• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.415-435
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• 2019

The purpose of this study is to analyze the returns to scale by estimating the bigeye tuna production function of Korean distant longline fisheries in WCFPC waters. In the analysis, number of crews, vessel tonnage, number of hooks, and bigeye tuna biomass are used as input variables and the catch amount of bigeye tuna is used as an output variable in the Cobb-Douglas production function. Prior to the function estimation, the biomass of bigeye tuna was estimated by the Bayesian state-space model. Results showed that the fixed effect model was selected based on the hausman test, and vessel tonnage, hooks, and biomass would have direct effects on the catch amount. In addition, it was shown that the bigeye tuna distant longline fisheries in WCFPC water would have increasing returns to scale.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.2
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• pp.95-104
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• 2019

This study is aimed to take a stock assessment of blackthroat seaperch Doederleinia seaperch regarding the fishing effort of large-powered Danish Seine Fishery and Southwest Sea Danish Seine Fishery. For the assessment, the state-space model was implemented and the standardized catch per unit effort (CPUE) of large powered Danish Seine Fishery and Southwest Sea Danish Seine Fishery which is necessary for the model was estimated with generalized linear model (GLM). The model was adequate for stock assessment because its r-square value was 0.99 and root mean square error (RMSE) value was 0.003. According to the model with 95% confidence interval, maximum sustainable yield (MSY) of Blackthroat seaperch is from 2,634 to 6,765 ton and carrying capacity (K) is between 33,180 and 62,820. Also, the catchability coefficient (q) is between 2.14E-06 and 3.95E-06 and intrinsic growth rate (r) is between 0.31 and 0.72.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.676-692
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• 2018

Saliency detection in neurobiology is a vehement research during the last few years, several cognitive and interactive systems are designed to simulate saliency model (an attentional mechanism, which focuses on the worthiest part in the image). In this paper, a bottom up saliency detection model is proposed by taking into account the color and luminance frequency features of RGB, CIE $L^*a^*b^*$ color space of the image. We employ low-level features of image and apply band pass filter to estimate and highlight salient region. We compute the likelihood probability by applying Bayesian framework at pixels. Experiments on two publically available datasets (MSRA and SED2) show that our saliency model performs better as compared to the ten state of the art algorithms by achieving higher precision, better recall and F-Measure.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.347-360
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• 2020

In this study, the Bayesian state-space model was used for the stock assessment of the Blackfin flounder. In addition, effective measures for the resource management were presentedwith the analysis on the effectiveness of fisheries management plans. According to the result of the analysis using the Bayesian state-space model, the main biometric value of Blackfin flounder was analyzed as 1,985 tons for maximum sustainable yield (MSY), 23,930 tons for carrying capacity (K), 0.000007765 for catchability coefficient (q) and 0.31 for intrinsic growth (r). Also the evaluation on the biological effect of TAC was done. The result showed that the Blackfin flounder biomass will be kept at 14,637 tons 20 years later given the present TAC volume of 1,761 tons. If the Blackfin flounder TAC volume is set to 1,600 tons, the amount of biomass will increase to 16,252 tons in the future. Lastly, the biological effectiveness of the policy to reduce fishing effort was assessed. The result showed that the Blackfin flounder biomass will be maintained at 13,776 tons if the current fishing efforts (currently hp) level is set and maintained. If the fishing effort is reduced by 20%, it will increase to 17,091 tons in the future. The analysis on the economic effect of TAC showed that NPV will be the lowest at 1,486,410 won in 2038, 20 years after the establishment of 2,500 tons of TAC volume. If the TAC volume is set at 2,000 tons, NPV was estimated to be the highest at 2,206,522,000 won. In addition, the analysis on the economic effect of the policy to reduce the amount of fishing effort found that NPV will be 2,235,592,000 won in 2038, 20 years after maintaining the current level of fishing effort. If the fishing effort is increased by 10%, NPV will be the highest at 2,257,575 won even thoughthe amount of biomass will be reduced.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.2
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• pp.183-188
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• 2022

It is a difficult task to estimate parameters in even a simple stock assessment model such as a surplus production model, using only data about temporal catch-per-unit-effort (CPUE) (or survey index) and fishery yields. Such difficulty is exacerbated when time-varying parameters are treated as random effects (aka state variables). To overcome the difficulty, previous studies incorporated somewhat subjective assumptions (e.g., B₁=K) or informative priors of parameters. A key is how to build an objective joint prior of parameters, reducing subjectivity. Given the limited data on temporal CPUEs and fishery yields from 1999-2020 for common squid Todarodes pacificus, we built a joint prior of only two parameters, intrinsic growth rate (r) and carrying capacity (K), based on the resilience level of the population (Froese et al., 2017), and used a Bayesian state-space production assessment model. We used template model builder (TMB), a R package for implementing the assessment model, and estimating all parameters in the model. The predicted annual biomass was in the range of 0.76×10⁶ to 4.06×10⁶ MT, the estimated MSY was 0.13×10⁶ MT, the estimated r was 0.24, and the estimated K was 2.10×10⁶ MT.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.451-480
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• 2022

