• Management Science and Financial Engineering
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• v.13 no.1
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• pp.73-91
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• 2007

We investigate factors that influence the choice of high-share brands(HSBs) vs. low-share brands(LSBs) among various product and consumer characteristics related to brand-share perceptions. Specifically, using 8 product categories varying in terms of purchase decision involvement, we show how the influencing factors vary across the categories. At the general level that cover all the 8 categories, our hierarchical Bayesian regressions analysis shows that factors that favor high-share brands are purchase decision involvement, search goods, experience goods, price-quality relationship, positive network externalities, and price-prestige beliefs. Conversely, consumers who value variety seeking and need for uniqueness favor low-share brands. The effects of these factors, however, vary across product categories. The identification of these characteristics can help brand managers establish a more effective brand-share strategy in such areas as setting an optimal market share goal, extending a brand, and developing ad copy. Furthermore, our consumer segmentation analysis demonstrates the general market has two distinct segments - (1) a segment composed of HSB buyers(86%) and (2) a segment composed of LSB buyers(14%). The two segments are also shown to have different significant factors that explain their brand choice. Our segmentation analysis can help marketers establish a marketing strategy that targets a specific segment of interest.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.852-858
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• 1991

An adaptive hierarchical classifier(AHCL) for Korean character recognition using a neural net is designed. This classifier has two neural nets: USACL (Unsupervised Adaptive Classifier) and SACL (Supervised Adaptive Classifier). USACL has the input layer and the output layer. The input layer and the output layer are fully connected. The nodes in the output layer are generated by the unsupervised and nearest neighbor learning rule during learning. SACL has the input layer, the hidden layer and the output layer. The input layer and the hidden layer arefully connected, and the hidden layer and the output layer are partially connected. The nodes in the SACL are generated by the supervised and nearest neighbor learning rule during learning. USACL has pre-attentive effect, which perform partial search instead of full search during SACL classification to enhance processing speed. The input of USACL and SACL is a directional edge feature with a directional receptive field. In order to test the performance of the AHCL, various multi-font printed Hangul characters are used in learning and testing, and its processing its speed and and classification rate are compared with the conventional LVQ(Learning Vector Quantizer) which has the nearest neighbor learning rule.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.125-135
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• 2010

Recently, the problem of global warming has issued seriously, so Green IT(Information Technology) using RFID/USN is concerned in order to solve environmental problems. In this paper, we implemented that public area like an underground parking lot could reduce unnecessary energy consumption used by lighting control system based on Ubiquitous Sensor Networks. The lighting control system for underground parking lot is comprised of intersection nodes for watching cars enter and leave, and light node for controlling light. It applies the routing protocol based on hierarchical cluster, hierarchical addressing method, and probability filtering method for the specific place like an underground parking lot. The result after experiments shows that the lighting control system could decrease electrical energy consumption to around 61.7%.

• The KIPS Transactions:PartA
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• v.16A no.1
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• pp.1-8
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• 2009

Ubiquitous computing requires an intelligent environment where the users do not need to be involved in the operation. The agent technology allows effective implementation of ubiquitous system, while agent platform provides efficient and stable interaction between the agents. In this paper we propose a hierarchical P2P networking approach where the messages are combined inside the agent platform and then compressed in two levels. The proposed approach capitalizes the static nature of the messages of typical context-aware applications. Experiment with an actual multi-agent system reveals that the response time and throughput are significantly improved compared to the existing scheme.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.719-739
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• 1996

A common control model used to implement computer integrated manufacturing(CIM) is based on the hierarchical decomposition of the shop floor activities, in which supervisory controllers are responsible for all the interactions among subordinates. Although the hierarchical control philosophy provides for easy understanding of complex systems, an emerging manufacturing paradigm, agile manufacturing, requires a new control structure necessary to accommodate the rapid development of a shop floor controller. This is what is called autonomous agent-based heterarchical control. As computing resources and communication network on the shop floor become increasingly intelligent and powerful, the new control architecture is about to come true in a modern CIM system. In this paper, heterarchical control is adopted and investigated, in which a controller for a unit of device performs three main functions - planning, scheduling and execution. Attention is paid to the planning function and all the detailed planning activities for heterarchical shop floor control are identified. Interactions with other functions are also addressed. In general, planning determines tasks to be scheduled in the future. In other words, planning analyzes process plans and transforms process plans into detailed plans adequate for shop floor control. Planning is also responsible for updating a process plan and identifying/resolving replanning activities whether they come from scheduling or execution.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.153-166
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• 2013

