• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.2
• /
• pp.333-342
• /
• 2022

Cellular Automata (CA) is a discrete and abstract computational model that is being applied in various fields. Applicable as an excellent pseudo-random sequence generator, CA has recently developed into a basic element of cryptographic systems. Several studies on CA-based stream ciphers have been conducted and it has been observed that the encryption strength increases when the radius of a CA's neighbor is increased when appropriate CA rules are used. In this paper, among CAs that can be applied as a one-dimensional pseudo-random number sequence generator (PRNG), one-dimensional 5-neighbor CAs are classified according to the connection state of their neighbors, and the ignition relationship of the characteristic polynomial is obtained. Also this paper propose a synthesis algorithm for an asymmetric 1-D linear 5-neighbor MLCA in which the radius of the neighbor is increased by 2 using the one-dimensional 3-neighbor 90/150 CA state transition matrix.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.2
• /
• pp.357-364
• /
• 2022

A pseudo-random number generator (PRNG) is a program used when a large amount of random numbers is needed. It is used to generate symmetric keys in symmetric key cryptography systems, generate public key pairs in public key cryptography or digital signatures, and generate columns used for padding with disposable pads. Cellular Automata (CA), which is useful for specific representing nonlinear dynamics in various scientific fields, is a discrete and abstract computational system that can be implemented in hardware and is applied as a PRNG that generates keys in cryptographic systems. In this paper, I propose an algorithm for synthesizing a programmable 5-neighbor CA based PRNG that can effectively generate a nonlinear sequence using 5-neighbor CA with the radius of the neighboring cell increased by 2.

• Journal of KIISE:Information Networking
• /
• v.30 no.5
• /
• pp.631-640
• /
• 2003

Because of multi-hop wireless communication, P2P applications in ad hoc networks suffer poor performance. We Propose neighbor caching strategy to overcome this shortcoming and show it is more efficient than self caching that nodes store data in theirs own cache individually. A node can extend its caching storage instantaneously with neighbor caching by borrowing the storage from idle neighbors, so overcome multi-hop wireless communications with data source long distance away from itself. We also present the ranking based prediction that selects the most appropriate neighbor which data can be stored in. The node that uses the ranking based prediction can select the neighbor that has high possibility to keep data for a long time and avoid caching the low ranked data. Therefore the ranking based prediction improves the throughput of neighbor caching. In the simulation results, we observe that neighbor caching has better performance, as large as network size, as long as idle time, and as small as cache size. We also show the ranking based prediction is an adaptive algorithm that adjusts times of data movement into the neighbor, so makes neighbor caching flexible according to the idleness of nodes

• Journal of Multimedia Information System
• /
• v.5 no.2
• /
• pp.67-78
• /
• 2018

This article proposes the modified KNN (K Nearest Neighbor) algorithm which considers the feature similarity and is applied to the word categorization. The texts which are given as features for encoding words into numerical vectors are semantic related entities, rather than independent ones, and the synergy effect between the word categorization and the text categorization is expected by combining both of them with each other. In this research, we define the similarity metric between two vectors, including the feature similarity, modify the KNN algorithm by replacing the exiting similarity metric by the proposed one, and apply it to the word categorization. The proposed KNN is empirically validated as the better approach in categorizing words in news articles and opinions. The significance of this research is to improve the classification performance by utilizing the feature similarities.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.5
• /
• pp.2398-2415
• /
• 2017

Content-Centric Networking (CCN) is a new Internet architecture with routing and caching centered on contents. Through its receiver-driven and connectionless communication model, CCN natively supports the seamless mobility of nodes and scalable content acquisition. In-network caching is one of the core technologies in CCN, and the research of efficient caching scheme becomes increasingly attractive. To address the problem of unbalanced cache load distribution in some existing caching strategies, this paper presents a neighbor cooperation based in-network caching scheme. In this scheme, the node with the highest betweenness centrality in the content delivery path is selected as the central caching node and the area of its ego network is selected as the caching area. When the caching node has no sufficient resource, part of its cached contents will be picked out and transferred to the appropriate neighbor by comprehensively considering the factors, such as available node cache, cache replacement rate and link stability between nodes. Simulation results show that our scheme can effectively enhance the utilization of cache resources and improve cache hit rate and average access cost.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.8
• /
• pp.2587-2605
• /
• 2022

