• Journal of Communications and Networks
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• 제9권4호
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• pp.499-510
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• 2007

Shortest path tree(SPT) construction is essential in high performance routing in an interior network using link state protocols. When some links have new state values, SPTs may be rebuilt, but the total rebuilding of the SPT in a static way for a large computer network is not only computationally expensive, unnecessary modifications can cause routing table instability. This paper presents a new update algorithm, dynamic shortest path tree(DSPT) that is computationally economical and that maintains the unmodified nodes mostly from an old SPT to a new SPT. The proposed algorithm reduces redundancy using a dynamic update approach where an edge becomes the significant edge when it is extracted from a built edge list Q. The average number of significant edges are identified through probability analysis based on an arbitrary tree structure. An update derived from significant edges is more efficient because the DSPT algorithm neglect most other redundant edges that do not participate in the construction of a new SPT. Our complexity analysis and experimental results show that DSPT is faster than other known methods. It can also be extended to solve the SPT updating problem in a graph with negative weight edges.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2018년도 춘계학술발표회
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• pp.5-5
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• 2018

Ginseng (Panax ginseng C.A. Meyer), one of the most widely used medicinal plants in traditional oriental medicine, is used for the treatment of various diseases. It has been classified according to its cultivation environment, such as field cultivated ginseng (FCG) and mountain cultivated ginseng (MCG). However, little is known about differences in gene expression in ginseng roots between field cultivated and mountain cultivated ginseng. In order to investigate the whole transcriptome landscape of ginseng, we employed High-Throughput sequencing technologies using the Illumina HiSeqTM2500 system, and generated a large amount of sequenced transcriptome from ginseng roots. Approximately 77 million and 87 million high-quality reads were produced in the FCG and MCG roots transcriptome analyses, respectively, and we obtained 256,032 assembled unigenes with an average length of 1,171 bp by de novo assembly methods. Functional annotations of the unigenes were performed using sequence similarity comparisons against the following databases: the non-redundant nucleotide database, the InterPro domains database, the Gene Ontology Consortium database, and the Kyoto Encyclopedia of Genes and Genomes pathway database. A total of 4,207 unigenes were assigned to specific metabolic pathways, and all of the known enzymes involved in starch and sucrose metabolism pathways were also identified in the KEGG library. This study indicated that alpha-glucan phosphorylase 1, putative pectinesterase/pectinesterase inhibitor 17, beta-amylase, and alpha-glucan phosphorylase isozyme H might be important factors involved in starch and sucrose metabolism between FCG and MCG in different environments.

• 디지털콘텐츠학회 논문지
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• 제10권2호
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• pp.189-198
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• 2009

이 논문에서는 직교 주파수분할 다중화(orthogonal frequency division multiplexing: OFDM) 수신기에서 수신 신호를 과표본화(oversampling)하여 성능을 개선하는 방법을 제안한다. 수신된 OFDM 신호를 복조하는 것은 각 부반송파에 해당하는 정현파 성분의 진폭과 위상을 추출하는 것과 동일하다. OFDM 수신신호를 과표본화 하면 주파수 영역에서 진폭은 동일하고 위상만 다른 신호를 과표본화율만큼 중복해서 얻을 수 있다. 이 성질을 이용하여 과표본화율만큼 신호대잡음비를 개선할 수 있다. 이 논문에서는 과표본화율이 정수인 경우만 가능하던 기존의 과표본화 방법을 일반적인 비정수로 확장하고 그에 적합한 수신기 구조를 제안하고자 한다. 또 모의실험을 통해 비이상적인 대역제한 필터를 사용하는 수신기의 성능을 비교함으로써 제안한 방식의 타당성을 보인다.

• 정보처리학회논문지C
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• 제12C권3호
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• pp.323-330
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• 2005

버퍼 오버플로우 공격은 가장 흔하고 위협적인 취약점 중의 하나이다. 최근 이러한 버퍼 오버플로우 공격을 막기 위하여 많은 연구가 이루어지고 있으나 실행시 발생하는 오버헤드 때문에 이를 적용하는 문제가 있다. 본 논문은 이진코드 형태의 파일에서 사용자 정의 함수를 변환하여 리턴 주소의 복사본을 스택의 특정 구역에 저장하고 공격 위험이 있는 문자열 함수를 재작성하고, 재작성된 함수 종료시 리턴 주소와 복사된 리턴 주소의 비교와 ebp 레지스터 값의 비교를 통해 오버플로우 공격을 탐지하는 방법을 제안한다.

