• Journal of Advanced Marine Engineering and Technology
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• v.40 no.5
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• pp.437-446
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• 2016

Feature selection has become an essential technique to reduce the dimensionality of data sets. Many features are frequently irrelevant or redundant for the classification tasks. The purpose of feature selection is to select relevant features and remove irrelevant and redundant features. Applications of the feature selection range from text processing, face recognition, bioinformatics, speaker verification, and medical diagnosis to financial domains. In this study, we focus on filter methods based on information entropy : IG (Information Gain), FCBF (Fast Correlation Based Filter), and mRMR (minimum Redundancy Maximum Relevance). FCBF has the advantage of reducing computational burden by eliminating the redundant features that satisfy the condition of approximate Markov blanket. However, FCBF considers only the relevance between the feature and the class in order to select the best features, thus failing to take into consideration the interaction between features. In this paper, we propose an improved FCBF to overcome this shortcoming. We also perform a comparative study to evaluate the performance of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1065-1085
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• 2020

With rapid growth of content demands, device-to-device (D2D) content sharing is exploited to effectively improve the service quality of users. Considering the limited storage space and various content demands of users, caching schemes are significant. However, most of them ignore the influence of the asynchronous content reuse and the selfishness of users. In this work, the user preferences are defined by exploiting the user-oriented content popularity and the current caching situation, and further, we propose the social-aware rate, which comprehensively reflects the achievable contents download rate affected by the social ties, the caching indicators, and the user preferences. Guided by this, we model the collaborative caching problem by making a trade-off between the redundancy of caching contents and the cache hit ratio, with the goal of maximizing the sum of social-aware rate over the constraint of limited storage space. Due to its intractability, it is computationally reduced to the maximization of a monotone submodular function, subject to a matroid constraint. Subsequently, two social-aware collaborative caching algorithms are designed by leveraging the standard and continuous greedy algorithms respectively, which are proved to achieve different approximation ratios in unequal polynomial-time. We present the simulation results to illustrate the performance of our schemes.

• Journal of Distribution Science
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• v.17 no.4
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• pp.27-32
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• 2019

Purpose - The business model is a method of creating corporate value, in existing "classification of business model", limitations and redundancy phenomena are applied when a new type flows in, and as consumer's purchasing decision of consumer behavior 5 steps. The classification schemes can be used for more accurate data analysis by proposing a new mapping technique in the fourth industry. Research design, data, and methodology - It was far more classified on the business model (BMS by BDS), and so on. Designing the new horizons of logistics, marketing, methodology by reclassifying these existing data to new useful data with the old methods, in order to analyze the areas where the problem has been raised for the point that the existing methods are not suitable configured. This will be applicable to the system of quaternary industry from the perspective of the buyer. Results - The mapping results of the consumer purchase decision were as follows,the 1^st stage (interest) was 23.73%, 2^nd stages (publicity) 33.90%, 3^rd stages (sales) 13.56%, 4^th stages (decision) 11.86%, 5^th stages (repurchaser) 16.95%. This verified that "the business model can be classified through "BMS by BDS". Conclusions - This structural classification is the basis of logistics marketing in the 4th industry, and proposes a innovative and effective model of constructing theory.

• Journal of Broadcast Engineering
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• v.7 no.4
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• pp.310-316
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• 2002

In this paper, we propose an adaptive search range decision algorithm for fast motion estimation of video coding. Block matching algorithm for motion vector estimation that improves coding efficiency by reduction of temporal redundancy has trade-off problem between the motion vector accuracy and the complexity. The proposed algorithm playing as a pre-processing of fast motion estimation adaptively determines the motion search range by the local statistics of neighboring motion vectors. resulting in dramatic reduction of the computational cost without the loss of coding efficiency. Experimental results show the capability of the proposed algorithm.

• Journal of Environmental Impact Assessment
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• v.22 no.3
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• pp.265-276
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• 2013

This study assessed documentation status of each environmental assessment items by analyzing the 243 case of marine EIS on the Consultation System of Sea Area Utilization. Observed rate of tidal elevation, current, temperature, salinity in maine environment were below 20%. The EFDC tool is applied substantially in hydrodynamic modeling. The verification process, however, is very insufficient using the recent observed data. Also, in-situ assessment rate of pelagic organism such as phytoplankton was below 50%, and assessment for Chlorophyll a was not accomplished. Ecological index evaluation for zooplankton and benthic ecosystem were not considered in statements. Especially, the rational assessment on the fisheries resources and protected species were very limited. It was necessary that the core assessment items (checklists) were established for environmental scoping. Furthermore, suggestion of information related to development, regional coastal management plan, aquaculture farms, and facilities were enhanced. The redundancy problem of proceedings between Environmental Impact Assessment and Sea Area Utilization Assessment System was improved.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.499-510
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• 2007

Shortest path tree(SPT) construction is essential in high performance routing in an interior network using link state protocols. When some links have new state values, SPTs may be rebuilt, but the total rebuilding of the SPT in a static way for a large computer network is not only computationally expensive, unnecessary modifications can cause routing table instability. This paper presents a new update algorithm, dynamic shortest path tree(DSPT) that is computationally economical and that maintains the unmodified nodes mostly from an old SPT to a new SPT. The proposed algorithm reduces redundancy using a dynamic update approach where an edge becomes the significant edge when it is extracted from a built edge list Q. The average number of significant edges are identified through probability analysis based on an arbitrary tree structure. An update derived from significant edges is more efficient because the DSPT algorithm neglect most other redundant edges that do not participate in the construction of a new SPT. Our complexity analysis and experimental results show that DSPT is faster than other known methods. It can also be extended to solve the SPT updating problem in a graph with negative weight edges.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.15-22
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• 2011

U-Healthcare service is a real-time service using the vital signs which are continuously transferred from monitoring sensors attached to mobile patients under the wireless network environments. It should monitor the health condition of mobile patients everywhere at any time. In this paper, we have improved two features of the three layered mobile patient monitoring system with load balancing ability. First, the simulation process has been improved by allowing the number of related nodes to be changed. Secondly, we have modified S node to which queue is added to reduce the loss rate of collecting data from patients during the delay of S node process. And the data from the patient with high priority can be transferred to the server immediately through the filtering function. Furthermore, we have solved the problem of redundancy in sharing information among S nodes by differentiating process time to each S node. By performing a DEVS Java-based system simulation, we have verified the efficiency of this improved system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.2
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• pp.29-36
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• 2003

This paper proposes a new 3D image transmission technique using digital watermarking for compatibility with conventional 2D digital TV. To transmit 3D images effectively, generally, we use image sequence transmission using temporal-spatial redundancy between stereo images. It is difficult for users with conventional digital TV to watch the transmitted 3D image sequence because of effectivity of 3D image compression. To improve such problem, in this paper, we perceive the concealment of new information of digital watermarking and conceal information of the other stereo image into three channels of the reference image. So we can watch the image with 3D TV as well as conventional digital TV when it is decoded.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.956-963
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• 2008

In a multi-hop wireless ad hoc network broadcasting is an elementary operation to support route discovery, address resolution and other application tasks. Broadcasting by flooding may cause serious redundancy, contention, and collision in the network which is referred to as the broadcast storm problem. Many broadcasting schemes have been proposed to give better performance than simple flooding in wireless ad hoc network. How to decide whether re-broadcast or not also poses a dilemma between reachability and efficiency under different host densities. In this paper, we propose enhanced broadcasting schemes, which can reduce re-broadcast packets without loss of reachability. Simulation results show that proposed schemes can offer better reachability as well as efficiency as compared to other previous schemes.