• Title/Summary/Keyword: Z-network

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A Study of Hierarchical Policy Model of Policy-based Integrated Security Management for managing Heterogeneous Security Systems (이종의 보안시스템 관리를 위한 정책 기반의 통합보안관리시스템의 계층적 정책모델에 관한 연구)

  • Lee, Dong-Yeong;Kim, Dong-Su;Jeong, Tae-Myeong
    • The KIPS Transactions:PartC
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    • v.8C no.5
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    • pp.607-614
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    • 2001
  • With a remarkable growth and expansion of Internet, the security issues emerged from intrusions and attacks such as computer viruses, denial of services and hackings to destroy information have been considered as serious threats for Internet and the private networks. To protect networks from those attacks, many vendors have developed various security systems such as firewalls, intrusion detection systems, and access control systems. However, managing those systems individually requires too much work and high cost. Thus, in order to manage integrated security management and establish consistent security management for various security products, the policy model of PN-ISMS (Policy Based Integrated Security Management System) has become very important. In this paper, present the hierarchical policy model which explore the refinement of high-level/conceptual policies into a number of more specific policies to form a policy hierarchy. A formal method of policy description was used as the basis of the mode in order to achieve precision and generality. Z-Notation was chosen for this propose. The Z-Notation is mathematical notation for expressing and communicating the specifications of computer programs. Z uses conventional notations of logic and set theory organized into expressions called schemas.

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An Experimental Performance Evaluation with Xenomai for WSN (WSN을 위한 Xenomai의 실험적 성능평가)

  • Son, Tae-Yeong;Rim, Seong-Rak
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.1
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    • pp.709-714
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    • 2017
  • Structures like bridges or buildings need to be checked continuously to diagnose their safety. However, it is extremely difficult for the people who access such structures to check all areas directly. To overcome this problem, there is a lot of active research into structural health monitoring (SHM) with wireless sensor nodes (WSNs). In this paper, for more accurate checking of SHM with WSNs, we experimentally compare and evaluate the performance of Xenomai, which provides real-time processing under the traditional Linux kernel. For this purpose, we patch Xenomai into the traditional Linux kernel of a commercial embedded board, Raspberry Pi, and implement a task that periodically reads vibration data of the z-axis from an accelerometer in order to analyze the natural frequency of cantilever beams. Reading the data from the traditional Linux kernel with the same method, we analyze the natural frequency of the cantilever beams using Smart Office Analyzer. Finally, to review the validity of Xenomai for WSNs, we obtain vibration data on the z-axis from the accelerometer via wired network and compared and analyzed them the same way.

Semantic Segmentation of Drone Imagery Using Deep Learning for Seagrass Habitat Monitoring (잘피 서식지 모니터링을 위한 딥러닝 기반의 드론 영상 의미론적 분할)

  • Jeon, Eui-Ik;Kim, Seong-Hak;Kim, Byoung-Sub;Park, Kyung-Hyun;Choi, Ock-In
    • Korean Journal of Remote Sensing
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    • v.36 no.2_1
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    • pp.199-215
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    • 2020
  • A seagrass that is marine vascular plants plays an important role in the marine ecosystem, so periodic monitoring ofseagrass habitatsis being performed. Recently, the use of dronesthat can easily acquire very high-resolution imagery is increasing to efficiently monitor seagrass habitats. And deep learning based on a convolutional neural network has shown excellent performance in semantic segmentation. So, studies applied to deep learning models have been actively conducted in remote sensing. However, the segmentation accuracy was different due to the hyperparameter, various deep learning models and imagery. And the normalization of the image and the tile and batch size are also not standardized. So,seagrass habitats were segmented from drone-borne imagery using a deep learning that shows excellent performance in this study. And it compared and analyzed the results focused on normalization and tile size. For comparison of the results according to the normalization, tile and batch size, a grayscale image and grayscale imagery converted to Z-score and Min-Max normalization methods were used. And the tile size isincreased at a specific interval while the batch size is allowed the memory size to be used as much as possible. As a result, IoU was 0.26 ~ 0.4 higher than that of Z-score normalized imagery than other imagery. Also, it wasfound that the difference to 0.09 depending on the tile and batch size. The results were different according to the normalization, tile and batch. Therefore, this experiment found that these factors should have a suitable decision process.

