• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권1호
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• pp.31-36
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• 2015

많은 불확실성 항목들은 소프트웨어 실행 시에 존재한다. 특히, 유사한 분야에서 전반적인 시스템에 많은 영향을 주게 된다. 불확실성 요소와 같은 모호성 요소의 관리는 소프트웨어 신뢰성을 위하여 중요한 요소가 된다. 따라서 모호성을 식별하여 불확실성 요소를 제거하도록 판단기준을 프로세스화 하였다. 또한 본 연구에서는 소프트웨어 개발 시, 모호성을 제거하기 위한 불확실성 식별 기준과 불확실성 처리 프로세스 및 정량적인 평가에 대하여 제시한다.

• Management Science and Financial Engineering
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• 제21권1호
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• pp.1-9
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• 2015

We consider an m-machine flow shop scheduling problem to minimize the latest completion time, where processing times are uncertain. Processing time uncertainty is described through a finite set of processing time vectors. The objective is to minimize maximum deviation from optimality for all scenarios. Since this problem is known to be NP-hard, we consider it with an ordered property. We discuss optimality properties and develop a pseudo-polynomial time approach for the problem with a fixed number of machines and scenarios. Furthermore, we find two special structures for processing time uncertainty that keep the problem NP-hard, even for two machines and two scenarios. Finally, we investigate a special structure for uncertain processing times that makes the problem polynomially solvable.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 춘계학술발표대회
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• pp.373-376
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• 2021

Deep neural networks have achieved almost human-level results in various tasks and have become popular in the broad artificial intelligence domains. Uncertainty estimation is an on-demand task caused by the black-box point estimation behavior of deep learning. The deep ensemble provides increased accuracy and estimated uncertainty; however, linearly increasing the size makes the deep ensemble unfeasible for memory-intensive tasks. To address this problem, we used model pruning and quantization with a deep ensemble and analyzed the effect in the context of uncertainty metrics. We empirically showed that the ensemble members' disagreement increases with pruning, making models sparser by zeroing irrelevant parameters. Increased disagreement implies increased uncertainty, which helps in making more robust predictions. Accordingly, an energy-efficient compressed deep ensemble is appropriate for memory-intensive and uncertainty-aware tasks.

• 한국기후변화학회지
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• 제7권4호
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• pp.407-419
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• 2016

The low flow is the necessary and important index to establish national water planning, however there are lots of uncertainty in the low flow estimation. Therefore, the objectives of this study are to assess the climate change uncertainty and the effects of hydrological models on low flow estimation. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods and 2 hydrological models were applied for evaluation. The study area were selected as Chungju dam and Soyang river dam basin, and the 30 days minimum flow is used for the low flow evaluation. The results of the uncertainty analysis showed that the hydrological model was the largest source of uncertainty about 41.5% in the low flow projection. The uncertainty of hydrological model is higher than the other steps (RCM, statistical post-processing). Also, VIC model is more sensitive for climate change compared to SWAT model. Therefore, the hydrological model should be thoroughly reviewed for the climate change impact assessment on low flow.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 학술대회지
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• pp.729-734
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• 2004

The e-Logistics means the virtual business activity and service architecture among the logistics companies based on the Internet technology. The management of vehicles' location in most conventional vehicle tracking system has some critical defects when it deals with data which are continuously changed. It means the conventional vehicle tracking system based on the conventional database is unable eventually to cope with the environment that should manage the frequently changed location of vehicles. The important things in the evaluation of the vehicle tracking system is to determine the threshold of cost of database ,update period and communication period between vehicles and the system. In other words, the difference between the reallocation of vehicle and the data in database can evaluate the overall performance of vehicle tracking systems. Most of the previous works considers only the information that is valid at the current time, and is hard to manage efficiently the past and future information. To overcome this problem, the efforts on moving objects management system(MOMS) and uncertainty processing have been started from a few years ago. In this paper, we propose an uncertainty processing model and system implementation of moving object that tracks the location of the vehicles. We adopted both linear-interpolation method and trigonometric function to chase up the location of vehicles for the past time as well as future time, respectively. We also explain the comprehensive examples of MOMS and uncertainty processing in parcel application that is one of major application of e-Logistics domain.

