• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4357-4378
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• 2017

In cooperative multi-relay networks, the relay nodes which are selected are very important to the system performance. How to choose the best cooperative relay nodes is an optimization problem. In this paper, multi-relay selection schemes which consider either single objective or multi-objective are proposed based on evolutionary algorithms. Firstly, the single objective optimization problems of multi-relay selection considering signal to noise ratio (SNR) or power efficiency maximization are solved based on the quantum bee colony optimization (QBCO). Then the multi-objective optimization problems of multi-relay selection considering SNR maximization and power consumption minimization (two contradictive objectives) or SNR maximization and power efficiency maximization (also two contradictive objectives) are solved based on non-dominated sorting quantum bee colony optimization (NSQBCO), which can obtain the Pareto front solutions considering two contradictive objectives simultaneously. Simulation results show that QBCO based multi-relay selection schemes have the ability to search global optimal solution compared with other multi-relay selection schemes in literature, while NSQBCO based multi-relay selection schemes can obtain the same Pareto front solutions as exhaustive search when the number of relays is not very large. When the number of relays is very large, exhaustive search cannot be used due to complexity but NSQBCO based multi-relay selection schemes can still be used to solve the problems. All simulation results demonstrate the effectiveness of the proposed schemes.

• Journal of Biosystems Engineering
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• v.19 no.2
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

• Proceedings of the Korean Institute of Resources Recycling Conference
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• 2005.05a
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• pp.57-61
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• 2005

In this study, the machine vision system for inspection using color recognition method have been designed and developed to automatically sort out a specified material such as Cu scraps or other non-ferrous metal scraps mixed in Fe scraps. The system consists of a CCD camera, light sources, a frame grabber, conveying devices and an air nozzled ejector, and is program-controlled by a image processing algorithm. The ejector is designed to be operated by an I/O interface communication with a hardware controller. The sorting examination results show that the efficiency of separating Cu scraps from the Fe scraps mixed with Cu scraps is around 90 % at the conveying speed of 15 m/min. and the system is proven to be excellent in terms of its efficiency. Therefore, it is expected that the system can be commercialized in shredder firms, if the high-speed automated sorting system will be realized.

• Korean Journal of Agricultural Science
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• v.27 no.1
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• pp.48-53
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• 2000

The various errors existing in a weight measurement system in most automatic egg sorting system available in Korean poultry farms have caused a large amount of economic losses to the egg producers. The object of this study was an importance of egg measurement system by changing both the number and the arrangements of load cells to reduce measuring errors. The results obtained were summarized as follow : 1. Four arrangements of load cells were selected as follows : layout I : Conventional one load cell method layout II : One load cell located as egg moving direction layout III : Two load cells located facing each other layout IV : Two load cells located as parallel with egg moving direction 2. The results of egg weight measurement according to four arrangements (Layout I, II, III, IV) showed that the average errors were 1.1218g, 0.5953g, 0.7786g, 0.2793g respectively. This indicated that the Layout IV (measuring by 2 load cells located parallel with the egg moving direction) caused the lowest average error and the best in precision. 3. The average vibration of axis X, y, Z were resulted as $5.1937{\times}10^{-3}G$, $9.3604{\times}10^{-3}G$, and $16.8657{\times}10^{-3}G$ respectively when sorting large sized egg. This indicated that the vibration of axis-Z was relatively higher than those of axis-X, and axis-Y.

• Land and Housing Review
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• v.1 no.1
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• pp.35-42
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• 2010

Most of the dredged sand generated from the sewage pipe maintenance project and the government's four-river project are disposed depending on abandonment and filling-up. This is caused by the lack of related recycling technology using dredged sand appropriately and high absorption rate and micro-particles of dredged sand producted from existing sand production system. Thus, this study carried out a quality assessment for the dredged sand produced through the optimum washing and sorting system supplementing problems of existing dredged sand production system as a part of research to examine performance of removing micro-particles and foreign substances. As a result of the assessment, the dredged sand produced through the cleaning and sorting system showed a wide quality improvement effect in absorption rate, 0.08 mm sieve pass amount, clay lump volume and organic impurity content, and it turned out to satisfy both the quality standards of this study, KS F 2573(recycled aggregate for concrete) and KS F 2526(aggregate for concrete) so it could be confirmed that it would be able to be used as an aggregate for concrete in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1681-1688
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• 2017

In this paper, we implemented a high-speed signal processing hardware system for Color Line Scan Camera using FPGA and Nor-Flash. The existing hardware system mainly processed by high-speed DSP based on software and it was a method of detecting defects mainly by RGB individual logic, however we suggested defect detection hardware using RGB-HSL hardware converter, FIFO, HSL Full-Color Defect Decoder and Image Frame Buffer. The defect detection hardware is composed of hardware look-up table in converting RGB to HSL and 4K HSL Full-Color Defect Decoder with high resolution. In addition, we included an image frame for comprehensive image processing based on two dimensional image by line data accumulation instead of local image processing based on line data. As a result, we can apply the implemented system to the grain sorting machine for the sorting of peanuts effectively.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1267-1267
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• 2001

