• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8A
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• pp.702-711
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• 2011

This paper proposes a HAG(Hidden-Node-Aware Grouping) algorithm for IEEE 802.15.4 networks to enhance the performance by eliminating collisions resulted from the hidden node problem without adopting the RTS/CTS packet exchanges. To solve the hidden node problem, the HAG algorithm organizes nodes into disjoint transmission groups by dynamically allocating hidden nodes into separate groups which take turns in a round robin way for their transmission. For dynamic group adjustment, it periodically evaluates the presence of hidden nodes based on subordinate nodes' receipt reports. To accurately measure its behavior, this paper also builds an analytical model to estimate its throughput fluctuation over various network topologies. The mathematical model along with simulation results confirmed that the HAG technique gracefully degraded the throughput of IEEE 802.15.4 networks whereas the standard IEEE 802.15.4 networks suffer severe throughput fallout as hidden nodes become populated.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.774-780
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• 2009

This paper proposes a transmitted power saving method for underwater acoustic sensors considering the acoustic wave propagation characteristic that propagation loss increases more rapidly in higher frequency band. In the proposed scheme, sensor nodes are divided into a few groups based on the distance between sink node and the sensor node, and each group uses its own frequency band. The node group with longer distance uses lower frequency and the node group with shorter distance uses higher frequency. By means of such a distance-dependent frequency allocation, all sensor nodes are able to maintain a certain target signal-to-noise ratio (SNR), but also save transmitted power. In addition, the optimum size of node group is obtained, and also a frequency allocation algorithm is proposed accordingly. Numerical results show that the proposed scheme saves transmitted power by more 10 dB comparing non-grouping methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2B
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• pp.107-116
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• 2006

In this paper, we propose a Sensing Resolution-based Grouping(SRG) protocol for wireless sensor networks. SRG is intended for meeting the application's sensing objectives, where sensor nodes are densely deployed and have the determinate accuracy requirement. The primary contribution of this paper is active group header node selection and round-robin procedure, which increase the sensing accuracy and evenly distribute the node energy consumption. The second contribution is use of energy efficient intermediate node selection by considering group size and energy consumption. We present the design principle of SRG and provide simulation results.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.81-91
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• 2014

This paper proposes hidden-node aware grouping (HAG) algorithm to enhance the performance of institute of electrical and electronics engineers (IEEE) 802.15.4 networks when they undergo either severe collisions or frequent interferences by hidden nodes. According to the degree of measured collisions and interferences, HAG algorithm dynamically transforms IEEE 802.15.4 protocol between a contention algorithm and a contention-limited one. As a way to reduce the degree of contentions, it organizes nodes into some number of groups and assigns each group an exclusive per-group time slot during which only its member nodes compete to grab the channel. To eliminate harmful disruptions by hidden nodes, especially, it identifies hidden nodes by analyzing the received signal powers that each node reports and then places them into distinct groups. For load balancing, finally it flexibly adapts each per-group time according to the periodic average collision rate of each group. This paper also extends a conventional Markov chain model of IEEE 802.15.4 by including the deferment technique and a traffic source to more accurately evaluate the throughput of HAG algorithm under both saturated and unsaturated environments. This mathematical model and corresponding simulations predict with 6%discrepancy that HAG algorithm can improve the performance of the legacy IEEE 802.15.4 protocol, for example, even by 95% in a network that contains two hidden nodes, resulting in creation of three groups.

• KIISE Transactions on Computing Practices
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• v.23 no.12
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• pp.677-683
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• 2017

Apache Storm is a representative real-time distributed processing system, which is able to process data streams quickly over distributed servers. Storm currently provides several stream grouping methods to distribute data traffic to multiple servers. Among them, the shuffle grouping may cause a processing delay problem and the local-or-shuffle grouping used to solve the problem may cause the problem of concentrating the traffic on a specific node. In this paper, we propose the locality-aware grouping to solve the problems that may arise in the existing Storm grouping methods. Experimental results show that the proposed locality-aware grouping is considerably superior to the existing shuffle grouping and the local-or-shuffle grouping. These results show that the new grouping is an excellent approach considering both the locality and load balancing which are limitations of the existing Storm.

