Search results for: online flood prediction system

Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy

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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.

Keywords: e-learning system, gamification, motivation, social comparison, visualization

Procedia PDF Downloads 146

Authors: İmren Öztürk Yılmaz, Abdullah Yasin Bilici, Yasin Atalay Candemir

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The system consists of 4 main elements: motion system, image acquisition system, image processing software, and control interface. The parts coming out of the production line to enter the image processing system with the conveyor belt at the end of the line. The 3D scanning of the produced part is performed with the laser scanning system integrated into the system entry side. With the 3D scanning method, it is determined at what position and angle the parts enter the system, and according to the data obtained, parameters such as part origin and conveyor speed are calculated with the designed software, and the robot is informed about the position where it will take part. The robot, which receives the information, takes the produced part on the belt conveyor and shows it to high-resolution cameras for quality control. Measurement processes are carried out with a maximum error of 20 microns determined by the experiments.

Keywords: quality control, industry 4.0, image processing, automated fault detection, digital visual inspection

Procedia PDF Downloads 107

Authors: Ana María Rojas Chaparro, Cristian Camilo Sarmiento Chaves

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Given the growing importance of logistics as a discipline for efficient management of materials flow and information, the adoption of tools that permit to create facilities in making decisions based on a global perspective of the system studied has been essential. The article shows how from a concepts-based model is possible to organize and represent in appropriate way the reality, showing accurate and timely information, features that make this kind of models an ideal component to support an information system, recognizing that information as relevant to establish particularities that allow get a better performance about the evaluated sector.

Keywords: system, information, conceptual model, logistics

Procedia PDF Downloads 487

Authors: Sulafah Basahel

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Nowadays, Higher Education Institutions (HEIs) around the world are attempting to utilize Information and Communication Technologies (ICTs) to enhance learning process and strategies of knowledge delivery for students through Distance Education (DE) system. Stakeholders in DE system face a complex situation of different ill-defined and related issues that influence decision making process. In this study system thinking as a body of knowledge is used to explore the emergent properties that produced from these connections between issues and could have either positive or negative outcomes for the DE development. Checkland Soft System Methodology (SSM) - Mode 2 is employed in a cultural context of Saudi Arabia for more knowledge acquisition purposes among multiple stakeholders in DE rather than solving problems to achieve an overall development of DE system. This paper will discuss some political, cultural issues and connections between them that impact on effectiveness of stakeholders’ activities and relations. This study will significantly contribute to both system thinking and education fields by leading decision makers in DE to reconsider future plans, strategies and right actions for more successful educational practices.

Keywords: distance education, higher education institutions, ill-defined issues, soft system methodology-Mode 2

Procedia PDF Downloads 265

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: D. G. Badagha, C. D. Modhera, S. A. Vasanwala

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There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Keywords: artificial neural network, high performance concrete, rebound hammer, strength prediction

Procedia PDF Downloads 149

Authors: Mohammed Alokshiya, Alaeddinne D. Eljamassi

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This study discusses the condition of bus service in Gaza Strip through testing certain hypotheses assuming that public is not satisfied with bus system in Gaza. This testing is proceeded using questionnaire. The study also includes the evaluation of ten bus stops in Gaza city as a case study using GIS, and suggests a design case study for the bus system in the university zone in Gaza city. The research indicates that there is a general dissatisfaction with bus system in Gaza Strip, with respect to buses in service, drivers and bus stops. The study also gives a design for a bus stop and its frequency in university zone in Gaza city. Finally, the researcher recommends that more interest should be given to bus system, through actual procedures such as insuring the suitability of bus for transferring passengers before updating bus license, decreasing taxes of importing new buses, and holding awareness raising sessions for bus drivers.

