Search results for: Seong Shin Hong
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 898

Search results for: Seong Shin Hong

718 A Study on Method for Identifying Capacity Factor Declination of Wind Turbines

Authors: Dongheon Shin, Kyungnam Ko, Jongchul Huh

Abstract:

The investigation on wind turbine degradation was carried out using the nacelle wind data. The three Vestas V80-2MW wind turbines of Sungsan wind farm in Jeju Island, South Korea were selected for this work. The SCADA data of the wind farm for five years were analyzed to draw power curve of the turbines. It is assumed that the wind distribution is the Rayleigh distribution to calculate the normalized capacity factor based on the drawn power curve of the three wind turbines for each year. The result showed that the reduction of power output from the three wind turbines occurred every year and the normalized capacity factor decreased to 0.12%/year on average.

Keywords: wind energy, power curve, capacity factor, annual energy production

Procedia PDF Downloads 411
717 Flow Characteristic Analysis for Hatch Type Air Vent Head of Bulk Cargo Ship by Computational Fluid Dynamics

Authors: Hanik Park, Kyungsook Jeon, Suchul Shin, Youngchul Park

Abstract:

The air vent head prevents the inflow of seawater into the cargo holds when it is used for the ballast tank on heavy weather. In this study, the flow characteristics and the grid size were created by the application of Computational Fluid Dynamics by taking into the consideration of comparison of test results. Then, the accuracy of the analysis was verified by comparing with experimental results. Based on this analysis, accurate turbulence model and grid size can be selected. Thus, the design characteristic of air vent head for bulk carrier contributes the reliability based on the research results.

Keywords: bulk carrier, FEM, SST, vent

Procedia PDF Downloads 496
716 Evaluation of Structural Behavior of Wide Sleepers on Asphalt Trackbed Due to Embedded Shear Keys

Authors: Seong Hyeok Lee, Jin Wook Lee, Bu Seog Ju, Woo Young Jung

Abstract:

Korea Train eXpress (KTX) is now being operated, which allows Korea being one of the countries that operates the high-speed rail system. The high-speed rail has its advantage of short time transportation of population and materials, which lead to many researches performed in this matter. In the case of high speed classical trackbed system, the maintenance and usability of gravel ballast system is costly. Recently, the concrete trackbed structure has been introduced as a replacement of classical trackbed system. In this case, the sleeper plays a critical role. Current study investigated to develop the track sleepers readily applicable to the top of the asphalt trackbed, as part of the trcakbed study utilizing the asphalt material. Among many possible shapes and design of sleepers, current study proposed two types of wide-sleepers according to the shear-key installation method. The structural behavior analysis and safety evaluation on each case was conducted using Korean design standard.

Keywords: wide sleepers, asphalt, high-speed railway, shear-key

Procedia PDF Downloads 411
715 Big Data Analysis with RHadoop

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

Procedia PDF Downloads 411
714 A Study of Curriculum for a Dual Bachelor’s Degree Including a Teaching Certificate

Authors: Hyeon Seok Kim, Inhoi Lee, Seong Baeg Kim, Kyunghee Ko, Kyung Eon Lee, Dong Sik Kang

Abstract:

In the age of globalization, higher education institutions attempt to equip students with global competence. In response, most universities have been developing and running various international programs. However, teacher education has been a neglected area in this trend. Therefore, in this study, we suggest a program that offers a dual bachelor’s degree from both universities located on different countries, focusing on teacher education institutions with different policies and regulations of teacher education programs that may become obstacles to designing a dual degree program. We discuss a possible way to get a dual degree including a teaching certificate at a specialized college, college of secondary education. To be specific, this research presents a way to attain two diplomas from Jeju National University (JNU) in Korea and Boise State University (BSU) in the U.S. It attempts to build an effective plan for students to declare simultaneous degrees at both universities. From the study, we find that it takes about 5 years to fulfill requirements for the dual degree at the undergraduate level.

Keywords: dual degree, curriculum, teaching certificate, college of secondary education, international program

Procedia PDF Downloads 264
713 Optimal Scheduling for Energy Storage System Considering Reliability Constraints

Authors: Wook-Won Kim, Je-Seok Shin, Jin-O Kim

Abstract:

This paper propose the method for optimal scheduling for battery energy storage system with reliability constraint of energy storage system in reliability aspect. The optimal scheduling problem is solved by dynamic programming with proposed transition matrix. Proposed optimal scheduling method guarantees the minimum fuel cost within specific reliability constraint. For evaluating proposed method, the timely capacity outage probability table (COPT) is used that is calculated by convolution of probability mass function of each generator. This study shows the result of optimal schedule of energy storage system.

