• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.53 no.3
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• pp.256-265
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• 2017

Seafood is attracting attention as a future food industry. In recent years, the demand for fishery equipment of mechanization, automation, and unmanned was increased due to the environment affected by seafood processing, stricter regulations on safety, decline and aging of fishery worker. Ark shell (Scapharca subcrenata) was being produced in many steps in the production process. The process has been made such as collection-landing-washing-first sort (goods/non-goods)-transports-second sort (size). It was undergone first and second steps by delivering to the consumer. Here, the first step is to sort goods to collection and the second step is to sort by size. The fishery workers need ten people in first step and six people in second step. The workload of one hour per kg is 4,247 kg/h in first step and 2,213 kg/h in second step. In addition, the goods ratio by work process was 79% in first step and 98% in the second step. In this process, a lot of fishery worker and working time is needed. Therefore, this study developed elemental techniques for an automated size sorting system considering the working process problem, time and situation for washing and sorting of ark shell.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.325-330
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• 2004

The Big O notation of a sorting algorithm analysis is an asymptotic algorithm analysis which gives information of a rough mathematical function with an infinite increase of a sample size, without any specification of a probabilistic model. Hence. in an application with a limited finite number of data, it is necessary to test efficiencies of sorting algorithms. I estimated probabilistic models which analyze the number of exchanges varying input sizes to sort. The estimated models to explain the relationship of sorting efficiency on the sample size (N of the sample size and S of the number of exchange of elements) are S=0.9305 $N^{1.339}$ for Quick sort algorithm with O(nlogn) time complexity, and S=0.2232 $N^{2.0130}$ for Insertion sort algorithm with O( $n^2$) time complexity. Furthermore, there are strongly supports that more than 99% of the above relationship could be explained by the estimated models (p＜0.001). These findings suggest it is necessary to analyze sorting algorithm efficiency in applications with a finite number of data or a newly developed sorting algorithm.

• Journal of Advanced Navigation Technology
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• v.15 no.2
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• pp.281-286
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• 2011

Data sorting is one of important pre-process to utilize huge data in modern society, but sorting spends a lot of time by sorting itself. In this paper, we presented hybrid sorting algorithm that splits array to sort concurrently in CPU and GPU. To do this, we decided most effective range of array based on hardware performance, then accomplished reducing whole sorting time by concurrent sorting on CPU and GPU. As shown in results of experiment, hybrid sorting improved about eight percent of sorting time in comparison with the sorting time using only GPU.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.2
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• pp.208-214
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• 2008

This paper presents a structural modification for the performance improvement of a grain sorting machine. The grain sorting machine is used to sort abnormal grains from normal grains such as rice or wheat. Vibration is one of main causes to deteriorate the sorting performance of the machine. Based on the finite element analysis and the experimental modal testing, the vibration characteristics were investigated for the sorting machine. Furthermore, in order to improve the sorting performance of the machine, the frame, chute and base plate of the sorting machine were modified by using the results of the vibration analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.566-576
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• 2017

Key-value stores proved its superiority by being applied to various NoSQL databases such as Redis, Memcached. Lookup performance is important because key-value store applications performs more lookup than insert operations in most environments. However, in traditional applications, lookup may be slow because hash tables are constructed out of linked-list. Therefore, cuckoo hashing has been getting attention from the academia for constant lookup time, and bucketized cuckoo hashing (BCH) has been proposed since it can achieve high load factor. In this paper, we introduce Sorting Cuckoo which inserts data using insertion sort in BCH structure. Sorting Cuckoo determines the existence of a key with a relatively small memory access because data are sorted in each buckets. In particular, the higher memory load factor, the better lookup performance than BCH's. Experimental results show that Sorting Cuckoo has smaller memory access than BCH's as many as about 19 million (25%) in 10 million negative lookup operations (key is not in the table), about 4 million times (10%) in 10 million positive lookup operations (where it is) with load factor 95%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.185-192
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• 1998

A new algorithm is proposed in this paper which efficiently performs join in the temporal database. The main idea is to sort the smaller relation and to partition the larger relation, and the proposed algorithm reduces the cost of sorting the larger relation. To show the usefulness of the algorithm, the cost is analyzed with respect to the number of accesses to secondary storage and compared with that of Sort-Merge algorithm. Through the comparisons, we present and verify the conditions under which the proposed algorithm always outperforms the Sort-Merge algorithm. The comparisons show that the proposed algorithm achieves 10∼30% gain under those conditions.

• The Journal of Korean Association of Computer Education
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• v.6 no.3
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• pp.1-8
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• 2003

In this paper, I proposed a sort algorithm named Information Block Sort Algorithm(IBSAl which is not influenced on distribution of data in the list and has time complexity of O(NlogN). Also I evaluated the IBSA using a simulator. Performance analysis shows that, in case of sorting randomly generated two millions data, the number of actual comparisons has taken place about 36% of the number of comparisons in the improved Quick sort algorithm and 22% in Quick sort algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.888-894
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• 2007

The computational complexity of a sphere decoder (SD) is conventionally reduced by decoding order scheme which sorts candidate symbols in the ascending order of the Euclidean distance from the output of a zero-forcing (ZF) receiver. However, since the ZF output may not be a reliable sorting reference, we propose two types of sorting schemes to allow faster decoding. The first is to use the newly found lattice points in the previous search round instead of the ZF output (Type I). Since these lattice points are closer to the received signal than the ZF output, they can serve as a more reliable sorting reference for finding the maximum likelihood (ML) solution. The second sorting scheme is to sort candidate symbols in descending order according to the number of candidate symbols in the following layer, which are called child symbols (Type II). These two proposed sorting schemes can be combined with layer sorting for more complexity reduction. Through simulation, the Type I and Type II sorting schemes were found to provide 12% and 20% complexity reduction respectively over conventional sorting schemes. When they are combined with layer sorting, Type I and Type II provide an additional 10-15% complexity reduction while maintaining detection performance.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.671-679
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• 2018

Sorting algorithms are the basic building blocks that computer science students need to learn. In recent years, sorting algorithms also have begun to be taught in K-12 classrooms using "the educational sorting game" described in CSUnplugged. However, although the educational sorting game was developed for students aged 8 and up, it is hard for K-12 teachers to play with their students because it is difficult for teachers to understand all of the algorithms and some popular algorithms do not work well in the educational sorting game. In this paper, we discuss what teachers should know, and experimentally analyze the performance of the existing algorithms when applied to the educational sorting game.

• The Journal of Fisheries Business Administration
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• v.49 no.4
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• pp.19-36
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• 2018

Overstock in aquaculture is a matter of concern in aquaculture management. To sort fish based on fingerling size in case of overstocking is an important problem in aquaculture farm. This study aims to determine the amount of fry overstock and sorting time in aquaculture farm. This study builds a mathematical model that finds the value of decision variables to optimize objective function summing up the fingerling purchasing cost, aquaculture farm operating cost and feeding cost under mortality and farming period constraints. The proposed mathematical model involves following biological and economical variables and coefficients: (1) number of fingerlings, (2) sorting time, (3) fish growth rate and variation, (4) mortality, (5) price of a fry (6) feeding cost, and (7) possible sorting periods. Numerical simulation is presented herein. The objective of numerical simulation is to provide decision makers to analyse and comprehend the proposed model. When extensive biological data about growth function of fry becomes available, the proposed model can be widely applicable to real aquaculture farms.