• Title/Summary/Keyword: Internal Network Information

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A Study on Relay Server Topology inside NAT for Pure P2P (순수 P2P를 위한 NAT 내부의 Relay Server 토폴로지에 관한 연구)

  • Shon, Hyung-Doh;Kang, Seung-Chan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.3
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    • pp.575-580
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    • 2008
  • Lately, the use of the NAT has become unavoidable with the increase of P2P traffic along with the exhaustion of IPv4 IP address. Due to NAT properties, NAT's internal host can only be connected through a relay method using the outside server. Accordingly, there is a lot of resource exhaustion of the relay server on the NAT exterior and network traffic increases. This essay proposes a topology that can form sessions to the NAT interior from the NAT exterior and that will decrease network traffic by placing NAT exterior relay servers in the NAT interior.

Directions of the Activation of the Development of a Small Innovative Enterprise

  • Antypenko, Nadiia;Dongcheng, Wang;Lysenko, Zhanna;Krasnonosova, Olena;Grynevych, Liudmyla
    • International Journal of Computer Science & Network Security
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    • v.21 no.12spc
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    • pp.495-502
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    • 2021
  • The study is devoted to substantiation of directions of intensification of development of small innovative enterprise, which has a significant impact on the overall innovation activity of the country and promotes innovative development, transition to more advanced technological systems. The outlined role of small business in innovative development in the direction of intensifying innovation in the economy, improving organization and production, as well as in the form of direct participation in the innovation process, production of science-intensive products, stimulating demand for innovation. A group of factors hindering the development of small innovative entrepreneurship was identified, including: financial aspects of the activity, shortcomings of organizational and communicative nature, underdeveloped technology market, information plan problems, internal production problems of small business, market problems. The directions of intensification of the development of small innovative entrepreneurship are substantiated, namely: financial and credit support of small innovative entrepreneurship; introduction of tax incentives; material and technical support; nationwide intensification of innovation activity; information support; development of innovation infrastructure. The involvement of the outlined directions of intensification of small innovative entrepreneurship will help to obtain a synergistic effect of innovative development of both small innovative business structures and the economy as a whole.

Inter-Process Correlation Model based Hybrid Framework for Fault Diagnosis in Wireless Sensor Networks

  • Zafar, Amna;Akbar, Ali Hammad;Akram, Beenish Ayesha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.536-564
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    • 2019
  • Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

Methodological Principles of Didactics Ddevelopment in Educational Activity of Higher Eeducation Institutions

  • Bortniuk, Tetiana;Smyrnova, Tetiana;Tkachenko, Tetiana;Yakymenko, Svitlana;Pushkar, Larysa;Desiatnyk, Kateryna
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.394-398
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    • 2022
  • The article determines that the study of the development of scientific and didactic knowledge about the educational process in higher education should be built mainly on the basis of qualitative research methods that ensure the identification and understanding of the changes taking place in didactic knowledge, in the unity of their internal and external manifestations. On the basis of the epistemological model of the study of science, a generalized model of didactic knowledge about the educational process in higher education, including didactic relations as a theoretical core, subject of research, research methods and positions of researchers, ways of interaction between science and educational practice, and thematic structures of didactic knowledge; scientific and methodological problems of didactic knowledge about the educational process in higher education at the present stage of its developments due to the post-nonclassical transformation and orientation of research towards the humanitarian ideal of scientific character.

New Cellular Neural Networks Template for Image Halftoning based on Bayesian Rough Sets

  • Elsayed Radwan;Basem Y. Alkazemi;Ahmed I. Sharaf
    • International Journal of Computer Science & Network Security
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    • v.23 no.4
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    • pp.85-94
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    • 2023
  • Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

Formation of Legal and Professional Competence of Students of Higher Educational institutions in the Context Of The COVID-19 Pandemic

  • Myroslav Kryshtanovych;Iryna Khomyshyn;Viktor Bardachov;Hryhorii Bukanov;Iryna Andrusiak;Liudmyla Antonova
    • International Journal of Computer Science & Network Security
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    • v.23 no.12
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    • pp.175-180
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    • 2023
  • The main purpose of the study is to identify the key aspects of the formation of legal and professional competence of students of higher educational institutions in the context of the COVID-19 pandemic. The modern system of public relations tightens the requirements for the professional and legal competence of specialists in all spheres of life. The development of a unified nationwide strategy in the field of education focused on the formation and development of young people's skills for life in the information society, is aimed at finding ways to form an active position of a future specialist, developing an experience of a holistic understanding of the professional activity, systemic action in solving new problems and tasks. The methodology includes a number of theoretical methods. Based on the results of the study, the main elements of the formation of legal and professional competence of students of higher educational institutions in the context of the COVID-19 pandemic.

