Search results for: traditional models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10915

Search results for: traditional models

4405 Tourists' Percepion of Osun Osogbo Festival in Osogbo, Osun State Nigeria

Authors: Yina Donald Orga

Abstract:

Osun Osogbo festival is one of the biggest art festivals in Nigeria with over 235, 518 tourist visits in 2014. The purpose of this study is to generate data on the tourists’ perception of Osun Osogbo Festival in Osogbo, Osun State Nigeria. Based on the population of 199, 860 tourist visits at Osun Osogbo festival in 2013, Krejcie and Morgan sample size table was used to select 768 tourists/respondents. Likert questionnaire were used to elicit data from the respondents. Descriptive statistic was used to describe the characteristics of respondents and analyse the tourists’ perception of the festival. The findings from data analysed suggest that the trend of domestic and international tourist visits in the past ten years for the festival had shown a consistent increase since 2004 except in 2007 and 2008 and continue to increase up to 2013. This is an indication that the tourists are satisfied with traditional, historical and authenticity features of the festival. Also, findings from the study revealed that the tourists are not satisfied with the number of toilets at Osun Sacred Grove, crowd control of visitors during the festival, medical personnel to cater for visitors during the festival, etc. In view of the findings of the study, the following recommendations are suggested; provision of more toilets at Osun Sacred grove, Osogbo Heritage Council to recruit festival guides to help control the huge crowd at the festival, the Government of State of Osun in conjunction with Red Cross Society should engage adequate medical personnel to cater for medical needs of visitors at the festival, etc.

Keywords: festival, perception, positive, tourists

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4404 Analysis of the Diffusion Behavior of an Information and Communication Technology Platform for City Logistics

Authors: Giulio Mangano, Alberto De Marco, Giovanni Zenezini

Abstract:

The concept of City Logistics (CL) has emerged to improve the impacts of last mile freight distribution in urban areas. In this paper, a System Dynamics (SD) model exploring the dynamics of the diffusion of a ICT platform for CL management across different populations is proposed. For the development of the model two sources have been used. On the one hand, the major diffusion variables and feedback loops are derived from a literature review of existing diffusion models. On the other hand, the parameters are represented by the value propositions delivered by the platform as a response to some of the users’ needs. To extract the most important value propositions the Business Model Canvas approach has been used. Such approach in fact focuses on understanding how a company can create value for her target customers. These variables and parameters are thus translated into a SD diffusion model with three different populations namely municipalities, logistics service providers, and own account carriers. Results show that, the three populations under analysis fully adopt the platform within the simulation time frame, highlighting a strong demand by different stakeholders for CL projects aiming at carrying out more efficient urban logistics operations.

Keywords: city logistics, simulation, system dynamics, business model

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4403 A Probabilistic Study on Time to Cover Cracking Due to Corrosion

Authors: Chun-Qing Li, Hassan Baji, Wei Yang

Abstract:

Corrosion of steel in reinforced concrete structures is a major problem worldwide. The volume expansion of corrosion products causes concrete cover cracking, which could lead to delamination of concrete cover. The time to cover cracking plays a key role to the assessment of serviceability of reinforced concrete structures subjected to corrosion. Many analytical, numerical, and empirical models have been developed to predict the time to cracking initiation due to corrosion. In this study, a numerical model based on finite element modeling of corrosion-induced cracking process is used. In order to predict the service life based on time to cover initiation, the numerical approach is coupled with a probabilistic procedure. In this procedure, all the influential factors affecting time to cover cracking are modeled as random variables. The results show that the time to cover cracking is highly variables. It is also shown that rust product expansion ratio and the size of more porous concrete zone around the rebar are the most influential factors in predicting service life of corrosion-affected structures.

