• 한국기계가공학회지
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• 제20권4호
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• pp.119-126
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• 2021

During the development of a weapon system, the concept of maintainability is used for quantitatively predicting and analyzing the maintenance time. However, owing to the complexity of a weapon system, the standard maintenance time predicted during the system's development differs significantly from the measured time during the operation of the equipment after the system's development. According to the analysis presented in this paper, the maintenance time can be predicted by considering the system's complexity on the basis of the military specifications, and the procedure can be Part B of Procedure II and Method B of Procedure V. The maintenance work elements affected by the system complexity were identified by the analytic hierarchy process technique, and the system-complexity-reflecting weights of the maintenance work elements were calculated by the Delphi method, which involves expert surveys. Based on MIL-HDBK-470A and MIL-HDBK-472, it is going to present a Korean-style maintainability prediction method that reflects system complexity of weapons systems.

• 한국인터넷방송통신학회논문지
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• 제15권6호
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• pp.311-319
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• 2015

본 논문에서는 산업공장 내의 생산 효율을 높이기 위하여 제조공정 자원을 예측하고 위험 관리를 효율적으로 이행하는 자원예측 및 위험관리를 위한 의사결정 시스템을 제안하였다. 각 공정에서 발생되는 다양한 정보들을 효율적으로 관리하는 세부 공정별 시나리오 생성이 어렵고, 동일한 공정 내에서도 다양한 제품의 생산하기 위해 제조 설비의 조건 변경이 빈번하다. 제품의 생산 주기 또한 일정하지 않아 연속되지 않은 데이터가 발생하여 소량의 데이터로 변동을 확인해야 하는 문제점이 있다. 이러한 문제점을 해결하기 위해서는 제조공정의 데이터 일원화, 공정 자원 예측, 위험 예측, 공정 현황 모니터링을 통하여 문제 발생시 즉각 조치가 가능하여야 한다. 본 논문에서는 설계도면 변경 범위, 자원 예측, 공정 완료 예정일을 회귀알고리즘을 이용하여 수식을 도출하였으며, 분류 트리 기법, 경계값 분석을 통하여 3단계로 의사결정 시스템을 제안하였다.

• ETRI Journal
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• 제27권5호
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• pp.511-524
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• 2005

In this paper, we propose a novel hardware architecture for an intra-prediction, integer transform, quantization, inverse integer transform, inverse quantization, and mode decision module for the macroblock engine of a new video coding standard, H.264. To reduce the cycle of intra prediction, transform/quantization, and inverse quantization/inverse transform of H.264, a reduction method for cycle overhead in the case of I16MB mode is proposed. This method can process one macroblock for 927 cycles for all cases of macroblock type by processing $4{\times}4$ Hadamard transform and quantization during $16{\times}16$ prediction. This module was designed using Verilog Hardware Description Language (HDL) and operates with a 54 MHz clock using the Hynix $0.35 {\mu}m$ TLM (triple layer metal) library.

• 대한기계학회논문집
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• 제17권9호
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• pp.2271-2279
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• 1993

In the case of life prediction on the structures and machines after long service, it is natural to consider a degradation problems. Most of degradation data form practical structures are isolated data obtained at the time of periodical inspection or repair. From such data, it may be difficult to obtain the degradation curve available and necessary for life prediction. In this paper, for the purpose of obtaining a degradation curves, developed the simulate degradation method and fatigue test and Charpy impact test were conducted on the degraded, simulate degraded and recovered materials. Fatigue life prediction were conducted by using the relationship between fracture transition temperature (DBTT : vTrs) obtained from the Charpy impact test through the degradation process and fatigue crack growth constants of m and C obtained from the fatigue test.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 가을 학술발표회 논문집
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• pp.201-208
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• 2000

In this study, the behavior of saturated sandy soils under dynamic loads - pore water pressure and effective stress - was investigated using Disturbed State Concept(DSC) model. The model parameters are evaluated from laboratory test data. During the process of loading and reverse loading, DSC model is utilized to trace strain-hardening and cyclic softening behavior. The procedure of back prediction proposed in this study are verified by comparing with laboratory test results. From the back prediction of pore water pressure and effective mean pressure under cyclic loading, excess pore water pressure increases up to initial effective confining pressure and effective mean pressure decrease close to zero in good greement with laboratory test results. Those results represent the liquefaction of saturated sandy soils under dynamic loads. The number of cycles at initial liquefaction using the model prediction is in good agreement with laboratory test results. Therefore, the results of this study state that the liquefaction of saturated sandy soils can be explained by the effective tress analysis.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.91-94
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• 2003

