• 대한기계학회논문집A
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• 제25권3호
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• pp.537-547
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• 2001

The paper proposes the fuzzy logic global approximate optimization strategies in optimal sizing of automotive A-pillar trim with rib structures for occupant head protection. Two different strategies referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the inherent nonlinearity in analysis model should be accommodated over the entire design space and the training data is not sufficiently provided. The objective of structural design is to determine the dimensions of rib in A-pillar, minimizing the equivalent head injury criterion HIC(d). The paper describes the head-form modeling and head impact simulation using LS-DYNA3D, and the approximation procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and subsequently presents their generalization capabilities in terms of number of fuzzy rules and training data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.227-247
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• 2018

For intermittently connected wireless sensor networks deployed in hash environments, sensor nodes may fail due to internal or external reasons at any time. In the process of data collection and recovery, we need to speed up as much as possible so that all the sensory data can be restored by accessing as few survivors as possible. In this paper a novel redundant data storage algorithm based on minimum spanning tree and quasi-randomized matrix-QRNCDS is proposed. QRNCDS disseminates k source data packets to n sensor nodes in the network (n>k) according to the minimum spanning tree traversal mechanism. Every node stores only one encoded data packet in its storage which is the XOR result of the received source data packets in accordance with the quasi-randomized matrix theory. The algorithm adopts the minimum spanning tree traversal rule to reduce the complexity of the traversal message of the source packets. In order to solve the problem that some source packets cannot be restored if the random matrix is not full column rank, the semi-randomized network coding method is used in QRNCDS. Each source node only needs to store its own source data packet, and the storage nodes choose to receive or not. In the decoding phase, Gaussian Elimination and Belief Propagation are combined to improve the probability and efficiency of data decoding. As a result, part of the source data can be recovered in the case of semi-random matrix without full column rank. The simulation results show that QRNCDS has lower energy consumption, higher data collection efficiency, higher decoding efficiency, smaller data storage redundancy and larger network fault tolerance.

• Structural Engineering and Mechanics
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• 제65권3호
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• pp.315-325
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• 2018

This paper predicts the flexural behaviour of reinforced concrete (RC) beams strengthened with a precast strip of ultra-high performance fiber-reinforced concrete (UHPFRC). In the first phase, ultimate load capacity of preloaded and strengthened RC beams by UHPFRC was predicted by using various analytical models available in the literature. RC beams were preloaded under static loading approximately to 70%, 80% and 90% of ultimate load of control beams. The models such as modified Kaar and sectional analysis predicted the ultimate load in close agreement to the corresponding experimental observations. In the second phase, the famous fatigue life models such as Papakonstantinou model and Ferrier model were employed to predict the number of cycles to failure and the corresponding deflection. The models were used to predict the life of the (i) strengthened RC beams after subjecting them to different pre-loadings (70%, 80% and 90% of ultimate load) under static loading and (ii) strengthened RC beams after subjecting them to different preloading cycles under fatigue loading. In both the cases precast UHPFRC strip of 10 mm thickness is attached on the tension face. It is found that both the models predicted the number of cycles to failure and the corresponding deflection very close to the experimental values. It can be concluded that the models are found to be robust and reliable for cement based strengthening systems also. Further, the Wang model which is based on Palmgren-Miner's rule is employed to predict the no. of cycles to failure and it is found that the predicted values are in very good agreement with the corresponding experimental observations.

• 한국컴퓨터정보학회논문지
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• 제13권6호
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• pp.77-86
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• 2008

웹 정보원은 사용자에게 제공되는 가장 큰 분산 데이터베이스로 간주될 수 있다. 분산된 웹 정보원을 가상적으로 통합하여 하나의 정보원으로 보고, 이 가상의 데이터베이스에 대하여 데이터베이스 질의어를 이용하여 검색하는 기능은 여러 가지 웹 기반 응용프로그램 개발에서 중요한 역할을 한다. 이러한 기능을 지원하기 위해서 브라우징 중심의 웹 문서로부터 데이터베이스 스키마를 추출해야 한다. 본 논문은 반 구조적인 웹 문서로부터 XML 스키마를 자동으로 생성하는 경험적 알고리즘을 제시한다. 이를 위하여 미리 정의된 구조태그 기반으로 후보패턴영역을 추출하고 후보패턴영역으로부터 패턴영역을 경험적으로 결정한다. 그리고 패턴영역으로부터 스키마생성규칙을 유도한다. 스키마생성규칙은 XQuery로 표현되기 때문에 공개된다양한 XML 도구를 사용하여 응용시스템을 개발할 수 있다. 개발된 시스템의 유효성을 보이기 위하여 다양한 웹정보원에 대하여 실험한 결과를 제시한다.