• Management Science and Financial Engineering
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• 제10권2호
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• pp.1-28
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• 2004

The integrated supply chain of business partners for e-Commerce in cyber space is defined as Logistics Chain if the cooperative activities are logistics-related. Logistics Chain could be managed effectively and efficiently by cooperative technologies of logistics chain execution. In this paper, we propose a routing and scheduling algorithm based on the Tabu search by adding geographical information into existing constraint for pick-up and delivery process to minimize service time and cost in logistics chain. And, we also consider an uncertainty processing for the tracing of moving object to control pick-up and delivery vehicles based on GPS/GIS/ITS. Uncertainty processing is required to minimize amount of telecommunication and database on vehicles tracing. Finally, we describe the Logistics Chain Execution (LCE) system to perform plan and control activities for postal logistics chain. To evaluate practical effects of the routing and scheduling system, we perform a pretest for the performance of the tabu search algorithm. And then we compare our result with the result of the pick-up and delivery routing plan generated manually by postmen.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.331-343
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• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Asia Marketing Journal
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• 제14권4호
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• pp.57-75
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• 2013

It is a well-established theory that emotion is influential in cognitive processing. Extensive prior research on emotion has shown that emotional factors, such as affect, mood, and feeling, play as information indicating whether he or she has enough knowledge. Most of their findings focused on the effect of emotional valence (i.g., one's subjective positivity or negativity related with the emotion). Recently, several studies on emotion suggest that there is another dimension of emotion, which affects the type of cognitive processing. The studies argue that emotional certainty facilitates heuristic processing, whereas emotional uncertainty promotes systematic processing. Based on the findings, current study examines the effect of certainty on attitudes and recall. Specifically, the authors investigate the effect of certainty on how much effort individuals use to process advertising information and how certainty affects attitude formation toward the advertised product. The authors also focus on recall to clarify the working mechanism of certainty on attitudes, because recall performance reflects the depth of information processing. Based on previous findings, the authors hypothesize that uncertainty (vs. certainty) leads to more favorable attitudes as well as better recall, and conduct an experiment using a fictitious advertisement with 218 participants. The results confirm the predicted effects of certainty only on attitudes not recall. A possible explanation of this discrepancy between attitudes and recall lies in the measurement method, unaided recall. To rule out this possibility, the authors perform an additional analysis with the participants who recall any correct information of the target advertisement. The results show certainty has a negative effect on both attitudes and recall. A bootstrapping test reveals that recall mediates the effect of certainty on attitudes. This result confirms that certainty decreases elaboration, which in turn leads to less favorable attitudes relative to uncertainty. Additionally, our data shows the association among certainty, recall, and attitudes by showing the indirect effect of certainty on attitudes via recall. This research encourages practitioners in the field to emphasize that they should focus on target audiences' emotional certainty before they provide the persuasive message, by showing that uncertainty promotes effortful processing, which in turn leads to better memory and more favorable attitudes.

• 품질경영학회지
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• 제45권3호
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• pp.533-547
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• 2017

Purpose: This study proposes the main sources of uncertainty and uncertainty analysis of a measurement system of insensitive munitions tests. Methods: We established the mathematical model for calculating measurement uncertainty of insensitive munitions tests, conducted experiments for calculating uncertainties of dynamic sensitivity and overshoot value, and estimated the distributions of uncertainty factors. Results: The measurement uncertainty calculation methods are presented, which include experimental data processing methods for calculating uncertainties of dynamic sensitivity and overshoot value. Conclusion: The measurement of explosion pressure in insensitive munitions tests is an important issue to the reporting test results and classifying reaction types. The more efforts to ensure the reliability of the insensitive munitions tests results are required.

• 한국정보과학회논문지:데이타베이스
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• 제33권3호
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• pp.261-270
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• 2006

위치기반서비스에서 이동체의 위치 데이타 수집 비용을 줄이기 위하여 위치 데이타를 주기적으로 수집한다. 주기적으로 수집된 위치 데이타는 보고 주기 사이의 위치 변화를 반영하지 못하기 때문에 시간에 대한 선형 함수를 이용하여 예측된 위치 데이타와 오차가 발생한다. 따라서 오차를 포함한 불확실한 미래위치데이타로 인하여 TPR 트리에서 현재위치질의의 정확도가 떨어지는 문제점이 발생한다. 이 논문에서는 불확실한 위치 데이타에 대한 현재질의를 처리하기 위하여 선형 함수에 의해 예측된 위치 데이타에 오차분을 반영한 불확실성 영역을 정의하고 불확실성 영역을 설정하기 위하여 최근 예측 오차 가중치 기법과 칼만 필터 기법을 제시한다. 또한 TPR 트리를 기반으로 불확실성 영역을 반영한 질의 처리기를 구현하고 성능 비교 평가를 수행한다. 성능 평가 결과에 따르면 기존의 선형함수 기반 질의처리 기법보다 불확실성 영역 기반 질의처리 기법이 최소 약 15% 이상의 정확도가 향상되는 장점을 가진다.