A hierarchical time division multiple access (HTDMA) medium access control (MAC) protocol is proposed for clustered mobile underwater acoustic networks. HTDMA consists of two TDMA scheduling protocols (i.e., TDMA1 and TDMA2) in order to accommodate mobile underwater nodes (UNs). TDMA1 is executed among surface stations (e.g., buoys) using terrestrial wireless communication in order to share mobility information obtained from UNs which move cluster to cluster. TDMA2 is executed among UNs, which send data to their surface station as a cluster head in one cluster. By sharing mobility information, a surface station can instantaneously determine the number of time slots in a TDMA2 frame up to as many as the number of UNs which is currently residing in its cluster. This can enhance delay and channel utilization performance by avoiding the occurrence of idle time slots. We analytically investigate the delay of HTDMA, and compare it with that of wellknown contention-free and contention-based MAC protocols, which are TDMA and Slotted-ALOHA, respectively. It is shown that HTDMA remarkably decreases delay, compared with TDMA and Slotted-ALOHA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9A
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• pp.874-881
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• 2010

Acoustic signal, which is a main carrier of underwater communication, attenuates along the traveled path heavily depending on the frequency as well as inter-node distance. In addition, since it has a long propagation delay, the conventional medium access control (MAC) schemes requiring complex signaling procedures and accordingly heavy overhead messages would not be appropriate in underwater communications. In this paper, we propose a code division multiple access (CDMA) scheme as a solution for MAC of underwater communication and evaluate the performance. A hierarchical data-gathering tree topology is considered and a staggered wake-up pattern is employed for the purpose of energy saving. As a performance measure, the data rate at each level of hierarchical topology is derived.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.653-668
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• 2012

In this study, an improved HMM based recognition model is proposed for online English and Korean handwritten characters. The pattern elements of the handwriting model are sub character strokes and ligatures. To deal with the problem of handwriting style variations, a modified Hierarchical Clustering approach is introduced to partition different writing styles into several classes. For each of the English letters and each primitive grapheme in Korean characters, one HMM that models the temporal and spatial variability of the handwriting is constructed based on each class. Then the HMMs of Korean graphemes are concatenated to form the Korean character models. The recognition of handwritten characters is implemented by a modified level building algorithm, which incorporates the Korean character combination rules within the efficient network search procedure. Due to the limitation of the HMM based method, a post-processing procedure that takes the global and structural features into account is proposed. Experiments showed that the proposed recognition system achieved a high writer independent recognition rate on unconstrained samples of both English and Korean characters. The comparison with other schemes of HMM-based recognition was also performed to evaluate the system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.193-200
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• 2022

Unknown cryptographic communication protocols may have advantage of guaranteeing personal and data privacy, but when used for malicious purposes, it is almost impossible to identify and respond to using existing network security equipment. In particular, there is a limit to manually analyzing a huge amount of traffic in real time. Therefore, in this paper, we attempt to identify packets of unknown cryptographic communication protocols and separate fields comprising a packet by using machine learning techniques. Using sequential patterns analysis, hierarchical clustering, and Pearson's correlation coefficient, we found that the structure of packets can be automatically analyzed even for an unknown cryptographic communication protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3638-3657
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• 2022

In urban vehicular edge computing (VEC) environments, one edge server always serves many task requests in its coverage which results in the resource-constrained problem. To resolve the problem and improve system utilization, we first design a general hierarchical resource management framework based on typical VEC network structures. Following the framework, a specific interacting protocol is also designed for our decision algorithm. Secondly, a greedy bidding-based multi-hop task scheduling decision algorithm is proposed to realize effective task scheduling in resource-constrained VEC environments. In this algorithm, the goal of maximizing system utility is modeled as an optimization problem with the constraints of task deadlines and available computing resources. Then, an auction mechanism named greedy bidding is used to match task requests to edge servers in the case of multiple hops to maximize the system utility. Simulation results show that our proposal can maximize the number of tasks served in resource constrained VEC networks and improve the system utility.