• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2037-2042
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• 2017

The manufacturing facility is generally operated by a pre-set program under the existing factory automation system. On the other hand, the manufacturing facility must decide how to operate autonomously in Industry 4.0. Determining the operation mode of the production facility itself means, for example, that it detects the abnormality such as the deterioration of the facility at the shop-floor, prediction of the occurrence of the problem, detection of the defect of the product, In this paper, we propose a manufacturing process modeling using a queue for detection of manufacturing process abnormalities at the shop-floor, and detect abnormalities in the modeling using SVM, one of the machine learning techniques. The queue was used for M / D / 1 and the conveyor belt manufacturing system was modeled based on ${\mu}$, ${\lambda}$, and ${\rho}$. SVM was used to detect anomalous signs through changes in ${\rho}$.

• Journal of the Korean Statistical Society
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• v.32 no.3
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• pp.311-311
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• 2003

This paper contains the following errors. 1. "$I_{\{x>D\}}{\lambda}dt_{p0}(t)s(x)$" should be added to the right hand side of (2.3). 2. "$I_{\{x>D\}}{\lambda}_{p0}(t)s(x)$" should be added to the right hand side of (2.6). 3. "$I_{\{x>D\}}{\lambda}_{p0}s(x)$" should be added to the right hand side of (2.9). 4. In Theorem 2.3 and its proof, "${\lambda}{\int}_{0}^{D}f(y)s(x-y)dy$" appears three times (including one in (2.20)). To each of these, "${\lambda}_{po}s(x)$" should be added. 5. In Remark 2.5, "${\lambda}dt_{p0}/s(x)dx" should be added to "${\int}_{0}^{D}{\lambda}dt\;s(x-y)dxf(y)dy$". As a result of these corrections, a simpler proof of Theorem 2.3 becomes available. Substituting (2.18), (2.21), (2.22) into the left hand side of (2.20) and comparing the result with (2.10), we have the right hand side of (2.20).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.3-11
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• 2005

This paper presents a performance analysis model based on an M/M/1 queue and Poisson distribution of input data traffic. The simulation on a pipelined AES system with processing rate of 10 rounds per clock shows $4.0\%$ higher performance than a non-pipelined version consuming 10 clocks per transaction. Physical implementation of pipelined AES with FPGA takes 3.5 times bigger gate counts than the non-pipelined version whereas the pipelined version yields only $3.5\%$ performance enhancement. The proposed analysis model can be used to optimize cost-performance of AES hardware designs.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.1-10
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• 2008

In this paper, a packet scheduling algorithm, called the modified PLFS, is proposed for real-time traffic in IEEE 802.22 WRAN systems. The modified PLFS(Packet Loss Fair Scheduling) algorithm utilizes not only the delay of the Head of Line(HOL) packets in buffer of each user but also the amount of expected loss packets in the next-next frame when a service will not be given in the next frame. The performances of the modified PLFS are compared with those of PLFS and M-LWDF in terms of the average packet loss rate and throughput. The simulation results show that the proposed scheduling algorithm performs much better than the PLFS and M-LWDF algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1206-1218
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• 1992

Token ring systems which control to switch the data stream of networks by passing the token have been widely used to medium access controls in many ring or bus topology LANs. The system could be modeled for analysis as single-server-multi-queue system of the cyclic service method. These concepts could be expanded to multi-token ring systems interconnected with single ring consisting of bridges implemented simply to be stored and transmitted. In the proposal for the performance analysis of the interconnected token ring system, in has been assumed M/G/1 queueing model that frame arrivals are the Poisson process at each station queue and frame sizes are independently and identically distributed. And the average time delays were analyzed mathematically for arbitrary frame transferred from source station to destination area. The time delay of the frame transmission could be explained as the sum of the average time which the token passed from arbitrary position to source station, such as the waiting time in the source station transferring the previous arrival frames, and the propagation time from source station to interdestinated point. These delays were given as the sum of the duration from inner and outer bridge queues, the time delays from inner and outer bridge queues, and the time from outer bridge queue to destination station. These results were investigated by varing parameters effected to total time delays. In the results, those factors to be effected to dominant the total time delays were increased were in the cases of the high arrival rates and the high ration of destination of the other outerring. The system were shown the time delays increased exponentially in spite of the priority service policy. In order to decreasing the number of outerrings and increasing the number of nodes in backbone relatively, so the systems could be decreased the total delay in the interconnected token ring system.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1162-1171
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• 1998

This paper presents a data structure that implements a mergable double-ended priority queue : namely an improved relaxed min-max-pair heap. By means of this new data structure, we suggest a parallel algorithm to merge priority queues organized in two relaxed heaps of different sizes, n and k, respectively. This new data-structure eliminates the blossomed tree and the lazying method used to merge the relaxed min-max heaps in [9]. As a result, employing max($2^{i-1}$,[(m+1/4)]) processors, this algorithm requires O(log(log(n/k))${\times}$log(n)) time. Also, on the MarPar machine, this method achieves a 35.205-fold speedup with 64 processors to merge 8 million data items which consist of two relaxed min-max heaps of different sizes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1093-1100
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• 2006

본 연구는 D-정책을 갖는 BMAP/G/1 대기행렬 시스템의 일량(workload) 및 대기시간(waiting time)을 분석한다. 유휴한 서버는 도착하는 고객들의 서비스 시간의 총합이 주어진 임계점 D를 넘어야만 서비스를 시작한다. 고객의 도착과정은 집단마코비안도착과정(BMAP, Batch Markovian Arrival Process)을 따른다. 본 논문에서는 이러한 시스템의 일량 및 대기시간에 대한 LST를 구하고, 이로부터 평균일량 및 평균대기시간을 유도한다. 또한 BMAP/G/1의 특별한 경우인 $M^X/G/1$인 경우와 대기시간의 비교를 행한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1320-1328
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• 2007

In recent year, the popularity of WLAN has generated much interests on improvement and performance analysis of the IEEE 802.11 protocol. In this paper, we analyze two medium access methods of the IEEE 802.11 MAC protocol by investigating the MAC layer packet service times when arrival packet sizes have a general probability distribution. We use the M/G/1/K queueing model to analyze the throughput and the delay performance of IEEE 802.11 MAC protocol in a wireless LAN. We compare the performances of Basic access method and RTS/CTS access method. We take some numerical examples for the system throughput and the queue dynamics including the mean packet delay and packet blocking probability.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.4
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• pp.297-302
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• 2005

Kopzon and Weiss adopted the notion of push-pull into the queueing system recently. We extend this queueing system to the ($N_1,N_2$)-policy version such that the original system corresponds to the special case $N_1=N_2=1$. For the extended system, we perform the cycle analysis and obtain the PGF of the stationary number of customers in the system.

• Korean Management Science Review
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• v.27 no.1
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• pp.17-31
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• 2010

Patients entering an emergency care center in a hospital usually visit medical processes in different orders depending on the urgency level and the medical treatments required. We formulate the patient flows among diverse processes in an emergency care center using the Jackson network, which is one of the queueing networks, in order to evaluate the system performances such as the expected queue length and the expected waiting time. We present a case study based on actual data collected from an emergency care center in a hospital, in order to prove the validity of applying the Jackson network model in practice. After assessing the current system performances, we provide operational strategies to reduce waiting at the bottleneck processes and evaluate the impact of those strategies on the entire system.