• 디지털콘텐츠학회 논문지
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• 제15권6호
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• pp.711-719
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• 2014

유비쿼터스 컴퓨팅 환경하에서 전자상거래 대규모가 대형화되고 취급되는 항목제품들도 다종 다양해지고 있는 것이 현실이다. 이러한 유비쿼터스 상거래 시스템은 편리하고 신속하게 제공되어야 하고 다이나믹한 환경에서 실시간성과 민첩성이 요구되고 있다. 데이터마이닝에서 추출한 지식을 적극적으로 활용하는 기법들이 전자상거래에서 구매 촉진을 증진시키는 마케팅 전략으로 활용되고 있다. 본 연구에서는 유비쿼터스 컴퓨팅 환경 하에 지능형 모바일 단말기를 이용한 추천을 위한 가중치기반 순차패턴 탐사를 이용한 추천서비스f를 제안하였다. 본 연구에서는 추천의 정확성을 향상시키고 구매력이 높은 항목제품 및 서비스를 추천하기 위해서 FRAT 세분화 기법을 이용한 가중치기반 순차패턴 탐사를 이용한 추천서비스를 제안하였다. 성능평가를 위해 현업에서 사용하는 인터넷 화장품 쇼핑몰의 데이터를 기반으로 데이터 셋을 구성하여 기존의 방법과 비교 실험을 통해 성능을 평가하여 효용성과 타당성을 입증하였다. 유비쿼터스 상거래에서 시간과 장소에 제약을 받지 않는 모바일 웹앱을 이용한 추천서비스를 위해서 이전방법보다 개선된 방법으로 추천서비스를 구현하였다.

• Journal of Information Processing Systems
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• 제9권4호
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• pp.511-537
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• 2013

Numerous data intensive applications demand the efficient processing of a new type of query, which is called a progressive query (PQ). A PQ consists of a set of unpredictable but inter-related step-queries (SQ) that are specified by its user in a sequence of steps. A conventional DBMS was not designed to efficiently process such PQs. In our earlier work, we introduced a materialized view based approach for efficiently processing PQs, where the focus was on selecting promising views for materialization. The problem of how to efficiently find usable views from the materialized set in order to answer the SQs for a PQ remains open. In this paper, we present a new index technique, called the Dynamic Materialized View Index (DMVI), to rapidly discover usable views for answering a given SQ. The structure of the proposed index is a special ordered tree where the SQ domain tables are used as search keys and some bitmaps are kept at the leaf nodes for refined filtering. A two-level priority rule is adopted to order domain tables in the tree, which facilitates the efficient maintenance of the tree by taking into account the dynamic characteristics of various types of materialized views for PQs. The bitmap encoding methods and the strategies/algorithms to construct, search, and maintain the DMVI are suggested. The extensive experimental results demonstrate that our index technique is quite promising in improving the performance of the materialized view based query processing approach for PQs.

• 한국통신학회논문지
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• 제33권9A호
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• pp.853-866
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• 2008

본 논문에서는 IEEE 802.22 기반의 인지라디오 시스템에서 다중 홉 릴레이 방식의 적용 방안을 제안한다. 먼저, 중계기를 통한 전송 시나리오를 가정하고 이를 지원하기 위한 물리 채널 프레임 구조를 예시한다. 다음으로, 분산 감지 (distributed sensing) 방식을 이용한 가용 채널 결정 방식을 제안하고 이를 토대로, 기지국 중심의 중앙집중형 (centralized) 채널 할당 기법 및 릴레이 전송을 위한 중계기 선택 알고리즘을 개발하였다. 그리고 수학적 해석과 시뮬레이션을 통한 성능 분석 결과는 제안한 다중 홉 릴레이 방식이 중계기를 사용하지 않은 기존의 인지 라디오 시스템에 비해 스펙트럼 이용효율과 시스템 수율 측면에서 성능 향상이 있음을 보여준다.

