• 전자공학회논문지A
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• 제31A권6호
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• pp.159-168
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• 1994

Stochastic computation is adopted to reduce the silicon area of the multipliers in implementing neural network in VLSI. In addition to this advantage, the stochastic computation has inherent random errors which is required for implementing Boltzmann machine. This random noise is useful for the simulated annealing which is employed to achieve the global minimum for the Boltzmann Machine. In this paper, we propose a method to implement the Boltzmann machine with stochastic computation and discuss the addition problem in stochastic computation and its simulated annealing in detail. According to this analysis Boltzmann machine using stochastic computation is suitable for the pattern recognition/completion problems. We have verified these results through the simulations for XOR, full adder and digit recognition problems, which are typical of the pattern recognition/completion problems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.666-668
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• 1998

In this paper we illustrate the design of a node label data flow machine based on self-timed paradigm. Data flow machines differ from most other parallel architectures, they are based on the concept of the data-driven computation model instead of the program store computation model. Since the data-driven computation model provides the excution of instructions asynchronously, it is natural to implement a data flow machine using self timed circuits.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.146-158
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• 2023

Smart City is gaining attention with the advancement of Information and Communication Technology (ICT). ICT provides the basis for smart city foundation; enables us to interconnect all the actors of a smart city by supporting the provision of seamless ubiquitous services and Internet of Things. On the other hand, Crowdsourcing has the ability to enable citizens to participate in social and economic development of the city and share their contribution and knowledge while increasing their socio-economic welfare. This paper proposed a hybrid model which is a compound of human computation, machine computation and citizen crowds. This proposed hybrid model uses knowledge-based crowdsourcing that captures collaborative and collective intelligence from the citizen crowds to form democratic knowledge space, which provision solutions in areas of civic innovations. This paper also proposed knowledge-based crowdsourcing framework which manages knowledge activities in the form of human computation tasks and eliminates the complexity of human computation task creation, execution, refinement, quality control and manage knowledge space. The knowledge activities in the form of human computation tasks provide support to existing crowdsourcing system to align their task execution order optimally.

• 한국산학기술학회논문지
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• 제11권6호
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• pp.2202-2206
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• 2010

본 논문에서는 FSM(finite-state machine)을 이용하여 차수 계산(degree computation)을 하지 않고 수정된 유클 리드 알고리즘(modified Euclidean algorithm)을 구현할 수 있는 구조를 제안한다. 제안된 구조는 차수계산이 필요없기 때문에 RS(Reed-Solomon) 복호기의 하드웨어 복잡도를 줄일 수 있고, 고속의 복호기 설계가 가능하게 된다. 제안된 구조를 이용하는 RS(255,239) 복호기를 Verilog HDL로 구현하였고, 기존의 복호기에 비해 게이트 수를 약 13%정도 줄일 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3482-3497
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• 2021

Artificial intelligence has emerged as the core of the 4th industrial revolution, and large amounts of data processing, such as big data technology and rapid data analysis, are inevitable. The most fundamental and universal data interpretation technique is an analysis of information through regression, which is also the basis of machine learning. Ridge regression is a technique of regression that decreases sensitivity to unique or outlier information. The time-consuming calculation portion of the matrix computation, however, basically includes the introduction of an inverse matrix. As the size of the matrix expands, the matrix solution method becomes a major challenge. In this paper, a new algorithm is introduced to enhance the speed of ridge regression estimator calculation through series expansion and computation recycle without adopting an inverse matrix in the calculation process or other factorization methods. In addition, the performances of the proposed algorithm and the existing algorithm were compared according to the matrix size. Overall, excellent speed-up of the proposed algorithm with good accuracy was demonstrated.

• 융합보안논문지
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• 제13권4호
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• pp.19-25
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• 2013

백본(코어) 네트워크에서 유연하고 안정적인 품질이 보장되는 서비스 제공에 대한 요구가 폭발적으로 증가하면서 이러한 요구를 수용하기 위해 제어평면의 프로토콜로 MPLS/GMPLS가 도입되었다. GMPLS 기반 제어평면에서 경로계산 및 상호연동 기능은 최적의 서비스 품질을 제공하기 위한 핵심기술 중의 하나이다. 이를 위해 IETF에서는 Path Computation Element (PCE) 구조를 제안하였다. PCE는 경로계산 전용의 네트워크 요소이며 경로계산을 요청하는 Path Computation Clients (PCC) 와 경로계산을 수행하는 PCE 간의 통신은 PCE 프로토콜 (PCEP)을 이용한다. 본 논문은 PCE 기반 경로계산 구조에 대해서 살펴보고 이를 기반으로 PCEP 설계 및 구현을 위한 몇 가지 요소를 제시하였다. 우선 본 논문에서는 PCEP Finite State Machine (FSM)을 포함하여 각 상태에서 필요한 동작 요소를 정리하였다. 또한 본 논문에서는 PCEP에서 제공하는 통신 채널을 효과적으로 제어하기 위한 내부/외부 인터페이스를 더불어 제안하였다.

• 한국지능시스템학회논문지
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• 제11권7호
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• pp.579-583
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• 2001

In the area of data clustering in high dimensional space, one of the difficulties is the time-consuming process for computing vector similarities. It becomes worse in the case of the agglomerative algorithm with the group-average link and mean centroid method, because the cluster similarity must be recomputed whenever the cluster center moves after the merging step. As a solution of this problem, we present an incremental method of similarity computation, which substitutes the scalar calculation for the time-consuming calculation of vector similarity with several measures such as the squared distance, inner product, cosine, and minimum variance. Experimental results show that it makes clustering speed significantly fast for very high dimensional data.

• 전자공학회논문지C
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• 제34C권1호
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• pp.28-41
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• 1997

This paper describes a parallel implementation of a neurla network ensemble developed for object recognition on the connection machine CM-2. The implementation ensures that multiple networks are implemented simultaneously starting from different initial weights and all training samples are applied to each network by one sample per a copy of each network. When compared with a sequential implementation, this accelerates the computation speed by O(N.m.n) where N, m, and n are the network, respectively. The speedup in the computation time and the convergence characteristics of sthe modified backpropagation learning precedure were evaluated by two-dimensional object recognition problem.

• 산업경영시스템학회지
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• 제18권35호
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• pp.107-114
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• 1995

This paper proposes the Tabu Search algorithm to minimize mean tardiness in the parallel machine scheduling problem. The algorithm reduces the computation time by employing restricted neighborhood and produces an efficient solution in this problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권2호
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• pp.566-579
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• 2012

Ubiquitous computing called pervasive one is based on the thought of pervading ability of computation in daily life applications. In other words, it aims to include computation in devices such as electronic equipment and automobiles. This has led to disengagement of computers from desktop form. Accordingly, the notice in ubiquitous computing being taken of a world steeped in remote and wireless computer-based-services. Handheld and wearable programmed devices such as sense and control appliances are such devices. This advancement is rapidly moving domestic tasks and life from device-and-human communication to the device-and-device model. This model called Machine to Machine (M2M) has led to acceleration of developments in sciences such as nano-science, bio-science, and information science. As a result, M2M led to appearance of applications in various fields such as, environment monitoring, agricultural, health care, logistics, and business. Since it is envisaged that M2M communications will play a big role in the future in all wireless applications and will be emerged as a progressive linkage for next-generation communications, this paper aims to consider how much M2M architectures can realize ubiquitous computing in daily life applications. This is carried out after acquainting and initiating readers with M2M architectures and arguments for M2M. Some of the applications was not achievable before but are becoming viable owing to emergence of M2M communications.