• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.59 no.2
• /
• pp.99-109
• /
• 2023

In this study, a comparative test operation was conducted through the alternate haul method to examine the selectivity of the four mesh sizes (60 mm, 90 mm, 110 mm, and 130 mm) of the trawl codend. The selectivity was analyzed using the SELECT model considering the fishing efficiency (split parameter) of each fishing gear in the comparative test fishing operation in the trawl and the maximum likelihood method for parameter estimation. A selectivity master curve was estimated for several mesh sizes using the extended-SELECT model. As a result of analyzing the selectivity for silver croaker based on the results of three times hauls for each experimental gear, it was found that the size of the fish caught increased as the size of the mesh size increased. When the selectivity for each mesh size analyzed by the SELECT model considering the split ratio was evaluated based on the size of the AIC value, the estimated split model was superior to the equal split model. Based on the master curve, the 50% selection length value was 2.893, which was estimated to be 136 mm based on the mesh size of 60 mm. In some selectivity models, there was a large deviance between observed and theoretical values due to the non-uniformity of the distribution of fished length classes. As a result, it is considered that appropriate sea trials and selectivity evaluation methods with high reliability should be applied to present trawl fishery resource management methods.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.58 no.1
• /
• pp.1-9
• /
• 2022

In this study, the selection action on the mesh in the net pot for whelk (Buccinum opisthoplectum) is experimentally considered, and the selectivity was compared by the SELECT model and the Nashimoto's method with the probability model according to the contact shape of the mesh and the whelk. The experiments of the mesh size selectivity was conducted for two mesh sizes: 70 mm (inner stretched size 65.4 mm) and 44 mm (inner stretched size 39.5 mm). Selectivity experiments were conducted three times in total for each mesh size used 264 whelks. In addition, Nashimoto's method analyzed the retention probability using probability model for whether the mesh passed or not based on the carapace width of the whelk. As a result of the selectivity analysis, the 50% selection carapace width for the mesh size of 70 mm was similar to 43.62 mm in the SELECT model and 42.64 mm in the Nashimoto's method. However, the 44 mm mesh with relatively small mesh size showed differences of 40.01 mm and 26.80 mm, respectively. As for the mesh size selectivity of whelk, it was found that the smaller the mesh size, the lower the selectivity. In addition, in the selectivity study on the mesh size of whelk, an evaluation method that closely considers the contact shape between the mesh and the target species is required.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.48 no.1
• /
• pp.10-19
• /
• 2012

The mesh selectivity of a drift net for yellow croaker (Larimichthys polyactis) was examined in field experiments with six different net mesh size (40, 45, 50, 55, 60 and 65mm) from April to December, 2008 in the coastal areas of Jeollanam-do in Korea. The total catch of 6,748 consisted of yellow croaker (n=6,310; 89.1% of total catch), common mackerel (n=158; 5.6%) and other species (n=280; 9.6%). The selectivity curve for yellow croaker was fit by the models of selectivity curve in SELECT method. The optimal mesh size for 50% retention for minimum landing size (191mm) of yellow croaker was estimated as 49.6mm-51mm by selectivity curves. And the bi-normal model for the selectivity curve was found to fit the data best.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.721-725
• /
• 2004

Multiple-count problem is occurred when rectangle objects span across several buckets. The Cumulative Density (CD) histogram is a technique which solves multiple-count problem by keeping four sub-histograms corresponding to the four points of rectangle. Although it provides exact results with constant response time, there is still a considerable issue. Since it is based on a query window which aligns with a given grid, a number of errors may be occurred when it is applied to real applications. In this paper, we proposed selectivity estimation techniques using the generalized cumulative density histogram based on two probabilistic models: (1) probabilistic model which considers the query window area ratio, (2) probabilistic model which considers intersection area between a given grid and objects. In order to evaluate the proposed methods, we experimented with real dataset and experimental results showed that the proposed technique was superior to the existing selectivity estimation techniques. The proposed techniques can be used to accurately quantify the selectivity of the spatial range query on rectangle objects.

• International Journal of Human Ecology
• /
• v.4 no.2
• /
• pp.77-87
• /
• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• Fisheries and Aquatic Sciences
• /
• v.11 no.1
• /
• pp.61-69
• /
• 2008

Using empirical data of fish performance and physiological limits as well as physical stimuli and environmental data, a cod-end selectivity model based on a chaotic behavior model using the psycho-hydraulic wheel and neural-network approach was established to predict fish escape or herding responses in trawl and cod-end designs. Fish responses in the cod-end were categorized as escape or herding reactions based on their relative positions and reactions to the net wall. Fish movements were regulated by three factors: escape time, a visual looming effect, and an index of body girth-mesh size. The model was applied to haddock in a North Sea bottom trawl including frequencies of movement components, swimming speed, angular velocity, distance to net wall, and the caught-fish ratio; simulation results were similar to field observations. The ratio of retained fish in the cod-end was limited to 37-95% by optomotor coefficient values of 0.3-1.0 and to 13-67% by looming coefficient values of 0.1-1.0. The selectivity curves generated by this model were sensitive to changes in mesh size, towing speed, mesh type, and mesh shape.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.51 no.4
• /
• pp.535-544
• /
• 2015

