• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.367-375
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• 2014

Recently the use of concrete post-installed set anchors has been increasing because this constructing method is flexible and easy to attach or fix structural members when we repair, reinforce, or remodel a concrete structures. Depending on the shear strength of steel, the strength of concrete, edge distance and anchor interval, etc, the anchor loaded in shearing exhibits various failure modes such as steel failure, concrete failure, concrete pryout. In this study, the objective is to investigate the effects of the variations like anchor embedment depth, anchor interval, edge distance and concrete strength on the shear failure behavior of post-installed concrete set anchor embedded in concrete. The results of embedment depth experiments show that concrete strength has much effection on the shallow embedment depth. Steel failure occur to all results of the anchor interval experiments, but concrete is failed when edge distance experiments that less than the embedment depth. Through the comparision of the same parameters experiments results show that as strong as concrete strength are the displacement results are small.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.53 no.2
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• pp.169-176
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• 2017

Tuna purse seine fishery in the western and central Pacific Ocean (WCPO) has been rapidly developed since early 1980s due to massive investment of major distant water fishing nations, and catch by purse seine fishery operating in the WCPO accounts for nearly half of the world's tuna total catch. As fishing efficiency is reflected by not only improving of individual vessel's capacity but also increasing number of active vessel, it is essential to understand vessel capacity for reliable assessment result on how fishery affects stock status of target species. In this study, fishing efficiency was analyzed by main factors which are representative of vessel capacity using fishing data and vessel information related to Korean tuna purse seine fishery operating in the western and central Pacific Ocean from 1992 to 2014. It showed that fishing efficiency of vessel tends to be higher when having larger vessel tonnage, higher engine power, lower vessel age and larger length of vessel. As for fishing efficiency by set type, CPUE of associated set with floating objects was generally higher than that of free school set, and CPUE of free school set seemed to have a greater effect on engine power and vessel age compared to other factors.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.482-496
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• 2008

Packet classification in the Internet routers requires multi-dimensional search for multiple header fields for every incoming packet in wire-speed, hence packet classification is one of the most important challenges in router design. Hierarchical packet classification is one of the most effective solutions since search space is remarkably reduced every time a field search is completed. However, hierarchical structures have two intrinsic issues; back-tracking and empty internal nodes. In this paper, we propose a new hierarchical packet classification algorithm which solves both problems. The back-tracking is avoided by using the set-pruning and the empty internal nodes are avoided by applying the binary search tree. Simulation result shows that the proposed algorithm provides significant improvement in search speed without increasing the amount of memory requirement. We also propose an optimization technique applying controlled rule copy in set-pruning.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1054-1061
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• 2004

At recent, people can easily access to information by Internet to be rapidly evolving. And also, the amount is rapidly increasing. So the techniques, to automatically extract the required information are very important to reduce the time and the effort for retrieving information. In this paper, we describe a collaborative filtering system for automatically recommending high-quality information to users with similar interests on arbitrarily narrow information domains. It asks a user to rate a gauge set of items. It then evaluates the user's rates and suggests a recommendation set of items. We interpret the process of evaluation as an inference mechanism that maps a gauge set to a recommendation set. We accomplish the mapping with FAM (Fuzzy Associative Memory). We implemented the suggested system in a Web server and tested its performance in the domain of retrieval of technical papers, especially in the field of information technologies. The experimental results show that it may provide reliable recommendations.

• Smart Structures and Systems
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• v.3 no.3
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• pp.341-356
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• 2007