Keywords: public transport, bus system, public satisfaction, bus stop locating

Procedia PDF Downloads 331

Authors: Merkineh Markos Lorato, Gedefaw Diress Alene

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Introduction: Visual impairment is any condition of the eye or visual system that results in loss/reduction of visual functioning. It significantly influences the academic routine and social activities of children, and the effect is severe for low-income countries like Ethiopia. So, this study aimed to determine the pooled prevalence of visual impairment among school children in Ethiopia. Methods: Databases such as Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, World Wide Web of Science, and Cochrane Library searched to retrieve eligible articles. In addition, Google Scholar and a reference list of the retrieved eligible articles were addressed. Studies that reported the prevalence of visual impairment were included to estimate the pooled prevalence. Data were extracted using a standardized data extraction format prepared in Microsoft Excel and analysis was held using STATA 11 statistical software. I² was used to assess the heterogeneity. Because of considerable heterogeneity, a random effect meta-analysis model was used to estimate the pooled prevalence of visual impairment among school children in Ethiopia. Results: The result of 9 eligible studies showed that the pooled prevalence of visual impairment among school children in Ethiopia was 7.01% (95% CI: 5.46, 8.56%). In the subgroup analysis, the highest prevalence was reported in South Nations Nationalities and Tigray region together (7.99%; 3.63, 12.35), while the lowest prevalence was reported in Addis Ababa (5.73%; 3.93, 7.53). Conclusion: The prevalence of visual impairment among school children is significantly high in Ethiopia. If it is not detected and intervened early, it will cause a lifetime threat to visually impaired school children, so that school vision screening program plan and its implementation may cure the life quality of future generations in Ethiopia.

Keywords: visual impairment, school children, Ethiopia, prevalence

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Authors: Ahmed Mozamel, Kemal Yildizli

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Due to mechanical energy losses and a competitive of minimizing these losses and increases the machine efficiency, the need for contactless gearing system has raised. In this work, one stage of mechanical planetary gear transmission system integrated with one stage of magnetic planetary gear system is designed as a two-stage hybrid gearbox system. The permanent magnets internal energy in the form of the magnetic field is used to create meshing between contactless magnetic rotors in order to provide self-system protection against overloading and decrease the mechanical loss of the transmission system by eliminating the friction losses. Classical methods, such as analytical, tabular method and the theory of elasticity are used to calculate the planetary gear design parameters. The finite element method (ANSYS Maxwell) is used to predict the behaviors of a magnetic gearing system. The concentric magnetic gearing system has been modeled and analyzed by using 2D finite element method (ANSYS Maxwell). In addition to that, design and manufacturing processes of prototype components (a planetary gear, concentric magnetic gear, shafts and the bearings selection) of a gearbox system are investigated. The output force, the output moment, the output power and efficiency of the hybrid gearbox system are experimentally evaluated. The viability of applying a magnetic force to transmit mechanical power through a non-contact gearing system is presented. The experimental test results show that the system is capable to operate continuously within the range of speed from 400 rpm to 3000 rpm with the reduction ratio of 2:1 and maximum efficiency of 91%.

Keywords: hybrid gearbox, mechanical gearboxes, magnetic gears, magnetic torque

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Authors: Bong-Keun Jung, Jung-Yeon Kim

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The aim of this study was to investigate usability of detachable brake system for moving apparatus such as baby strollers, manual wheelchairs or walkers. The current brake system was proposed to prevent that moving apparatus slip on sloping roadways when unattended as current built-in manual brake for the moving apparatus is not able to react for the matter. The developed detachable brake system enacted by force sensor on the hand grip showed the possibilities to prevent unexpected accident due to uncontrolled stroller or wheelchair use. To investigate the quality and acceptance of this new technology, standard stroller testbed was built and the use of moving apparatus which attached to the proposed brake system was analyzed through video recording. Additional usability questionnaires were given to test users for measuring usability issues.

Keywords: brake system, stroller, wheelchair, usability test

Procedia PDF Downloads 732

Authors: Abbas Anser, Ahmad Irfan

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The main purpose of the VAV (Variable Air Volume) in Heating, Ventilation, and Air Conditioning (HVAC) system is to reduce energy consumption and make the buildings comfortable for the occupants. For better performance of the air conditioning system, different control techniques have been developed. In this paper, an Improved Sliding Mode Control (ISMC), based on Power Rate Exponential Reaching Law (PRERL), has been implemented on a VAV air conditioning system. Through the proposed technique, fast response and robustness have been achieved. To verify the efficacy of ISMC, a comparison of the suggested control technique has been made with Exponential Reaching Law (ERL) based SMC. And secondly, chattering, which is unfavorable as it deteriorates the mechanical parts of the air conditioning system by the continuous movement of the mechanical parts and consequently it increases the energy loss in the air conditioning system, has been alleviated. MATLAB/SIMULINK results show the effectiveness of the utilized scheme, which ensures the enhancement of the energy efficiency of the VAV air conditioning system.