Keywords: energy storage system (ESS), optimal scheduling, dynamic programming, reliability constraints

Procedia PDF Downloads 379
712 Investigation of Astrocyte Physiology on Stiffness-Controlled Cellulose Acetate Nanofiber as a Tissue Scaffold

Authors: Sun Il Yu, Jung Hyun Joo, Hwa Sung Shin

Abstract:

Astrocytes are known as dominant cells in CNS and play a role as a supporter of CNS activity and regeneration. Recently, three-dimensional culture of astrocytes were actively applied to understand in vivo astrocyte works. Electrospun nanofibers are attractive for 3D cell culture system because they have a high surface to volume ratio and porous structure, and have already been used for 3D astrocyte cultures. In this research, the stiffness of cellulose acetate (CA) nanofiber was controlled by heat treatment. As stiffness increased, astrocyte cell viability and adhesion increased. Reactivity of astrocyte was also upregulated in stiffer CA nanofiber in terms of GFAP, an intermediate filament protein. Finally, we demonstrated that stiffness-controllable CA is attractive for astrocyte tissue engineering.

Keywords: astrocyte, cellulose acetate, nanofiber, tissue scaffold

Procedia PDF Downloads 329
711 Isogeometric Topology Optimization in Cracked Structures Design

Authors: Dongkyu Lee, Thanh Banh Thien, Soomi Shin

Abstract:

In the present study, the isogeometric topology optimization is proposed for cracked structures through using Solid Isotropic Material with Penalization (SIMP) as a design model. Design density variables defined in the variable space are used to approximate the element analysis density by the bivariate B-spline basis functions. The mathematical formulation of topology optimization problem solving minimum structural compliance is an alternating active-phase algorithm with the Gauss-Seidel version as an optimization model of optimality criteria. Stiffness and adjoint sensitivity formulations linked to strain energy of cracked structure are proposed in terms of design density variables. Numerical examples demonstrate interactions of topology optimization to structures design with cracks.

Keywords: topology optimization, isogeometric, NURBS, design

Procedia PDF Downloads 463
710 Finite Element Analysis of Ball-Joint Boots under Environmental and Endurance Tests

Authors: Young-Doo Kwon, Seong-Hwa Jun, Dong-Jin Lee, Hyung-Seok Lee

Abstract:

Ball joints support and guide certain automotive parts that move relative to the frame of the vehicle. Such ball joints are covered and protected from dust, mud, and other interfering materials by ball-joint boots made of rubber—a flexible and near-incompressible material. The boots may experience twisting and bending deformations because of the motion of the joint arm. Thus, environmental and endurance tests of ball-joint boots apply both bending and twisting deformations. In this study, environmental and endurance testing was simulated via the finite element method performed by using a commercial software package. The ranges of principal stress and principal strain values that are known to directly affect the fatigue lives of the parts were sought. By defining these ranges, the number of iterative tests and modifications of the materials and dimensions of the boot can be decreased. Therefore, instead of performing actual part tests, manufacturers can perform standard fatigue tests in trials of different materials by applying only the defined range of stress or strain values.

Keywords: boot, endurance tests, rubber, FEA

Procedia PDF Downloads 242
709 Investigation on Performance of Optical Shutter Panels for Transparent Displays

Authors: Jaehong Kim, Sunhee Park, HongSeop Shin, Kyongho Lim, Suhyun Kwon, Don-Gyou Lee, Pureum Kim, Moojong Lim, JongSang Baek

Abstract:

Transparent displays with OLEDs are the most commonly produced forms of see-through displays on the market or in development. In order to block the visual interruption caused by the light coming from the background, the special panel is combined with transparent displays with OLEDs. There is, however, few studies performance of optical shutter panel for transparent displays until now. This paper, therefore, describes the performance of optical shutter panels. The novel evaluation method was developed by measuring the amount of light which can form a transmitted background image. The new proposed method could tell how recognizable transmitted background images cannot be seen, and is consistent with viewer’s perception.

