• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.212-216
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• 2024

Feature Selection have turned into the main point of investigations particularly in bioinformatics where there are numerous applications. Deep learning technique is a useful asset to choose features, anyway not all calculations are on an equivalent balance with regards to selection of relevant features. To be sure, numerous techniques have been proposed to select multiple features using deep learning techniques. Because of the deep learning, neural systems have profited a gigantic top recovery in the previous couple of years. Anyway neural systems are blackbox models and not many endeavors have been made so as to examine the fundamental procedure. In this proposed work a new calculations so as to do feature selection with deep learning systems is introduced. To evaluate our outcomes, we create relapse and grouping issues which enable us to think about every calculation on various fronts: exhibitions, calculation time and limitations. The outcomes acquired are truly encouraging since we figure out how to accomplish our objective by outperforming irregular backwoods exhibitions for each situation. The results prove that the proposed method exhibits better performance than the traditional methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.111-121
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• 2006

Recently, many studies have been performed to apply airborne LIDAR data to extracting urban models. In order to model efficiently the man-made objects which are the main components of these urban models, it is important to extract automatically planar patches from the set of the measured three-dimensional points. Although some research has been carried out for their automatic extraction, no method published yet is sufficiently satisfied in terms of the accuracy and completeness of the segmentation results and their computational efficiency. This study thus aimed to developing an efficient approach to automatic segmentation of planar patches from the three-dimensional points acquired by an airborne LIDAR system. The proposed method consists of establishing adjacency between three-dimensional points, grouping small number of points into seed patches, and growing the seed patches into surface patches. The core features of this method are to improve the segmentation results by employing the variable threshold value repeatedly updated through a statistical analysis during the patch growing process, and to achieve high computational efficiency using priority heaps and sequential least squares adjustment. The proposed method was applied to real LIDAR data to evaluate the performance. Using the proposed method, LIDAR data composed of huge number of three dimensional points can be converted into a set of surface patches which are more explicit and robust descriptions. This intermediate converting process can be effectively used to solve object recognition problems such as building extraction.

• Journal of The Korean Association For Science Education
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• v.32 no.10
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• pp.1551-1566
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• 2012

In this study, the effects of grouping by students' collectivism in cooperative learning strategy applied to middle school science classes on their academic achievement, science learning motivation, and perceptions of science learning environment were investigated. Students' perceptions of cooperative learning were also studied through survey and interview. The students were assigned to the control, heterogeneous, and homogeneous groups, and taught for 12 class hours. The analyses of results revealed that interactive effects between the instruction and the level of collectivism were found in the test scores of achievement, science learning motivation, and relevance, and that there were main effects in the test scores of confidence, perceptions of science learning environment, affiliation, and rule clarity. The achievement test scores of the students with low collectivism in the homogeneous group were significantly higher than those in the heterogeneous group. The test scores on science learning motivation and relevance of the students with high collectivism in the homogeneous and heterogeneous groups were significantly higher than those in the control group. In addition, the test scores of confidence and affiliation in the treatment groups were significantly higher than those in the control group. The test scores on perceptions of science learning environment and rule clarity in the homogeneous groups were significantly higher than those in the control group. There were also differences in the perceptions of science cooperative learning by students' collectivism.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.9_10
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• pp.1015-1025
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• 2003

This paper proposes a method for constructing the virtual characters adopting the personal body types for the clothing coordination. At first, the method produces the 38 kinds of the Korean 3D body models considering sex, ages and body types, and constructs model DB. We select a model similar to the personal body size from DB and deform the selected model according to body size. The method deforms the model linearly for height 12 items, width 6 items, depth 5 items and round 13 items, and constructs the personal character fitted to the personal body size. The preprocess for model deformation consists of grouping for body part and establishing the feature points. Linear deformation for each group leads us to easy construction of the virtual personal characters. This method has two advantages as follows: 1. Large reduction of man power, cost and time for DB construction of the body 3D models, since the preprocess permits us to effectively use the various body models whose geometrical structures are different, 2 Suitability to Web-based clothing coordination, since the body deformation method is simple and its speed is very high.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.120-125
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• 2000