Keywords: corrosion, crack width, probabilistic, service life

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4402 Analysis of Production Forecasting in Unconventional Gas Resources Development Using Machine Learning and Data-Driven Approach

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

Abstract:

Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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4401 Design and Optimization of Flow Field for Cavitation Reduction of Valve Sleeves

Authors: Kamal Upadhyay, Zhou Hua, Yu Rui

Abstract:

This paper aims to improve the streamline linked with the flow field and cavitation on the valve sleeve. We observed that local pressure fluctuation produces a low-pressure zone, central to the formation of vapor volume fraction within the valve chamber led to air-bubbles (or cavities). Thus, it allows simultaneously to a severe negative impact on the inner surface and lifespan of the valve sleeves. Cavitation reduction is a vitally important issue to pressure control valves. The optimization of the flow field is proposed in this paper to reduce the cavitation of valve sleeves. In this method, the inner wall of the valve sleeve is changed from a cylindrical surface to the conical surface, leading to the decline of the fluid flow velocity and the rise of the outlet pressure. Besides, the streamline is distributed inside the sleeve uniformly. Thus, the bubble generation is lessened. The fluid models are built and analysis of flow field distribution, pressure, vapor volume and velocity was carried out using computational fluid dynamics (CFD) and numerical technique. The results indicate that this structure can suppress the cavitation of valve sleeves effectively.

Keywords: streamline, cavitation, optimization, computational fluid dynamics

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4400 Theoretical Analysis of Self-Starting Busemann Intake Family

Authors: N. Moradian, E. Timofeev, R. Tahir

Abstract:

In this work, startability of the Busemann intake family with weak/strong conical shock, as most efficient intakes, via overboard mass spillage method is theoretically analyzed. Masterix and Candifix codes are used to numerically simulate few models of this type of intake and verify the theoretical results. Portions of the intake corresponding to various flow capture angles are considered to have mass spillage in the starting process of this intake. This approach allows for overboard mass spillage via a V-shaped slot with the tip of V coinciding with the focal point of the Busemann flow. The theoretical results, achieved using two different theories, of self-started Busemann takes with weak/strong conical shock show that significant improve in intake startability using overboard spillage technique. The starting phenomena of Busemann intakes with weak conical shock and seven different capture angles are numerically simulated at freestream Mach number of 3 to find the minimum area ratios of self-started intakes. The numerical results confirm the theoretical ones achieved by authors.

Keywords: Busemann intake, conical shock, overboard spillage, startability

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4399 Artificial Intelligent-Based Approaches for Task ‎Offloading, ‎Resource ‎Allocation and Service ‎Placement of ‎Internet of Things ‎Applications: State of the Art

Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib‎

Abstract:

In order to support the continued growth, critical latency of ‎IoT ‎applications, and ‎various obstacles of traditional data centers, ‎mobile edge ‎computing (MEC) has ‎emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes, or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other, making task offloading (TO), ‎resource allocation (RA), and service placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP, and RA recent multi-‎objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications‎.

Keywords: mobile edge computing, multi-objective optimization, artificial ‎intelligence ‎approaches, task offloading, resource allocation, ‎ service placement

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4398 Three Dimensional Flexible Dynamics of Continuous Cislunar Payloads Transfer System

Authors: Y. Yang, Dian Ming Xing, Qiu Hua Du

Abstract:

Based on the Motorized Momentum Exchange Tether (MMET), with the principle of momentum exchange, the three dimension flexible dynamics of continuous cislunar payloads transferring system (CCPTS) is built by Lagrange method and its numerical solution is solved by Mathematica software. In the derivation precession of potential energy, this paper uses the Tylor expansion method to simplify the Lagrange equation. Furthermore, the tension coming from the centripetal load is considered in the elastic potential energy. The comparison simulation results between the 3D rigid model and 3D flexible model of CCPTS shows that the tether flexibility has important influence on CCPTS’s orbital parameters (such as radius of CCPTS’s COM and the true anomaly) and the tether’s rotational movement, the relative deviation of radius and the true anomaly between the two dynamic models is about 0.00678% and 0.00259%, the relative deviation of the angle of tether-span and local gravity gradient is about 3.55%. Additionally, the external torque has an apparent influence on the tether’s axial vibration.