H.264/AVC is the upcoming video coding standard of ITU-T H.264 and ISO MPEG-4 AVC. The new standard can achieve a significant improvement up to 50％ in compression ratio compared to MPEG-4 advanced simple profile. In this paper, we propose the novel intra prediction scheme to speed up intra prediction process in H.264/AVC decoder and show the hardware architecture for it. The proposed scheme uses the concurrent processing of the 4$\times$4 intra prediction, which is based on that some 4$\times$4 block pairs in a 16$\times$16 luma block can be processed concurrently. The proposed scheme can reduce intra prediction time by 33 ％.

• ETRI Journal
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• 제34권5호
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• pp.753-758
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• 2012

As the next-generation video coding standard, High Efficiency Video Coding (HEVC) has adopted advanced coding tools despite the increase in computational complexity. In this paper, we propose a selective bi-prediction method to reduce the encoding complexity of HEVC. The proposed method evaluates the statistical property of the sum of absolute differences in the motion estimation process and determines whether bi-prediction is performed. A performance comparison of the complexity reduction is provided to show the effectiveness of the proposed method compared to the HEVC test model version 4.0. On average, 50% of the bi-prediction time can be reduced by the proposed method, while maintaining a negligible bit increment and a minimal loss of image quality.

• 해양환경안전학회지
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• 제4권1호
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• pp.31-40
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• 1998

Through the combination of existing tidal prediction model and numerical tidal model, the efficient tidal prediction system was formulated and applied to the neighboring area of Pusan port. Because all tidal constituents for tidal prediction (69 tidal constituents are normally used) couldn't be considered due to the physical limits on computing process, some errors between the observed and predicted values were inevitably occurred. But it was confirmed that the computed values with maximum 10% of relative errors can be obtained if four major tidal constituents(M2, S2, K1, O1) are used. Thus, if other constituents than four major tidal constituents are additionally used, more accurate values will be obtained. Furthermore, if the database for harmonic constants in coastal waters is made in advance, using the numerical tidal model, prompt tidal prediction can be achieved at any time when it is required.

• International journal of advanced smart convergence
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• 제10권4호
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• pp.104-109
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• 2021

In the aftermath of the global pandemic that started in 2019, there have been many changes in the import/export and supply/demand process of agricultural products in each country. Amid these changes, the necessity and importance of each country's food self-sufficiency rate is increasing. There are several conditions that must accompany efficient agricultural activities, but among them, temperature is by far one of the most important conditions. For this reason, the need for high-accuracy climate data for stable agricultural activities is increasing, and various studies on climate prediction are being conducted in Korea, but data that can visually confirm climate prediction data for farmers are insufficient. Therefore, in this paper, we propose an artificial intelligence-based temperature prediction algorithm that can predict future temperature information by collecting and analyzing temperature data of farms in Gyeonggi-do in Korea for the last 10 years. If this algorithm is used, it is expected that it can be used as an auxiliary data for agricultural activities.

• 정보과학회 논문지
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• 제44권10호
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• pp.1026-1033
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• 2017

본 논문은 계층적 디리슐레 과정(HDP)과 은닉 마르코프 모형(HMM)이 결합된 베이스 통계학적 방법과 HMM의 상태 지속 정보를 이용한 건강 상태 예측 방법을 제안한다. HDP-HMM은 베이스 방법의 HMM 확장 모형으로서 건강의 동적 특성을 고려하여 불확실하고 가늠하기조차도 어려운 건강 상태의 수를 추정할 수 있게 해준다. 모의 데이터와 실제 건건 검진 데이터를 이용한 시험을 통하여 흥미 있는 행동 특성을 볼 수 있었으며 최대 5년까지로 제한한 미래 예측도 충분한 가능함을 확인하였다. 미래는 불확실하며 예측 문제는 본질적으로 어렵다. 그러나 본 연구의 실험 결과로 동적인 문맥 하에서 다중 후보 가설을 제시함으로서 실용 가능한 건강상태의 장기 예측이 가능하다는 것을 읽을 수 있었다.