• The Mathematical Education
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• v.43 no.3
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• pp.309-314
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• 2004

A standardized scoring system for college interview entrance examination means we standardize the score of examination to adjust the degree of difficulty among questions and difference of panel's disposition. A standardized scoring system were newly enforced at college interview entrance examination from 2001. Colleges want to choose the most suitably qualified students, taking full advantage of interview examination. Also they should always prepare for questions, plan the answers and a standardized scoring system so that all candidates get a fair shake. The main purpose of this paper is to provide a standardized scoring system for interview examination. The results of interview examination are ranked from highest to lowest and each candidate have different rank from several panels. So some unit scores from panels are given for each candidate using standard normal distribution. Then we calculate the mean unit score for each candidate and final interview entrance examination scores are given using the mean unit score for each candidate.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.543-545
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• 2003

In this study, the authors evaluate the suitability of the candidate routes selected by the route selection method, which is developed by the authors, by combination of Geographic Information Systems (GIS) and Analytic Hierarchy Process. To evaluate the suitability of the candidate routes, from the viewpoint of the residents, we have considered element factors such as, population, household, aging situation, elevation, gradient, housing density and the Control Point. The results of this study are expected to assess the suitability of the candidate routes of the hillside transportation for the residents and examine the application limit of the route selection method.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.47-56
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• 2022

Recently bank card number recognition plays an important role in improving payment efficiency. In this paper we propose a new bank-card number identification algorithm. The proposed algorithm consists of three modules which include edge detection, candidate region generation, and recognition. The module of 'edge detection' is used to obtain the possible digital region. The module of 'candidate region generation' has the role to expand the length of the digital region to obtain the candidate card number regions, i.e. to obtain the final bank card number location. And the module of 'recognition' has Convolutional deep learning Neural Network (CNN) to identify the final bank card numbers. Experimental results show that the identification rate of the proposed algorithm is 95% for the card numbers, which shows 20% better than that of conventional algorithm or method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.2
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• pp.21-30
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• 2000

If there exists a model that calculates the proper candidate position whenever the game of Go is in progress, it can be used for setting up the prototype of the candidate generation algorithm without using case-based reasoning. In this paper, we analyze Go through combinatorial game theory and on the basis of probability matrix (PM) showing the difference of the territory of the black and the white. We design and implement a candidate generation system(CGS) to find the candidates at a situation in Go. CGS designed in this paper can compute Influence power, safety, probability value(PV), and PM and then generate candidate positions for a present scene, once a stone is played at a scene. The basic strategy generates five candidates for the Present scene, and then chooses one with the highest PV. CGS generates the candidate which emphasizes more defence tactics than attack ones. In the opening game of computer Go, we can know that CGS which has no pattern is somewhat superior to NEMESIS which has the Joseki pattern.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.193-200
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• 2018

In a formal speech, the speaker's voice has a variety of effects on the listener. Depending on the voice characteristics, the effectiveness and efficiency of the speech change as well. In the presidential election, the candidate's voice characteristics will affect the cognition of voters. Thus, we need to understand about the a more effective voice of candidate. This study proves whether voters will change their cognition if the candidate changes owe voice. If the cognition of voters can be changed according to the changed voice characteristics of the candidate, we will be able to explain what voices are needed for the candidate. We will also be able to suggest the necessary voice change strategies for effective speech. We describe cognition change of the voters according to the change of the voices of the presidential candidates by the dimension of the sori-engineering and the cognitive dimension. Hence, this study explains the voice characteristics and change strategies needed for candidates for effective speech.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.445-453
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• 2016

Fixed robust routing is attracting attention as routing that achieves high robustness against changes in traffic patterns without conducting traffic measurement and performing dynamic route changes. Fixed robust routing minimizes the worst-case maximum link load by distributing traffic of every source-destination (s-d) router pair onto multiple candidate paths (multipath routing). Multipath routing, however, can result in performance degradation of Transmission Control Protocol (TCP) because of frequent out-of-order packet arrivals. In this paper, we first investigate the influence of multipath routing on TCP performance under fixed robust routing with a simulation using ns-2. The simulation results clarify that TCP throughput greatly degrades with multipath routing. We next propose a candidate path selection method to improve TCP throughput while suppressing the worst-case maximum link load to less than the allowed level under fixed robust routing. The method selects a single candidate path for each of a predetermined ratio of s-d router pairs in order to avoid TCP performance degradation, and it selects multiple candidate paths for each of the other router pairs in order to suppress the worst-case maximum link load. Numerical examples show that, provided the worst-case maximum link load is less than 1.0, our proposed method achieves about six times the TCP throughput as the original fixed robust routing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6A
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• pp.500-505
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• 2009