Keywords: cislunar transfer, dynamics, momentum exchange, tether

Procedia PDF Downloads 266
4397 Global Best Practice Paradox; the Failure of One Size Fits All Approach to Development a Case Study of Pakistan

Authors: Muhammad Naveed Iftikhar, Farah Khalid

Abstract:

Global best practices as ordained by international organizations comprise a broader top-down approach to development problems, without taking into account country-specific factors. The political economy of each country is extremely different and the failure of several attempts of international organizations to implement global best practice models in developing countries each with its unique set of variables, goes on to show that this is not the most efficient solution to development problems. This paper is a humble attempt at shedding light on some specific examples of failures of the global best practices. Pakistan has its unique set of problems and unless those are added to the broader equation of development, country-specific reform and growth will continue to pose a challenge to reform programs initiated by international organizations. The three case studies presented in this paper are just a few prominent examples of failure of the global best practice, top-down, universalistic approach to development as ordained by international organizations. Development and reform can only be achieved if local dynamics are given their due importance. The modus operandi of international organizations needs to be tailored according to each country’s unique politico-economic environment.

Keywords: best practice, development, context

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4396 Concept of the Active Flipped Learning in Engineering Mechanics

Authors: Lin Li, Farshad Amini

Abstract:

The flipped classroom has been introduced to promote collaborative learning and higher-order learning objectives. In contrast to the traditional classroom, the flipped classroom has students watch prerecorded lecture videos before coming to class and then “class becomes the place to work through problems, advance concepts, and engage in collaborative learning”. In this paper, the active flipped learning combines flipped classroom with active learning that is to establish an active flipped learning (AFL) model, aiming to promote active learning, stress deep learning, encourage student engagement and highlight data-driven personalized learning. Because students have watched the lecture prior to class, contact hours can be devoted to problem-solving and gain a deeper understanding of the subject matter. The instructor is able to provide students with a wide range of learner-centered opportunities in class for greater mentoring and collaboration, increasing the possibility to engage students. Currently, little is known about the extent to which AFL improves engineering students’ performance. This paper presents the preliminary study on the core course of sophomore students in Engineering Mechanics. A series of survey and interviews have been conducted to compare students’ learning engagement, empowerment, self-efficacy, and satisfaction with the AFL. It was found that the AFL model taking advantage of advanced technology is a convenient and professional avenue for engineering students to strengthen their academic confidence and self-efficacy in the Engineering Mechanics by actively participating in learning and fostering their deep understanding of engineering statics and dynamics

Keywords: active learning, engineering mechanics, flipped classroom, performance

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4395 Rank-Based Chain-Mode Ensemble for Binary Classification

Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

Abstract:

In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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4394 Universal Design Building Standard for India: A Critical Inquiry

Authors: Sushil Kumar Solanki, Rachna Khare

Abstract:

Universal Design is a concept of built environment creation, where all people are facilitated to the maximum extent possible without using any type of specialized design. However, accessible design is a design process in which the needs of people with disabilities are specifically considered. Building standards on accessibility contains scoping and technical requirements for accessibility to sites, facilities, building and elements by individual with disability. India is also following its prescriptive types of various building standards for the creation of physical environment for people with disabilities. These building standards are based on western models instead of research based standards to serve Indian needs. These standards lack contextual connect when reflects in its application in the urban and rural environment. This study focuses on critical and comparative study of various international building standards and codes, with existing Indian accessibility standards to understand problems and prospects of concept of Universal Design building standards for India. The result of this study is an analysis of existing state of Indian building standard pertaining to accessibility and future need of performance based Universal Design concept.

Keywords: accessibility, building standard, built-environment, universal design

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4393 Professional Competences of E-Learning Lecturers: Case of Russian National Platforms of Open Education

Authors: Polina Pekker

Abstract:

This work analyzes the role of lecturers in e-learning in Russia. It is based on qualitative research of lecturers who conduct courses on Russian national platforms of open education. The platform is based on edx software (provider of massive open online courses). The interviews with e-learning lecturers were conducted: from December 2015 till January 2016 and from April 2016 till May 2016. The results of interviews (face-to-face, telephone, skype) show, firstly, the difference between the role of lecturers in e-learning and in traditional education and, secondly, that the competition between lecturers is high in Russia. The results of interviews in Russia show that e-learning lecturer should have several special professional competences: the ability to keep attention of audiences without real contact, the ability to work on camera and competences related with e-learning course support (test, forum, communication on forum and etc.) It is concluded that lecturers need special course on acting and speech skills and on conducting and organizing of e-learning course in Russia. It is planned to conduct French study. When results from French research will be totally ready, they will be compared to Russian. As well French platform, France Universite Numerique, was launched earlier, in January 2014, so Russian lecturers should get best practice from the French colleagues.

