• Digital Contents
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• no.11 s.66
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• pp.98-102
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• 1998

장황한(redundant) ; 쓸모없는(detrop), 산만한(diffuse), 과잉의(excessive), 필수적이지 않은(inessential), 완곡한(periphrastic), 반복적인(repetitious), 원하지 않는(unwanted), 불필요한(unnecessary) 등은 Chambers Twentieth Century 유의어 사전에서 발췌된 redundant의 유사어들이다(동 사전은 concise, essential, necessary 등과 같은 redundant의 반의어들의 명단도 잘 정리되어 있다). GROUP BY와 HAVING(이후부터는 GBH로 칭하기로 한다)으로 시작하는 절(clauses)들이 SQL내에서 반복적으로 사용된다는 사실을 알고 있는지에 대한 의문을 제기할 수 있다. 다시 말해, SQL 내에서 표현되고, 상기의 절들 모두 또는 어느 한쪽이 포함된 어떠한 종류의 상식적인 질문도 그러한 절들을 사용하지 않고도 표현될 수 있다는 것이다(필자가 여기서 '상식적'이란 말로 한정한 이유는 나중에 설명하겠다). 필자는 중복성에 관해 설명하고 이것이 내포하고 있는 의미에 관해 논의코자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.574-575
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• 2018

The generation of redundant data according to the spatial-temporal correlation in a wireless sensor network that reduces the network lifetime by consuming unnecessary energy. In this paper, data collection experiment through the particulate matter sensor is carried out to confirm the spatial-temporal data redundancy and we propose permitted limit setting method for data transmission to solve this problem. In the proposed method, the data transmission permitted limit is set by using the integrated average value in the cluster. The set permitted limit reduces the redundant data of the member node and it is shows that redundant data reduction is possible even in a variable environment of collected data by resetting the permitted limit in the cluster head.

• Journal of Information Display
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• v.10 no.1
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• pp.6-15
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• 2009

In this paper, a new approach is proposed for the efficient generation of computer-generated holograms (CGHs) using the spatially redundant data on a 3D object and the novel look-up table (N-LUT) method. First, the pre-calculated N-point principle fringe patterns (PFPs) were calculated using the 1-point PFP of the N-LUT. Second, spatially redundant data on a 3D object were extracted and re-grouped into the N-point redundancy map using the run-length encoding (RLE) method. Then CGH patterns were generated using the spatial redundancy map and the N-LUT method. Finally, the generated hologram patterns were reconstructed. In this approach, the object points that were involved in the calculation of the CGH patterns were dramatically reduced, due to which the computational speed was increased. Some experiments with a test 3D object were carried out and the results were compared with those of conventional methods.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.589-598
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• 2018

To maintain safety and reliability of reactors, redundant sensors are usually used to measure critical variables and estimate their averaged time-dependency. Nonhealthy sensors can badly influence the estimation result of the process variable. Since online condition monitoring was introduced, the online cross-calibration method has been widely used to detect any anomaly of sensor readings among the redundant group. The cross-calibration method has four main averaging techniques: simple averaging, band averaging, weighted averaging, and parity space averaging (PSA). PSA is used to weigh redundant signals based on their error bounds and their band consistency. Using the consistency weighting factor (C), PSA assigns more weight to consistent signals that have shared bands, based on how many bands they share, and gives inconsistent signals of very low weight. In this article, three approaches are introduced for improving the PSA technique: the first is to add another consistency factor, so called trend consistency (TC), to include a consideration of the preserving of any characteristic edge that reflects the behavior of equipment/component measured by the process parameter; the second approach proposes replacing the error bound/accuracy based weighting factor ($W^a$) with a weighting factor based on the Euclidean distance ($W^d$), and the third approach proposes applying $W^d$, TC, and C, all together. Cold neutron source data sets of four redundant hydrogen pressure transmitters from a research reactor were used to perform the validation and verification. Results showed that the second and third modified approaches lead to reasonable improvement of the PSA technique. All approaches implemented in this study were similar in that they have the capability to (1) identify and isolate a drifted sensor that should undergo calibration, (2) identify a faulty sensor/s due to long and continuous missing data range, and (3) identify a healthy sensor.