Keywords: PID, SMC, HVAC, PRERL, feedback linearization, VAV, chattering

Procedia PDF Downloads 115

Authors: Xiaoqing Peng, Aijing Luo, Yang Chen

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Background: Cyberchondria, as an "emerging risk" accompanied by the information era, is a new abnormal pattern characterized by excessive or repeated online searches for health-related information and escalating health anxiety, which endangers people's physical and mental health and poses a huge threat to public health. Objective: To explore and discuss the research status, hotspots and trends of Cyberchondria. Methods: Based on a total of 77 articles regarding "Cyberchondria" extracted from Web of Science from the beginning till October 2019, the literature trends, countries, institutions, hotspots are analyzed by bibliometric analysis, the concept definition of Cyberchondria, instruments, relevant factors, treatment and intervention are discussed as well. Results: Since "Cyberchondria" was put forward for the first time in 2001, the last two decades witnessed a noticeable increase in the amount of literature, especially during 2014-2019, it quadrupled dramatically at 62 compared with that before 2014 only at 15, which shows that Cyberchondria has become a new theme and hot topic in recent years. The United States was the most active contributor with the largest publication (23), followed by England (11) and Australia (11), while the leading institutions were Baylor University(7) and University of Sydney(7), followed by Florida State University(4) and University of Manchester(4). The WoS categories "Psychiatry/Psychology " and "Computer/ Information Science "were the areas of greatest influence. The concept definition of Cyberchondria is not completely unified in the world, but it is generally considered as an abnormal behavioral pattern and emotional state and has been invoked to refer to the anxiety-amplifying effects of online health-related searches. The first and the most frequently cited scale for measuring the severity of Cyberchondria called “The Cyberchondria Severity Scale (CSS) ”was developed in 2014, which conceptualized Cyberchondria as a multidimensional construct consisting of compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals which was proved to be not necessary for this construct later. Since then, the Brazilian, German, Turkish, Polish and Chinese versions were subsequently developed, improved and culturally adjusted, while CSS was optimized to a simplified version (CSS-12) in 2019, all of which should be worthy of further verification. The hotspots of Cyberchondria mainly focuses on relevant factors as follows: intolerance of uncertainty, anxiety sensitivity, obsessive-compulsive disorder, internet addition, abnormal illness behavior, Whiteley index, problematic internet use, trying to make clear the role played by “associated factors” and “anxiety-amplifying factors” in the development of Cyberchondria, to better understand the aetiological links and pathways in the relationships between hypochondriasis, health anxiety and online health-related searches. Although the treatment and intervention of Cyberchondria are still in the initial stage of exploration, there are kinds of meaningful attempts to seek effective strategies from different aspects such as online psychological treatment, network technology management, health information literacy improvement and public health service. Conclusion: Research on Cyberchondria is in its infancy but should be deserved more attention. A conceptual consensus on Cyberchondria, a refined assessment tool, prospective studies conducted in various populations, targeted treatments for it would be the main research direction in the near future.

Keywords: cyberchondria, hypochondriasis, health anxiety, online health-related searches

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Authors: Wenjuan Du, Jingtian Bi, Tong Wang, Haifeng Wang

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Grid connection of a large-scale wind farm affects power system small-signal angular stability in two aspects. Firstly, connection of the wind farm brings about the change of load flow and configuration of a power system. Secondly, the dynamic interaction is introduced by the wind farm with the synchronous generators (SGs) in the power system. This paper proposes a method to assess the two aspects of the effect of the wind farm on power system small-signal angular stability. The effect of the change of load flow/system configuration brought about by the wind farm can be examined separately by displacing wind farms with constant power sources, then the effect of the dynamic interaction of the wind farm with the SGs can be also computed individually. Thus, a clearer picture and better understanding on the power system small-signal angular stability as affected by grid connection of the large-scale wind farm are provided. In the paper, an example power system with grid connection of a wind farm is presented to demonstrate the proposed approach.

