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Applications with higher fault tolerance index are considered more reliable and trustworthy to drive quality. In recent years application development has been shifted from traditional desktop and web to native and hybrid application(s) for the web and mobile platforms. With the emergence of Internet of things IOTs, cloud and big data trends, the need for measuring Fault Tolerance for these complex nature applications has increased to evaluate their performance. There is a phenomenal gap between fault tolerance metrics development and measurement. Classic quality metric models focused on metrics for traditional systems ignoring the essence of today’s applications software, hardware & deployment characteristics. In this paper, we have proposed simple metrics to measure fault tolerance considering general requirements for Web and Mobile Applications. We have aligned factors – subfactors, using GQM for metrics development considering the nature of mobile we apps. Systematic Mathematical formulation is done to measure metrics quantitatively. Three web mobile applications are selected to measure Fault Tolerance factors using formulated metrics. Applications are then analysed on the basis of results from observations in a controlled environment on different mobile devices. Quantitative results are presented depicting Fault tolerance in respective applications.

Keywords: web and mobile applications, reliability, fault tolerance metric, quality metrics, GQM based metrics

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Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

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The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

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Authors: Chien-Kuo Chiu

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In the displacement-based seismic design and evaluation, equivalent linearization method is one of the approximation methods to estimate the maximum inelastic displacement response of a system. In this study, the accuracy of two equivalent linearization methods are investigated. The investigation consists of three soil condition in Taiwan (Taipei Basin 1, 2, and 3) and five different heights of building (H_r= 10, 20, 30, 40, and 50 m). The first method is the Taiwan equivalent linearization method (TELM) which was proposed based on Japanese equivalent linear method considering the modification factor, α_T= 0.85. On the basis of Lin and Miranda study, the second method is proposed with some modification considering Taiwan soil conditions. From this study, it is shown that Taiwanese equivalent linearization method gives better estimation compared to the modified Lin and Miranda method (MLM). The error index for the Taiwanese equivalent linearization method are 16%, 13%, and 12% for Taipei Basin 1, 2, and 3, respectively. Furthermore, a ductility demand spectrum of single-degree-of-freedom (SDOF) system is presented in this study as a guide for engineers to estimate the ductility demand of a structure.

Keywords: displacement-based design, ductility demand spectrum, equivalent linearization method, RC buildings, single-degree-of-freedom

Procedia PDF Downloads 154

Authors: A. Chateauneuf, M. Mostoufi, D. Vyncke

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Monte Carlo (MC) simulation is a technique that provides approximate solutions to a broad range of mathematical problems. A drawback of the method is its high computational cost, especially in a high-dimensional setting, such as estimating the Tail Value-at-Risk for large portfolios or pricing basket options and Asian options. For these types of problems, one can construct an upper bound in the convex order by replacing the copula by the comonotonic copula. This comonotonic upper bound can be computed very quickly, but it gives only a rough approximation. In this paper we introduce the Comonotonic Monte Carlo (CoMC) simulation, by using the comonotonic approximation as a control variate. The CoMC is of broad applicability and numerical results show a remarkable speed improvement. We illustrate the method for estimating Tail Value-at-Risk and pricing basket options and Asian options when the logreturns follow a Black-Scholes model or a variance gamma model.

Keywords: control variate Monte Carlo, comonotonicity, option pricing, scientific computing

Procedia PDF Downloads 502

Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

Procedia PDF Downloads 293

Authors: Mariana Stuparu-Cretu, Doina-Carina Voinescu, Rodica-Mihaela Dinica, Daniela Borda, Camelia Vizireanu, Gabriela Iordachescu, Camelia Busila

