Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ($\bar{r_j}$) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, $EBV^*=EBV_j(1-k\bar{{r}_j})$ Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.
The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.
The Journal of Korean Institute of Communications and Information Sciences
/
v.25
no.6A
/
pp.794-801
/
2000
In this paper, the efficient new performance evaluation method for digital communication channels is suggested and verified its efficiency in terms of simulation run-tim for the digital satellite broadcasting satellite TV channel. In order to solve the difficulties of the existing Importance Sampling(IS) Technics, we adopted the discrete probability mass function(PMF) in the new method for estimating the statistical characteristics of received signals from the measured Nth order central moments. From the discrete probability mass function obtained with less number of the received signal than the one required in the IS technic, continuous cumulative probability function and its inverse function are exactly estimated by using interpolation and extrapolation technic. And the overall channel is simplified with encoding block, inner channel performance degra-dation modeing block which is modeled with the Uniform Random Number Generator (URNG) and concatenated Inverse Cummulative Pr bility Distribution function, and decoding block. With the simplified channel model, the overall performance evaluation can be done within a drastically reduced time. The simulation results applied to the nonlinear digital satellite broadcasting TV channel showed the great efficiency of the alogrithm in the sense of computer run time, and demonstrated that the existing problems of IS for the nonlinear satellite channels with coding and M-dimensional memory can be completely solved.
This paper describes three methods for the estimation of the impulse reponse in an indoor acoustic transfer system which rather has long reverberation time by the cross spectrum. The first method, which is the conventional one, will use the white noise as the source signal. Therefore, the very long time window data and numerous number of DFT are necessary for this estimation. The second method has been disigned in order to shorten the length of time window of the first method by using a burst of noise as the source signal. The third method which will be suggested in this paper uses too types of definite signal with short duration time of the source signal. According to the view point of computation capacity, and estimation accuracy of the impulse response, the compared experimental results show that the third method will be better than the others.
Ghang, Ho-Young;Han, Young-Joo;Jeong, Sang-Jin;Bhak, Jong;Lee, Sung-Hoon;Kim, Tae-Hyung;Kim, Chul-Hong;Kim, Sang-Soo;Al-Mulla, Fahd;Youn, Chan-Hyun;Yoo, Hyang-Sook;The HUGO Pan-Asian SNP Consortium, The HUGO Pan-Asian SNP Consortium
Genomics & Informatics
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v.9
no.4
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pp.181-188
/
2011
In planning a model-based phylogenic study for highly related ethnic data, the SNP marker number is an important factor to determine for relationship inferences. Genotype frequency data, utilizing a sub sampling method, from 63 Pan Asian ethnic groups was used for determining the minimum SNP number required to establish such relationships. Bootstrap random sub-samplings were done from 5.6K PASNPi SNP data. DA distance was calculated and neighbour-joining trees were drawn with every re-sampling data set. Consensus trees were made with the same 100 sub-samples and bootstrap proportions were calculated. The tree consistency to the one obtained from the whole marker set, improved with increasing marker numbers. The bootstrap proportions became reliable when more than 7,000 SNPs were used at a time. Within highly related ethnic groups, the minimum SNPs number for a robust neighbor-joining tree inference was about 7,000 for a 95% bootstrap support.