Keywords: power system small-signal angular stability, power system low-frequency oscillations, electromechanical oscillation modes, wind farms, double fed induction generator (DFIG)

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Authors: Mohamad Saberi, Arash Sohrabi

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Tuned liquid damper is one the passive structural control ways which has been used since mid-1980 decade for seismic control in civil engineering. This system is made of one or many tanks filled with fluid, mostly water that installed on top of the high raised structure and used to prevent structure vibration. In this article we will show how to make seismic table contain TLD system and analysis the result of using this system in our structure. Results imply that when frequency ratio approaches 1 this system can perform its best in both dissipate energy and increasing structural damping. And also results of these serial experiments are proved compatible with Hunzer linear theory behaviour.

Keywords: TLD, seismic table, structural system, Hunzer linear behaviour

Procedia PDF Downloads 372

Authors: Mohammed N. Al Kindi, Mazin Al Khabouri, Khalsa Al Lamki, Tommasso Pappuci, Giovani Romeo, Nadia Al Wardy

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Hereditary hearing loss is a heterogeneous group of complex disorders with an overall incidence of one in every five hundred newborns presented as syndromic and non-syndromic forms. Cadherin-related 23 (CDH23) is one of the listed deafness causative genes. CDH23 is found to be expressed in the stereocilia of hair cells and the retina photoreceptor cells. Defective CDH23 has been associated mostly with prelingual severe-to-profound sensorineural hearing loss (SNHL) in either syndromic (USH1D) or non-syndromic SNHL (DFNB12). An Omani family diagnosed clinically with severe-profound sensorineural hearing loss was genetically analysed by whole exome sequencing technique. A novel homozygous missense variant, c.A7451C (p.D2484A), in exon 53 of CDH23 was detected. One hundred and thirty control samples were analysed where all were negative for the detected variant. The variant was analysed in silico for pathogenicity verification using several mutation prediction software. The variant proved to be a pathogenic mutation and is reported for the first time in Oman and worldwide. It is concluded that in silico mutation prediction analysis might be used as a useful molecular diagnostics tool benefiting both genetic counseling and mutation verification. The aspartic acid 2484 alanine missense substitution might be the main disease-causing mutation that damages CDH23 function and could be used as a genetic hearing loss marker for this particular Omani family.

Keywords: Cdh23, d2484a, in silico, Oman

Procedia PDF Downloads 209

Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

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This paper deals with human activity recognition from sensor data. It is an active research area, and the main objective is to obtain a high recognition rate. In this work, a recognition system based on expert systems is proposed; the recognition is performed using the objects, object states, and gestures and taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions and the activity). The system recognizes complex activities after decomposing them into simple, easy-to-recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

Procedia PDF Downloads 100

Authors: Marlies Achenbach

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System competencies play a key role to ensure an effective and efficient improvement of production systems. Thus, there can be observed an increasing demand for developing system competencies in industry as well as in engineering education. System competencies consist of the following two main abilities: Evaluating the current state of a production system and developing a target state. The innovative course ‘multi-perspective learning in a real production plant (multi real)’ is developed to create a learning setting that supports the development of these system competencies. Therefore, the setting combines two innovative aspects: First, the Learning takes place in heterogeneous groups formed by students as well as professionals and managers from industry. Second, the learning takes place in a real production plant. This paper presents the innovative didactic concept of ‘multi real’ in detail, which will initially be implemented in October/November 2016 in the industrial engineering, logistics and mechanical master’s program at TU Dortmund University.

Keywords: experiential learning, heterogeneous groups, improving production systems, system competencies

Procedia PDF Downloads 418

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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Authors: Mary Booth

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Biophotovoltaics is a method of green energy generation derived from exposing plants to lights. Its vast potential is hampered by the public’s relative ignorance of its existence. This work aims to formalize the principles of the physical processes of biophotovoltaics into a comprehensible visual software model, thus amplifying the human thought process. The methods used involve initially crafting a scale model of a working biophotovoltaic system from household materials inspired by the work of Paolo Bombelli. The scale model is then programmed into a system-level simulation, wherein a 3D animation dissects the system and its general energy generation process. The completed 3D system-level simulation ultimately creates a simplified visual understanding of the complex principles of the biophotovoltaic system.

Keywords: 3D, biophotovoltaics, render

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Authors: Kostas Metaxiotis, Kostas Liagkouras

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This study presents an Expert System specially designed to be used with Multiobjective Evolutionary Algorithms (MOEAs) for the solution of the portfolio selection problem. The validation of the proposed hybrid System is done by using data sets from Hang Seng 31 in Hong Kong, DAX 100 in Germany and FTSE 100 in UK. The performance of the proposed system is assessed in comparison with the Non-dominated Sorting Genetic Algorithm II (NSGAII). The evaluation of the performance is based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it. The results show that the proposed hybrid system is efficient for the solution of this kind of problems.