Keywords: e-courses lecturer, e-learning, professional competences of lecturers, national Russian and French platforms of open education

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4392 Intuitive Decision Making When Facing Risks

Authors: Katharina Fellnhofer

Abstract:

The more information and knowledge that technology provides, the more important are profoundly human skills like intuition, the skill of using nonconscious information. As our world becomes more complex, shaken by crises, and characterized by uncertainty, time pressure, ambiguity, and rapidly changing conditions, intuition is increasingly recognized as a key human asset. However, due to methodological limitations of sample size or time frame or a lack of real-world or cross-cultural scope, precisely how to measure intuition when facing risks on a nonconscious level remains unclear. In light of the measurement challenge related to intuition’s nonconscious nature, a technique is introduced to measure intuition via hidden images as nonconscious additional information to trigger intuition. This technique has been tested in a within-subject fully online design with 62,721 real-world investment decisions made by 657 subjects in Europe and the United States. Bayesian models highlight the technique’s potential to measure skill at using nonconscious information for conscious decision making. Over the long term, solving the mysteries of intuition and mastering its use could be of immense value in personal and organizational decision-making contexts.

Keywords: cognition, intuition, investment decisions, methodology

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4391 Project HDMI: A Hybrid-Differentiated Mathematics Instruction for Grade 11 Senior High School Students at Las Piñas City Technical Vocational High School

Authors: Mary Ann Cristine R. Olgado

Abstract:

Diversity in the classroom might make it difficult to promote individualized learning, but differentiated instruction that caters to students' various learning preferences may prove to be beneficial. Hence, this study examined the effectiveness of Hybrid-Differentiated Mathematics Instruction (HDMI) in improving the students’ academic performance in Mathematics. It employed the quasi-experimental research design by using a comparative analysis of the two variables: the experimental and control groups. The learning styles of the students were identified using the Grasha-Riechmann Student Learning Style Scale (GRSLSS), which served as the basis for designing differentiated action plans in Mathematics. In addition, adapted survey questionnaires, pre-tests, and post-tests were used to gather information and were analyzed using descriptive and correlational statistics to find the relationship between variables. The experimental group received differentiated instruction for a month, while the control group received traditional teaching instruction. The study found that Hybrid-Differentiated Mathematics Instruction (HDMI) improved the academic performance of Grade 11-TVL students, with the experimental group performing better than the control group. This program has effectively tailored the teaching methods to meet the diverse learning needs of the students, fostering and enhancing a deeper understanding of mathematical concepts in Statistics & Probability, both within and beyond the classroom.

Keywords: differentiated instruction, hybrid, learning styles, academic performance

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4390 Design and Optimization of Sustainable Buildings by Combined Cooling, Heating and Power System (CCHP) Based on Exergy Analysis

Authors: Saeed Karimi, Ali Behbahaninia

Abstract:

In this study, the design and optimization of combined cooling, heating, and power system (CCHP) for a sustainable building are dealt with. Sustainable buildings are environmentally responsible and help us to save energy also reducing waste, pollution and environmental degradation. CCHP systems are widely used to save energy sources. In these systems, electricity, cooling, and heating are generating using just one primary energy source. The selection of the size of components based on the maximum demand of users will lead to an increase in the total cost of energy and equipment for the building complex. For this purpose, a system was designed in which the prime mover (gas turbine), heat recovery boiler, and absorption chiller are lower than the needed maximum. The difference in months with peak consumption is supplied with the help of electrical absorption chiller and auxiliary boiler (and the national electricity network). In this study, the optimum capacities of each of the equipment are determined based on Thermo economic method, in a way that the annual capital cost and energy consumption will be the lowest. The design was done for a gas turbine prime mover, and finally, the optimum designs were investigated using exergy analysis and were compared with a traditional energy supply system.