The existing fruit sorter has the method of tilting tray and extracting fruits by the action of solenoid or springs. In peaches, the most sort processing is supported by man because the sorter make fatal damage to peaches. In order to sustain commodity and quality of peach non-destructive, non-contact and real time based sorter was needed. This study was performed to develop peach sorter using near-infrared spectroscopy in real time and nondestructively. The prototype was developed to decrease internal and external damage of peach caused by the sorter, which had a way of extracting tray with it. To decrease positioning error of measuring sugar contents in peaches, fiber optic with two direction diverged was developed and attached to the prototype. The program for sorting and operating the prototype was developed using visual basic 6.0 language to measure several quality index such as chlorophyll, some defect, sugar contents. The all sorting result was saved to return farmers for being index of good quality production. Using the prototype, program and MLR(multiple linear regression) model, it was possible to estimate sugar content of peaches with the determination coefficient of 0.71 and SEC of 0.42bx using 16 wavelengths. The developed MLR model had determination coefficient of 0.69, and SEP of 0.49bx, it was better result than single point measurement of 1999's. The peach sweetness grading system based on NIR reflectance method, which consists of photodiode-array sensor, quartz-halogen lamp and fiber optic diverged two bundles for transmitting the light and detecting the reflected light, was developed and evaluated. It was possible to predict the soluble solid contents of peaches in real time and nondestructively using the system which had the accuracy of 91 percentage and the capacity of 7,200 peaches per an hour for grading 2 classes by sugar contents. Draining is one of important factors for production peaches having good qualities. The reason why one farm's product belows others could be estimated for bad draining, over-much nitrogen fertilizer, soil characteristics, etc. After this, the report saved by the peach grading system will have to be good materials to farmers for production high quality peaches. They could share the result or compare with others and diagnose their cultural practice.

• Journal of Biosystems Engineering
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• v.40 no.4
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• pp.327-334
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• 2015

Purpose: A falling-type weight sorter equipped with a load cell was developed to sort lightweight dried persimmons. The performance of the sorter was also evaluated. Methods: The electronic weight sorter for dried persimmon comprises a feeder part, a weight-measurement part, an indicator part, a carrier cup, a discharging part, and a driving part. The weight setting and zero-point adjustment are performed digitally for the convenience of users. For the experimental trials, 228 rubber-clay specimens (representative of dried persimmons) in the weight range of 24.73~99.56 g were manufactured for use in experiments to evaluate the performance of the sorter. Results: The average error of the weight measurements from three experimental trials was 1.655%, with a bias of -0.492 g, a root-mean-square error (RMSE) of ${\pm}0.808g$, and a coefficient of determination ($R^2$ ) of 0.997. Conclusions: The load-cell-based electronic dried-persimmon weight sorter developed in this study facilitates effective, precise, and convenient sorting of dried persimmons.

• The Korean Journal of Physiology and Pharmacology
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• v.12 no.4
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• pp.199-204
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• 2008

KIF1B${\beta}$ is a member of the Kinesin superfamily proteins (KIFs), which are microtubule-dependent molecular motors that are involved in various intracellular organellar transport processes. KIF1B${\beta}$ is not restricted to neuronal systems, however, is widely expressed in other tissues, even though the function of KIF1B${\beta}$ is still unclear. To elucidate the KIF1B${\beta}$-binding proteins in non-neuronal cells, we used the yeast two-hybrid system, and found a specific interaction of KIF1B${\beta}$ and the sorting nexin (SNX) 17. The C-terminal region of SNX17 is required for the binding with KIF1B${\beta}$. SNX17 protein bound to the specific region of KIF1Bf3 (813-916. aa), but not to other kinesin family members. In addition, this specific interaction was also observed in the Glutathione S-transferase pull-down assay. An antibody to SNX17 specifically co-immunoprecipitated KIF1B${\beta}$ associated with SNX17 from mouse brain extracts. These results suggest that SNX17 might be involved in the KIF1B${\beta}$-mediated transport as a KIF1B${\beta}$ adaptor protein.

• International Journal of Contents
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• v.4 no.1
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• pp.20-25
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• 2008

The development of communication technology and the spread of computers and internet have affected to the field of education. In this paper, we design a learning process with LAMS to make the new education environment which is required in an information age. We made the learning environment with LAMS which develops the learner's algorithmic thinking faculty on some sorting algorithm, especially such as selection sort, bubble sort and insertion sort algorithm. In addition, we analyse the effectiveness of the learning environment. The designed contents were applied to elementary school students' learning and a questionnaire survey was conducted after a learning course. The research of the questionnaire shows that the learning system using LAMS motivates a learner for learning and provides a convenient learning environment.