• Asian-Australasian Journal of Animal Sciences
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• v.22 no.1
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• pp.1-6
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• 2009

Genetic variability is an important component in the ability of populations to adapt in the face of environmental change. Severe human impacts reduced Muzzafarnagri sheep of India from 500,000 in 1972 to 10,989 in 1973-74. Here we report for the first time the effect of this population decline on levels of genetic variability at 13 FAO recommended ovine microsatellite loci and contrast levels of variability to that in a breed from the same geographical region, which differed in numbers, by an order of magnitude (Marwari sheep). Of the 13 loci, 100% were polymorphic in both breeds. A high degree of genetic variation was observed within populations in terms of both allele diversity (number of alleles per locus, >4) and gene diversity (expected heterozygosity, >0.5), which implied that there is still a substantial amount of genetic diversity at the nuclear loci in a declining population. Nevertheless, overall low number of alleles per locus and relatively less abundance of low frequency alleles in Muzzafarnagri sheep suggested that genetic variability has been comparatively reduced in this population. Bottleneck analysis indicated that a genetic bottleneck did not occur during the most recent decline. In addition, we found that the differentiation among populations was moderate ($F_{ST}$= 11.8%). This study on assessment of genetic effects of the population declines in ovines is a step towards identification of genetically impoverished or healthy populations, which could prove to be a useful tool to facilitate conservation planning in this important species of small ruminants.

• Journal of Game and Entertainment
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• v.2 no.1
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• pp.8-16
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• 2006

The development of multicast communication services in the Internet is expected to lead a stable packet transfer even though On-Line Games generate heavy traffic. The Core Based Tree scheme among many multicast protocols is the most popular and suggested recently. However, CBT exhibits two major deficiencies traffic concentration or poor core placement problem. Thus, measuring the bottleneck link bandwidth along a path is important to understand the performance of multicast. We propose a method in which the core router's state is classified into SS(Steady State), NS(Normal State) and BS(Bottleneck State) according to the estimated link speed rate, and also the changeover of multicast routing scheme for traffic overload. In addition, we introduce Anycast routing tree, an efficient architecture for constructing shard multicast trees.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.162-165
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• 2012

In this paper, the method of controlling velocity between joining vehicles at the point of bottleneck using information and communications technology of WAVE method based V2V and V2I are proposed for the driving with high fuel efficiency. Using the derived fuel-efficiency comparative analysis model, it was shown that the proposed method's fuel efficiency is better than traffic light method demanding periodically vehicle's stop. Also, this method provides the derivation algorithm for deceleration and acceleration for controlling velocity between vehicles approaching bottleneck area.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.231-242
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• 2007

This study was conducted to identify the relation of bottleneck and satisfaction factors in Korean succession companies. The final goal of this paper is finding some strategies and supporting system for Korean succession companies. According to the results of the study, we found four latent variables of the cause variables and two latent variables of the result variables. Three latent variables of the cause variables have an direct effect on two latent variables of the result variables.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.70-77
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• 2015

In this paper, we present experimental results evaluating the performance of the Multipath TCP over shared bottleneck path in series of benchmark tests. In summary, we find that the Multipath TCP's fairness as well as its competitive responds to the change of network conditions such as latency, loss rate${\cdots}$ MPTCP is extremely unfair and powerful with regular TCP in ideal network conditions but its throughput decreases clearly even less than regular TCP in worse network conditions with very high latency, higher packet loss rate.

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.40-47
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• 2002

This paper analyzes the performance of an optical line termination system in ATM based Passive Optical Network(PON) using the operational analysis. We analyze it using system parameters such as utilization, throughput and routing frequency based on the buffer structure in each block of ATM-PON. Furthermore, we derive the mean response time and the visit ratio of each block, and then search the bottleneck block that hinders the system performance. We found that the 622Mbps 16x16 switching block is the bottleneck block for ATM-PON. In this bottleneck block, the loss probability increases rapidly when the cell arrival rate increases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4108-4122
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• 2019

Workflow process mining is becoming a more and more valuable activity in workflow-supported enterprises, and through which it is possible to achieve the high levels of qualitative business goals in terms of improving the effectiveness and efficiency of the workflow-supported information systems, increasing their operational performances, reducing their completion times with minimizing redundancy times, and saving their managerial costs. One of the critical challenges in the workflow process mining activity is to devise a reasonable approach to discover and recognize the bottleneck points of workflow process models from their enactment event histories. We have intuitively realized the fact that the iterative process pattern of redo-activities ought to have the high possibility of becoming a bottleneck point of a workflow process model. Hence, we, in this paper, propose an algorithmic approach and its implementation to discover the redo-activities and their performers' involvements patterns from workflow process enactment event logs. Additionally, we carry out a series of experimental analyses by applying the implemented algorithm to four datasets of workflow process enactment event logs released from the BPI Challenges. Finally, those discovered redo-activities and their performers' involvements patterns are visualized in a graphical form of information control nets as well as a tabular form of the involvement percentages, respectively.

• Korean Journal of Cognitive Science
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• v.27 no.2
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• pp.275-301
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• 2016

Attentional blink (AB) refers to the phenomena where conscious report for a target (T2) subsequent to the first target (T1) in a stream of items under rapid serial visual presentation (RSVP) becomes difficult if the T2 follows no later than 500ms after the T1. The present study examined the effect of T1 visibility on T2 AB strength according to the bottleneck account proposing that the amount of allocated resources for T1 memory consolidation determines the strength of AB against T2. In the low-visibility condition, the T1 had a gray color for a low stimulus contrast against the black background whereas had a bright and saturated color in the high-visibility condition. In both visibility conditions, the T1 was also highly distinct from the remaining distractors. A multi-RSVP method was also used for increasing location uncertainty of the targets supposedly consuming on average attentional resources for the targets. Two experiments revealed that AB strength was more intense in the low-visibility than high-visibility condition, and the pattern of difference went more pronounced if T2 visibility was improved. The results indicate that T1 visibility can affect more strongly when attentional resources are relatively lacking for resolving the T1 bottleneck, and support for the bottleneck account proposing that the level of T1's visibility can determine the intensity of the T1 bottleneck.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• ETRI Journal
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• v.15 no.3
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• pp.1-26
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• 1994

Simulated annealing is an attractive, but expensive, heuristic method for approximating the solution to combinatorial optimization problems. Attempts to parallel simulated annealing, particularly on distributed memory multicomputers, are hampered by the algorithm's requirement of a globally consistent system state. In a multicomputer, maintaining the global state S involves explicit message traffic and is a critical performance bottleneck. To mitigate this bottleneck, it becomes necessary to amortize the overhead of these state updates over as many parallel state changes as possible. By using this technique, errors in the actual cost C(S) of a particular state S will be introduced into the annealing process. This paper places analytically derived bounds on this error in order to assure convergence to the correct optimal result. The resulting parallel simulated annealing algorithm dynamically changes the frequency of global updates as a function of the annealing control parameter, i.e. temperature. Implementation results on an Intel iPSC/2 are reported.