Keywords: optical shutter panel, optical performance, transparent display, visual interruption

Procedia PDF Downloads 505
708 Grain Refinement of Al-7Si-0.4Mg Alloy by Combination of Al-Ti-B and Mg-Al2Ca Mater Alloys and Their Effects on Tensile Property

Authors: Young-Ok Yoon, Su-Yeon Lee, Seong-Ho Ha, Gil-Yong Yeom, Bong-Hwan Kim, Hyun-Kyu Lim, Shae K. Kim

Abstract:

Al-7Si-0.4Mg alloy (designated A356) is widely used in the automotive and aerospace industries as structural components due to an excellent combination of castability and mechanical properties. Grain refinement has a significant effect on the mechanical properties of castings, mainly since the distribution of secondary phase is changed. As a grain refiner, the Al-Ti-B master alloys containing TiAl3 and TiB2 particles have been widely used in Al foundries. The Mg loss and Mg based inclusion formation by the strong affinity of Mg to oxygen in the melting process of Mg contained alloys have been an issue. This can be significantly improved only by Mg+Al2Ca master alloy as an alloying element instead of pure Mg. Moreover, the eutectic Si modification and grain refinement is simultaneously obtained because Al2Ca behaves as Ca, a typical Si modifier. The present study is focused on the combined effects of Mg+Al2Ca and Al-Ti-B master alloys on the grain refiment of Al-7Si-0.4Mg alloy and their proper ratio for the optimum effect. The aim of this study, therefore, is to investigate the change of the microstructure in Al-7Si-0.4Mg alloy with different ratios of Ti and Al2Ca (detected Ca content) and their effects on the tensile property. The distribution and morphology of the secondary phases by the grain refinement will be discussed.

Keywords: Al-7Si-0.4Mg alloy, Al2Ca, Al-Ti-B alloy, grain refinement

Procedia PDF Downloads 404
707 The Influence of Alginate Microspheres Modified with DAT on the Proliferation and Adipogenic Differentiation of ASCs

Authors: Shin-Yi Mao, Jiashing Yu

Abstract:

Decellularized adipose tissue (DAT) has received lots of attention as biological scaffolds recently. DAT that extracted from the extracellular matrix (ECM) of adipose tissues holds great promise as a xenogeneic biomaterial for tissue engineering and regenerative medicine. In our study, 2-D DATsol film was fabricated to enhance cell adhesion, proliferation, and differentiation of ASCs in vitro. DAT was also used to modify alginate for improvement of cell adhesion. Alginate microspheres modified with DAT were prepared by Nisco. These microspheres could provide a highly supportive 3-D environment for ASCs. In our works, ASCs were immobilized in alginate microspheres modified with DAT to promoted cell adhesion and adipogenic differentiation. Accordingly, we hypothesize that tissue regeneration in vivo could be promoted with the aid of modified microspheres in future.

Keywords: adipose stem cells, decellularize adipose tissue, Alginate, microcarries

Procedia PDF Downloads 419
706 Unraveling Language Contact through Syntactic Dynamics of ‘Also’ in Hong Kong and Britain English

Authors: Xu Zhang

Abstract:

This article unveils an indicator of language contact between English and Cantonese in one of the Outer Circle Englishes, Hong Kong (HK) English, through an empirical investigation into 1000 tokens from the Global Web-based English (GloWbE) corpus, employing frequency analysis and logistic regression analysis. It is perceived that Cantonese and general Chinese are contextually marked by an integral underlying thinking pattern. Chinese speakers exhibit a reliance on semantic context over syntactic rules and lexical forms. This linguistic trait carries over to their use of English, affording greater flexibility to formal elements in constructing English sentences. The study focuses on the syntactic positioning of the focusing subjunct ‘also’, a linguistic element used to add new or contrasting prominence to specific sentence constituents. The English language generally allows flexibility in the relative position of 'also’, while there is a preference for close marking relationships. This article shifts attention to Hong Kong, where Cantonese and English converge, and 'also' finds counterparts in Cantonese ‘jaa’ and Mandarin ‘ye’. Employing a corpus-based data-driven method, we investigate the syntactic position of 'also' in both HK and GB English. The study aims to ascertain whether HK English exhibits a greater 'syntactic freedom,' allowing for a more distant marking relationship with 'also' compared to GB English. The analysis involves a random extraction of 500 samples from both HK and GB English from the GloWbE corpus, forming a dataset (N=1000). Exclusions are made for cases where 'also' functions as an additive conjunct or serves as a copulative adverb, as well as sentences lacking sufficient indication that 'also' functions as a focusing particle. The final dataset comprises 820 tokens, with 416 for GB and 404 for HK, annotated according to the focused constituent and the relative position of ‘also’. Frequency analysis reveals significant differences in the relative position of 'also' and marking relationships between HK and GB English. Regression analysis indicates a preference in HK English for a distant marking relationship between 'also' and its focused constituent. Notably, the subject and other constituents emerge as significant predictors of a distant position for 'also.' Together, these findings underscore the nuanced linguistic dynamics in HK English and contribute to our understanding of language contact. It suggests that future pedagogical practice should consider incorporating the syntactic variation within English varieties, facilitating leaners’ effective communication in diverse English-speaking environments and enhancing their intercultural communication competence.

