• Title/Summary/Keyword: distance between nodes

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Analysis of Spatial Variability for Infiltration Rate of Field Soil -I. Variogram (토양(土壤)중 물의 침투속도(浸透速度)의 공간변이성(空間變異性) 분석(分析) -I. Variogram)

  • Park, Chang-Seo;Kim, Jai-Joung;Cho, Seong-Jin
    • Korean Journal of Soil Science and Fertilizer
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    • v.16 no.4
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    • pp.305-310
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    • 1983
  • Spatial variability of infiltration rates of 96 samples from Hwadong SiCL was studied by using geostatistical concepts. The measurement was made at the nodes of the regular grid consisting of 12 rows and 8 columns. Sample spacing within rows and columns was 3 and 2 meters, respectively. This study illustrated the use of variogram as a tool to identify the degree of dependency of the infiltration rate on the distance between pairs of measurements and how to take advantage of this dependency. Fractile diagram showed that the distribution of observation was approximately normal. The range of the variogram was about 7.4 meters. The minimum number of samples necessary to reproduce the results similar to the 96 measured values was 8 to 10. Coefficients of theoretical variogram function for computing kriged values and kriged varionces of nuogget effect, slope, and range were 0.444 cm/day, 0.003 cm/day, and 7.4 m, respectively.

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Protocol implementation for simultaneous signal continuation acquisition of industrial plant machine condition in wireless sensor networks (산업플랜트 기계상태 동시신호 연속취득을 위한 무선센서 네트워크프로토콜 구현)

  • Lee, Hoo-Rock;Chung, Kyung-Yul;Rhyu, Keel-Soo
    • Journal of Advanced Marine Engineering and Technology
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    • v.39 no.7
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    • pp.760-764
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    • 2015
  • Wireless sensors, installed on machinery, and Time Division Multiple Access (TDMA) transmission make an ideal system for monitoring machine conditions in industrial plants because there is no need for electronic wiring. However, there has not yet been a successful field application of such a system, capable of continuously transmitting data at sample rates greater than 100 Hz. In this research, a TDMA network protocol capable of acquiring data from multiple sensors at sample rates greater than 100 Hz was developed for field application. The protocol was implemented in a single cluster-star topology network, and the system was evaluated based on the node number and transmission distance. Network simulator 2 (ns-2) was used for a real field simulation. Non-TDMA and TDMA protocol cases were compared using four sensor nodes. In the cases of 20-s and 40-s transmission times, there was little difference between the reception rates of the non-TDMA and TDMA systems. However, the difference was much greater when using a 60-s transmission time.

A Study on the Analysis Effect Factors of Illegal Parking Using Data Mining Techniques (데이터마이닝 기법을 활용한 불법주차 영향요인 분석)

  • Lee, Chang-Hee;Kim, Myung-Soo;Seo, So-Min
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.13 no.4
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    • pp.63-72
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    • 2014
  • With the rapid development in the economy and other fields as well, the standard of living in South Korea has been improved, and consequently, the demand of automobiles has quickly increased. It leads to various traffic issues such as traffic congestion, traffic accident, and parking problem. In particular, this illegal parking caused by the increase in the number of automobiles has been considered one of the main reasons to bring about traffic congestion as intensifying any dispute between neighbors in relation to a parking space, which has been also coming to the fore as a social issue. Therefore, this study looked into Daejeon Metropolitan City, the city that is understood to have the highest automobile sharing rate in South Korea but with relatively few cases of illegal parking crackdowns. In order to investigate the theoretical problems of the illegal parking, this study conducted a decision-making tree model-based Exhaustive CHAID analysis to figure out not only what makes drivers park illegally when they try to park vehicles but also those factors that would tempt the drivers into the illegal parking. The study, then, comes up with solutions to the problem. According to the analysis, in terms of the influential factors that encourage the drivers to park at some illegal areas, it was learned that these factors, the distance, a driver's experience of getting caught, the occupation and the use time in order, have an effect on the drivers' deciding to park illegally. After working on the prediction model, four nodes were finally extracted. Given the analysis result, as a solution to the illegal parking, it is necessary to establish public parking lots additionally and first secure the parking space for the vehicles used for living and working, and to activate the campaign for enhancing illegal parking crackdown and encouraging civic consciousness.