Keywords: sustainable building, CCHP, energy optimization, gas turbine, exergy, thermo-economic

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4389 Analysing Representations of ‘Leftover’ Women in Chinese Media: Taking the Film ‘The Last Woman Standing’ and ‘I Do’ as Examples

Authors: Ting Li Liu

Abstract:

‘Leftover woman’ or ‘3S’ woman is the term used to describe a well-educated, high income, independent woman who is single and never married around 30 years in Chinese society. With the naming of this demographic of ‘leftover women’, their family, dating culture, mate selection and marriage attract public concern. Massive media representations of ‘leftover women’ occur daily; the research aims to present several media representations of women’s anxiety about their singlehood and related marital issues around thirty. The research triangulates two areas of media representation of ‘leftover women’: films and audience reviews on ‘Douban Movie’ website. Drawing on traditional media studies, Fairclough’s critical discourse analysis combined with multimodal techniques is applied to the research to analyze the representations of ‘leftover women’ and their implications for marital culture in China, in conjunction with a feminist perspective. The conference paper will discuss two case studies: the film ‘The last woman standing’ and ‘I Do’. Paying attention to different aspects of ‘leftover women’, the research aims to re-examine the representations of ‘leftover women’ in selected scenes, such as their age anxiety, family, marriage, dating process, careers, etc. The paper also includes public beliefs about ‘leftover women’ from online audience reviews. In conclusion, the emergence of ‘leftover women’ is a reflection of Chinese tradition’s impact on people’s lives and new changes in Chinese families and their attitude to marriage.

Keywords: leftover women, marriage, family, media culture, China

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4388 Culture as a Barrier: Political Rights of Women in Pakhtun Society

Authors: Muhammad Adil

Abstract:

Women in different parts of the world confront several barriers to accomplishing their legal rights, particularly political rights. One of the common barriers in this respect is the indigenous culture of the locality. In the same way, women in Khyber Pakhtunkhwa are facing difficulties in accomplishing their political rights. The most significant obstacle in this context is Pakhtunwali, the traditional code of conduct in Pakhtun society, which is perceived as a substantial impediment for Pakhtun women in practicing their political rights as guaranteed by the Constitution of Pakistan and international legal instruments. Several codes of Pakhtunwali, like peghor (slander or abuse), tor (blame or disgraced), sharam (shame and dishonor), purdah (gender segregation), and ghayrat (honor) have a prominent role in this regard. The research approach employed a combination of both qualitative and quantitative methods to ensure a thorough exploration of the subject. Not only different documents have been analyzed but also a questionnaire has been developed to get accurate findings. Simultaneously, both primary and secondary data have been utilized. The finding shows that the Pakhtun culture is a formidable hurdle in accomplishing women’s political rights in Pakhtun society, particularly in rural areas. Observation reveals that a prevailing societal perception is that having women as their representatives would be viewed as a challenge to the honor of Pakhtun men. Consequently, women candidates who participated in the general elections in Khyber Pakhtunkhwa received only 1 percent or less than 1 percent of the votes compared to their male counterparts. It is recommended that certain codes of Pakhtunwali should be redefined and made compatible with international legal instruments.

Keywords: constitution, fundamental rights, honor, pakhtunwali.

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4387 Bringing the Confidence Intervals into Choropleth Mortality Map: An Example of Tainan, Taiwan

Authors: Tzu-Jung Tseng, Pei-Hsuen Han, Tsung-Hsueh Lu

Abstract:

Background: Choropleth mortality map is commonly used to identify areas with higher mortality risk. However, the use of choropleth map alone might result in the misinterpretation of differences in mortality rates between areas. Two areas with different color shades might not actually have a significant difference in mortality rates. The mortality rates estimated for an area with a small population would be less stable. We suggest of bringing the 95% confidence intervals (CI) into the choropleth mortality map to help users interpret the areal mortality rate difference more properly. Method: In the first choropleth mortality map, we used only three color to indicate standardized mortality ratio (SMR) for each district in Tainan, Taiwan. The red color denotes that the SMR of that district was significantly higher than the Tainan average; on the contrary, the green color suggests that the SMR of that district was significantly lower than the Tainan average. The yellow color indicates that the SMR of that district was not statistically significantly different from the Tainan average. In the second choropleth mortality map, we used traditional sequential color scheme (color ramp) for different SMR in 37 districts in Tainan City with bar chart of each SMR with 95% CI in which the users could examine if the line of 95% CI of SMR of two districts overlapped (nonsignificant difference). Results: The all-causes SMR of each district in Tainan for 2008 to 2013 ranged from 0.77 (95% CI 0.75 to 0.80) in East District to 1.39 Beimen (95% CI 1.25 to 1.52). In the first choropleth mortality map, only 16 of 37 districts had red color and 8 districts had green color. For different causes of death, the number of districts with red color differed. In the first choropleth mortality map we added a bar chart with line of 95% CI of SMR in each district, in which the users could visualize the SMR differences between districts. Conclusion: Through the use of 95% CI the users could interpret the aral mortality differences more properly.

Keywords: choropleth map, small area variation, standardized mortality ratio (SMR), Taiwan

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4386 Review and Classification of the Indicators and Trends Used in Bridge Performance Modeling

Authors: S. Rezaei, Z. Mirzaei, M. Khalighi, J. Bahrami

Abstract:

Bridges, as an essential part of road infrastructures, are affected by various deterioration mechanisms over time due to the changes in their performance. As changes in performance can have many negative impacts on society, it is essential to be able to evaluate and measure the performance of bridges throughout their life. This evaluation includes the development or the choice of the appropriate performance indicators, which, in turn, are measured based on the selection of appropriate models for the existing deterioration mechanism. The purpose of this article is a statistical study of indicators and deterioration mechanisms of bridges in order to discover further research capacities in bridges performance assessment. For this purpose, some of the most common indicators of bridge performance, including reliability, risk, vulnerability, robustness, and resilience, were selected. The researches performed on each index based on the desired deterioration mechanisms and hazards were comprehensively reviewed. In addition, the formulation of the indicators and their relationship with each other were studied. The research conducted on the mentioned indicators were classified from the point of view of deterministic or probabilistic method, the level of study (element level, object level, etc.), and the type of hazard and the deterioration mechanism of interest. For each of the indicators, a number of challenges and recommendations were presented according to the review of previous studies.

Keywords: bridge, deterioration mechanism, lifecycle, performance indicator

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4385 Recurrent Patterns of Netspeak among Selected Nigerians on WhatsApp Platform: A Quest for Standardisation

Authors: Lily Chimuanya, Esther Ajiboye, Emmanuel Uba

Abstract:

One of the consequences of online communication is the birth of new orthography genres characterised by novel conventions of abbreviation and acronyms usually referred to as Netspeak. Netspeak, also known as internet slang, is a style of writing mainly used in online communication to limit the length of text characters and to save time. The aim of this study is to evaluate how second language users of the English language have internalised this new convention of writing; identify the recurrent patterns of Netspeak; and assess the consistency of the use of the identified patterns in relation to their meanings. The study is corpus-based, and data drawn from WhatsApp chart pages of selected groups of Nigerian English speakers show a large occurrence of inconsistencies in the patterns of Netspeak and their meanings. The study argues that rather than emphasise the negative impact of Netspeak on the communicative competence of second language users, studies should focus on suggesting models as yardsticks for standardising the usage of Netspeak and indeed all other emerging language conventions resulting from online communication. This stance stems from the inevitable global language transformation that is eminent with the coming of age of information technology.

Keywords: abbreviation, acronyms, Netspeak, online communication, standardisation

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4384 Determination of Chemical and Adsorption Kinetics: An Investigation of a Petrochemical Wastewater Treatment Utilizing GAC

Authors: Leila Vafajoo, Feria Ghanaat, Alireza Mohmadi Kartalaei, Amin Ghalebi

Abstract:

