• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.113-125
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• 2011

As information resources have become more various and the number of the resources has increased, knowledge customization on the social web has been becoming more difficult. To reduce the burden, we offer a framework for context-based similarity calculation for knowledge customization using ontology on the CBR. Thereby, we newly developed context- and intensity-based similarity calculation methods which are applied to extraction of the most similar case considered semantic similarity and syntactic, and effective creation of the user-tailored knowledge using the selected case. The process is comprised of conversion of unstructured web information into cases, extraction of an appropriate case according to the user requirements, and customization of the knowledge using the selected case. In the experimental section, the effectiveness of the developed similarity methods are compared with other edge-counting similarity methods using two classes which are compared with each other. It shows that our framework leads higher similarity values for conceptually close classes compared with other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.536-551
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• 2017

With the advancement and deployment of leading-edge telecommunication technologies for sensing and collecting, computing related information, Cloud of Things (CoTs) has emerged as a typical application platform that is envisioned to revolutionize the daily activities of human society, such as intelligent transportation, modern logistics, food safety, environmental monitoring, etc. To avoid any possible malicious attack and resource abuse, employing hash functions is widely recognized as one of the most effective approaches for CoTs to achieve message integrity and data authentication. The Whirlpool hash function has served as part of the joint ISO/IEC 10118-3 International Standard by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). In this paper, we propose an effective differential fault analysis on Whirlpool in the byte-oriented random fault model. The mathematical analysis and experimental results show that 8 random faults on average are required to obtain the current 512-bit message input of whirlpool and the secret key of HMAC-Whirlpool. Our work demonstrates that Whirlpool and HMAC-Whirlpool are both vulnerable to the single byte differential fault analysis. It provides a new reference for the security analysis of the same structure of the hash functions in the CoTs.

• Journal of Internet Computing and Services
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• v.8 no.2
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• pp.55-65
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• 2007

BcN is a high-quality broadband network for multimedia services integrating telecommunication, broadcasting, and Internet seamlessly at anywhere, anytime, and using any device. BcN is Particularly vulnerable to intrusion because it merges various traditional networks, wired, wireless and data networks. Because of this, one of the most important aspects in BcN is security in terms of reliability. So, in this paper, we suggest the sharing mechanism of security data among various service networks on the BcN. This distributed, hierarchical architecture enables BcN to be robust of attacks and failures, controls data traffic going in and out the backbone core through IP edge routers integrated with IDRS. Our proposed anomaly detection scheme on IDRS for BcN service also improves detection rate compared to the previous conventional approaches.

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.59-68
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• 2005

In this paper, for compression and transmission of 3D image, we propose an algorithm which executes 3D discrete cosine transform(DCT) for 3D images, hierarchically segments 3D blocks of an image in comparison with the original image and executes finite-state vector quantization(FSVQ) for each 3D block. Using 3D DCT coefficient feature, a 3D image is segmented hierarchically into large smooth blocks and small edge blocks, then the block hierarchy informations are transmitted. The codebooks are constructed for each hierarchical blocks respectively, the encoder transmits codeword index using FSVQ for reducing encoded bit with hierarchical segmentation information. The new algorithm suggested in this paper shows that the quality of Small Lobster and Head image increased by 1,91 dB and 1.47 dB respectively compared with those of HFSVQ.

• Journal of Internet Computing and Services
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• v.9 no.2
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• pp.51-59
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• 2008

As the innovative IT are being developed and applied in the e-business environment, firms are recognizing the fact that amount of customer information is providing care competitive edge. However, sensitive privacy information are abused and misused, and it is affecting the firms to require appropriate measures to protect privacy information and implement security techniques to safeguard carparate resources. This research analyzes the threat of privacy information exposure in the e-business environment, suggest the IPM-Trusted Privacy Policy Model in order to resolve the related problem, and examines 4 key mechanisms (CAM, SPM, RBAC Controller, OCM) focused on privacy protection. The model is analyzed and designed to enable access management and control by assigning user access rights based on privacy information policy and procedures in the e-business environment. Further, this research suggests practical use areas by applying TPM to CRM in e-business environment.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.55-63
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• 2017

One of the purposes of Information Technology (IT) is to support human response to natural and social problems such as natural disasters and spread of disease, and to improve the quality of human life. Recent climate change has happened worldwide, natural disasters threaten the quality of life, and human safety is no longer guaranteed. IT must be able to support tasks related to disaster response, and more importantly, it should be used to predict and minimize future damage. In South Korea, the data related to the damage is checked out by each local government and then federal government aggregates it. This data is included in disaster reports that the federal government discloses by disaster case, but it is difficult to obtain raw data of the damage even for research purposes. In order to obtain data, information extraction may be applied to disaster reports. In the field of information extraction, most of the extraction targets are web documents, commercial reports, SNS text, and so on. There is little research on information extraction for government disaster reports. They are mostly text, but the structure of each sentence is very different from that of news articles and commercial reports. The features of the government disaster report should be carefully considered. In this paper, information extraction method for South Korea government reports in the word format is presented. This method is based on patterns and dictionaries and provides some additional ideas for tokenizing the damage representation of the text. The experiment result is F1 score of 80.2 on the test set. This is close to cutting-edge information extraction performance before applying the recent deep learning algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2953-2960
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• 2014

In the field of image recognition, circle detection is one of the most widely used techniques. Conventional algorithms are mainly based on Hough transform, which is the most straightforward algorithm for detecting circles and for providing enough robust algorithm. However, it suffers from large memory requirements and high computational loads, and sometimes tends to detect incorrect circles. This paper proposes an optimal circle detection and approximation method which is applicable for inspecting fiber optic connector endface. The proposed method finds initial center coordinates and radius based on the initial edge lines. Then, by introducing the simplified K-means algorithm, the proposed method investigates a substitute-circle by minimizing the area of non-overlapped regions. Through extensive simulations, it is shown that the proposed method can improve the error rate by as much as 67% and also can reduce the computing time by as much as 80%, compared to the Hough transform provided by the OpenCV library.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.549-557
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• 2015

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.103-110
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• 2013

RFID is estimated to have great potential for hospitals to reduce various costs, reconsider patients' safety, and provide high quality medical service. As the ubiquitous technology allows the medical market to expand, medical centers all around the country are fiercely competing against one another. In order to increase the hospital's competitive edge by reducing IT expenses and concentrating on medical practice, the need to establish a u-Hospital using advanced IT technology is rapidly rising. This paper implements an RFID based u-Hospital system by using ubiquitous computing technology to design a location tracking device for all surgical patients, which can secure the patients' safety and increase the quality of medical service through interlocking hospital information systems.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.601-608
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• 2014

In this study we propose an image denoising algorithm appropriate for mobile smart phone equipped with limited computing ability, which has better performance and at the same time comparable quality comparing with previous studies. The proposed image denoising algorithm for mobile smart phone cameras in low level light environment reduces computational complexity and also prevents edge smoothing by extracting just Gaussian noises from the noisy input image. According to the experiment result, we verified that our algorithm has much better PSNR value than methods applying mean filter or median filter. Also the result image from our algorithm has better clear quality since it preserves edges while smoothing input image. Moreover, the suggested algorithm reduces computational complexity about 52% compared to the method applying original Laplacian mask computation, and we verified that our algorithm has good denoising quality by implementing the algorithm in Android smart phone.