Design and Implementation of parallel Media server in current system environment (기존 시스템 환경에서의 병렬 미디어 서버의 설계 및 구현)

  • 김경훈;류재상;김서균;남지승
    • Proceedings of the IEEK Conference
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    • 2000.06c
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    • pp.97-100
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    • 2000
  • As network resources have become faster and demands for multimedia service through network have increased, the demand for Media server system has increased. These kinds of media server solve their bottle neck problem of internal storage device by using parallel system which takes advantage of fast network resource. Many vendors have suggested each of their media server system to solve these problem radically, but most of them require major modification of infra component and additional drawback has added. For example, storage mechanism for specific media requires new file system which is totally different from traditional one, and algorithm for enhancing performance may not suit for traditional operating system environment. In this paper, we designed a parallel media server based on web interface of traditional system and implemented a program for media server. Implemented server system performs parallel processing through web interface without any modification of traditional system, and controls which is related to merging load by distributed data is charged only to client and control server and consequently load of storage server can be minimized. And also, data transfer protocol for streaming media includes Retransfer algorithm and client Admission control policy relevant to performance of whole system.

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A Neural Net System Self-organizing the Distributed Concepts for Speech Recognition (음성인식을 위한 분산개념을 자율조직하는 신경회로망시스템)

  • Kim, Sung-Suk;Lee, Tai-Ho
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.5
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    • pp.85-91
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    • 1989
  • In this paper, we propose a neural net system for speech recognition, which is composed of two neural networks. Firstly the self-supervised BP(Back Propagation) network generates the distributed concept corresponding to the activity pattern in the hidden units. And then the self-organizing neural network forms a concept map which directly displays the similarity relations between concepts. By doing the above, the difficulty in learning the conventional BP network is solved and the weak side of BP falling into a pattern matcher is gone, while the strong point of generating the various internal representations is used. And we have obtained the concept map which is more orderly than the Kohonen's SOFM. The proposed neural net system needs not any special preprocessing and has a self-learning ability.

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Partial Discharge Pattern Recognition of Cast Resin Current Transformers Using Radial Basis Function Neural Network

  • Chang, Wen-Yeau
    • Journal of Electrical Engineering and Technology
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    • v.9 no.1
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    • pp.293-300
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    • 2014
  • This paper proposes a novel pattern recognition approach based on the radial basis function (RBF) neural network for identifying insulation defects of high-voltage electrical apparatus arising from partial discharge (PD). Pattern recognition of PD is used for identifying defects causing the PD, such as internal discharge, external discharge, corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. Since an insulation defect, such as one resulting from PD, would have a corresponding particular pattern, pattern recognition of PD is significant means to discriminate insulation conditions of high-voltage electrical apparatus. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD pattern recognition of cast resin current transformer (CRCT) models. These tests used artificial defects created in order to produce the common PD activities of CRCTs by using feature vectors of field-test PD patterns. The significant features are extracted by using nonlinear principal component analysis (NLPCA) method. The experimental data are found to be in close agreement with the recognized data. The test results show that the proposed approach is efficient and reliable.

MASS ESTIMATION OF IMPACTING OBJECTS AGAINST A STRUCTURE USING AN ARTIFICIAL NEURAL NETWORK WITHOUT CONSIDERATION OF BACKGROUND NOISE

  • Shin, Sung-Hwan;Park, Jin-Ho;Yoon, Doo-Byung;Choi, Young-Chul
    • Nuclear Engineering and Technology
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    • v.43 no.4
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    • pp.343-354
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    • 2011
  • It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.