In this paper, We present a low complexity candidate list generation scheme in iterative MIMO receiver. Since QAM modulation can be decomposed into HP symbols and LP symbol and HP symbol is robust in error capability, we generate HP symbol list with simple ZF detector output and its corresponding neighbor HP symbols, Then, based on HP symbol list, the LP symbol list is generated by using the sphere decoder. From the second iteration, since apriori value from channel decoder is available, the candidate list is updated based on demodulated apriori value. Through the simulation, we observe that at the first iteration, the BER performance is worse than LSD. However, as the number of iteration is increased, the proposed scheme has almost same performance as LSD. Moreover, the proposed one has reduced candidate list generation time and lower number of candidate list compared with LSD.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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• pp.1061-1065
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• 2005

Growth rate is one of the economically important quantitative traits that affect carcass quantity in beef cattle. Two genes, bovine insulin-like growth factor I (IGF-I) and myogenic factor 5 (MYF5), were chosen as candidate genes for growth traits due to their important role in growth and development of mammals. The objectives of this study were to determine gene-specific single nucleotide polymorphism (SNP) markers of the IGF-I and MYF5 positional candidate genes and to investigate their associations with growth traits in Korean cattle. Genotyping of the SNP markers in these candidate genes was carried out using the single strand conformation polymorphism (SSCP) analysis. The frequencies of A and B alleles were 0.72 and 0.28 for IGF-I gene and 0.39 and 0.61 for MYF5 gene, respectively, in Korean cattle population examined. The gene-specific SNP marker association analysis indicated that the SNP genotype in IGF-I gene showed a significant association (p<0.05) with weight at 3 months (W3), and cows with AB genotype had higher W3 than BB genotype cows. The SNP genotype of MYF5 gene was found to have a significant effect (p<0.05) on the weight at 12 months (W12) and average daily gain (ADG), and cows with BB and AB genotypes had higher W12 and ADG compared with cows with AA genotype, respectively. However, no significant association between the SNP genotypes and any other growth traits was detected. The gene-specific SNP markers in the IGF-I and MYF5 candidate genes may be useful for selection on growth traits in Korean cattle.

• Journal of KIISE
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• v.42 no.2
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• pp.145-154
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• 2015

This paper proposes an enhanced projection candidate selection algorithm to improve the performance of the existing path prediction algorithm. Various user path prediction algorithms have previously been developed, but those algorithms are inappropriate for a real-time and close user path prediction environment. To resolve this issue, a new prediction algorithm has been proposed, but several problems still remain. In particular, this algorithm should be enhanced to provide much faster processing performance. The major cause of the high processing time of the previous path prediction algorithm is the high time complexity of its projection candidate selection. Therefore, this paper proposes a new path fragment management structure and an improved projection candidate selection algorithm to improve the processing speed of the existing projection candidate selection algorithm. This paper also shows the effectiveness of the algorithm herein proposed through a comparative performance evaluation.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.1-6
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• 2014

Color image processing based on smoke detection is suitable detecting target to early detection of fire smoke. A method for detecting the smoke is processed in the pre-processing movement and color. And Next, characteristics of smoke such as diffusion, texture, shape, and directionality are used to post-processing. In this paper, propose the detection method of density distribution characteristic in characteristics of smoke. the generate a candidate regions by color thresholding image in Detecting the movement of smoke to the 10Frame interval and accumulated while 1second image. then check whether the pattern of the smoke by candidate regions to applying OBTP(Object Block Ternary Pattern). every processing is Block-based processing, moving detection is decided the candidate regions of the moving object by applying an adaptive threshold to frame difference image. The decided candidate region accumulates one second and apply the threshold condition of the smoke color. make the ternary pattern compare the center block value with block value of 16 position in each candidate region of the smoke, and determine the smoke by compare the candidate ternary pattern and smoke ternary pattern.