• The Journal of Korean Medicine
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• v.32 no.1
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• pp.56-66
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• 2011

Background: This was a study to analyze Sanghanron through network theory, as the first attempt to construct network models for systems biomedicine in traditional Korean medicine. For this purpose, we investigated the network structure with priority given to two-node connections between symptoms and herbs of Taeyangbyung compilation in Sanghanron. Purpose: We had three goals in carrying out this study. First, to establish the minimum clinical grouping data sets for symptoms and herbs of Taeyangbyung compilation in Sanghanron. Second, to make index files for the obtained data sets. Third, to generate a network structure for systems biomedicine in this part, and analyze its relationship. Methods: Using MS office Excel and Netminer software, we constructed the minimum clinical grouping data sets and the network for systems biomedicine about symptoms and herbs of Taeyangbyung compilation in Sanghanron, and analyzed its relationship. Results: We established the minimum clinical grouping data sets for symptoms and herbs of Taeyangbyung compilation in Sanghanron, using MS Excel. We constructed a network to structurize our database through two-node connections of Netminer program, and analyzed its relationships. Conclusions: Further research on network model for systems biomedicine between symptoms and herbs for three Yang and three Um(Taeyang, Soyang, Yangmyung, Taeum, Soum, Gualum) disease compilation is necessary.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.123-132
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• 1998

The group formation problem of the machine and part is a very important issue in the planning stage of cellular manufacturing systems. This paper investigates Self-Organizing Map(SOM) neural networks approach to machine-part grouping problem. We present a two-phase algorithm based on SOM for grouping parts and machines. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. Output layer in SOM network is one-dimensional structure and the number of output node has been increased sufficiently to spread out the input vectors in the order of similarity. The proposed algorithm performs remarkably well in comparison with many other algorithms for the well-known problems shown in previous papers.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.253-258
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• 2003

We consider the problem of grouping orders into lots. The problem is modelled by a graph G=(V,E), where each node ${\nu}{\in}V$ denotes order specification and its weight ${\omega}(\nu)$ the orders on hand for the specification. We can construct a lot simply from orders of single specification. For a set of nodes (specifications) ${\theta}{\subseteq}V$, if the distance of any two nodes in $\theta$ is at most d, it is also possible to make a lot using orders on the nodes. The objective is to maximize the number of lots with size exactly $\lambda$. In this paper, we prove that our problem is NP-Complete when $d=2,{\lambda}=3$ and each weight is 0 or 1. Moreover, it is also shown to be NP-Complete when $d=1,{\lambda}=3$ and each weight is 1,2 or 3.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.83-89
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• 2016

The group formation problem of the machine and part is a critical issue in the planning stage of cellular manufacturing systems. The machine-part grouping with alternative process plans means to form machine-part groupings in which a part may be processed not only by a specific process but by many alternative processes. For this problem, this study presents an algorithm based on self organizing neural networks, so called SOM (Self Organizing feature Map). The SOM, a special type of neural networks is an intelligent tool for grouping machines and parts in group formation problem of the machine and part. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. In the proposed algorithm, output layer in SOM network had been set as one-dimensional structure and the number of output node has been set sufficiently large in order to spread out the input vectors in the order of similarity. In the first stage of the proposed algorithm, SOM has been applied twice to form an initial machine-process group. In the second stage, grouping efficacy is considered to transform the initial machine-process group into a final machine-process group and a final machine-part group. The proposed algorithm was tested on well-known machine-part grouping problems with alternative process plans. The results of this computational study demonstrate the superiority of the proposed algorithm. The proposed algorithm can be easily applied to the group formation problem compared to other meta-heuristic based algorithms. In addition, it can be used to solve large-scale group formation problems.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.317-320
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• 2002

In this thesis, we designed specific LonWorks nodes for lighting control then implemented the lighting control system through the operating scenarios. Developed lighting controller plays a role of one network node and according to information from other nodes, decides whether it toms on the light or not. In this way the lights can be controlled by using the location information of light in the lighting control node and the grouping information of the lights in the switch node.