Petrochemical industries are playing an important role in producing wastewaters. Nowadays different methods are employed to treat these materials. The goal of the present research was to reduce the COD of a petrochemical wastewater via adsorption technique using a commercial granular activated carbon (GAC) as adsorbent. In the current study, parameters of kinetic models as well as; adsorption isotherms were determined through utilizing the Langmuir and Freundlich isotherms. The key parameters of KL= 0.0009 and qm= 33.33 for the former and nf=0.5 and Kf= 0.000004 for the latter isotherms resulted. Moreover, a correlation coefficient of above 90% for both cases proved logical use of such isotherms. On the other hand, pseudo-first and -second order kinetics equations were implemented. These resulted in coefficients of k1=0.005 and qe=2018 as well as; K2=0.009 and qe=1250; respectively. In addition, obtaining the correlation coefficients of 0.94 and 0.68 for these 1st and 2nd order kinetics; respectively indicated advantageous use of the former model. Furthermore, a significant experimental reduction of the petrochemical wastewater COD revealed that, using GAC for the process undertaken was an efficient mean of treatment. Ultimately, the current investigation paved down the road for predicting the system’s behavior on industrial scale.

Keywords: petrochemical wastewater, adsorption, granular activated carbon, equilibrium isotherm, kinetic model

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4383 Feasibility of Using Bike Lanes in Conjunctions with Sidewalks for Ground Drone Applications in Last Mile Delivery for Dense Urban Areas

Authors: N. Bazyar Shourabi, K. Nyarko, C. Scott, M. Jeihnai

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Ground drones have the potential to reduce the cost and time of making last-mile deliveries. They also have the potential to make a huge impact on human life. Despite this potential, little work has gone into developing a suitable feasibility model for ground drone delivery in dense urban areas. Today, most of the experimental ground delivery drones utilize sidewalks only, with just a few of them starting to use bike lanes, which a significant portion of some urban areas have. This study works on the feasibility of using bike lanes in conjunction with sidewalks for ground drone applications in last-mile delivery for dense urban areas. This work begins with surveying bike lanes and sidewalks within the city of Boston using Geographic Information System (GIS) software to determine the percentage of coverage currently available within the city. Then six scenarios are examined. Based on this research, a mathematical model is developed. The daily cost of delivering packages using each scenario is calculated by the mathematical model. Comparing the drone delivery scenarios with the traditional method of package delivery using trucks will provide essential information concerning the feasibility of implementing routing protocols that combine the use of sidewalks and bike lanes. The preliminary results of the model show that ground drones that can travel via sidewalks or bike lanes have the potential to significantly reduce delivery cost.

Keywords: ground drone, intelligent transportation system, last-mile delivery, sidewalk robot

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4382 3D Visualization for the Relationship of the Urban Rule and Building Form by Using CityEngine

Authors: Chin Ku, Han liang Lin

Abstract:

The purpose of this study is to visualize how the rule related to urban design influences the building form by 3D modeling software CityEngine. In order to make the goal of urban design clearly connect to urban form, urban planner or designer should understand how the rule affects the form, especially the building form. In Taiwan, the rule pertained to urban design includes traditional zoning, urban design review and building codes. However, zoning cannot precisely expect the outcome of building form and lack of thinking about public realm and 3D form. In addition to that, urban design review is based on case by case, do not have a comprehensive regulation plan and the building code is just for general regulation. Therefore, rule cannot make the urban form reach the vision or goal of the urban design. Consequently, another kind of zoning called Form-based code (FBC) has arisen. This study uses the component of FBC which pertained to urban fabric such as street width, block and plot size, etc., to be the variants of building form, and find out the relationship between the rule and building form. There are three stages of this research, it will start from a field survey of Taichung City in Taiwan to induce the rule-building form relationship by using cluster analysis and descriptive Statistics. Second, visualize the relationship through the parameterized and codified process in CityEngine which is the procedural modeling, and can analyze, monitor and visualize the 3D world. Last, compare the CityEngine result with real world to examine how extent do this model represent the real world appearance.

Keywords: 3D visualization, CityEngine, form-based code, urban form

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4381 Compilation of Tall Building with Green Architecture Case Study: Babolsar City (North of Iran) at 2014-2015

Authors: Seyyed Hossein Alavi, Soudabeh Mehri Talarposhti

Abstract:

Quick development of urban population need for housing on the one hand and prevention of irregular urban extension for optimum usage of urban land, resolving problems of urban physiognomy, land using, and environmental issues and urban transport, on the other hand, proposed tall building as urban area extension requirement in developing and advanced countries. Beside the tall building, protection, and creation of green architecture is one the most important issues of today's architecture world. This research is about attending tall building with green architecture in Babolsar city 2015. For this, the issues that can make favorite conditions for green architecture has been discussed. The purpose of this discussion is skeleton extension and accessing interactions between architecture and related technologies. This discussion with using of qualitative research methods (Analytical Description) tried to studying designed performance models and also studying and analyzing the inside and foreign articles and books. Hope this research is useful in solving the existing problems in this issue.

