• 한국ITS학회:학술대회논문집
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• 2010.05a
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• pp.18-21
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• 2010

• Asia pacific journal of information systems
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• v.16 no.3
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• pp.67-93
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• 2006

Some consumers prefer online and others prefer offline. What makes them prefer online or offline? There has been a lack of theoretical development to adequately explain consumers' channel switching behavior between traditional physical stores and new virtual stores. Through consumers' purchase decision processes, this study examined the reasons why consumers changed channels depending on purchase process stages. Consumer's purchase decision process could be divided into three stages: pre-purchase stage, purchase stage, and post-purchase stage. We used the intention of channel selection as a surrogate dependent variable of channel selection. And some constructs, that is, channel function, channel benefits, customer relationship benefits, and perceived behavioral control, were selected as independent variables. In buying look-and-feel products, it was identified that consumers preferred virtual stores to physical stores at pre-purchase stage. To put it concretely, all constructs except channel benefits were more influenced to consumers at virtual stores. This result implied that information searching function, which is a main function at pre-purchase stage, was better supported by virtual stores than physical stores. In purchase stage, consumers preferred physical stores to virtual stores. Specially, all constructs influenced much more to consumers at physical stores. This result implied that although escrow service and trusted third parties were introduced, consumers felt that financial risk, performance risk, social risk, etc. still remained highly online. Finally, consumers did not prefer any channel at post-purchase stage. But three independent variables, i.e. channel function, channel benefits, and customer relationship benefits, were significantly preferred at physical stores rather than virtual stores at post-purchase stage. So we concluded that physical stores were a little more preferred to virtual stores at post-purchase stage. Through this study, it was identified that most consumers might switch channels according to purchase process stages. So, first of all, sales representatives should decide that what benefits should be given them through virtual stores at the pre-purchase stage and through physical stores at the purchase and post-purchase stages, and then devise collaborative channel strategies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.564-571
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• 2009

In this paper, we propose out-of -band collaborative spectrum sensing scheme in the cognitive radio (CR) base station operated by the multiple frequency channels. Also this paper presents the signal detection results for ATSC digital TV signal as an incumbent signal and derives signal detection probability and false alarm probability for the out-of-band collaborative spectrum sensing scheme in frequency selective Rayleigh fading channel. Numerical results demonstrate that the sensing performance is improved by the out-of-band collaborative spectrum sensing in the case that the incumbent signal powers measured by the CR terminals of the multiple frequency channels are almost similar.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.40-46
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• 2010

Multi-user MIMO (Multiple-Input Multiple-Output) systems require collaborative PF schedulers to improve the performance of the log sum of average transmission rates. While the performance of single cell based conventional PF schedulers has been evaluated over various channel conditions, scheduling algorithms by multiple base stations which select multiple users over a given time frame and their performance require further investigations. In this paper, we apply a collaborative PF scheduler to the distributed multi-user MIMO system, which assigns radio resources to multiple users by exchanging user channel information from base stations located in three adjacent sectors. We further evaluate its performance in terms of the log sum of average transmission rates. The performance is compared to that of the full-search collaborative PF scheduler which searches over all possible combinations of user groups, and that of a parallel PF scheduler that determines users without channel information exchange among base stations. We show the log sum of average transmission rates of the collaborative PF scheduler outperforms that of the parallel PF scheduler in low percentile region. In addition, the collaborative PF scheduler exhibits a negligible performance degradation when compared to the full-search collaborative PF scheduler while a significant reduction of the computational complexity is achievable at the same time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.101-109
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• 2008

In this paper, we introduce clustering scheme to calculate probability of detection which is practically required for conventional weighted-collaborative sensing technique. We also propose an improved weighted-collaborative spectrum sensing scheme using new weight generation algorithm to achieve better performance in Cognitive Radio systems. We calculate Pd in each cluster which is a CR users group with similar channel situation. New weight factor is generated using square sum of all cluster's Pds. Simulations under slow fading show that we can get better total detection probability and lower false alarm rate when PU (Primary User) suddenly terminates their transmission.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2723-2733
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• 2023

Transuranic nuclides (such as ²³⁸Pu, ²⁵²Cf, ²⁴⁹Bk, etc.) have a wide range of application in industry, medicine, agriculture, and other fields. However, due to the complex conversion chain and remarkable fission losses in the process of transuranic nuclides production, the generation amounts are extremely low. High flux reactor with high neutron flux and flexible irradiation channels, is regarded as the promising candidate for producing transuranic nuclides. It is of great significance to increase the conversion ratio of transuranic nuclides, resulting in higher efficiency and better economy. In this paper, we perform an optimization design evaluation of producing transuranic nuclides in high flux reactor, which includes optimization design of irradiation target and influence study of reactor core loading. It is demonstrated that the production rate increases with appropriately determined target material and target structure. The target loading scheme in the irradiation channel also has a significant influence on the production of transuranic nuclides.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.128-138
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• 2007

With the development of broadcasting technology from analogue to interactive digital, the number of TV channels and contents provided to audience is increasing in a rapid speed. In this multi-media and multi-channel world, it is difficult to adapt to the increase of TV channel numbers and their contents merely using remote controller to search channels. Due to this reason, EPG (Electronic Program Guide) has been one of the essential services providing convenience to audience. So EPG complying with European DVB-MHP specifications, which will be also our domestic standard, is proposed in this paper. In order to provide audiences with DiTV contents they preferred, we apply collaborative filtering algorithm to recommend contents according to preference value of audience group with similar preference. And we use JavaXlet application which is based on MHP to implement this EPG, while the result can be verified by OpenMHP emulator.

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.749-756
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• 2006

Broadcast nature of wireless medium and path-loss reduction create a favourable condition for collaborative communications (CC) among single-antenna users to gain the powerful benefits of multi-antenna system without the demand for physical arrays. This paper proposes a CC strategy adapting to the propagation environment changes by optimizing the transmit signal amplification factors to simplify the structure of maximum likelihood (ML) detector and to obtain the minimum error probability as well. The closed-form BER expression was also derived and compared to the simulation results to evaluate the performance of the suggested solution. A variety of numerical results revealed the cooperation significantly outperforms non-cooperative counterpart under flat Rayleigh fading channel plus AWGN (Additive White Gaussian Noise).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3771-3788
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• 2015

This paper studies the distributed energy efficient resource management in the Internet of Things (IoT). Wireless communication networks support the IoT without limitation of distance and location, which significantly impels its development. We study the communication channel and energy management in the wireless communication network supported IoT to improve the ability of connection, communication, share and collaboration, by using the game theory and distributed learning algorithm. First, we formulate an energy efficient neighbor collaborative game model and prove that the proposed game is an exact potential game. Second, we design a distributed energy efficient channel selection learning algorithm to obtain the global optimum in a distributed manner. We prove that the proposed algorithm will asymptotically converge to the global optimum with geometric speed. Finally, we make the simulations to verify the theoretic analysis and the performance of proposed algorithm.