Keywords: also, Cantonese, English, focus marker, frequency analysis, language contact, logistic regression analysis

Procedia PDF Downloads 26
705 Investigation on Optical Performance of Operational Shutter Panels for Transparent Displays

Authors: Jaehong Kim, Sunhee Park, HongSeop Shin, Kyongho Lim, Suhyun Kwon, Don-Gyou Lee, Pureum Kim, Moojong Lim, JongSang Baek

Abstract:

Transparent displays with OLEDs are the most commonly produced forms of see-through displays on the market or in development. In order to block the visual interruption caused by the light coming from the background, the special panel is combined with transparent displays with OLEDs. There is, however, few studies optical performance of operational shutter panel for transparent displays until now. This paper, therefore, describes the optical performance of operational shutter panels. The novel evaluation method was developed by measuring the amount of light which can form a transmitted background image. The new proposed method could tell how recognize transmitted background images cannot be seen, and is consistent with viewer’s perception.

Keywords: transparent display, operational shutter panel, optical performance, OLEDs

Procedia PDF Downloads 418
704 Detection of Curvilinear Structure via Recursive Anisotropic Diffusion

Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

Abstract:

The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

Procedia PDF Downloads 209
703 Evaluation of Hand Grip Strength and EMG Signal on Visual Reaction

Authors: Sung-Wook Shin, Sung-Taek Chung

Abstract:

Hand grip strength has been utilized as an indicator to evaluate the motor ability of hands, responsible for performing multiple body functions. It is, however, difficult to evaluate other factors (other than hand muscular strength) utilizing the hand grip strength only. In this study, we analyzed the motor ability of hands using EMG and the hand grip strength, simultaneously in order to evaluate concentration, muscular strength reaction time, instantaneous muscular strength change, and agility in response to visual reaction. In results, the average time (and their standard deviations) of muscular strength reaction EMG signal and hand grip strength was found to be 209.6 ± 56.2 ms and 354.3 ± 54.6 ms, respectively. In addition, the onset time which represents acceleration time to reach 90% of maximum hand grip strength, was 382.9 ± 129.9 ms.

Keywords: hand grip strength, EMG, visual reaction, endurance

Procedia PDF Downloads 433
702 Cross-Comparison between Land Surface Temperature from Polar and Geostationary Satellite over Heterogenous Landscape: A Case Study in Hong Kong

Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

Abstract:

Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

Procedia PDF Downloads 47
701 Compressive Strength Evaluation of Underwater Concrete Structures Integrating the Combination of Rebound Hardness and Ultrasonic Pulse Velocity Methods with Artificial Neural Networks

Authors: Seunghee Park, Junkyeong Kim, Eun-Seok Shin, Sang-Hun Han

Abstract:

In this study, two kinds of nondestructive evaluation (NDE) techniques (rebound hardness and ultrasonic pulse velocity methods) are investigated for the effective maintenance of underwater concrete structures. A new methodology to estimate the underwater concrete strengths more effectively, named “artificial neural network (ANN) – based concrete strength estimation with the combination of rebound hardness and ultrasonic pulse velocity methods” is proposed and verified throughout a series of experimental works.

