• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4087-4102
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• 2014

Two-way relaying is an effective way of improving system spectral efficiency by making use of physical layer network coding. However, energy efficiency in OFDM-based bidirectional relaying with asymmetric traffic requirement has not been investigated. In this study, we focused on subcarrier transmission mode selection, bit loading, and power allocation in a multicarrier single amplified-and-forward relay system. In this scheme, each subcarrier can operate in two transmission modes: one-way relaying and two-way relaying. The problem is formulated as a mixed integer programming problem. We adopt a structural approximation optimization method that first decouples the original problem into two suboptimal problems with fixed subcarrier subsets and then finds the optimal subcarrier assignment subsets. Although the suboptimal problems are nonconvex, the results obtained for a single-tone system are used to transform them to convex problems. To find the optimal subcarrier assignment subsets, an iterative algorithm based on subcarrier ranking and matching is developed. Simulation results show that the proposed method can improve system performance compared with conventional methods. Some interesting insights are also obtained via simulation.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.904-907
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• 2002

In this paper, we describe an algorithm to automatically generate an intermediate scene using the bidirectional disparity morphing from the parallel stereopair. To compute the disparity between two reference images, we use the 2-step fast block matching algorithm that restricts the searching range and accelerates the speed of the computation of the disparity. We also define three occluding patterns so as to smooth the computed disparities, especially for occluded regions. They are derived from the peculiar properties of the disparity map. The smoothed disparity maps present that the false disparities are well corrected and the boundary between foreground and background becomes sharper. We discuss the advantages of this algorithm compared to the commonly used schemes and we show some experimental results with real data.

• Convergence Security Journal
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• v.21 no.3
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• pp.75-80
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• 2021

This study provided personnel and recruitment information related to job offer and job hunting, and proposed a non-face-to-face platform that can facilitate matching of one-time services as well as periodic services. The existing recruitment and job search method for personal assistant of the disabled is a one-way matching method in which a person in charge of the service providing centers assigns an activity assistant belonging to the institution when a consumer requests an personal assistant service, so the choice of job seekers is very weak. The job matching platform of the activity assistant for the disabled can be logged in separately by dividing users and separating them into the interface of the disabled or the disabled family members (job seekers) and activity assistants for the disabled (job seekers). Search for job offer and job seekers that meet their respective conditions, and real-time bidirectional decision-making through the chat function, and when the activity assistance service is completed, recruiters and job seekers can write service reviews and evaluations from their own point of view. The real-time interactive decision-making matching platform will also help minimize blind spots where it is difficult to provide services when short-term or one-time assistance is needed.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.701-704
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• 1998

본 논문에서는 스테레오 정합에서 불연속성과 폐색영역을 고려하고 다중 계층 구조를 사용한 relaxation 알고리듬을 이용하여 좌우 영상간의 최적의 정합점을 찾는 스테레오 정합을 구현하였다. 잡음을 제거하기 위해 베이시안 필터링 방법을 사용하였다. 좌우 영상에서 얻은 변이(disparity)를 이용하여 좌우 폐색영역(occlusion region)을 구한 후, 다시 최적의 변이를 얻기 위해 내삼과정을 통해 양쪽의 정보를 상호 보완하는 병렬적인 relaxation 방법을 구현한다. 구현한 방법은 다양한 영상에 적용하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.571-576
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• 2024

Ontologies are created by domain experts, but the same content may be expressed differently by each expert due to different understandings of domain knowledge. Since the ontology standardization is still lacking, multiple ontologies can be exist within the same domain, resulting in a phenomenon called the ontology heterogeneity. Therefore, we propose a novel ontology matching method that combines SCBOW(: Siames Continuois Bag Of Words) and BERT(: Bidirectional Encoder Representations from Transformers) models to solve the ontology heterogeneity issue. Ontologies are expressed as a graph and the SimRank algorithm is used to solve the one-to-many problem that can occur in ontology matching problems. Experimental results showed that our approach improves performance by about 8% over traditional matching algorithm. Proposed method can enhance and refine the alignment technology used in ontology matching.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.175-188
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• 2010