Keywords: tall building, green architecture, skeleton extension, Babolsar city

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4380 Fabrication of Pure and Doped MAPbI3 Thin Films by One Step Chemical Vapor Deposition Method for Energy Harvesting Applications

Authors: S. V. N. Pammi, Soon-Gil Yoon

Abstract:

In the present study, we report a facile chemical vapor deposition (CVD) method for Perovskite MAPbI3 thin films by doping with Br and Cl. We performed a systematic optimization of CVD parameters such as deposition temperature, working pressure and annealing time and temperature to obtain high-quality films of CH3NH3PbI3, CH3NH3PbI3-xBrx and CH3NH3PbI3-xClx perovskite. Scanning electron microscopy and X-ray Diffraction pattern showed that the perovskite films have a large grain size when compared to traditional spin coated thin films. To the best of our knowledge, there are very few reports on highly quality perovskite thin films by various doping such as Br and Cl using one step CVD and there is scope for significant improvement in device efficiency. In addition, their band-gap can be conveniently and widely tuned via doping process. This deposition process produces perovskite thin films with large grain size, long diffusion length and high surface coverage. The enhancement of the output power, CH3NH3PbI3 (MAPbI3) dye films when compared to spin coated films and enhancement in output power by doping in doped films was demonstrated in detail. The facile one-step method for deposition of perovskite thin films shows a potential candidate for photovoltaic and energy harvesting applications.

Keywords: perovskite thin films, chemical vapor deposition, energy harvesting, photovoltaics

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4379 On the Effectiveness of Educational Technology on the Promotion of Exceptional Children or Children with Special Needs

Authors: Nasrin Badrkhani

Abstract:

The increasing use of educational technologies has created a tremendous transformation in all fields and most importantly, in the field of education and learning. In recent decades, traditional learning approaches have undergone fundamental changes with the emergence of new learning technologies. Research shows that suitable educational tools play an effective role in the transmission, comprehension, and impact of educational concepts. These tools provide a tangible basis for thinking and constructing concepts, resulting in an increased interest in learning. They provide real and true experiences to students and convey educational meanings and concepts more quickly and clearly. It can be said that educational technology, as an active and modern teaching method, with capabilities such as engaging multiple senses in the educational process and involving the learner, makes the learning environment more flexible. It effectively impacts the skills of children with special needs by addressing their specific needs. Teachers are no longer the sole source of information, and students are not mere recipients of information. They are considered the main actors in the field of education and learning. Since education is one of the basic rights of every human being and children with special needs face unique challenges and obstacles in education, these challenges can negatively affect their abilities and learning. To combat these challenges, one of the ways is to use educational technologies for more diverse, effective learning. Also, the use of educational technology for students with special needs has increasingly proven effective in boosting their self-confidence and helping them overcome learning challenges, enhancing their learning outcomes.

Keywords: communication technology, students with special needs, self-confidence, raising the expectations and progress

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4378 Predictive Analysis for Big Data: Extension of Classification and Regression Trees Algorithm

Authors: Ameur Abdelkader, Abed Bouarfa Hafida

Abstract:

Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

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4377 Ensemble Methods in Machine Learning: An Algorithmic Approach to Derive Distinctive Behaviors of Criminal Activity Applied to the Poaching Domain

Authors: Zachary Blanks, Solomon Sonya

Abstract:

Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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4376 Applied Bayesian Regularized Artificial Neural Network for Up-Scaling Wind Speed Profile and Distribution

Authors: Aghbalou Nihad, Charki Abderafi, Saida Rahali, Reklaoui Kamal

Abstract:

Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights.

Keywords: bayesian regularization, neural network, wind shear, accuracy

Procedia PDF Downloads 492