• ETRI Journal
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• v.39 no.1
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• pp.1-12
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• 2017

In this paper, we present a new approach for the progressive compression of three-dimensional (3D) mesh geometry using redundant frame dictionaries and sparse approximation techniques. We construct the proposed frames from redundant linear combinations of the eigenvectors of a combinatorial mesh Laplacian matrix. We achieve a sparse synthesis of the mesh geometry by selecting atoms from a frame using matching pursuit. Experimental results show that the resulting rate-distortion performance compares favorably with other progressive mesh compression algorithms in the same category, even when a very simple, sub-optimal encoding strategy is used for the transmitted data. The proposed frames also have the desirable property of being able to be applied directly to a manifold mesh having arbitrary topology and connectivity types; thus, no initial remeshing is required and the original mesh connectivity is preserved.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.2
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• pp.183-194
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• 1995

This research paper describes several possible suggestions which are essential to develop for Built-In-Test(BIT) related systems, such as more precise BIT parameter analysis, sensitivity analysis of the impact of BIT on redundant systems, statistical inference of field data for BIT performance parameters, methods of reducing BIT false alarms, BIT application in industrial automation and remote control, prevent the system from the impact of BIT failure, undetections and false alarms, life cycle cost analysis for BIT. And, it is mainly focused on redundancy technique for solving BIT diagnostic problems. Algorithms for redundant systems : overlapping technique, flexible redundant BITs are presented and case study will be shown based on various experiment.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.820-831
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• 2020

Extractive document summarization aims to select a few sentences while preserving its main information on a given document, but the current extractive methods do not consider the sentence-information repeat problem especially for news document summarization. In view of the importance and redundancy of news text information, in this paper, we propose a neural extractive summarization approach with joint sentence semantic clipping and selection, which can effectively solve the problem of news text summary sentence repetition. Specifically, a hierarchical selective encoding network is constructed for both sentence-level and document-level document representations, and data containing important information is extracted on news text; a sentence extractor strategy is then adopted for joint scoring and redundant information clipping. This way, our model strikes a balance between important information extraction and redundant information filtering. Experimental results on both CNN/Daily Mail dataset and Court Public Opinion News dataset we built are presented to show the effectiveness of our proposed approach in terms of ROUGE metrics, especially for redundant information filtering.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.205-214
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• 2016

As a large amount of graph-structured data is widely used in various applications such as social networks, semantic web, and bio-informatics, keyword-based search over graph data has been getting a lot of attention. In this paper, we propose an efficient method for keyword search over graph data to find a set of top-k answers that are relevant as well as non-redundant in structure. We define a non-redundant answer structure for a keyword query and a relevance measure for the answer. We suggest a new indexing scheme on the relevant paths between nodes and keyword terms in the graph, and also propose a query processing algorithm to find top-k non-redundant answers efficiently by exploiting the pre-calculated indexes. We present effectiveness and efficiency of the proposed approach compared to the previous method by conducting an experiment using a real dataset.

• Journal of Power Electronics
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• v.11 no.4
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• pp.533-541
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• 2011

The redundant operation of a parallel AC to DC converter via a serial communication bus is presented. The proposed system consists of three isolated CUK power factor correction modules. The controller for each converter is a dsPIC30F6010 microcontroller while a RS485 communication bus and the clock signal are used for synchronizing the data communication. The control strategy of the redundant operation relies on the communication of information among each of the modules, which communicate via a RS485 serial bus. This information is received from the communication checks of the converter module connected to the system to share the load current. Performance evaluations were conducted through experimentation on a three-module parallel-connected prototype, with a 578W load and a -48V dc output voltage. The proposed system has achieved the following: the current sharing is quite good, both the transient response and the steady state. The converter modules can perform the current sharing immediately, when a fault is found in another converter module. In addition, the transient response occurs in the system, and the output voltages are at their minimum overshoot and undershoot. Finally, the proposed system has a relatively simple implementation for the redundant operation.

• 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.