• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.319-326
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• 2004

To help network intrusion detection systems(NIDSs) keep up with the demands of today's networks, that we the increasing network throughput and amount of attacks, a radical new approach in hardware and software system architecture is required. In this paper, we propose a Network Processor(NP) based In-Line mode NIDS that supports the packet payload inspection detecting the malicious behaviors, as well as the packet filtering and the traffic metering. In particular, we separate the filtering and metering functions from the deep packet inspection function using two-level searching scheme, thus the complicated and time-consuming operation of the deep packet inspection function does not hinder or flop the basic operations of the In-line mode system. From a proto-type NP-based NIDS implemented at a PC platform with an x86 processor running Linux, two Gigabit Ethernet ports, and 2.5Gbps Agere PayloadPlus(APP) NP solution, the experiment results show that our proposed scheme can reliably filter and meter the full traffic of two gigabit ports at the first level even though it can inspect the packet payload up to 320 Mbps in real-time at the second level, which can be compared to the performance of general-purpose processor based Inspection. However, the simulation results show that the deep packet searching is also possible up to 2Gbps in wire speed when we adopt 10Gbps APP solution.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.473-486
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• 2005

The Hippocratic database model recently proposed by Agrawal et at. incorporates privacy protection capabilities into relational databases. The authors have subsequenty proposed the Hippocratic XML daかabase model[4], an extension of the Hippocratic database model for XML databases. In this paper, we propose a new concept that we cail the dynamic predicate(DP) for effective access control in the Hippocratic XML database model. A DP is a novel concept that represents a dynamically constructed rendition that tan be adapted for determining the accessibility of elements during query execution. DPs allow us to effectively integrate authorization checking into the query plan so that unauthorized elements are excluded in the process of query execution. Using synthetic and real data, we have performed extensive experiments comparing query processing time with those of existing access control mechanisms. The results show that the proposed access control mechanism improves the wall clock time by up to 219 times over the top-down access control strategy and by up to 499 times over the bottom-up access control strategy. The major contribution of our, paper is enabling effective integration of access control mechanisms with the query plan using the DP under the Hippocratic XML database model.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.427-432
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• 2012

The article herein suggested a compound repository and a descriptive method to develop a compound knowledge process. A data target saved in a compound knowledge repository suggested in this article includes all compound knowledge meta data and digital resources, which can be divided into the three following factors according to the purpose: user roles, functional elements, and service ranges. The three factors are basic components to describe abstract models of repository. In this article, meta data of compound knowledge are defined by being classified into the two factors. A component stands for the property about a main agent, activity unit or resource that use and create knowledge, and a context presents the context in which knowledge object are included. An agent of the compound knowledge process performs classification, registration, and pattern information management of composite knowledge, and serves as data flow and processing between compound knowledge repository and user. The agent of the compound knowledge process consists of the following functions: warning to inform data search and extraction, data collection and output for data exchange in an distributed environment, storage and registration for data, request and transmission to call for physical material wanted after search of meta data. In this article, the construction of a compound knowledge repository for recommendation system to be developed can serve a role to enhance learning productivity through real-time visualization of timely knowledge by presenting well-put various contents to users in the field of industry to occur work and learning at the same time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.90-102
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• 2011

Recently, the grade of users using wireless communication services which transmits and re-transmits to the signal via the broadcasting satellite have a variety. However the ships not preparing of H.264 standard devices should not received the realtime data because the broadcasting stations have transmitted the compressed video data through the satellite communication. Therefore this paper proposes H.264 to MPEG-2 transcoding for the ships using MPEG-2 devices. Proposed method improves a speed and object quality in H.264 to MPEG-2 transcoding by analysis features of macroblock modes in H.264. In the Intra mode of P-frame, it proposes new method by computing coincidence proportion after comparing of Intra mode methods of H.264 and MPEG-2. In the Inter mode, it proposes a PMV(predictive motion vector) considering movement of motion vectors in H.264 decoder. we reuses a PMV directly as like the final MV in MPEG-2 encoder and refinements the MV after coincidence ratio comparing of variable motion vectors of H.264 and these of MPEG-2. The experimental results from proposed method show a considerable reduction in processing time, as much as 70% and 67% respectively, with a small objective quality reduction in PSNR.