Keywords: underwater concrete, rebound hardness, Schmidt hammer, ultrasonic pulse velocity, ultrasonic sensor, artificial neural networks, ANN

Procedia PDF Downloads 496
700 Balancing and Synchronization Control of a Two Wheel Inverted Pendulum Vehicle

Authors: Shiuh-Jer Huang, Shin-Ham Lee, Sheam-Chyun Lin

Abstract:

A two wheel inverted pendulum (TWIP) vehicle is built with two hub DC motors for motion control evaluation. Arduino Nano micro-processor is chosen as the control kernel for this electric test plant. Accelerometer and gyroscope sensors are built in to measure the tilt angle and angular velocity of the inverted pendulum vehicle. Since the TWIP has significantly hub motor dead zone and nonlinear system dynamics characteristics, the vehicle system is difficult to control by traditional model based controller. The intelligent model-free fuzzy sliding mode controller (FSMC) was employed as the main control algorithm. Then, intelligent controllers are designed for TWIP balance control, and two wheels synchronization control purposes.

Keywords: balance control, synchronization control, two-wheel inverted pendulum, TWIP

Procedia PDF Downloads 367
699 Improved K-Means Clustering Algorithm Using RHadoop with Combiner

Authors: Ji Eun Shin, Dong Hoon Lim

Abstract:

Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

Procedia PDF Downloads 403
698 An Adaptive Cooperative Scheme for Reliability of Transmission Using STBC and CDD in Wireless Communications

Authors: Hyun-Jun Shin, Jae-Jeong Kim, Hyoung-Kyu Song

Abstract:

In broadcasting and cellular system, a cooperative scheme is proposed for the improvement of performance of bit error rate. Up to date, the coverage of broadcasting system coexists with the coverage of cellular system. Therefore each user in a cellular coverage is frequently involved in a broadcasting coverage. The proposed cooperative scheme is derived from the shared areas. The users receive signals from both broadcasting base station and cellular base station. The proposed scheme selects a cellular base station of a worse channel to achieve better performance of bit error rate in cooperation. The performance of the proposed scheme is evaluated in fading channel.

Keywords: cooperative communication, diversity, STBC, CDD, channel condition, broadcasting system, cellular system

Procedia PDF Downloads 477
697 Mobile Application Tool for Individual Maintenance Users on High-Rise Residential Buildings in South Korea

Authors: H. Cha, J. Kim, D. Kim, J. Shin, K. Lee

Abstract:

Since 1980's, the rapid economic growth resulted in so many aged apartment buildings in South Korea. Nevertheless, there is insufficient maintenance practice of buildings. In this study, to facilitate the building maintenance the authors classified the building defects into three levels according to their level of performance and developed a mobile application tool based on each level's appropriate feedback. The feedback structure consisted of 'Maintenance manual phase', 'Online feedback phase', 'Repair work phase of the specialty contractors'. In order to implement each phase the authors devised the necessary database for each phase and created a prototype system that can develop on its own. The authors expect that the building users can easily maintain their buildings by using this application.

Keywords: building defect, maintenance practice, mobile application, system algorithm

Procedia PDF Downloads 172
696 Thermal and Acoustic Design of Mobile Hydraulic Vehicle Engine Room

Authors: Homin Kim, Hyungjo Byun, Jinyoung Do, Yongil Lee, Hyunho Shin, Seungbae Lee

Abstract:

Engine room of mobile hydraulic vehicle is densely packed with an engine and many hydraulic components mostly generating heat and sound. Though hydraulic oil cooler, ATF cooler, and axle oil cooler etc. are added to vehicle cooling system of mobile vehicle, the overheating may cause downgraded performance and frequent failures. In order to improve thermal and acoustic environment of engine room, the computational approaches by Computational Fluid Dynamics (CFD) and Boundary Element Method (BEM) are used together with necessary modal analysis of belt-driven system. The engine room design layout and process, which satisfies the design objectives of sound power level and temperature levels of radiator water, charged air cooler, transmission and hydraulic oil coolers, is discussed.

Keywords: acoustics, CFD, engine room design, mobile hydraulics

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695 Principal Well-Being at Hong Kong: A Quantitative Investigation

Authors: Junjun Chen, Yingxiu Li

Abstract:

The occupational well-being of school principals has played a vital role in the pursuit of individual and school wellness and success. However, principals’ well-being worldwide is under increasing threat because of the challenging and complex nature of their work and growing demands for school standardisation and accountability. Pressure is particularly acute in the post-pandemicfuture as principals attempt to deal with the impact of the pandemic on top of more regular demands. This is particularly true in Hong Kong, as school principals are increasingly wedged between unparalleled political, social, and academic responsibilities. Recognizing the semantic breadth of well-being, scholars have not determined a single, mutually agreeable definition but agreed that the concept of well-being has multiple dimensions across various disciplines. The multidimensional approach promises more precise assessments of the relationships between well-being and other concepts than the ‘affect-only’ approach or other single domains for capturing the essence of principal well-being. The multiple-dimension well-being concept is adopted in this project to understand principal well-being in this study. This study aimed to understand the situation of principal well-being and its influential drivers with a sample of 670 principals from Hong Kong and Mainland China. An online survey was sent to the participants after the breakout of COVID-19 by the researchers. All participants were well informed about the purposes and procedure of the project and the confidentiality of the data prior to filling in the questionnaire. Confirmatory factor analysis and structural equation modelling performed with Mplus were employed to deal with the dataset. The data analysis procedure involved the following three steps. First, the descriptive statistics (e.g., mean and standard deviation) were calculated. Second, confirmatory factor analysis (CFA) was used to trim principal well-being measurement performed with maximum likelihood estimation. Third, structural equation modelling (SEM) was employed to test the influential factors of principal well-being. The results of this study indicated that the overall of principal well-being were above the average mean score. The highest ranking in this study given by the principals was to their psychological and social well-being (M = 5.21). This was followed by spiritual (M = 5.14; SD = .77), cognitive (M = 5.14; SD = .77), emotional (M = 4.96; SD = .79), and physical well-being (M = 3.15; SD = .73). Participants ranked their physical well-being the lowest. Moreover, professional autonomy, supervisor and collegial support, school physical conditions, professional networking, and social media have showed a significant impact on principal well-being. The findings of this study will potentially enhance not only principal well-being, but also the functioning of an individual principal and a school without sacrificing principal well-being for quality education in the process. This will eventually move one step forward for a new future - a wellness society advocated by OECD. Importantly, well-being is an inside job that begins with choosing to have wellness, whilst supports to become a wellness principal are also imperative.

Keywords: well-being, school principals, quantitative, influential factors

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694 Event Related Potentials in Terms of Visual and Auditory Stimuli

Authors: Seokbeen Lim, KyeongSeok Sim, DaKyeong Shin, Gilwon Yoon

Abstract:

Event-related potential (ERP) is one of the useful tools for investigating cognitive reactions. In this study, the potential of ERP components detected after auditory and visual stimuli was examined. Subjects were asked to respond upon stimuli that were of three categories; Target, Non-Target and Standard stimuli. The ERP after stimulus was measured. In the experiment of visual evoked potentials (VEPs), the subjects were asked to gaze at a center point on the monitor screen where the stimuli were provided by the reversal pattern of the checkerboard. In consequence of the VEP experiments, we observed consistent reactions. Each peak voltage could be measured when the ensemble average was applied. Visual stimuli had smaller amplitude and a longer latency compared to that of auditory stimuli. The amplitude was the highest with Target and the smallest with Standard in both stimuli.

Keywords: auditory stimulus, EEG, event related potential, oddball task, visual stimulus

Procedia PDF Downloads 259
693 Exploring Framing Effect and Repetition Effect of the Persuasive Message on Moral Decision Making in Conflict of Interests

Authors: Sae-Yeon Seong, EunSun Chung, Dongjoo Chin

Abstract:

Conflict of interest (COI) is one of the dominant circumstantial factors of moral corruption across various fields. Several management strategies have been proposed to prevent self-interested decision making in COIs. Among these strategies, message persuasion has been considered as a practical and effective approach. Framing and repetition are two of the major factors in the persuasion effect of message. Therefore, their effect on moral decision making in COI should be explored systematically. The purpose of this study was to compare the differential effects of positively framed message and negatively framed message, and secondly, to investigate how the effectiveness of persuasive message changes through repetitive exposures. A total of 63 participants were randomly assigned to one of 3 framing conditions: positive framing, negative framing, and no-message condition. Prior to the online experiment involving a consultation task, the differently framed persuasive message was presented to the participants. This process was repeated four times in a row. The results showed that participants with positive-framing message were less likely to provide self-interested consultation than participants in the no-message condition. Also, a U-shaped quadric relation between repetition and self-interest consultation was found. Implications and limitations are further discussed.