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Obesity is involved in the etiology or acceleration of progression of important non-communicable diseases, such as: metabolic, cardiovascular, rheumatological, oncological and depression. It is a need to prevent the obesity occurrence, like a key link in disease management. From this point of view, the best approach is to early educate youngsters upon the need for a healthy nutrition lifestyle associated with constant physical activities. The objective of the study was to assess correlations between weight condition, physical activities and food preferences of students from South East Romania. Questionnaires were applied on high school students in Galati: 1006 girls and 880 boys, aged between 14 and 19 years (being approved by Local School Inspectorate and the Ethics Committee of the 'Dunarea de Jos' University of Galati). The collected answers have been statistically processed by using the multivariate regression method (PLS2) by Unscramble X program (Camo, Norway). Multiple variables such as age group, body mass index, nutritional habits and physical activities were separately analysed, depending on gender and general mathematical models were proposed to explain the obesity trend at an early age. The study results show that overweight and obesity are present in less than a fifth of the adolescents who were surveyed. With a very small variation and a strong correlation of over 86% for 99% of the cases, a general preference for sweet foods, nocturnal eating associated with computer work and a reduced period of physical activity is noticed for girls. In addition, the overweight girls consume sweet juices and alcohol, although a percentage of them also practice the gym. There is also a percentage of the normoponderal girls that consume high caloric foods which predispose this group to turn into overweight cases in time. Within the studied group, statistics for the boys show a positive correlation of almost 87% for over 96% of cases. They prefer high calories foods, fast food, and sweet juices, and perform medium physical activities. Both overweight and underweight boys are more sedentary. Over 15% of girls and over a quarter of boys consume alcohol. All these bad eating habits seem to increase with age, for both sexes. To conclude, obesity and overweight assessed in adolescents in S-E Romania reveal nonsignificant percentage differences between boys and girls. However, young people in this area of the country are sedentary in general; a significant percentage prefers sweets / sweet juices / fast-food and practice computer nourishing. The authors consider that at this age, it is very useful to adapt nutritional education by new methods of food processing and market supply. This would require an early understanding of the difference among foods and nutrients and the benefits of physical activities integrated into the healthy current lifestyle, as a measure for preventing and managing non-communicable chronic diseases related to nutritional errors and sedentarism. Acknowledgment— This study has been partial founded by the Francophone University Agency, Project Réseau régional dans le domaine de la santé, la nutrition et la sécurité alimentaire (SaIN), no.21899/ 06.09.2017.

Keywords: adolescents, body mass index, nutritional habits, obesity, physical activity

Procedia PDF Downloads 247

Authors: Samira Karimi-Mansoub, Rahem Abri

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Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches.

Keywords: filtering systems, personalized web search, user modeling, user search behavior

Procedia PDF Downloads 267

Authors: Isaac Kofi Mensah

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The manual system of voting has been the most widely used system of electing representatives around the globe, particularly in Africa. Due to the known numerous problems and challenges associated with the manual system of voting, many countries are migrating to the electronic voting system as a suitable and credible means of electing representatives over the manual paper-based system. This research paper therefore investigated the factors influencing adoption and use of an electronic voting system in Ghana. A total of 400 Questionnaire Instruments (QI) were administered to potential respondents in Ghana, of which 387 responded representing a response rate of 96.75%. The Technology Acceptance Model was used as the theoretical framework for the study. The research model was tested using a simple linear regression analysis with SPSS. A little of over 71.1% of the respondents recommended the Electoral Commission (EC) of Ghana to adopt an electronic voting system in the conduct of public elections in Ghana. The results indicated that all the six predictors such as perceived usefulness (PU), perceived ease of use (PEOU), perceived free and fair elections (PFFF), perceived credible elections (PCE), perceived system integrity (PSI) and citizens trust in the election management body (CTEM) were all positively significant in predicting the readiness of citizens to adopt and use an electronic voting system in Ghana. However, jointly, the hypotheses tested revealed that apart from Perceived Free and Fair Elections and Perceived Credible and Transparent Elections, all the other factors such as PU, Perceived System Integrity and Security and Citizen Trust in the Election Management Body were found to be significant predictors of the Willingness of Ghanaians to use an electronic voting system. All the six factors considered in this study jointly account for about 53.1% of the reasons determining the readiness to adopt and use an electronic voting system in Ghana. The implications of this research finding on elections in Ghana are discussed.