In order to efficiently detect community structure in complex networks, community detection algorithms can be designed from the perspective of node similarity. However, the appropriate parameters should be chosen to achieve community division, furthermore, these existing algorithms based on the similarity of common neighbors have low discrimination between node pairs. To solve the above problems, a noval community detection algorithm using closeness similarity based on common neighbor node clustering entropy is proposed, shorted as CSCDA. Firstly, to improve detection accuracy, common neighbors and clustering coefficient are combined in the form of entropy, then a new closeness similarity measure is proposed. Through the designed similarity measure, the closeness similar node set of each node can be further accurately identified. Secondly, to reduce the randomness of the community detection result, based on the closeness similar node set, the node leadership is used to determine the most closeness similar first-order neighbor node for merging to create the initial communities. Thirdly, for the difficult problem of parameter selection in existing algorithms, the merging of two levels is used to iteratively detect the final communities with the idea of modularity optimization. Finally, experiments show that the normalized mutual information values are increased by an average of 8.06% and 5.94% on two scales of synthetic networks and real-world networks with real communities, and modularity is increased by an average of 0.80% on the real-world networks without real communities.

• Journal of the Korea Computer Industry Society
• /
• v.5 no.9
• /
• pp.1025-1030
• /
• 2004

In multimedia database systems, the k nearest neighbor query occurs frerluently and requires the processing cost higher than other spatial queries do. The numberof searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the k nearest neighbor query. In this paper, we propose the search distance which can reduce the computation time of the optimal search distance.

• Korean Journal of Clinical Laboratory Science
• /
• v.39 no.2
• /
• pp.91-95
• /
• 2007

The number of children patients with tinea pedis and onychomycosis diagnosed on clinical findings and culture at the Catholic Dermatological Clinic in Daegu City were 144,446 for 2 years from January 2005 to December 2006. 120 children were suspected of having clinical onychomycosis or tinea pedis. KOH smears and cultures on the Potato corn meal dextrose agars (PDCA) were done for the suspected toe webs, nails and uninvolved neighbor toe webs. Socks were dusted and cultured to check contamination of clothes. Family infections were checked by questionnaire. The incidence was 92 (0.06%) out of 144,446 outpatients in tinea pedis, 28 (0.02%) in onychomycosis. Trichophyton(T.) rubrums were isolated from all of the 7 cases of onychomycosis. T. mentagrophytes was isolated from 5 cases of the tinea pedis patients and T. rubrum was isolated from 50 (92.5%) cases of the tinea pedis. The right side was predominant for onychomycosis of both toe nails (23 of 25) and finger nails (3 of 3). No fungal elements were detected from normal looking neighbor toe webs by KOH examinations. However, culture on PDCA agars showed T. rubrum isolates from 3 toe webs. 7 showed positive cultures from the socks. From the questionnaire, 94 had family infections.

• Korean Journal of Remote Sensing
• /
• v.30 no.5
• /
• pp.651-664
• /
• 2014

Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

• The Bulletin of The Korean Astronomical Society
• /
• v.35 no.1
• /
• pp.75.2-75.2
• /
• 2010

We investigate the dependence of occurrence of bar in galaxies on galaxy properties and environment. The environmental conditions considered include the large-scale background density and distance to the nearest neighbor galaxy. We use a volume-limited sample of 33,296 galaxies brighter than $M_r$=-19.5+5logh at $0.02{\leqq}z{\leqq}0.05489$, drawn from the Sloan Digital Sky Survey Data Release 7. We classify the galaxies into early and late types, and identify bars by visual inspection. We find that the fraction of barred galaxies ($f_{bar}$) is 18.2% on average in the case of late-type galaxies, and depends on both u-r color and central velocity dispersion $(\sigma);f_{bar}$ is a monotonically increasing function of u-r color, and has a maximum value at intermediate velocity dispersion (${\sigma}{\simeq}170km\;s^{-1}$). This trend suggests that bars are dominantly hosted by systems having intermediate-mass with no recent interaction or merger history. We also find that $f_{bar}$ does not directly depend on the large-scale background density as its dependence disappears when other physical parameters are fixed. We discover the bar fraction decreases as the separation to the nearest neighbor galaxy becomes smaller than 0.1 times the virial radius of the neighbor regardless of neighbor's morphology. These results imply that it is difficult for bars to be maintained during strong tidal interactions, and that the source for this phenomenon is gravitational and not hydrodynamical.