Category-based Feature Inference in Causal Chain (인과적 사슬구조에서의 범주기반 속성추론)

  • Choi, InBeom;Li, Hyung-Chul O.;Kim, ShinWoo
    • Science of Emotion and Sensibility
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    • v.24 no.1
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    • pp.59-72
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    • 2021
  • Concepts and categories offer the basis for inference pertaining to unobserved features. Prior research on category-based induction that used blank properties has suggested that similarity between categories and features explains feature inference (Rips, 1975; Osherson et al., 1990). However, it was shown by later research that prior knowledge had a large influence on category-based inference and cases were reported where similarity effects completely disappeared. Thus, this study tested category-based feature inference when features are connected in a causal chain and proposed a feature inference model that predicts participants' inference ratings. Each participant learned a category with four features connected in a causal chain and then performed feature inference tasks for an unobserved feature in various exemplars of the category. The results revealed nonindependence, that is, the features not only linked directly to the target feature but also to those screened-off by other feature nodes and affected feature inference (a violation of the causal Markov condition). Feature inference model of causal model theory (Sloman, 2005) explained nonindependence by predicting the effects of directly linked features and indirectly related features. Indirect features equally affected participants' inference regardless of causal distance, and the model predicted smaller effects regarding causally distant features.

Control Method for the Number of Travel Hops for the ACK Packets in Selective Forwarding Detection Scheme (선택적 전달 공격 탐지기법에서의 인증 메시지 전달 홉 수 제어기법)

  • Lee, Sang-Jin;Kim, Jong-Hyun;Cho, Tae-Ho
    • Journal of the Korea Society for Simulation
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    • v.19 no.2
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    • pp.73-80
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    • 2010
  • A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.

Growth Characteristics of Small and Medium Type Watermelon According to Number of Stem Training and Position of Fruit Setting in the Winter Season (겨울철 줄기유인 수 및 착과 위치에 따른 중·소과종 수박의 생육 특성)

  • Kim, So-Hui;Choi, Gyeong-Lee;Choi, Su-Hyun;Lim, Mi-Young;Jeong, Ho-Jeong
    • Journal of Bio-Environment Control
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    • v.29 no.2
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    • pp.189-195
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    • 2020
  • This research was carried out to find the proper number of stem training and position of fruit setting that can be stably produced for the cultivation in small and medium types of watermelon during winter. The treatments for the number of stem training were 2-, 3-, 4-stems, respectively. Growth characteristics (plant height, stem diameter, no. of node, etc.) by number of stem training were higher in 2-stem than in 3-4-stem. However, Fruit characteristics such as weight, length, width were high in the 4-stem. There is no significant difference between the soluble solids and fruit setting rate depending on the stem training. The position of fruit setting were three points: 2nd, 3rd, 4th female flower positions. The fruit setting is one fruit per plant. The average fruit setting nodes of 2nd, 3rd and 4th female flowers were 11.5, 15.8 and 23.1 nodes, respectively. The 4th female flower was 0.8 kg heavier than 2nd female flower because of its increased weight as position of fruit setting was higher. However, the soluble solids decreased as the position of fruit setting increased, with the second female flower being 1.3°Bx higher than the 4th female flower. The Fruit setting rate was no significant difference. Considering the growth and fruit characteristics, it is believed that the small and medium-sized watermelon in winter will have a high quality production of watermelon when the stem training is 3-stem and the position of fruit setting is 3rd female flower. However, it is thought that additional studies are needed to stabilize the income of watermelon-growing farms, such as planting distance and adhesion of small and medium-sized varieties.

Local Shape Analysis of the Hippocampus using Hierarchical Level-of-Detail Representations (계층적 Level-of-Detail 표현을 이용한 해마의 국부적인 형상 분석)

  • Kim Jeong-Sik;Choi Soo-Mi;Choi Yoo-Ju;Kim Myoung-Hee
    • The KIPS Transactions:PartA
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    • v.11A no.7 s.91
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    • pp.555-562
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    • 2004
  • Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.