Keywords: credible elections, Election Management Body (EMB), electronic voting, Ghana, Technology Acceptance Model (TAM)

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Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

Procedia PDF Downloads 170

Authors: Jingwen Shan

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In order to explore the key factors affecting the robot program learning intention of school students, this study takes the technology acceptance model as the theoretical basis and invites 167 students from Jiading District of Shanghai as the research subjects. In the robot course, the model of school students on their learning behavior is constructed. By verifying the causal path relationship between variables, it is concluded that teachers can enhance students’ perceptual usefulness to robotics courses by enhancing subjective norms, entertainment perception, and reducing technical anxiety, such as focusing on the gradual progress of programming and analyzing learner characteristics. Students can improve perceived ease of use by enhancing self-efficacy. At the same time, robot hardware designers can optimize in terms of entertainment and interactivity, which will directly or indirectly increase the learning intention of the robot course. By changing these factors, the learning behavior of primary and secondary school students can be more sustainable.

Keywords: TAM, learning behavior intentions, robot courses, primary and secondary school students

Procedia PDF Downloads 133

Authors: Ebrahim H. Kapeel, Ahmed M. Kamel, Hossam Hendy, Yehia Z. Elhalwagy

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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control law is designed for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.

Keywords: attitude control, nonlinear PID, dynamic inversion

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Authors: Jung-Hun Cho, Tae-Heon Moon, Jin-Hak Lee

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Land price contains the comprehensive characteristics of urban space, representing the social and economic features of the city. Accordingly, land price can be utilized as an indicator, which can identify the changes of spatial structure and socioeconomic variations caused by urban development. This study attempted to explore the changes in land price by a new road construction. Methodologically, it adopted Space Syntax, which can interpret urban spatial structure comprehensively, to identify the relationship between the forms of road networks and land price. The result of the regression analysis showed the ‘integration index’ of Space Syntax is statistically significant and has a strong correlation with land price. If the integration value is high, land price increases proportionally. Subsequently, using regression equation, it tried to predict the land price changes of each of the lots surrounding the roads that are newly opened. The research methods or study results have the advantage of predicting the changes in land price in an easy way. In addition, it will contribute to planners and project managers to establish relevant polices and smoothing urban regeneration projects through enhancing residents’ understanding by providing possible results and advantages in their land price before the execution of urban regeneration and development projects.

Keywords: space syntax, urban regeneration, spatial structure, official land price

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Authors: Oktavia Eka Puspita

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The possibility of using Solid Lipid Nanoparticles (SLN) for topical use is an interesting feature concerning this system has occlusive properties on the skin surface therefore enhance the penetration of drugs through the stratum corneum by increased hydration. This advantage can be used to enhance the drug penetration of topical delivery such as Diclofenac sodium for the relief of signs and symptoms of osteoarthritis, rheumatoid arthritis and ankylosing spondylitis. The purpose of this study was focused on the preparation and physical characterization of Diclofenac sodium loaded SLN (D-SLN). D loaded SLN were prepared by hot homogenization followed by ultrasonication technique. Since the occlusion factor of SLN is related to its particle size the formulation of D-SLN in present study two formulations different in its surfactant contents were prepared to investigate the difference of the particle size resulted. Surfactants selected for preparation of formulation A (FA) were lecithin soya and Tween 80 whereas formulation B (FB) were lecithin soya, Tween 80, and Sodium Lauryl Sulphate. D-SLN were characterized for particle size and distribution, polydispersity index (PI), zeta potential using Beckman-Coulter Delsa™ Nano. Overall, the particle size obtained from FA was larger than FB. FA has 90% of the particles were above 1000 nm, while FB has 90% were below 100 nm.

Keywords: solid lipid nanoparticles, hot homogenization technique, particle size analysis, topical administration

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Authors: C. Hall, J. Ramos, V. Ramasamy

