• Journal of the Korea Concrete Institute
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• v.26 no.4
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• pp.545-553
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• 2014

This study suggested an integrated classification method for generalized characteristics of PC beam-column connection according to connection details. Quantifying the failure mode of PC-beam column connection and characteristics of corresponding details, this study suggested to use deformation contribution of each element of beam-column assemblage. According to the expected failure mode of beam-column connection assemblage, PC beam-column connection can be classified into 'equivalent monolithic system' and 'jointed system'. In this study, four test specimens were tested for verification of detailed classification method of PC beam-column connections. Test was carried out with typical beam-column connection test method. Load was applied at the top of test specimen and end of beams were restrained by hinge. In order to verify the deformation contribution of each test specimen, 34-LVDTs were mounted on test specimen. According to test results, deformation contribution of each test specimen have different characteristics. Deformation characteristics of joint and other components which are quantified by test results, equivalent monolithic system can be classified into two categories. Strong connection have extremely small deformation contribution of joint and much larger deformation contribution was shown in flexural behavior of beam. The other type of beam-column connection is ductile connection which allows the larger deformation in joint area compared with strong connection.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.50-50
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• 2014

We present a new catalog of galaxies in the wider region of the Virgo cluster, based on the Sloan Digital Sky Survey (SDSS) Data Release 7. The Extended Virgo Cluster Catalog (EVCC) covers an area of 725 deg2 or 60.1 Mpc2. It is 5.2 times larger than the footprint of the classical Virgo Cluster Catalog (VCC) and reaches out to 3.5 times the virial radius of the Virgo cluster. We selected 1324 spectroscopically targeted galaxies with radial velocities less than 3000 km s-1. In addition, 265 galaxies that have been missed in the SDSS spectroscopic survey but have available redshifts in the NASA Extragalactic Database are also included. Our selection process secured a total of 1589 galaxies of which 676 galaxies are not included in the VCC. The certain and possible cluster members are defined by means of redshift comparison with a cluster infall model. We employed two independent and complementary galaxy classification schemes: the traditional morphological classification based on the visual inspection of optical images and a characterization of galaxies from their spectroscopic features. SDSS u, g, r, i, and z passband photometry of all EVCC galaxies was performed using Source Extractor. We compare the EVCC galaxies with the VCC in terms of morphology, spatial distribution, and luminosity function. The EVCC defines a comprehensive galaxy sample covering a wider range in galaxy density that is significantly different from the inner region of the Virgo cluster. It will be the foundation for forthcoming galaxy evolution studies in the extended Virgo cluster region, complementing ongoing and planned Virgo cluster surveys at various wavelengths.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.131-143
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• 2007

The current trends in information technology and intelligent systems use data mining techniques to discover patterns and extract rules from distributed databases. In distributed environment, the extracted rules from data mining techniques can be used in dynamic replications, adaptive load balancing and other schemes. However, transmission of large data through the system can cause errors and unreliable results. This paper proposes the intelligent distributed platform based on dynamic group binding using mobile agents which addresses the use of intelligence in distributed environment. The proposed grouping service implements classification scheme of objects. Data compressor agent and data miner agent extracts rules and compresses data, respectively, from the service node databases. The proposed algorithm performs preprocessing where it merges the less frequent dataset using neuro-fuzzy classifier before sending the data. Object group classification, data mining the service node database, data compression method, and rule extraction were simulated. Result of experiments in efficient data compression and reliable rule extraction shows that the proposed algorithm has better performance compared to other methods.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1590-1597
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• 1999

Advertisements on the Web, rising as a major profit source of Web services, have a distinctive characteristic of detailed classification of potential customers, compared with those of other conventional media such as TV and newspaper. It is therefore possible to advertise selectively according to personal characteristics and to record precise advertisement effects. Web-based advertisement management systems of nowadays have the capability to select ones compatible with personal environment characteristics and registered information, and to provide processed information and knowledge about advertisement effects based on usage recordings. However, they have severe problems in modeling diverse requirements or characteristics of users : customers, advertisers and ISP, and in matching and coordinating of them. In order to solve these problems, we propose a frame work for coordinating the needs of users, advertisers, and ISPs, which is built on top of tree-style classification of advertisements. Other schemes are supported around the framework as follows : (1) characteristics management of pages within themselves, (2) rule-based modeling of advertisement target, and (3) user modeling and case-based analysis. We propose a prototype system within the framework.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8A
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• pp.858-870
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• 2007