Analysis of Roadkill Hotspot According to the Spatial Clustering Methods (공간 군집지역 탐색방법에 따른 로드킬 다발구간 분석)

  • Song, Euigeun;Seo, Hyunjin;Kim, Kyungmin;Woo, Donggul;Park, Taejin;Choi, Taeyoung
    • Journal of Environmental Impact Assessment
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    • v.28 no.6
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    • pp.580-591
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    • 2019
  • This study analyzed roadkill hotspots in Yeongju, Mungyeong-si Andong-si and Cheongsong-gun to compare the method of searching the area of the spatial cluster for selecting the roadkill hotspots. The local spatial autocorrelation index Getis-Ord Gi* statistics were calculated by different units of analysis, drawing hotspot areas of 9% from 300 m and 14% from 1 km on the basis of the total road area. The rating of Z-score in the 1km hotspot area showed the highest Z-score in the 28th National Road section on the border between Yecheon-gun and Yeongj-si. The kernel density method performed general kernel density estimation and network kernel density estimation analysis, both of which made it easier to visualize roadkill hotspots than district unit analysis, but there were limitations that it was difficult to determine statistically significant priority. As a result, local hotspot areas were found to be different according to the cluster analysis method, and areas that are in common need of reduction measures were found to be the hotspot of 28th National Road through Yeongju-si and Yecheon-gun. It is deemed that the results of this study can be used as basic data when identifying roadkill hotspots and establishing measures to reduce roadkill.

Discovering the Anti-cancer Effects of Ligusticum Chuanxiong through Network-based Pharmacology Analysis and Molecular Docking: An Inquiry into Natural Products (네트워크 기반 약리학 분석 및 분자 도킹을 통한 천궁의 항암 효과 예측: 천연물에 대한 탐구)

  • Do Kyung Han;Jee Won Shon;Eui Suk Sung;Youn Sook Kim;Won G. An
    • Journal of Life Science
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    • v.33 no.11
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    • pp.876-886
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    • 2023
  • In some cases of head and neck cancers (HNC), surgical interventions may result in the loss of organs and/or changes to their functions, thereby significantly affecting the patient's quality of life. As a result, the surgical treatment of HNC patients is often limited to specific cases, and alternative treatment modalities, such as chemotherapy, are considered. However, serious adverse effects caused by chemotherapy, such as severe nausea and vomiting, necessitate the need for the development of adjunctive methods to minimize patient suffering. Chuanxiong, Ligusticum chuanxiong (L. chuanxiong), is a natural herb used in Eastern medicine to treat cerebrovascular disorders and headaches. This study aimed to predict the effect and potential of L. chuanxiong as an auxiliary anticancer drug through network-based pharmacology and molecular docking analysis. The study results showed that 40 out of 41 genes of L. chuanxiong shared common targets of HNC and their proteins could be used to target HNC cells to prevent cancer progression. The results of the functional enrichment analysis confirmed that L. chuanxiong is associated with the neuroactive-ligand metabolism and neurotransmitter pathways, indicating its potential medicinal value as an adjuvant in HNC treatment. Lastly, our findings demonstrated that the active ingredient of L. chuanxiong, (Z)-Ligustilide, has the ATP binding site of heat shock protein 90, a protein known to promote the activation of cancer cells. These results suggest that L. chuanxiong is a promising candidate for developing auxiliary anticancer drugs, and further research could potentially lead to the discovery of newer and safer anti-cancer agents.

Identification of novel potential drugs and miRNAs biomarkers in lung cancer based on gene co-expression network analysis

  • Sara Hajipour;Sayed Mostafa Hosseini;Shiva Irani;Mahmood Tavallaie
    • Genomics & Informatics
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    • v.21 no.3
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    • pp.38.1-38.8
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    • 2023
  • Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Zsummary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

An MPEG-4 Compliant Interactive Multimedia Streaming Platform Using Overlay Networks

  • Kim, Hyun-Cheol;Patrikakis, Charalampos Z.;Minogiannis, Nikos;Karamolegkos, Pantelis N.;Lambiris, Alex;Kim, Kyu-Heon
    • ETRI Journal
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    • v.28 no.4
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    • pp.411-424
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    • 2006
  • This paper presents a multimedia streaming platform for efficiently transmitting MPEG-4 content over IP networks. The platform includes an MPEG-4 compliant streaming server and client, supporting object-based representation of multimedia scenes, interactivity, and advanced encoding profiles defined by the ISO standard. For scalability purposes, we employ an application-layer multicast scheme for media transmission using overlay networks. The overlay network, governed by the central entity of the network distribution manager, is dynamically deployed according to a set of pre-defined criteria. The overlay network supports both broadcast delivery and video-on-demand content. The multimedia streaming platform is standards-compliant and utilizes widespread multimedia protocols such as MPEG-4, real-time transport protocol, real-time transport control protocol, and real-time streaming protocol. The design of the overlay network was architected with the goal of transparency to both the streaming server and the client. As a result, many commercial implementations that use industry-standard protocols can be plugged into the architecture relatively painlessly and can enjoy the benefits of the platform.