• Journal of the Korean Chemical Society
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• v.60 no.1
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• pp.69-81
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• 2016

The purpose of this study was to find out the validation of instructional strategies using the Advanced Laboratory Equipment (ALE class) by investigating science high school students’ perception on ALE in chemistry classrooms and to consider the need for development of teaching materials on ALE class. 7 sessions of ALE including experiments with innovative equipment were developed and applied to 21 students in D Science High School. At the end of the sessions, questionnaire was given to the students. We also collected qualitative data by interviewing 9 students who participated in the questionnaire. We analyzed the data collected by In-depth interviews and students’ experimental reports. The result showed that ALE class was effective to enhance students’ understanding of learning concepts because the experimental time was shortened in real time data processing. Some students showed creative performance on solving scientific problems by using everyday materials in experimental process and developed perceptions of practical inquiry. Through this process, students’ positive attitudes and interests in science and heuristic inquiry skills were also enhanced. Developing ALE lesson materials will be helpful for students to understand science and technology and the domain of science in broader contexts.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.561-574
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• 2008

The spot detection phase of the 2-DE image analysis program segments a gel image into spot regions by an image segmentation algorithm and fits the spot regions to a spot shape model and quantifies the spot informations for the next phases. Currently the watershed algorithm is generally used as the segmentation algorithm and there are the Gaussian model and the diffusion model for the shape model. The diffusion model is closer to real spot shapes than the Gaussian model however spots have very various shapes and especially an asymmetric formation in x-coordinate and y-coordinate. The reason for asymmetric formation of spots is known that a protein could not be diffused completely because the 2-DE could not be processed under the ideal environment usually. Accordingly we propose an asymmetric diffusion model in this paper. The asymmetric diffusion model assumes that a protein spot is diffused from a disc at initial time of diffusing process, but is diffused asymmetrically for x-axis and y-axis respectively as time goes on. In experiments we processed spot matching for 19 gel images by using three models respectively and evaluated averages of SNR for comparing three models. As averages of SNR we got 14.22dB for the Gaussian model, 20.72dB for the diffusion model and 22.85dB for the asymmetric diffusion model. By experimental results we could confirm the asymmetric diffusion model is more efficient and more adequate for spot matching than the Gaussian model and the diffusion model.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.471-478
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• 2004

Electromyogram (EMC) signal generated by voluntary contraction of muscles is often used in a rehabilitation devices such as an upper limb prosthesis because of its distinct output characteristics compared to other bio-signals. This paper proposes an EMG-based human-computer interface (HCI) for the control of the above-elbow prosthesis or the wheelchair. To control such rehabilitation devices, user generates four commands by combining voluntary contraction of two different muscles such as levator scapulae muscles and flexor-extensor carpi ulnaris muscles. The muscle contraction is detected by comparing the mean absolute value of the EMG signal with a preset threshold value. However. since the time difference in muscle firing can occur when the patient tries simultaneous co-contraction of two muscles, it is difficult to determine whether the patient's intention is co-contraction. Hence, the use of the comparison method using a single threshold value is not feasible for recognizing such co-contraction motion. Here, we propose a novel method using double threshold values composed of a primary threshold and an auxiliary threshold. Using the double threshold method, the co-contraction state is easily detected, and diverse interface commands can be used for the EMG-based HCI. The experimental results with real-time EMG processing showed that the double threshold method is feasible for the EMG-based HCI to control the myoelectric prosthetic hand and the powered wheelchair.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.684-698
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• 2004

The Hippocratic database model recently proposed by Agrawal et al. incorporates privacy protection capabilities into relational databases. Since the Hippocratic database is based on the relational database, it needs extensions to be adapted for XML databases. In this paper, we propose the Hippocratic XML database model, an extension of the Hippocratic database model for XML databases and present an efficient access control mechanism under this model. In contrast to relational data, XML data have tree-like hierarchies. Thus, in order to manage these hierarchies of XML data, we extend and formally define such concepts presented in the Hippocratic database model as privacy preferences, privacy policies, privacy authorizations, and usage purposes of data records. Next, we present a new mechanism, which we call the authorization index, that is used in the access control mechanism. This authorization index, which is Implemented using a multi-dimensional index, allows us to efficiently search authorizations implied by the authorization granted on the nearest ancestor using the nearest neighbor search technique. Using synthetic and real data, we have performed extensive experiments comparing query processing time with those of existing access control mechanisms. The results show that the proposed access control mechanism improves the wall clock time by up to 13.6 times over the top-down access control strategy and by up to 20.3 times over the bottom-up access control strategy The major contributions of our paper are 1) extending the Hippocratic database model into the Hippocratic XML database model and 2) proposing an efficient across control mechanism that uses the authorization index and nearest neighbor search technique under this model.