• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.68-75
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• 2005

This paper presents a new method for the optimization of feed rate in sculptured surface machining. A NC verification model based on Z-map was utilized to obtain chip load according to feed per tooth. This optimization method can regenerate a new NC program with respect to the commanded cutting conditions and the NC program that was generated from CAM system. The regenerated NC program has not only the same data of the ex-NC program but also the updated feed rate in every block. The new NC data can reduce the cutting time and produce precision products with almost even chip load to the feed per tooth. This method can also reduce tool chipping and make constant tool wear.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1156-1158
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• 2015

본 연구는 기업의 전략 의사결정(Strategic Decision-Making) 실무에 빅데이터를 활용하기 위한 방안으로 하둡-맵 리듀스(Map Reduce)를 통해 처리한 데이터를 이용해 퍼지 인식도(Fuzzy Cognitive Map)의 인과 행렬을 작성하고, 작성된 퍼지 인식도를 활용하는 경영 의사결정 방법과 의사 결정 지원 시스템(DSS: Decision Support System)을 제안한다. 제안을 위해 관련 연구 및 개념, 퍼지 인식도를 기반으로 하는 의사결정 지원 시스템과 제안한 시스템이 갖는 장점, 그리고 퍼지 인식도 기반 의사결정 지원 시스템의 실제 활용 가능성에 대해서 실험을 통해 검증한 내용을 담고 있다.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.39-47
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• 2021

Lempel-Ziv coding is one of the most famous source coding schemes. The output of this source coding is usually a non-uniform code, which requires additional source coding, such as arithmetic coding, to reduce a redundancy. However, this additional source code increases complexity and decoding latency. Thus, this paper proposes the optimal maximum a-posteriori (MAP) receiver for non-uniform source non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC). First, we derive an analytical expression of the bit-error rate (BER) for non-uniform source NOMA with SSC. Then, Monte Carlo simulations demonstrate that the BER of the optimal MAP receiver for the non-uniform source improves slightly, compared to that of the conventional receiver for the uniform source. Moreover, we also show that the BER of an approximate analytical expression is in a good agreement with the BER of Monte Carlo simulation. As a result, the proposed optimal MAP receiver for non-uniform source could be a promising scheme for NOMA with SSC, to reduce complexity and decoding latency due to additional source coding.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.397-406
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• 2014

In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.87-96
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• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

• International journal of advanced smart convergence
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• v.5 no.2
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• pp.59-65
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• 2016

With the recent growth in cloud computing, big data processing and collaboration between businesses are emerging as new paradigms in the IT industry. In an environment where a large amount of data is generated in real time, such as SNS, big data processing techniques are useful in extracting the valid data. MapReduce is a good example of such a programming model used in big data extraction. With the growing collaboration between companies, problems of duplication and heterogeneity among data due to the integration of old and new information storage systems have arisen. These problems arise because of the differences in existing databases across the various companies. However, these problems can be negated by implementing the MapReduce technique. This paper proposes a collaboration system based on Database as a Service, or DBaaS, to solve problems in data integration for collaboration between companies. The proposed system can reduce the overhead in data integration, while being applied to structured and unstructured data.

• Journal of Korea Game Society
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• v.10 no.4
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• pp.73-80
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• 2010

This paper proposes an effective method to select MIP-Map level of texture images for ray-traced texture mapping. This MIP-Map level selection method requires only the total length of intersected ray. By supporting MIP-Map for texture mapping, we can reduce the texture aliasing effects, while our approach decreases rendering performance very slightly.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.122-125
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• 2014

본 논문에서는 실시간 모바일 클라우드 컴퓨팅(mobile cloud computing)을 위한 맵리듀스(Map Reduce) 응용 처리 기법으로써 데이터 전송 경로 관리, 노드(nod) 간 다른 처리 속도로 인한 문제점 개선을 통한 성능 향상 기법들과 맵리듀스 작업의 효과적인 반복적 및 스트리밍(streaming)실행 기법들을 분석한다.

• Food Science of Animal Resources
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• v.31 no.2
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• pp.147-157
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• 2011

Mycobacterium avium paratuberculosis (MAP), the cause of Johne's disease in animals, may be a causative agent of Crohn's disease (CD) in humans, but the evidence supporting this claim is controversial. Milk, meat, and water could be potential sources of MAP transmission to humans. Thus, if the link between MAP and Crohn's disease is substantiated, the fact that MAP has been detected in retail foods could be a public health concern. The purpose of the present study was to review the link between MAP and CD, the prevalence of MAP in foods, heat inactivation, control of MAP during food processing, and detection methods for MAP. Although MAP positive rates in retail milk in nine countries ranged from 0 to 2.9% by the culture method and from 4.5 to 15.5% by PCR, high temperature short time pasteurization can effectively control MAP. The effectiveness of pasteurization to inactivate MAP depends on the initial concentration of the MAP in raw milk. Development of highly sensitive and specific rapid detection methods for MAP may enhance investigation into the relationship between MAP and CD, the prevention of the spread of MAP, and problem-solving related to food safety. Collaboration and efforts by government agencies, the dairy industry, farmers, veterinarians, and scientists will be required to reduce and prevent MAP in food.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.991-1000
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• 2010

The Hierarchical Mobile IPv6 (HMIPv6) has been proposed to accommodate frequent mobility of the Mobile Node. HMIPv6 can effectively reduce the signaling overhead and latency. However, it has a problem that the registration of a mobile node concentrates on the furthest MAP(Mobility Anchor Point) when the mobile node enters into a new domain. This paper proposes a new load distribution mechanism by using the concept of Nash Bargaining Solution. The main advantage of the proposed scheme can prevent load concentration from being registered to the specified MAP based on the weight value according to the available resource-ratio of a MAP. With a simulation study, the proposed scheme can improve network performance under widely diverse traffic load intensities.