• Steel and Composite Structures
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• 제18권3호
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• pp.547-563
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• 2015

Deflection in a beam of a composite frame is a serviceability design criterion. This paper presents a methodology for rapid prediction of long-term mid-span deflections of beams in composite frames subjected to service load. Neural networks have been developed to predict the inelastic mid-span deflections in beams of frames (typically for 20 years, considering cracking, and time effects, i.e., creep and shrinkage in concrete) from the elastic moments and elastic mid-span deflections (neglecting cracking, and time effects). These models can be used for frames with any number of bays and stories. The training, validating, and testing data sets for the neural networks are generated using a hybrid analytical-numerical procedure of analysis. Multilayered feed-forward networks have been developed using sigmoid function as an activation function and the back propagation-learning algorithm for training. The proposed neural networks are validated for an example frame of different number of spans and stories and the errors are shown to be small. Sensitivity studies are carried out using the developed neural networks. These studies show the influence of variations of input parameters on the output parameter. The neural networks can be used in every day design as they enable rapid prediction of inelastic mid-span deflections with reasonable accuracy for practical purposes and require computational effort which is a fraction of that required for the available methods.

• 한국시스템다이내믹스연구
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• 제6권1호
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• pp.125-145
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• 2005

The Sihwaho Project got off to a bad start, which led to a series of mishaps and an imbalance of the whole project. The purpose of this study is to select the case of Sihwaho as a research subject, clean up the contamination caused by the ill planned project, develop suitable measures to stabilize the lake environment, and find the implications of similar development projects. For this, the authorshave conducted three simulations after studying the structural reasons for the failure of the Sihwaho Policy by identifying cause and effect relationships, pre-testing a number of policy measures for the current lake project, and presenting measures for solving the contamination problem at the lake. The simulations have shown us that filling the lake with seawater is inadequate to solve the problem and that we also have to make efforts to reduce the volume of wastes to the lake as well. The authorshave also analyzed the degree of difference between the simulation and survey results for scenario 1, in which we have studied how much seawater can reduce the contamination of the Sihwaho Lake without the effort to reduce the volume of wastes into the lake. The survey showed that most citizens and employees of the Ministry of Environment did not think it would be serious as the simulation results pointed out, and the employees of the Ministry of Environment were more optimistic about the situation than the public.

• Journal of Information Processing Systems
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• 제7권4호
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• pp.717-732
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• 2011

Classification in biomedical applications is an important task that predicts or classifies an outcome based on a given set of input variables such as diagnostic tests or the symptoms of a patient. Traditionally the classification algorithms would have to digest a stationary set of historical data in order to train up a decision-tree model and the learned model could then be used for testing new samples. However, a new breed of classification called stream-based classification can handle continuous data streams, which are ever evolving, unbound, and unstructured, for instance--biosignal live feeds. These emerging algorithms can potentially be used for real-time classification over biosignal data streams like EEG and ECG, etc. This paper presents a pioneer effort that studies the feasibility of classification algorithms for analyzing biosignals in the forms of infinite data streams. First, a performance comparison is made between traditional and stream-based classification. The results show that accuracy declines intermittently for traditional classification due to the requirement of model re-learning as new data arrives. Second, we show by a simulation that biosignal data streams can be processed with a satisfactory level of performance in terms of accuracy, memory requirement, and speed, by using a collection of stream-mining algorithms called Optimized Very Fast Decision Trees. The algorithms can effectively serve as a corner-stone technology for real-time classification in future biomedical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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• pp.4162-4179
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• 2017

The main purpose of this research is to investigate relationships between the significant control factors on acceptance intention to User Experience (UX) sports smart wearable devices by applying Technology Readiness (TR) and Unified Theory of Technology (UTAUT). Research survey targeted on users of golf smart devices in Seoul. A total 534 questionnaires were collected and used for testing hypotheses. Methods to analyze the data included frequency analysis, reliability analysis, confirmatory factor analysis, correlation analysis, and structural equation modeling in accordance with the purpose of the study by using SPSS and AMOS. The results are as follows; First, positive TR had a significantly positive effect on social influence, effort expectancy, facilitating conditions, perceived enjoyment, performance expectancy. Second, negative TR had a significant negative effect on performance expectancy, social influence, facilitating conditions, perceived enjoyment. Third, TR had a no significantly effect on behavioral intention. Fourth, performance expectancy, perceived enjoyment and facilitating conditions had a significantly positive effect on behavioral intention. Fifth, behavioral intention had a significantly positive effect on use behavior. Thus it became crucial to identify the difference in acceptance intention models per each products are as follows. Positive TR of golf-related mobile application users has a positive effect on both technology acceptance belief and acceptance intention, whereas negative TR has no statistically significant effect on technology acceptance belief nor acceptance intention.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권10호
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• pp.365-370
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• 2014

사물 인터넷(Internet of Things : IoT) 환경이 이미 네트워크기반의 서비스 분야에서 가장 대표적인 패러다임이 되었음에도 불구하고, 인간과 사물 및 환경이 서로 제약 없이 연결되는 특성으로 인하여 해당 환경에 특화된 테스트 기법은 여전히 많은 연구가 필요한 상황이다. 에뮬레이터 기반에서 테스트 대상 장치를 구동하는 대부분의 기존 방식은 IoT와 같이 그 연결이 다양해지고 장치의 구분이 불분명해질수록 실제 환경과의 격차가 커져 결론적으로 부정확한 테스트 결과가 산출될 가능성이 높다. 본 논문에서는 이러한 문제를 개선하고자 각각의 장치들의 오버헤드를 최소화함과 동시에 대상 코드의 특정 부분이 중복적으로 테스트되지 않는 특징을 가진 BitTorrent기반의 테스트 커버리지 측정 기법을 제안한다.