Yield per recruit model is the most popular method for fisheries stock assessment. However, stock assessment using yield per recruit model can lead to recruitment overfishing as this model only considers the maximum yield per recruit without spawning biomass for reproduction. For this reason, spawning biomass per recruit model which reveals variations of spawning stock biomass per fishing mortality (F) and age at first capture ($t_c$) is considered as more proper method for stock assessment. There are mainly two methods for spawning biomass per recruit model known as age specific selectivity method and knife-edged selectivity method. In the knife-edged selectivity method, the spawning biomass per recruit has been often calculated using biomass per recruit value by multiplying the maturity ratio of the recruited age. But the maturity ratio in the previous method was not considered properly in previous studies. Therefore, a new method of the knife-edged selectivity model was suggested in this study using a weighted average of the maturity ratio for ages from the first capture to the lifespan. The optimum fishing mortality in terms of $F_{35%}$ which was obtained from the new method was compared to the old method for small yellow croaker stock in Korea. The value of $F_{35%}$ using the new knife-edged selectivity model was 0.302/year and the value using the old model was 0.349/year. However, the value of $F_{35%}$ using the age specific selectivity model was estimated as 0.320/year which was closer to the value from the new knife-edged selectivity model.

• Korean Journal of Chemical Engineering
• /
• v.35 no.11
• /
• pp.2157-2163
• /
• 2018

Catalytic reactors have been essential for chemical engineering process, and different designs of reactors in multi-scales have been previously studied. Computational fluid dynamics (CFD) utilized in reactor designs have been gaining interest due to its cost-effective advantage in designing the actual reactors before its construction. In this work, butadiene synthesis via oxidative dehydrogenation (ODH) of n-butene using tubular reactor was used as a case study in the CFD model. The effects of coolant and reactor diameter were investigated in assessing the reactor performance. Based on the results of the CFD model, the conversion and selectivity were 86.5% and 59.5% respectively in a fixed bed reactor under adiabatic condition. When coolants were used in a tubular reactor, reactor temperature profiles showed that solar salt had lower temperature gradients inside the reactor than the cooling water. Furthermore, higher conversion (90.9%) and selectivity (90.5%) were observed for solar salt as compared to the cooling water (88.4% for conversion and 86.3% for selectivity). Meanwhile, reducing the reactor diameter resulted in smaller temperature gradients with higher conversion and selectivity.

• Fisheries and Aquatic Sciences
• /
• v.7 no.3
• /
• pp.163-170
• /
• 2004

A fishing simulator for towed fishing gear was investigated in order to mimic the fish behavior in capture process and investigate fishing selectivity. A fish behavior model using a psycho-hydraulic wheel activated by stimuli is established to introduce Lorenz chaos equations and a neural network system and to generate the components of realistic fish capture processes. The fish positions within the specified gear geometry are calculated from normalized intensities of the stimuli of the fishing gear components or neighboring fish and then these are related to the sensitivities and the abilities of the fish. This study is applied to four different towed gears i.e. a bottom trawl, a midwater trawl, a two-boat seine, and an anchovy boat seine and for 17 fish species as mainly caught. The Alpha cluster computer system and Fortran MPI (Message-Passing Interface) parallel programming were used for rapid calculation and mass data processing in this chaotic behavior model. The results of the simulation can be represented as animation of fish movements in relation to fishing gear using Open-GL and C graphic programming and catch data as well as selectivity analysis. The results of this simulator mimicked closely the field studies of the same gears and can therefore be used in further study of fishing gear design, predicting selectivity and indoor training systems.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.59 no.3
• /
• pp.189-195
• /
• 2023

This study quantitatively evaluated size selectivity for three netting shapes (T0; regular, T45, T90) and hanging ratio (35%, 70%) of T0 netting used for trawl codend. The size selectivity experiment was performed in a tank using a cube experimental model with a length of 50 cm on one side and 389 experimental individuals, jack mackerel (Trachurus japonicus). In the selectivity analysis, a selectivity curve was created based on the selection ratio using a logistic function, and the 25%, 50%, and 70% selection length and selection range (SR) were obtained. The T0 netting was 19.54 cm when the 50% selective length, which is a selectivity evaluation index, had a hanging ratio of 35%, a selection range of 0.51 cm, and 22.70 cm and 3.08 cm for the hanging ratio of 70%. The T45 netting was 24.34 cm and 2.13 cm, and the T90 netting was 23.51 cm and 2.84 cm. The results of the T45 netting and the T90 netting are similar, and the 50% selection length and selection range were relatively larger than the T0 netting. There was a significant difference in the correlation between the circumference of the inner circle of the mesh by the shape of the netting and the body girth of the experimental individual (Pearson test, r = 0.86, p < 0.05). There was no significant difference in the correlation between the selection ratio by the T0 netting, T45 netting, and T90 netting with a 70% hanging ratio (one-way ANOVA, p > 0.05). The results of this study showed that selectivity such as T45 netting and T90 netting appeared when the hanging ratio, which maximizes the area of T0 netting, was maintained at 70%.