A good understanding of normal modal variability of civil structures due to varying environmental conditions such as temperature and wind is important for reliable performance of vibration-based damage detection methods. This paper addresses the quantification of wind-induced modal variability of a cable-stayed bridge making use of one-year monitoring data. In order to discriminate the wind-induced modal variability from the temperature-induced modal variability, the one-year monitoring data are divided into two sets: the first set includes the data obtained under weak wind conditions (hourly-average wind speed less than 2 m/s) during all four seasons, and the second set includes the data obtained under both weak and strong (typhoon) wind conditions during the summer only. The measured modal frequencies and temperatures of the bridge obtained from the first set of data are used to formulate temperature-frequency correlation models by means of artificial neural network technique. Before the second set of data is utilized to quantify the wind-induced modal variability, the effect of temperature on the measured modal frequencies is first eliminated by normalizing these modal frequencies to a reference temperature with the use of the temperature-frequency correlation models. Then the wind-induced modal variability is quantitatively evaluated by correlating the normalized modal frequencies for each mode with the wind speed measurement data. It is revealed that in contrast to the dependence of modal frequencies on temperature, there is no explicit correlation between the modal frequencies and wind intensity. For most of the measured modes, the modal frequencies exhibit a slightly increasing trend with the increase of wind speed in statistical sense. The relative variation of the modal frequencies arising from wind effect (with the maximum hourly-average wind speed up to 17.6 m/s) is estimated to range from 1.61% to 7.87% for the measured 8 modes of the bridge, being notably less than the modal variability caused by temperature effect.

• Toxicological Research
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• v.32 no.4
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• pp.289-300
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• 2016

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.3
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• pp.55-63
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• 2015

Post-installed concrete set anchors are installed after the concrete hardened. These anchors increasing usage in development of construction equipment and flexible construction. The anchor loaded in shearing exhibits various failure modes such as steel failure, concrete failure, concrete pryout, depending on the shear strength of steel, the strength of concrete, edge distance and anchor interval, etc,. In this study, the objective is to investigate the effects of the variations like anchor embedment depth, edge distance and concrete strength on experimental and finite element analysis of shear failure behavior of post-installed concrete set anchor for light load embedded in concrete. The results of embedment depth experiments show that concrete strength has much affection on the shallow embedment depth. Concrete strength has no much affection with anchor interval and edge distance parameter and both experimental results occurred same failure mode. By comparing the experimental results that occurred steel failure mode show that as strong as concrete strength are the displacement results are small.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.40-47
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• 2014

Recently the use of concrete post-installed set anchors has been increasing because this constructing method is flexible and easy to attach or fix structural members when we repair, reinforce, or remodel structures. Accordingly, designers and builders of Korea depend on foreign design codes since there are no exact domestic anchor design codes that they could credit. The anchor in plain concrete loaded in tensile exhibits various failure modes such as concrete breakout, splitting, steel failure, pull-out and side-face blowout, that depending on the tensile strength of the steel, the strength of concrete, embedment depth, interval, the edge distance and the presence of adjacent anchor. The objective is to investigate the effects of the variations like anchor embedment depth, interval and edge distance on pull-out fracture behavior of post-installed concrete set anchor embedded in plain concrete.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.758-767
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• 2017

IoT paradigm which makes a information without direct intervention of a human and interworks with other objects, humans and systems is attracting attention. It will be expected the number of smart devices equipped with sensors and wireless communication capabilities is reached to about 260 billion by 2020. With the vast amount of sending data generated from rapidly increasing number of smart devices, it will bring up the traffic growth over internet and congestion in wireless networks. In this paper, we utilize the smart device as a sink node to collect and forward the sensing data periodically in IoT and propose a heuristic algorithm for a selection of sink nodes' set with each sink node satisfies the QoS its applications because a selection of optimal sink nodes' set is NP-hard problem. The complexity of proposed heuristic algorithm is $O(m^3)$ and faster than the optimal algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.132-137
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• 2019

The amount of data generated from medical images is increasingly exceeding the limits of professional visual analysis, and the need for automated medical image analysis is increasing. For this reason, this study evaluated the classification and accuracy according to the presence or absence of tumor using Inception V3 deep learning model, using MRI medical images showing normal and tumor findings. As a result, the accuracy of the deep learning model was 90% for the training data set and 86% for the validation data set. The loss rate was 0.56 for the training data set and 1.28 for the validation data set. In future studies, it is necessary to secure the data of publicly available medical images to improve the performance of the deep learning model and to ensure the reliability of the evaluation, and to implement modeling by improving the accuracy of labeling through labeling classification.