• 무역학회지
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• 제44권6호
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• pp.119-134
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• 2019

This study focuses on a recent WTO SPS dispute related to Korea Import Bans and Testing and Certification Requirements for Radionuclides (DS495) in order to learn from the case and take proactive measures to prevent potential import restrictions by Japan on Korean seafood. Korean-Radionuclides (Japan) emphasizes the importance of sufficient scientific evidence, especially scientific information from relevant international organizations, in an effort to take preventive measures towards Japan's restrictions on Korean seafood imports. Japan claims that a novel parasite, Kudoa septempuctata, in Korean flatfish causes food poisoning. As food poisoning is a serious concern, there is a low possibility that Japan's enhanced monitoring measures would be more trade restrictive than required as prescribed in Article 5.6 of the WTO SPS Agreement. In addition, Korea is the biggest exporter of olive flounder to Japan. Hence, the possibility that similar conditions could be established is low in relation to non-discriminatory principles under the WTO SPS Agreement. Accordingly, we should collect relevant scientific evidence, improve domestic sanitary management of fishery products, and seek export diversification so that we prepare for potential import restrictions by Japan and minimize implications.

• 국제강구조저널
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• 제18권5호
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• pp.1483-1496
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• 2018

Negligible research has been conducted to date on how to analyse weakened columns, thus safety risks are still involved when structures are weakened prior to demolition. There are various methods available for demolishing steel structures. One of the most effective methods that has been developed involves pre-cutting steel columns at a certain height, so that the least effort can be used to collapse the structure by means of pulling out some of the columns. This paper presents (a) an experimental setup developed to test the capacity of axially loaded weakened columns, which is used to (b) validate a finite element (FE) model. The two pre-cuts that are presented in this paper are (1) the double window cut and (2) the triangular window cut, which are both commonly used in industry. A column weakened with a double window cut or triangular window cut reduces the axial load capacity by up to 50 and 40%, respectively. The FE models developed predict the axial failure load of weakened columns for a double window cut and triangular window cut are generally within an accuracy of less than 8 and 10%, respectively. It is shown at higher slendernesses the influence of column cuts is less than would be intuitively expected because global buckling becomes dominant.

• 대한금속재료학회지
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• 제47권12호
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• pp.881-886
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• 2009

Research into the replacement of injured systems and tissue in the human body is advancing rapidly. Recently, Ti-Ni shape memory alloys have shown excellent biofunctionality related to their shape memory effect and superelasticity. In this study, the effect of an acid or an alkali treatment on the bioactivity in 49Ti-Ni and 51.5Ti-48.5Ni alloys is investigated in an effort to utilize Ti-Ni alloy as a biomaterial. In addition, the biocompatibility in a SBF solution is assessed through in vitro testing. A porous surface was formed on the surface of both alloys after a chemical treatment. According to the in vitro test, apatite formed on the surfaces of both alloys. The forming rate of apatite in the Ti-rich alloy was faster that in the Ni-rich alloy. The formation of apatite provided proof of the bioactivity of the Ti-Ni alloy. A small quantity of Ni was eluted at the initial stage, whereas Ni was not found for 12 days in the Ti-rich alloy and for 8 days in the Ni-rich alloy. In the case of the treated 51.5Ti-Ni alloy, the shape memory property was worsened but the biocompatibility was improved.

• Steel and Composite Structures
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• 제44권3호
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• pp.389-406
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• 2022

Recycling concrete construction waste is an encouraging step toward green and sustainable building. A lot of research has been done on recycled aggregate concretes (RACs), but not nearly as much has been done on concrete made with recycled aggregate. Recycled aggregate concrete, on the other hand, has been found to have a lower mechanical productivity compared to conventional one. Accurately estimating the mechanical behavior of the concrete samples is a most important scientific topic in civil, structural, and construction engineering. This may prevent the need for excess time and effort and lead to economic considerations because experimental studies are often time-consuming, costly, and troublous. This study presents a comprehensive data-mining-based model for predicting the splitting tensile strength of recycled aggregate concrete modified with glass fiber and silica fume. For this purpose, first, 168 splitting tensile strength tests under different conditions have been performed in the laboratory, then based on the different conditions of each experiment, some variables are considered as input parameters to predict the splitting tensile strength. Then, three hybrid models as GWO-RF, GWO-MLP, and GWO-SVR, were utilized for this purpose. The results showed that all developed GWO-based hybrid predicting models have good agreement with measured experimental results. Significantly, the GWO-RF model has the best accuracy based on the model performance assessment criteria for training and testing data.

• 산경연구논집
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• 제13권9호
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• pp.1-9
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• 2022

Purpose: This study evaluates the ability to improve the economic welfare of rural communities in Indonesia by using the inequality measures of the distribution of information between leaders and their people as a variable that weakens the capacity of increasing the welfare. Research Design, Data, and Methodology: The research designed by developing an instrument using data validity and reliability testing. Before, primary data collected through interviews, questionnaires, observation, and documentation on the selected respondents. Then, the research method used is mixed methods research, in which quantitative and qualitative methods combined. Result: The finding from this study is that there is an inequality measure in the form of a high gap between the score of information distribution obtained by the village government compared to the score of the community, which has led to the welfare of the village which is still at a moderate level and not ready to become a prosperous society. Conclusion: The weakness of the village community is related to two things, namely the behavior and knowledge of the community about the issues, so the implication is that there must be a strong effort from the central government to ensure that technology is more evenly distributed to all villagers.