TCP is popular protocol for reliable data delivery in the Internet. In recent years, wireless environments with transmission errors are becoming more common. Therefore, there is significant interest in using TCP over wireless links. Previous works have shown that, unless the protocol is modified, TCP may perform poorly on paths that include a wireless link subject to transmission errors. The reason for this is the implicit assumption in TCP that all packet losses are due to congestion which causes unnecessary reduction of transmission rate when the cause of packet losses are wireless transmission errors. In this paper, we propose a new LDA that monitors the network congestion level using ROTT. And we evaluate the performance of our scheme and compare with TCP Veno, Spike scheme with NS2(Network Simulator 2). In the result of our experiment, our scheme reduces the packet loss misclassification to maximum 55% of other schemes. And the results of another simulation show that our scheme raise its transmission rate with the fairness preserved.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.93-100
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• 2007

Internet had spread in all fields with the fast speed during the last 10 years. Lately, wireless network is also spreading rapidly. Also, number of times that succeed attack attempt and invasion for wireless network is increasing rapidly TMS system was developed to overcome these threat on wireless network. Existing TMS system supplies active confrontation mechanism on these threats. However, existent TMS has limitation that new form of attack do not filtered efficiently. Therefor this paper proposes a new method that it automatically compute the threat from the imput packets with vector space model and detect anomaly detection of wireless network. Proposed mechanism in this research analyzes similarity degree between packets, and detect something wrong symptom of wireless network and then classify these threats automatically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.175-181
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• 2022

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.143-167
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• 2015

This paper addresses the issue how the total life cycle cost may be minimized and how the cost should be allocated to the acquirer and developer. This paper differentiates post life cycle change (PLCC) endeavors from PLCC activities, rigorously classifies PLCC endeavors according to the result of PLCC endeavors, and rigorously defines the life cycle cost of a software product. This paper reviews classical definitions of software 'maintenance' types and proposes a new typology of PLCC activities too. The proposed classification schemes are exhaustive and mutually exclusive, and provide a new paradigm to review existing literatures regarding software cost estimation, software 'maintenance,' software evolution, and software architecture from a new perspective. This paper argues that the long-term interest of the acquirer is not protected properly because warranty period is typically too short and because the main concern of warranty service is given to removing the defects detected easily. Based on the observation that defects are caused solely by errors the developer has committed for software while defects are often induced by using for hardware (so, this paper cautiously proposes not to use the term 'maintenance' at all for software), this paper argues that the cost to remove defects should not be borne by the acquirer for software.

• The Journal of Korean Medical History
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• v.27 no.2
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• pp.63-74
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• 2014

The purpose of this study is to investigate the organization and contents of "CheongKangEuiGam" and raise interests in study on Oriental Medicine in the 20th century. Songjae, LeeJongHyeong was a disciple of Cheongkang and published this book in 1984 by organizing the medical theory of Cheongkang, KimYoungHoon who lived in the turbulent period from the late period of Joseon to a chaotic state of Korea after the independence of Korea. Even though it is relatively recently published, it is a very important clinical book as well as historical material to look at the aspects of Oriental Medicine in the 20th century. The book contains several notable medical thoughts. First, you can look at one perspective of the 20th century Oriental Western medical study which is initiated by the introduction of Western Medicine in classification schemes and description of disease symptoms. In addition, he uses medicinal herbs such as Cyperus rotundus L., Pinellia ternate(Thunb.) Breit., Poria cocos Wolf, Angelica gigas Nakai, Cnidium officinale, and Paeonia lactiflora Pall as important items, it is found that qi and blood depressed gallbladder is considered as the main pathology of the disease. In terms of names and meaning of prescriptions, he prefers to use mild medicinal herbs rather than intense medicinal herbs. It seems that he tries to help people's lives with cheap and effective medicinal herbs.