• Industrial Engineering and Management Systems
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• 제4권1호
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• pp.1-22
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• 2005

This paper presents new scheduling heuristics, namely Mean Progressive Weighted Tardiness Estimator (MPWT) Heuristic Method and modified priority rules with sequence-dependent setup times consideration. These are designed to solve job shop scheduling problems with new performance measures - progressive weighted tardiness penalties. More realistic constraints, which are inter-machine overlapping sequence-dependent setup times, are considered. In real production environments, inter-machine overlapping sequence-dependent setups are significant. Therefore, modified scheduling generation algorithms of active and nondelay schedules for job shop problems with inter-machine overlapping sequence-dependent setup times are proposed in this paper. In addition, new customer-based measures of performance, which are total earliness and progressive weighted tardiness, and total progressive weighted tardiness, are proposed. The objective of the first experiment is to compare the proposed priority rules with the consideration of sequence-dependent setup times and the standard priority rules without setup times consideration. The results indicate that the proposed priority rules with setup times consideration are superior to the standard priority rules without the consideration of setup times. From the second experiment and the third experiment to compare the proposed MPWT heuristic approach with the efficient priority rules with setup times consideration, the MPWT heuristic method is significantly superior to the Batched Apparent Tardiness Cost with Sequence-dependent Setups (BATCS) rule, and other priority rules based on total earliness and progressive weighted tardiness, and total earliness and tardiness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.264-284
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• 2021

As the next-generation network architecture, software-defined networking (SDN) has great potential. But how to forward data packets safely is a big challenge today. In SDN, packets are transferred according to flow rules which are made and delivered by the controller. Once flow rules are modified, the packets might be redirected or dropped. According to related research, we believe that the key to forward data flows safely is keeping the consistency of flow rules. However, existing solutions place little emphasis on the safety of flow rules. After summarizing the shortcomings of the existing solutions, we propose FRChain to ensure the security of SDN data forwarding. FRChain is a novel scheme that uses blockchain to secure flow rules in SDN and to detect compromised nodes in the network when the proportion of malicious nodes is less than one-third. The scheme places the flow strategies into blockchain in form of transactions. Once an unmatched flow rule is detected, the system will issue the problem by initiating a vote and possible attacks will be deduced based on the results. To simulate the scheme, we utilize BigchainDB, which has good performance in data processing, to handle transactions. The experimental results show that the scheme is feasible, and the additional overhead for network performance and system performance is less than similar solutions. Overall, FRChain can detect suspicious behaviors and deduce malicious nodes to keep the consistency of flow rules in SDN.

• 정보과학회 논문지
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• 제41권10호
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• pp.762-773
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• 2014

시맨틱 웹상에서 RDFS로 표현된 데이터의 사용 증가로 인하여, 대용량 데이터의 추론에 대한 많은 요구가 생겨나고 있다. 많은 연구자들은 대용량 온톨로지 추론을 수행하기 위해서 하둡과 같은 고가의 분산 프레임워크를 활용한다. 그러나, 적절한 사이즈의 RDFS 트리플 추론을 위해서는 굳이 고가의 분산 환경 시스템을 사용하지 않고 단일 머신에서도 논리적 프로그래밍을 이용하면 분산 환경과 유사한 추론 성능을 얻을 수 있다. 본 논문에서는 단일 머신에 논리적 프로그래밍 방식을 적용한 대용량 RDFS 추론 기법을 제안하였고 다중 머신을 기반으로 한 분산 환경 시스템과 비교하여 2억개 정도의 트리플에 대한 RDFS 추론 시스템을 적용한 경우 분산환경과 비슷한 성능을 보이는 것을 실험적으로 증명하였다. 효율적인 추론을 위해 온톨로지 모델을 세부적으로 분리한 메타데이터 구조와 대용량 트리플의 색인 방안을 제안하고 이를 위해서 전체 트리플을 하나의 모델로 로딩하는 것이 아니라 각각 온톨로지 추론 규칙에 따라 적절한 트리플 집합을 선택하였다. 또한 논리 프로그래밍이 제공하는 Unification 알고리즘 기반의 트리플 매칭, 검색, Conjunctive 질의어 처리 기반을 활용하는 온톨로지 추론 방식을 제안한다. 제안된 기법이 적용된 추론 엔진을 LUBM1500(트리플 수 2억개) 에 대해서 실험한 결과 166K/sec의 추론 성능을 얻었는데 이는 8개의 노드(8 코아/노드)환경에서 맵-리듀스로 수행한 WebPIE의 185K/sec의 추론 속도와 유사함을 실험적으로 증명하였다. 따라서 단일 머신에서 수행되는 본 연구 결과는 트리플의 수가 2억개 정도까지는 분산환경시스템을 활용하지 않고도 분산환경 시스템과 비교해서 비슷한 성능을 보이는 것을 확인할 수 있었다.