Keywords: expert systems, multi-objective optimization, evolutionary algorithms, portfolio selection

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Authors: Liliana Rusu

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The goal of the proposed work is to provide a more comprehensive picture of the wind and wave climate in the Romanian nearshore, using the results provided by numerical models. The Romanian coastal environment is located in the western side of the Black Sea, the more energetic part of the sea, an area with heavy maritime traffic and various offshore operations. Information about the wind and wave climate in the Romanian waters is mainly based on observations at Gloria drilling platform (70 km from the coast). As regards the waves, the measurements of the wave characteristics are not so accurate due to the method used, being also available for a limited period. For this reason, the wave simulations that cover large temporal and spatial scales represent an option to describe better the wave climate. To assess the wind climate in the target area spanning 1992–2016, data provided by the NCEP-CFSR (U.S. National Centers for Environmental Prediction - Climate Forecast System Reanalysis) and consisting in wind fields at 10m above the sea level are used. The high spatial and temporal resolution of the wind fields is good enough to represent the wind variability over the area. For the same 25-year period, as considered for the wind climate, this study characterizes the wave climate from a wave hindcast data set that uses NCEP-CFSR winds as input for a model system SWAN (Simulating WAves Nearshore) based. The wave simulation results with a two-level modelling scale have been validated against both in situ measurements and remotely sensed data. The second level of the system, with a higher resolution in the geographical space (0.02°×0.02°), is focused on the Romanian coastal environment. The main wave parameters simulated at this level are used to analyse the wave climate. The spatial distributions of the wind speed, wind direction and the mean significant wave height have been computed as the average of the total data. As resulted from the amount of data, the target area presents a generally moderate wave climate that is affected by the storm events developed in the Black Sea basin. Both wind and wave climate presents high seasonal variability. All the results are computed as maps that help to find the more dangerous areas. A local analysis has been also employed in some key locations corresponding to highly sensitive areas, as for example the main Romanian harbors.

Keywords: numerical simulations, Romanian nearshore, waves, wind

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Authors: Arun Dhakal, Geoff Cockfield, Tek Narayan Maraseni

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This paper attempts to fulfil the gap in measuring adoption in agroforestry studies. It explains the derivation of an index of adoption rate in a Nepalese context and examines the factors affecting adoption of agroforestry-based land management practice (AFLMP) in the Dhanusha District of Nepal. Data about the different farm practices and the factors (bio-physical, socio-economic) influencing adoption were collected during focus group discussion and from the randomly selected households using a household survey questionnaire, respectively. A multivariate regression model was used to determine the factors. The factors (variables) found to significantly affect adoption of AFLMP were: farm size, availability of irrigation water, education of household heads, agricultural labour force, frequency of visits by extension workers, expenditure on farm inputs purchase, household’s experience in agroforestry, and distance from home to government forest. The regression model explained about 75% of variation in adoption decision. The model rejected ‘erosion hazard’, ‘flood hazard’ and ‘gender’ as determinants of adoption, which in case of single agroforestry practice were major variables and played positive role. Out of eight variables, farm size played the most powerful role in explaining the variation in adoption, followed by availability of irrigation water and education of household heads. The results of this study suggest that policies to promote the provision of irrigation water, extension services and motivation to obtaining higher education would probably provide the incentive to adopt agroforestry elsewhere in the terai of Nepal.

Keywords: agroforestry, adoption index, determinants of adoption, step-wise linear regression, Nepal

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Authors: Jummalla Aashrith, N. L. Shiva Sai, K. Bhavya Sri

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The swift progress of web technology has not only amassed a vast reservoir of internet data but also triggered a substantial surge in data generation. The internet has metamorphosed into one of the dynamic hubs for online education, idea dissemination, as well as opinion-sharing. Notably, the widely utilized social networking platform Twitter is experiencing considerable expansion, providing users with the ability to share viewpoints, participate in discussions spanning diverse communities, and broadcast messages on a global scale. The upswing in online engagement has sparked a significant curiosity in subjective analysis, particularly when it comes to Twitter data. This research is committed to delving into sentiment analysis, focusing specifically on the realm of Twitter. It aims to offer valuable insights into deciphering information within tweets, where opinions manifest in a highly unstructured and diverse manner, spanning a spectrum from positivity to negativity, occasionally punctuated by neutrality expressions. Within this document, we offer a comprehensive exploration and comparative assessment of modern approaches to opinion mining. Employing a range of machine learning algorithms such as Naive Bayes and Logistic Regression, our investigation plunges into the domain of Twitter data streams. We delve into overarching challenges and applications inherent in the realm of subjectivity analysis over Twitter.

