• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.493-495
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• 2008

캐시 에너지의 소비 전력을 줄이기 위해 필터 캐시가 제안되었다. 필터 캐시의 사용으로 인해 많은 전력 사용 감소 효과를 가져왔으나, 상대적으로 시스템 성능도 더불어 감소하게 되었다. 필터 캐시의 사용으로 인한 성능 감소를 최소화하기 위해서, 본 논문에서는 기존에 제안된 주요 필터 캐시 예측 모델들을 소개하며, 각각의 방식에 있어서의 핵심 특징 및 해당 방식의 문제점을 분석한다. 이를 바탕으로 본 논문에서는 모드 선택 비트를 활용하는 개선된 형태의 새로운 필터 캐시 예측기 모델을 제안한다. 제안된 방식은 MSB라 불리는 참조 비트를 고안하여, 이를 기존의 필터캐시와 BTB에 새롭게 활용한다. 실험 결과, 제안된 방식은 기존 방식 대비, 전력 소모량 시간 지연면에서 평균 5%의 성능 향상을 가져 왔다.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.67-72
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• 2022

Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.

• Korean Journal of Culture and Social Issue
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• v.16 no.4
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• pp.447-468
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• 2010

The purpose of this study was to attain a clearer understanding of the reciprocal effects of deviant self-concept and delinquent behaviors by applying a latent state-trait autoregressive modeling approach. Although traditional autoregressive cross-lagged (ARCL) modeling has been widely applied to test the longitudinal reciprocal relationship between the two constructs, it could produce misspecified findings if there were trait-like processes involved in this relationship. The latent state-trait autoregressive(LST-AR) modeling was applied to control trait effects of deviant self-concept and to examine the reciprocal causal relations between the two constructs. Data were taken from a sample of 3,449 eighth graders who were followed annually for 5 years from the Korea Youth Panel Study. The combining LST-AR model with ARCL model substantiated the reciprocal effects of deviant self-concept and delinquent behaviors, even after the stable trait component of deviant self-concept was taken into account. The present findings shed lights on the reciprocal effects of behaviors (i.e., delinquency) and self concepts (i.e., deviant self-concept). Not only did behaviors change corresponding self-concept, but the ways adolescents perceived themselves influenced their behaviors.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.575-582
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• 2000

Because FIFO thread scheduling used in the existing multithreaded models does not consider locality in programs, it may result in the decrease of the performance of execution, caused by the frequent context switching overhead and delay of execution of relatively short frames. Quantum unit scheduling enhances the performance a little, but it still has the problems such as the decrease in the processor utilization and the longer delay due to its heavy dependency on the priority of the quantum units. In this paper, we propose shortest-frame-first(SFF) thread scheduling algorithm. Our algorithm selects and schedules the frame that is expected to take the shortest execution time using thread size and synchronization information analyzed at compile-time. We can estimate the relative execution time of each frame at compile-time. Using SFF thread scheduling algorithm on the multithreaded models, we can expect the faster execution, better utilization of the processor, increased throughput and short waiting time compared to FIFO scheduling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.736-742
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• 2003

This paper presents the propagation path loss in a tunnel which is a kinds of underground environments. To predict propagation path loss more accurately, we choose a straight tunnel with rectangular cross-section. The simulated receiver powers that are using a hybrid waveguide model and a Ray-Tracing method, are compared with the measured ones as a function of distance between TX and RX antennas in tunnel. The attenuation value of regression analysis for measured power in the tunnel is 0.0238dB/m which is similar to the one of the EH1.2 mode, 0.0246dB/m in hybrid waveguide model. By comparing simulation with measurement in tunnels, it has been shown that the measured values are approximate to the simulated results of ray-tracing model. In the analysis of wide-band channel characteristics of the tunnel, the more the distance between TX and RX antennas in tunnel increases, RMS delay spread increases and coherence bandwidth decreases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.929-935
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• 2008

As internet telephony services based on Session initiation Protocol (SIP) enter the spotlight as marketable technology, many products based on SIPs have been developed and utilized for home and office telephony services. The call connection of an internet phone is classified into specific call connections and group call connections. Group call connections have a forking function which delivers the message to all of the group members. This function requires excessive message control for a call connection and creates heavy traffic in the network. In the internet cail system model. most of the call-setup messages are directed to the proxy server during a short time period. This heavy message load brings an unwanted delay in message processing and. as a result, call setup can not be made. To solve the delay problem, we simplified the analysis of the call-setup message in the proxy server, and processed the forking function distributed for the group call-setup message. In this thesis, a new system model to minimize the load is proposed and the subsequent implementation of this model demonstrates the performance improvement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.229-240
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• 2012

The development of multimedia applications followed by development of high-speed networks has improved the performance of mobile devices with high transfer speed broadband. Mobile internet access has made possible seamless indoor and outdoor mobile multicast services. Multicasting services are used to support efficient group communications. However, mobile multicasting services have two constraints: tunnel convergence and handover latency. Many protocols and handover methods have been proposed to address these problems. The inter-LMA optimized handover model for multicasting services has previously been proposed for PMIPv6-based networks. The proposed model removes the tunnel convergence issue and reduces router processing costs. It also makes possible the performance of fast handover operations with adaptive transmission mechanisms. In addition, the proposed scheme exhibits low packet delivery costs and handover latency in comparison with existing schemes, and ensures fast handover when moving the inter-LMA domain

• Korean Journal of Construction Engineering and Management
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• v.6 no.6 s.28
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• pp.142-151
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• 2005

On public constructions, that the first planed projects delay than the scheduled completion day occurrence frequently because gap between the scheduled construction durations and the actual construction durations. These facts connect with not only problems of the construction during as the construction delay but also brought about the distribution costs increase as the failure of facility use plan and the people discomfort weight, failure of the production and the supply using facility then tremendous loss of each part etc. For reduce these loss, it must improve accuracy of the scheduled construction duration estimating when it order. This study try contribute to a successful manage of public project and reduce the construction duration extension frequent of the construction during, and then ensure the suitable construction duration by present the estimation model of the scheduled construction duration that include the construction duration correct element using as an index on the scheduled construction duration estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1058-1065
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• 2008

In the Internet, as computer resource is developed, multimedia data request being increase more and more. It is effective way that process both high capacity-data and real-time data. Overlay Multicast is an effective method for efficient utilization of system resources and network bandwidth without using hardware customization. Overlay Multicast is an effective method for multimedia data service to multi-users. Multicast tree reconstruction is required when a non-leaf host leaves or fails. In this paper, relay-frame interval is selected as revealed network-state with jitter. In our proposal, multi-user service control algorithm gives a delay effect in multimedia request time. The simulation results show that our proposal takes shorter period of time than the other algorithms to reconstruct a similar tree and that it is a more effective way to deal with a lot of nodes that have lost their multi-user nodes.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.99-110
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• 2019

As the 4th industrial revolution progressing, manufacturers are trying to apply intelligent information technologies such as IoT(internet of things) and machine learning. In the semiconductor/LCD/tire manufacturing process, schedule plan that minimizes setup change and due date violation is very important in order to ensure efficient production. Therefore, in this paper, we suggest the deep learning based scheduling generation model minimizes setup change and due date violation in parallel machines. The proposed model learns patterns of minimizing setup change and due date violation depending on considered order using the amount of historical data. Therefore, the experiment results using three dataset depending on levels of the order list, the proposed model outperforms compared to priority rules.