A new correction method is required for the Geostationary Ocean Color Imager (GOCI), which is the world's first ocean color observing sensor in geostationary orbit. In this paper we introduce a new method of atmospheric and the Bidirectional Reflectance Distribution Function(BRDF) correction for GOCI. The Spectral Shape Matching Method(SSMM) and the Sun Glint Correction Algorithm(SGCA) were developed for atmospheric correction, and BRDF correction was improved using Inherent Optical Property(IOP) data. Each method was applied to the Sea-Viewing Wide Field-of-view Sensor(SeaWiFS) images obtained in the Korean sea area. More accurate estimates of chlorophyll concentrations could be possible in the turbid coastal waters as well as areas severely affected by aerosols.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.549-561
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• 2022

In the Khmer writing system, the Khmer script is the official letter of Cambodia, written from left to right without a space separator; it is complicated and requires more analysis studies. Without clear standard guidelines, a space separator in the Khmer language is used inconsistently and informally to separate words in sentences. Therefore, a segmented method should be discussed with the combination of the future Khmer natural language processing (NLP) to define the appropriate rule for Khmer sentences. The critical process in NLP with the capability of extensive data language analysis necessitates applying in this scenario. One of the essential components in Khmer language processing is how to split the word into a series of sentences and count the words used in the sentences. Currently, Microsoft Word cannot count Khmer words correctly. So, this study presents a systematic library to segment Khmer phrases using the bi-directional maximal matching (BiMM) method to address these problematic constraints. In the BiMM algorithm, the paper focuses on the Bidirectional implementation of forward maximal matching (FMM) and backward maximal matching (BMM) to improve word segmentation accuracy. A digital or prefix tree of data structure algorithm, also known as a trie, enhances the segmentation accuracy procedure by finding the children of each word parent node. The accuracy of BiMM is higher than using FMM or BMM independently; moreover, the proposed approach improves dictionary structures and reduces the number of errors. The result of this study can reduce the error by 8.57% compared to FMM and BFF algorithms with 94,807 Khmer words.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1872-1879
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• 2001

As multiview video applications become more popular, correspondence problem for stereo image matching plays an important role in expanding view points. Thus, we propose an efficient dense disparity estimation algorithm considering features of each image pair of multiview image sets. Main concepts of the proposed algorithm are based on the region-dividing-bidirectional-pixel-matching method. This algorithm makes matching process efficient and keeps the reliability of the estimated disparities. Other improvement have obtained by proposed cost function, matching window expanding technique, disparity regularization, and disparity assignment in ambiguous region. These techniques make disparities more stable by removing false disparities and ambiguous regions. The estimated disparities are used to synthesize intermediate views of multiview images. Computer simulation demonstrates the excellence of the proposed algorithm in both subjective and objective evaluations. In addition, processing time is reduced as well.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.229-237
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• 2002

Natural synthesis of real and virtual images is a key technology in mixed reality. For this purpose, we propose an efficient dense disparity estimation algorithm and a synthesis algorithm considering features of stereo images. Dense disparities are estimated hierarchically from the low to high resolution images. In the process, the region-dividing-bidirectional-matching algorithm makes matching process efficient and keeps the reliability of the estimated disparities, and dense disparities are assigned considering edge information. finally, mixed reality stereo images are synthesized by comparing depth data of real and virtual Images. Computer simulation shows that the proposed algorithms estimate very stable disparity vectors with sharp edge and synthesize natural stereo mixed reality images.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.242-248
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• 2022

The article presents the analysis of modern methods of automatic comparison of original and unoriginal text to detect textual plagiarism. The study covers two types of plagiarism - literal, when plagiarists directly make exact copying of the text without changing anything, and intelligent, using more sophisticated techniques, which are harder to detect due to the text manipulation, like words and signs replacement. Standard techniques related to extrinsic detection are string-based, vector space and semantic-based. The first, most common and most successful target models for detecting literal plagiarism - N-gram and Vector Space are analyzed, and their advantages and disadvantages are evaluated. The most effective target models that allow detecting intelligent plagiarism, particularly identifying paraphrases by measuring the semantic similarity of short components of the text, are investigated. Models using neural network architecture and based on natural language sentence matching approaches such as Densely Interactive Inference Network (DIIN), Bilateral Multi-Perspective Matching (BiMPM) and Bidirectional Encoder Representations from Transformers (BERT) and its family of models are considered. The progress in improving plagiarism detection systems, techniques and related models is summarized. Relevant and urgent problems that remain unresolved in detecting intelligent plagiarism - effective recognition of unoriginal ideas and qualitatively paraphrased text - are outlined.