SNMP(Simple Network Management Protocol) could have the overhead of network, if the number of the agent system which is managed by the management system is increased by the polling for the collection of network management information and the reply traffic for it. In this Paper, the polling method used in SNMP is improved, and Group Polling method is proposed. This can reduce the overhead of network, on case that the agent system is to be increased. The proposed method collects information by grouping agent systems, and have smaller reply latency time and communication overhead than the previous method. So if the number of agent system or the Polling count is numerous, the proposed method is more efficient. As the result of the prototype test, the increasement of agent system can have small variation of traffic and transmission delay time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1773-1779
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• 2008

Images play the most important role in human perception. In order to send the image information by the digital type, the compression is essential. Recently, a lot of studies on encoding algorithms for image by wavelet transform are going on. In this paper, a quadtree-based method of image compression applied to the images decomposed by wavelet transform by using the correlations between pixels and '0' data grouping is proposed. For the proposed method, the experimental gray image with $256{\times}256$ size and 8[bit], is used. And, the performance of proposed method is evaluated to compare with DCT compression method.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.253-260
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• 2015

Because mass of activity records of individuals and organizations are accumulated in the digital space and amount of information is also increasing exponentially, the most urgent requirements of users is the tool for 'efficient' acquisition of 'useful' information. This paper try digital convergence to combine a domain specific technology with real time issue detection and grouping based on Web media. To derive core functionalities, we collect and analyze user requirements of national defense issue detection services. By utilizing linguistic resources specialized on national defence area and discovering features for measuring issue importance, we try to seek differentiation domain specific issue detection method. Finally we compare our detection results based on the development outputs of prototype.

• Journal of Life Science
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• v.9 no.2
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• pp.176-181
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• 1999

In order to understand molecular phylogenetics of silkworm (Bombyx mori), we analyzed the sequences of BmoMAR isolated from Bomhyx mori that is partial coding gene of transposase of mariner-like element(MLE). By pairwise comparing nucleotide sequences of BmoMAR with ten previously reported insect MLEs accessed in GeneBank, the average genetic distance was estimated to be 0.4840. The phylogenetics tree constructed from nine insect species except for human MLE(Hsmarl) by UPGMA method indicated that MLEs are divided into three clusters, and Drosophila mariutiana was independently subgrouped. Bombyx mori(BmoMAR) was subgrouped with microcaddishfly (Orthotrichia cristata), webworm(Atteva punctella), almond moth(Ephestia cautella), Hyalopora cecropia which we lepidoptera. Phylogenetics tree according to UPGMA principle, on the basis of informative nucleotide sequences of nine insect MLEs, indicated that Bombyx mori was more closely related to microcaddishfly(Orthotrichia cristata) and webworm (Atteva punctella) of lepidoptera. We suggest that insect MLEs are a useful key for studying molecular phylogenetics among intra species of insects.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.4
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• pp.112-120
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• 2006

Multicarrier code division multiple access(MC-CDMA) system that combines multicarrier modulation with CDMA offers robustness to frequency selective fading and can support higher rate data transmission with higher spectral efficiency. A new asynchronous MC-CDMA system to implement multiple data rate communications is proposed in this paper. In a W-CDMA downlink the orthogonal variable spreading factor(OVSF) code is used for variable spreading factor for various multimedia traffic. Proposed system utilizes the OVSF code that generated by generation property for spreading. The proposed MC-CDMA system use different lengths of OVSF code as a spreading code according to their data rate. The groupwise processing is accomplished by code grouping in OVSF code generation tree. For the analysis of average BER performance, numerical method and computer simulation were used. We also compare the system performance with that of a single rate MC-CDMA system used orthogonal code as a spreading code.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2375-2382
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• 2011

The user clustering for web navigation pattern discovery is very useful to get preference and behavior pattern of users for web pages. In addition, the information by the user clustering is very essential for web personalization or customer grouping. In this paper, an algorithm for clustering the web navigation path of users is proposed and then some special navigation patterns can be recognized by the algorithm. The proposed algorithm has two clustering phases. In the first phase, all paths are classified into k-groups on the bases of the their similarities. The initial solution obtained in the first phase is not global optimum but it gives a good and feasible initial solution for the second phase. In the second phase, the first phase solution is improved by revising the k-means algorithm. In the revised K-means algorithm, grouping the paths is performed by the hyperplane instead of the distance between a path and a group center. Experimental results show that the proposed method is more efficient.