Keywords: machine learning, sentiment analysis, visualisation, python

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Authors: June-Jei Kuo, Yi-Chuan Hsieh

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Because of the rapid growth of information technology, more and more libraries introduce the new information retrieval systems to enhance the users’ experience, improve the retrieval efficiency, and increase the applicability of the library resources. Nevertheless, few of them are discussed the usability from the users’ aspect. The aims of this study are to understand that the scenario of the information retrieval system utilization, and to know why users are willing to continuously use the web-scale discovery system to improve the web-scale discovery system and promote their use of university libraries. Besides of questionnaires, observations and interviews, this study employs both Information System Success Model introduced by DeLone and McLean in 2003 and the flow theory to evaluate the system quality, information quality, service quality, use, user satisfaction, flow, and continuing to use web-scale discovery system of students from National Chung Hsing University. Then, the results are analyzed through descriptive statistics and structural equation modeling using AMOS. The results reveal that in web-scale discovery system, the user’s evaluation of system quality, information quality, and service quality is positively related to the use and satisfaction; however, the service quality only affects user satisfaction. User satisfaction and the flow show a significant impact on continuing to use. Moreover, user satisfaction has a significant impact on user flow. According to the results of this study, to maintain the stability of the information retrieval system, to improve the information content quality, and to enhance the relationship between subject librarians and students are recommended for the academic libraries. Meanwhile, to improve the system user interface, to minimize layer from system-level, to strengthen the data accuracy and relevance, to modify the sorting criteria of the data, and to support the auto-correct function are required for system provider. Finally, to establish better communication with librariana commended for all users.

Keywords: web-scale discovery system, discovery system, information system success model, flow theory, academic library

Procedia PDF Downloads 94

Authors: Angelo I. Aquino, Luis Ma. T. Bo-ot

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We use the Homotopy Analysis Method (HAM) to solve the system of equations modeling the two-level system and extract results which will pinpoint to turbulent behavior. We look at multi-valued solutions as indicative of turbulence or turbulent-like behavior. We take dierent specic cases which result in multi-valued velocities. The solutions are in series form and application of HAM ensures convergence in some region.

Keywords: multivalued solutions, homotopy analysis method, two-level system, equation

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Authors: P. C. Tewari, Parveen Kumar

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The paper describes the availability analysis of milling system of a rice milling plant using probabilistic approach. The subsystems under study are special purpose machines. The availability analysis of the system is carried out to determine the effect of failure and repair rates of each subsystem on overall performance (i.e. steady state availability) of system concerned. Further, on the basis of effect of repair rates on the system availability, maintenance repair priorities have been suggested. The problem is formulated using Markov Birth-Death process taking exponential distribution for probable failures and repair rates. The first order differential equations associated with transition diagram are developed by using mnemonic rule. These equations are solved using normalizing conditions and recursive method to drive out the steady state availability expression of the system. The findings of the paper are presented and discussed with the plant personnel to adopt a suitable maintenance policy to increase the productivity of the rice milling plant.

Keywords: availability modeling, Markov process, milling system, rice milling plant

Procedia PDF Downloads 229

Authors: Prof. Ammal Mokhtar Metwally, Samia M. Sami, Nihad A. Ibrahim, Fatma A. Shaaban, Iman I. Salama

Abstract:

Objectives: Reducing neonatal mortality by 2030 is still a challenging goal in developing countries. low birth weight (LBW) is a significant contributor to this, especially where weighing newborns is not possible routinely. The present study aimed to determine a simple, easy, reliable anthropometric measure(s) that can predict LBW) and neonatal mortality. Methods: A prospective cohort study of 570 babies born in districts of El Menia governorate, Egypt (where most deliveries occurred at home) was examined at birth. Newborn weight, length, head, chest, mid-arm, and thigh circumferences were measured. Follow up of the examined neonates took place during their first four weeks of life to report any mortalities. The most predictable anthropometric measures were determined using the statistical package of SPSS, and multiple Logistic regression analysis was performed.: Results: Head and chest circumferences with cut-off points < 33 cm and ≤ 31.5 cm, respectively, were the significant predictors for LBW. They carried the best combination of having the highest sensitivity (89.8 % & 86.4 %) and least false negative predictive value (1.4 % & 1.7 %). Chest circumference with a cut-off point ≤ 31.5 cm was the significant predictor for neonatal mortality with 83.3 % sensitivity and 0.43 % false negative predictive value. Conclusion: Using chest circumference with a cut-off point ≤ 31.5 cm is recommended as a single simple anthropometric measurement for the prediction of both LBW and neonatal mortality. The predicted measure could act as a substitute for weighting newborns in communities where scales to weigh them are not routinely available.

Keywords: low birth weight, neonatal mortality, anthropometric measures, practical screening

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Authors: Faith Fang Xi Ooi, Kam-Fong Lee

Abstract:

Headlines are generally the summary of the content of news articles. With the added influence of hectic lifestyles, readers may rely solely on the headlines for information. In the media, what is reported concerning health issues are government responses and community involvement. There is a need for a call to action to curb health issues and not just reporting on what the government is doing about these health-related issues. In other words, linguistic elements of persuasive communicative function should be realized when reporting on health issues. Hence, this paper aims at identifying and analyzing the transitivity, Mood and Modality systems in two hundred news headlines from two Malaysian online news portals, namely The Star Online and New Straits Times. This study employs the purposive sampling method to obtain the news headlines on healthy eating using the search keyword ‘healthy eating’ and is based on Halliday’s Systemic Functional Linguistics (SFL) framework. The results show that the Material process dominates the process types along with its participants of Scope and Goal. The mood type that constitutes most of the headlines in the two newspapers is the declarative mood. Moreover, for Modality, the median Probability constitutes the highest in the headlines on healthy eating. This study contributes to the implications of being a source of reference for news writers and producers in constructing news headlines and for health campaign strategists to realize the persuasive appeals to influence behaviors and attitudes of the public towards healthy eating.

Keywords: healthy eating, modality, mood, news headlines, SFL

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Authors: Po-Chun Lee, Li-Lin Liang, Ching-Yuan Huang

Abstract:

Purpose: Research on electronic word-of-mouth (eWOM)& online review has been widely used in service industry management research in recent years. The SERVQUAL scale is the most commonly used method to measure service quality. Therefore, the purpose of this research is to combine electronic word of mouth & online review with the SERVQUAL scale. To explore the comparative study of positive and negative electronic word-of-mouth reviews of a certain armed force general hospital in Taiwan. Data sources: This research obtained online word-of-mouth comment data on google maps from a military hospital in Taiwan in the past ten years through Internet data mining technology. Research methods: This study uses the semantic content analysis method to classify word-of-mouth reviews according to the revised PZB SERVQUAL scale. Then carry out statistical analysis. Results of data synthesis: The results of this study disclosed that the negative reviews of this military hospital in Taiwan have been increasing year by year. Under the COVID-19 epidemic, positive word-of-mouth has a downward trend. Among the five determiners of SERVQUAL of PZB, positive word-of-mouth reviews performed best in “Assurance,” with a positive review rate of 58.89%, Followed by 43.33% of “Responsiveness.” In negative word-of-mouth reviews, “Assurance” performed the worst, with a positive rate of 70.99%, followed by responsive 29.01%. Conclusions: The important conclusions of this study disclosed that the total number of electronic word-of-mouth reviews of the military hospital has revealed positive growth in recent years, and the positive word-of-mouth growth has revealed negative growth after the epidemic of COVID-19, while the negative word-of-mouth has grown substantially. Regardless of the positive and negative comments, what patients care most about is “Assurance” of the professional attitude and skills of the medical staff, which needs to be strengthened most urgently. In addition, good “Reliability” will help build positive word-of-mouth. However, poor “Responsiveness” can easily lead to the spread of negative word-of-mouth. This study suggests that the hospital should focus on these few service-oriented quality management and audits.

Keywords: quality of medical service, electronic word-of-mouth, armed forces general hospital

Procedia PDF Downloads 174