• 로봇학회논문지
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• 제1권1호
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• pp.81-88
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• 2006

Control of a robot manipulator in contact with the environment is usually conducted by the direct feedback control using a force-torque sensor or the indirect impedance control. In these methods, however, the control algorithms become complicated and the performance of position and force control cannot be improved because of the mechanical properties of the passive components. To cope with such problems, redundant actuation has been used to enhance the performance of position control and force control. In this research, a Double Actuator Unit (DAU) is proposed, with which the force control algorithm can be simplified and can make the robot ensure the safety during the external collision. The DAU is composed of two actuators; one controls the position and the other modulates the joint stiffness. Using this unit, it is possible to independently control the position and stiffness. The DAU based on the planetary gears is investigated in this paper. Performance using the DAU is also verified by various experiments. It is shown that the manipulator using this mechanism provides better safety during the impact with the environment by reducing the joint stiffness appropriately on detecting the collision of a manipulator.

• 로봇학회논문지
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• 제12권1호
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• pp.42-54
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• 2017

Using an inverse of the geometric Jacobian matrix is one of the most popular ways to control robot manipulators, because the Jacobian matrix contains the relationship between joint space velocities and operational space velocities. However, the control algorithm based on Jacobian matrix has algorithmic singularities: The robot manipulator becomes unstable when the Jacobian matrix loses rank. To solve this problem, various methods such as damped and filtered inverse have been proposed, but comparative studies to evaluate the performance of these algorithms are insufficient. Thus, this paper deals with a comparative analysis of six representative singularity avoidance algorithms: Damped Pseudo Inverse, Error Damped Pseudo Inverse, Scaled Jacobian Transpose, Selectively Damped Inverse, Filtered Inverse, and Task Transition Method. Especially, these algorithms are verified through computer simulations with a virtual model of a humanoid robot, THORMANG, in order to evaluate tracking error, computational time, and multiple task performance. With the experimental results, this paper contains a deep discussion about the effectiveness and limitations of each algorithm.

• Molecules and Cells
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• 제37권1호
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• pp.36-42
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• 2014

The tomato (Solanum lycopersicum L.) is a model plant for genome research in Solanaceae, as well as for studying crop breeding. Genome-wide single nucleotide polymorphisms (SNPs) are a valuable resource in genetic research and breeding. However, to do discovery of genome-wide SNPs, most methods require expensive high-depth sequencing. Here, we describe a method for SNP calling using a modified version of SAMtools that improved its sensitivity. We analyzed 90 Gb of raw sequence data from next-generation sequencing of two resequencing and seven transcriptome data sets from several tomato accessions. Our study identified 4,812,432 non-redundant SNPs. Moreover, the workflow of SNP calling was improved by aligning the reference genome with its own raw data. Using this approach, 131,785 SNPs were discovered from transcriptome data of seven accessions. In addition, 4,680,647 SNPs were identified from the genome of S. pimpinellifolium, which are 60 times more than 71,637 of the PI212816 transcriptome. SNP distribution was compared between the whole genome and transcriptome of S. pimpinellifolium. Moreover, we surveyed the location of SNPs within genic and intergenic regions. Our results indicated that the sufficient genome-wide SNP markers and very sensitive SNP calling method allow for application of marker assisted breeding and genome-wide association studies.

• 지능정보연구
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• 제6권2호
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• pp.63-76
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• 2000

Research on group decisions and electroinc meeting systems have been increasing rapidly according to the widespread of Internet technology. Although various issues have been raised in empirical research, we will try to solve an issue on idea categorizing in the group decision making process of elecronic meeting systems. Idea categorizing used at existing group decision support systems was performed in a top-down procedure and mostly participants\` by manual work. This resulted in tacking as long in idea categorizing as it does for idea generating, clustering an idea in multiple categories, and identifying almost similar redundant categories. However such methods have critical limitation in the electronic meeting systems, we suggest an intelligent idea categorizing methodology which is a bottom-up approach. This method consists of steps to present idea using keywords, identifying keywords\` affinity, computing similarity among ideas, and clustering ideas. This methodology allows participants to interact iteratively for clear manifestation of ambiguous ideas. We also developed a prototype system, IIC (intelligent idea categorizer) and evaluated its performance using the comparision experimetn with other systems. IIC is not a general purposed system, but it produces a good result in a given specific domain.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.83-93
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• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1448-1463
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• 2021

With the continuous development of cloud storage, plenty of redundant data exists in cloud storage, especially multimedia data such as images and videos. Data deduplication is a data reduction technology that significantly reduces storage requirements and increases bandwidth efficiency. To ensure data security, users typically encrypt data before uploading it. However, there is a contradiction between data encryption and deduplication. Existing deduplication methods for regular files cannot be applied to image deduplication because images need to be detected based on visual content. In this paper, we propose a secure image deduplication scheme based on hashing and clustering, which combines a novel perceptual hash algorithm based on Local Binary Pattern. In this scheme, the hash value of the image is used as the fingerprint to perform deduplication, and the image is transmitted in an encrypted form. Images are clustered to reduce the time complexity of deduplication. The proposed scheme can ensure the security of images and improve deduplication accuracy. The comparison with other image deduplication schemes demonstrates that our scheme has somewhat better performance.