Keywords: conflicts of interest, persuasive message, framing effect, repetition effect, self-interested behavior

Procedia PDF Downloads 147
692 Toxicity Identification and Evaluation for the Effluent from Seawater Desalination Facility in Korea Using D. magna and V. fischeri

Authors: Sung Jong Lee, Hong Joo Ha, Chun Sang Hong

Abstract:

In recent years, the interests on the impacts of industrial wastewater on aquatic ecosystem have increased with concern about ecosystem protection and human health. Whole effluent toxicity tests are used to monitor toxicity by unknown toxic chemicals as well as conventional pollutants from industrial effluent discharges. This study describes the application of TIE (toxicity identification evaluation) procedures to an acutely toxic effluent from a Seawater desalination facility in industrial complex which was toxic to Daphnia magna. In TIE phase I (characterization step), the toxic effects by heavy metals, organic compounds, oxidants, volatile organic compounds, suspended solids and ammonia were screened and revealed that the source of toxicity is far from these toxicants group. Chemical analysis (TIE phase II) on TDS showed that the concentration of chloride ion (24,215 ~ 29,562 mg/L) was substantially higher than that predicted from EC50 for D. magna. In confirmation step (TIE phase III), chloride ion was demonstrated to be main toxicant in this effluent by the spiking approach, species sensitivity approach, and deletion approach. Calcium, potassium, magnesium, sodium, fluorine, sulfate ion concentration was not shown toxicity from D. magna. Finally, we concluded that chloride was the most contributing toxicant in the waste water treatment plant. Further research activities are needed for technical support of toxicity identification and evaluation on the various types of wastewater treatment plant discharge in Korea. Acknowledgement: This research was supported by a grant (16IFIP-B089911-03) from Plant Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: TIE, D. magna, V. fischeri, seawater desalination facility

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691 Energy and Carbon Footprint Analysis of Food Waste Treatment Alternatives for Hong Kong

Authors: Asad Iqbal, Feixiang Zan, Xiaoming Liu, Guang-Hao Chen

Abstract:

Water, food, and energy nexus is a vital subject to achieve sustainable development goals worldwide. Wastewater (WW) and food waste (FW) from municipal sources are primary contributors to their respective wastage sum from a country. Along with the loss of these invaluable natural resources, their treatment systems also consume a lot of abiotic energy and resources input with a perceptible contribution to global warming. Hence, the global paradigm has evolved from simple pollution mitigation to a resource recovery system (RRS). In this study, the prospects of six alternative FW treatment scenarios are quantitatively evaluated for Hong Kong in terms of energy use and greenhouse emissions (GHEs) potential, using life cycle assessment (LCA). Considered scenarios included: aerobic composting, anaerobic digestion (AD), combine AD and composting (ADC), co-disposal, and treatment with wastewater (CoD-WW), incineration, and conventional landfilling as base-case. Results revealed that in terms of GHEs saving, all-new scenarios performed significantly better than conventional landfilling, with ADC scenario as best-case and incineration, AD alone, CoD-WW ranked as second, third, and fourth best respectively. Whereas, composting was the worst-case scenario in terms of energy balance, while incineration ranked best and AD alone, ADC, and CoD-WW ranked as second, third, and fourth best, respectively. However, these results are highly sensitive to boundary settings, e.g., the inclusion of the impact of biogenic carbon emissions and waste collection and transportation, and several other influential parameters. The study provides valuable insights and policy guidelines for the decision-makers locally and a generic modelling template for environmental impact assessment.

Keywords: food waste, resource recovery, greenhouse emissions, energy balance

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690 Development of Construction Cost Optimization System Using Genetic Algorithm Method

Authors: Hyeon-Seung Kim, Young-Hwan Kim, Sang-Mi Park, Min-Seo Kim, Jong-Myeung Shin, Leen-Seok Kang

Abstract:

The project budget at the planned stage might be changed by the insufficient government budget or the design change. There are many cases more especially in the case of a project performed for a long period of time. If the actual construction budget is insufficient comparing with the planned budget, the construction schedule should also be changed to match the changed budget. In that case, most project managers change the planned construction schedule by a heuristic approach without a reasonable consideration on the work priority. This study suggests an optimized methodology to modify the construction schedule according to the changed budget. The genetic algorithm was used to optimize the modified construction schedule within the changed budget. And a simulation system of construction cost histogram in accordance with the construction schedule was developed in the BIM (Building Information Modeling) environment.

Keywords: 5D, BIM, GA, cost optimization

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689 Convolutional Neural Network Based on Random Kernels for Analyzing Visual Imagery

Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

Abstract:

The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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