The Japanese Flying Squid (Todarodes pacificus) is a commercially important species in South Korea and the most popular species among consumers. However commercial catches of Japanese Flying Squid have been declining since 2000. In this study, we conducted a stock assessment to identify stock status. This study differed from previous studies in two aspects: a greater amount of available fishing effort data was used, and data from China, Japan, and Korea were included. A CMSY (catch-maximum sustainable yield) model was used to estimate MSY, biomass and exploitation with Bayesian state-space implementation of the Schaefer (BSS) model for the method of stock assessment, and evaluated the species by dividing into two groups, 'Korea' and ' Korea·China·Japan'. In all cases, Japanese flying squid biomass showed a general decreasing trend. Additionally, the biomass estimated for 2020 was lower than the biomass necessary to achieve the maximum sustainable yield. To manage Japanese Flying Squid effectively, it is necessary to strengthen the resource management strategies of individual countries and prepare a cooperative plan among countries.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.19-26
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• 1987

In analyzing time series, estimating the level or the current mean of the process plays an important role in understanding its structure and in being able to make forecasts. The studies the class of time series models where the level of the process is assumed to follow a random walk and the deviation from the level follow an ARMA process. The estimation and forecasting problem in a Bayesian framework and uses the Kalman filter to obtain forecasts based on estimates of level. In the analysis of time series, we usually make the assumption that the time series is generated by one model. However, in many situations the time series undergoes a structural change at one point in time. For example there may be a change in the distribution of random variables or in parameter values. Another example occurs when the level of the process changes abruptly at one period. In order to study such problems, the assumption that level follows a random walk process is relaxed to include a major level change at a particular point in time. The major level change is detected by examining the likelihood raio under a null hypothesis of no change and an alternative hypothesis of a major level change. The author proposes a method for estimation the size of the level change by adding one state variable to the state space model of the original Kalman filter. Detailed theoretical and numerical results are obtained for th first order autoregressive process wirth level changes.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.907-912
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• 2007

The present level of ubiquitous computing technology have developed to the point where Home-server provides services that user require directly for user in the intelligent space. But it will need intelligent system to provides more active services for user in the near future. In this paper, we define the environment information about situation that user is in as Context, and collect the Context that stereotype as 4W1H form for construct the system that can decision service will be provide from information about a situation that user is in, without user's involvement. Additionally we collect information about user's emotional state, use these informations as nodes of Bayesian network for probabilistic reasoning. From that, we materialize Context Awareness system about it that what kind of situation user is in. And, we propose the Context-based Service reasoning model using Bayesian Network from the result of Context Awareness.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.354-362
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• 2010

This paper proposes a new method for a hierarchical analysis of human gait by dividing the motion into gait direction and gait posture using the tool of dynamic Bayesian network. Based on Factorial HMM (FHMM), which is a type of DBN, we design the Gait Motion Decoder (GMD) in a circular architecture of state space, which fits nicely to human walking behavior. Most previous studies focused on human identification and were limited in certain viewing angles and forwent modeling of the walking action. But this work makes an explicit and separate modeling of pedestrian pose and posture to recognize gait direction and detect orientation change. Experimental results showed 96.5% in pose identification. The work is among the first efforts to analyze gait motions into gait pose and gait posture, and it could be applied to a broad class of human activities in a number of situations.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.3
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• pp.175-181
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• 2020

For the success of a structural integrity management, it is essential to acquire structural response data at some critical locations with limited number of sensors. In this study, the structural response of numerical model was estimated by data fusion approach based on the Kalman filter known as stochastic recursive filter. Firstly, transient direct analysis was conducted to calculate the acceleration and strain of the numerical standing beam model, then the noise signals were mixed to generate the numerical measurement signals. The acceleration measurement signal was provided to the Kalman filter as an information on the external load, and the displacement measurement, which was transformed from the strain measurement by using strain-displacement conversion relationship, was provided into the Kalman filter as an observation information. Finally, the Kalman filter estimated the displacement by combining both displacements calculated from each numerically measured signal, then the estimated results were compared with the results of the transient direct analysis.