Seo, Hwa-jeong;Seok, Seon-hee;Kim, Kyoung-hoon;Kim, Ho-won
Journal of the Korea Institute of Information Security & Cryptology
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v.25
no.3
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pp.501-507
/
2015
The online banking service handles a banking business over the internet, it is necessary to ensure that all financial transactions are processed securely. So, there are various authentication technique for e-banking service : a certificate, a personal identification number(PIN), a security card and a one-time password(OTP). Especially, the security card is most important means including secret information. If the secret information of card is leaked, it means not only loss of security but also easy to attack because security card is a difficult method to get. In this paper, we propose that a multi-channel security card saves an secret information in distributed channel. Proposed multi-channel security card reduces vulnerability of the exposed and has a function to prevent phishing attacks through decreasing the amount of information displayed and generating secret number randomly.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.2
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pp.452-458
/
2021
The value and importance of personal information are increasing due to the increasing number of fields where the Internet environment and computing environment are used, and user authentication technology is also changing. Until now, accredited certificates, which are mainly used in the financial sector, are being replaced with biometric authentication technology due to the problem of revocation. However, another problem is that biometric information cannot be modified once it is leaked. Recently, with the advent of blockchain technology, research on user authentication methods has actively progressed. In this paper, both public certificate and blockchain-based user authentication can be used without system change, and a new DID issuance and reissuance method that can replace the resident registration number is presented. The proposed system can be used without restrictions in a blockchain. However, the currently used DID requires installation of an application at the Interworking Support Center for verification. Since a DID can be authenticated without registering as a member, indiscriminate information collection can be prevented. Security, convenience, and determinism are compared with the existing system, and excellence is proven based on various attack methods, its portability, and proxy use.
Login process uses both ID and password information to authenticate someone and to permit its access privilege on system. However, an attacker can get those ID and password information by using existing packet sniffing or key logger programs. It cause privacy problem as those information can be used as a hacking and network attack on web server and web e-mail system. Therefore, a more secure and advanced authentication mechanism should be required to enhance the authentication process on existing system. In this paper, we propose a multi-factor authentication process by using software form of secure card system combined with existing ID/Password based login system. Proposed mechanism uses a random number generated from the his/her own handset with biometric information. Therefore, we can provide a one-time password function on web login system to authenticate the user using multi-factor form. Proposed scheme provide enhanced authentication function and security because it is a 'multi-factor authentication mechanism' combined with handset and biometric information on web login system.
Journal of the Korea Society of Computer and Information
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v.16
no.3
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pp.251-260
/
2011
In this paper, we proposed a scheme that it safely exchanges encrypted keys without Trust Third Party (TTP) and Pre-distributing keys in multi-hop clustering sensor networks. Existing research assume that it exists a TTP or already it was pre-distributed a encrypted key between nodes. However, existing methods are not sufficient for USN environment without infrastructure. Some existing studies using a random number Diffie-Hellman algorithm to solve the problem. but the method was vulnerable to Replay and Man-in-the-middle attack from the malicious nodes. Therefore, authentication problem between nodes is solved by adding a ��TESLA. In this paper, we propose a modified Diffie-Hellman algorithm that it is safe, lightweight, and robust pair-wise agreement algorithm by adding One Time Password (OTP) with timestamp. Lastly, authentication, confidentiality, integrity, non-impersonation, backward secrecy, and forward secrecy to verify that it is safe.
Call centers do not simply play a role of responding to customers' calls, but they have developed into a core unit for maintaining competitiveness through services, marketing, or sales. Since the service quality of call centers heavily affects customer satisfaction, organizations have focused on enhancing it by reducing waiting time and increasing service level. One of the techniques, which improve the service quality of call centers, is to employ multi-skilled agents that can handle more than one type of calls. This study deals with three issues relevant to multi-skilled agents. First, we analyze how the way of allocating a specific group of agents to a set of skills affects the performance of call centers. Secondly, we investigate the relationship between the number of multi-skilled agents and the performance of call centers. Finally, we examine the impact of agent selection rules on the performance of call centers. Two selection rules are compared : the first rule is to assign a call to any available agent at random while the other rule is to assign a call preferably to single-skilled agents over multi-skilled agents when applicable. Based on simulation experiments, we suggest three implications. First, as the length of cycles in the agent-skill configuration network becomes longer, call centers achieve higher service level and shorter waiting time. Secondly, simulation results show that as the portion of multi-skilled agents increases, the performance of call centers improves. However, most of the improvement is attained when the portion of multi-skilled agents is relatively low. Finally, the agent selection rules do not significantly affect the call centers' performance, but the rule of preferring single-skilled agents tends to distribute the workload among agents more equally.
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