• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2259-2277
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• 2023

We propose a probabilistic fish growth model for smart aquaculture systems equipped with IoT sensors that monitor the ecological environment. As IoT sensors permeate into smart aquaculture systems, environmental data such as oxygen level and temperature are collected frequently and automatically. However, there still exists data on fish weight, tank allocation, and other factors that are collected less frequently and manually by human workers due to technological limitations. Unlike sensor data, human-collected data are hard to obtain and are prone to poor quality due to missing data and reading errors. In a situation where different types of data are mixed, it becomes challenging to develop an effective fish growth model. This study explores the unique characteristics of such a combined environmental and weight dataset. To address these characteristics, we develop a preprocessing method and a probabilistic fish growth model using mixed data sampling (MIDAS) and overlapping mixtures of Gaussian processes (OMGP). We modify the OMGP to be applicable to prediction by setting a proper prior distribution that utilizes the characteristic that the ratio of fish groups does not significantly change as they grow. We conduct a numerical study using the eel dataset collected from a real smart aquaculture system, which reveals the promising performance of our model.

• Tunnel and Underground Space
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• v.12 no.3
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• pp.189-197
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• 2002

In recent years, the probabilistic analysis has been used in rock slope engineering. This is because uncertainty is pervasive in rock slope engineering and most geometric and geotechnical parameters of discontinuity and rock masses are involved with uncertainty. Whilst the traditional deterministic analysis method fails to properly deal with uncertainty, the probabilistic analysis has advantages quantifying the uncertainty in parameters. As a probabilistic analysis method, the Monte Carlo simulation has been used commonly. However, the Monte Carlo simulation requires many repeated calculations and therefore, needs much effort and time to calculate the probability of failure. In contrast, the point estimate method involves a simple calculation with moments for random variables. In this study the probability of failure in rock slope is evaluated by the point estimate method and the results are compared to the probability of failure obtained by Monte Carlo simulation method.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2221-2229
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• 2020

After the Fukushima Daiichi nuclear power plant (NPP) accident, level 3 probabilistic safety assessment (PSA) has emerged as an important task in order to assess the risk level of the multi-unit NPPs in a single nuclear site. Accurate calculation of the radionuclide concentrations and exposure doses to the public is required if a nuclear site has multi-unit NPPs and large number of people live near NPPs. So, there has been a great need to develop a new method or procedure for the fast and accurate offsite consequence calculation for the multi-unit NPP accident analysis. Since the multi-unit level 3 PSA is being currently performed assuming that all the NPPs are located at the same position such as a center of mass (COM) or base NPP position, radionuclide concentrations or exposure doses near NPPs can be drastically distorted depending on the locations, multi-unit NPP alignment, and the wind direction. In order to overcome this disadvantage of the COM method, the idea of a new multiple location (ML) method was proposed and implemented into a new tool MURCC (multi-unit radiological consequence calculator). Furthermore, the MURCC code was further improved for the multi-unit level 3 PSA that has the arbitrary number of multi-unit NPPs. The objectives of this study are to (1) qualitatively and quantitatively compare COM and ML methods, and (2) demonstrate the strength and efficiency of the ML method. The strength of the ML method was demonstrated by the applications to the multi-unit long-term station blackout (LTSBO) accidents at the four-unit Vogtle NPPs. Thus, it is strongly recommended that this ML method be employed for the offsite consequence analysis of the multi-unit NPP accidents.

• ETRI Journal
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• v.36 no.5
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.505-511
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• 2018

Long term capacity expansion planning has to be carried out to satisfy pre-defined system reliability criterion. For purpose of assessing system reliability, probabilistic simulation technique has been widely adopted. However, the way how to approximate generator outage, especially maintenance outage, in probabilistic simulation scheme can significantly influence on reliability assessment. Therefore, in this paper, 3 different maintenance approximation methods are applied to investigate the quantitative impact of maintenance approximation method on long term capacity expansion planning.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.119-131
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• 1988

Vehicle Scheduling Problem (VSP) is a generic name given to a whole class of problems involving the visiting of "stations" by "vehicles," where a time is associated with each activity. The studies performed to date have the common feature of a single objective while satisfying a set of restrictions and known customer supplies or demands. However, VSPs may involve relevant multiple objectives and probabilistic supplies or demands at stations, creating multicriteria stochastic VSPs. This paper proposes a heuristic algorithm based on goal programming approach to schedule the most satisfactory vehicle routes of a bicriteria VSP with probabilistic supplies at stations. The two relevant objectives are the minimization of the expected travel distance of vehicles and the minimization of the due time violation for collection service at stations by vehicles. The algorithm developed consists of three major stages. In the first stage, an artificial capacity of vehicle is determined, on the basis of decision maker's subjective estimates. The second one clusters a set of stations into subsets by applying an efficient cluster method developed. In the third one, the stations in each subset are scheduled by applying an iterative goal programming heuristic procedure to each cluster.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.61-69
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• 2001

We present a probabilistic reasoning method for inferring knowledge about mathematical truth before an automated theorem prover completes a proof. We use a Bayesian analysis to update beleif in truth, given theorem-proving progress, and show how decision-theoretic methods can be used to determine the value of continuing to deliberate versus taking immediate action in time-critical situations.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1234-1239
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• 2011

The scan matching is widely used in localization and mapping of mobile robots. This paper presents a probabilistic scan matching method. To improve the performance of the scan matching, a direction of data point is incorporated into the scan matching. The direction of data point is calculated using the line fitted by the neighborhood data. Owing to the incorporation, the performance of the matching was improved. The number of iterations in the scan matching decreased, and the tolerance against a high rotation between scans increased. Based on real data of a laser range finder, experiments verified the performance of the proposed direction augmented probabilistic scan matching algorithm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2495-2500
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• 1994

A method of prediction for the fatigue life of surface crack, that is, initial cracks grow and penetrate through the thickness, was presented in the previous study of the author. Effects of parameters such as the initial crack length, material factors, etc., for the life were discussed. In this paper, the probabilistic distribution of the life is calculated. Effects of the distribution of parameters for the distribution of life were also discussed.

• Computers and Concrete
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• v.21 no.4
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• pp.419-429
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• 2018

Climate changes, such as increasing of $CO_2$ concentration and global warming, will impact on the carbonation service life of concrete structures. Moreover, slag blended concrete has a lower carbonation resistance than control concrete. This study presents a probabilistic numerical procedure for evaluating the impact of climate change on carbonation service life of slag blended concrete. This numerical procedure considers both corrosion initiation period and corrosion propagation period. First, in corrosion initiation period, by using an integrated hydration-carbonation model, the amount of carbonatable substances, porosity, and carbonation depth are calculated. The probability of corrosion initiation is determined through Monte Carlo method. Second, in corrosion propagation period, a probabilistic model is proposed to calculate the critical corrosion degree at surface cracking, the probability of surface cracking, and service life. Third, based on the service life in corrosion initiation period and corrosion propagation period, the whole service life is calculated. The analysis shows that for concrete structures with 50 years service life, after considering climate changes, the service life reduces about 7%.