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S-Domain Equivalent System for Electromagnetic Transient Studies PART I : Frequency Dependent Network Equivalent (전자기 과도현상 해석을 위한 S 영역 등가시스템 PART I : 주파수 의존 시스템 등가)

  • 왕용필
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.52 no.11
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    • pp.632-638
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    • 2003
  • Modern power systems are very complex and to model them completely is impractical for electromagnetic transient studies. Therefore areas outside the immediate area of interest must be represented by some form of frequency dependent equivalent. The s-domain rational function form of frequency dependent equivalent does not need refitting if the simulation time-step is changed in the electromagnetic transient program. This is because the s-domain rational function coefficients are independent of the simulation time-step, unlike the z-domain rational function coefficients. S-domain rational function fitting techniques for representing frequency dependent equivalents have been developed using Least Squares Fitting(LSF). However it does not suffer the implementation error that exited in this work as it ignored the instantaneous term. This paper Presents the formulation for developing 1 Port Frequency Dependent Network Equivalent(FDNE) with the instantaneous term in S-domain and illustrates its use. This 1 port FDNE have been applied to the CIGRE Benchmark Rectifier test AC system. The electromagnetic transient package PSCAD/EMTDC is used to assess the transient response of the 1 port (FDNE) developed with Thevenin and Norton Equivalent network. The study results have indicated the robustness and accuracy of 1 port FDNE for electromagnetic transient studies.

Method for Adjusting Single Matching Network for High-Power Transfer Efficiency of Wireless Power Transfer System

  • Seo, Dong-Wook;Lee, Jae-Ho;Lee, Hyungsoo
    • ETRI Journal
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    • v.38 no.5
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    • pp.962-971
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    • 2016
  • A wireless power transfer (WPT) system is generally designed with the optimum source and load impedance in order to achieve the maximum power transfer efficiency (PTE) at a specific coupling coefficient. Empirically or intuitively, however, it is well known that a high PTE can be attained by adjusting either the source or load impedance. In this paper, we estimate the maximum achievable PTE of WPT systems with the given load impedance, and propose the condition of source impedance for the maximum PTE. This condition can be reciprocally applied to the load impedance of a WPT system with the given source impedance. First, we review the transducer power gain of a two-port network as the PTE of the WPT system. Next, we derive two candidate conditions, the critical coupling and the optimum conditions, from the transducer power gain. Finally, we compare the two conditions carefully, and the results therefore indicate that the optimum condition is more suitable for a highly efficient WPT system with a given load impedance.

A Compensation Control Method Using Neural Network for Mechanical Deflection Error in SCARA Robot with Random Payload

  • Lee, Jong Shin
    • Journal of the Korean Society of Mechanical Technology
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    • v.13 no.3
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    • pp.7-16
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    • 2011
  • This study proposes the compensation method for the mechanical deflection error of a SCARA robot. While most studies on the related subject have dealt with the development of a control algorithm for improvement of robot accuracy, this study presents the control method reflecting the mechanical deflection error which is predicted in advance. The deflection at the end of the gripper of SCARA robot is caused by the self-weights and payloads of Arm 1, Arm 2 and quill. If the deflection is constant even though robot's posture and payload vary, there may not be a big problem on robot accuracy because repetitive accuracy, that is relative accuracy, is more important than absolute accuracy in robot. The deflection in the end of the gripper varies as robot's posture and payload change. That's why the moments $M_x$, $M_y$ and $M_z$ working on every joint of a robot vary with robot's posture and payload size. This study suggests the compensation method which predicts the deflection in advance with the variations in robot's posture and payload using neural network. To do this, I chose the posture of robot and the payloads at random, found the deflections by the FEM analysis, and then on the basis of this data, made compensation possible by predicting deflections in advance successively with the variations in robot's posture and payload through neural network learning.