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Hydrocarbon-based fuel vehicles are a major contributor to air pollution due to harmful emissions produced, leading to a demand for cleaner fuel types. A leader in this pursuit is hydrogen, with its application in vehicles producing zero harmful emissions and the only by-product being water. To compete with the performance of conventional vehicles, hydrogen gas must be stored on-board of vehicles in cylinders at high pressures (35–70 MPa) and have a short refueling duration (approximately 3 mins). However, the fast-filling of hydrogen cylinders causes a significant rise in temperature due to the combination of the negative Joule-Thompson effect and the compression of the gas. This can lead to structural failure and therefore, a maximum allowable internal temperature of 85°C has been imposed by the International Standards Organization. The technological solution to tackle the issue of rapid temperature rise during the refueling process is to decrease the temperature of the gas entering the cylinder. Pre-cooling of the gas uses a heat exchanger and requires energy for its operation. Thus, it is imperative to determine the least amount of energy input that is required to lower the gas temperature for cost savings. A validated universal thermodynamic model is used to identify an energy-efficient pre-cooling strategy. The model requires negligible computational time and is applied to previously validated experimental cases to optimize pre-cooling requirements. The pre-cooling characteristics include the location within the refueling timeline and its duration. A constant pressure-ramp rate is imposed to eliminate the effects of rapid changes in mass flow rate. A pre-cooled gas temperature of -40°C is applied, which is the lowest allowable temperature. The heat exchanger is assumed to be ideal with no energy losses. The refueling of the cylinders is modeled with the pre-cooling split in ten percent time intervals. Furthermore, varying burst durations are applied in both the early and late stages of the refueling procedure. The model shows that pre-cooling in the later stages of the refuelling process is more energy-efficient than early pre-cooling. In addition, the efficiency of pre-cooling towards the end of the refueling process is independent of the pressure profile at the inlet. This leads to the hypothesis that pre-cooled gas should be applied as late as possible in the refueling timeline and at very low temperatures. The model had shown a 31% reduction in energy demand whilst achieving the same final gas temperature for a refueling scenario when pre-cooling was applied towards the end of the process. The identification of the most energy-efficient refueling approaches whilst adhering to the safety guidelines is imperative to reducing the operating cost of hydrogen refueling stations. Heat exchangers are energy-intensive and thus, reducing the energy requirement would lead to cost reduction. This investigation shows that pre-cooling should be applied as late as possible and for short durations.

Keywords: cylinder, hydrogen, pre-cooling, refueling, thermodynamic model

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Authors: Omar Amoudi, Mariya Khalid

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The limitation of the public funds for the infrastructure projects and with the deterioration of international oil prices and the negative consequences on the economies of oil producing and exporting countries, Oman has encouraged the partnership between the public and private sectors. As the private sector has a role in planning, financing, designing, operating and the maintenance of the public services. There is no doubt that, the adoption of Public Private Partnership (PPP) strategy faces many challenges which might affect the project seriously if it is not overcome in earlier time. These challenges depend on the level of understanding of the strategy, the roles and regulations and the availability of resources as well. This research aims at identifying the challenges facing the PPP infrastructure projects in Oman based on the similar previous studies supported by questionnaire survey and semi structured interviews. It also seeks to discuss the rationale for adoption in Oman and uncover the current status of PPP strategy. The identified challenges were ranked according to the importance index of each challenge. After analysis of data, it has observed that, the main challenges facing PPPs projects in Oman are high participation cost, high projects cost and regulation changes. The PPP strategy has to be adopted well and with a high level of experience in order to ensure a successful implementation of PPP projects in Oman.

Keywords: public private partnership (PPP), challenges, infrastructure, Oman

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Authors: Peng Wang, Tigang Jiang

Abstract:

The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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Authors: Sukhbir Singh

Abstract:

This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

Abstract:

The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Wenzhe Li, Xiaoyu Ying, Grace Ding

Abstract:

Architecture plane form is an important consideration in the design of green buildings due to its significant impact on energy performance. The most effective method to consider energy performance in the early design stages is parametric modelling. This paper presents a methodology to program plane forms using MATLAB language, generating 16 kinds of plane forms by changing four designed parameters. DesignBuilder (an energy consumption simulation software) was proposed to simulate the energy consumption of the generated planes. A regression mathematical model was established to study the relationship between the plane forms and their energy consumption. The main finding of the study suggested that there was a cubic function relationship between the depth-ratio of U-shaped buildings and energy consumption, and there is also a cubic function relationship between the width-ratio and energy consumption. In the design, the depth-ratio of U-shaped buildings should not be less than 2.5, and the width-ratio should not be less than 2.

Keywords: graphic parameterization, green building design, mathematical model, plane form

Procedia PDF Downloads 140