• Journal of Astronomy and Space Sciences
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• v.35 no.3
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• pp.143-149
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• 2018

The ionosphere has been monitored by ionosondes for over five decades since the 1960s in Korea. An ionosonde typically produces an ionogram that displays radio echoes in the frequency-range plane. The trace of echoes in the plane can be read either manually or automatically to derive useful ionospheric parameters such as foF2 (peak frequency of the F2 layer) and hmF2 (peak height of the F2 layer). Monitoring of the ionosphere should be routinely performed in a given time cadence, and thus, automatic scaling of an ionogram is generally executed to obtain ionospheric parameters. However, an auto-scaling program can generate undesirable results that significantly misrepresent the ionosphere. In order to verify the degree of misrepresentation by an auto-scaling program, we performed manual scaling of all 35,136 ionograms measured at Jeju ($33.43^{\circ}N$, $126.30^{\circ}E$) throughout 2012. We compared our manually scaled parameters (foF2 and hmF2) with auto-scaled parameters that were obtained via the ARTIST5002 program. We classified five cases in terms of the erroneous scaling performed by the program. The results of the comparison indicate that the average differences with respect to foF2 and hmF2 between the two methods approximately correspond to 0.03 MHz and 4.1 km, respectively with corresponding standard deviations of 0.12 MHz and 9.58 km. Overall, 36 % of the auto-scaled results differ from the manually scaled results by the first decimal number. Therefore, future studies should be aware of the quality of auto-scaled parameters obtained via ARTIST5002. Hence, the results of the study recommend the use of manually scaled parameters (if available) for any serious applications.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.380-390
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• 1998

In the present work a finite element formulation using dynamic explicit time integration scheme is used for numerical analysis of auto-body panel stamping processes. The lumping scheme is employed for the diagonal mass matrix and linearizing dynamic formulation. A contact scheme is developed by combining the skew boundary condition and direct trial-and-error method. In this work, for economic analysis the faster punch velocity and the mass scaling method are introduced. To investigate the effects of punch velocity and mass scaling, the various values of punch velocity and the various mass scalings are used for numerical analysis. Computations are carried out for analysis of complicated auto-body panel stamping processes such as forming of an oil pan and a fuel tank.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.223-230
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• 2013

Sudden enhancements of daytime NmF2 appeared in Anyang ionosonde data during summer seasons in 2006-2007. In order to investigate the causes of this unusual enhancement, we compared Anyang NmF2's with the total electron contents (GPS TECs) observed at Daejeon, and also with ionosonde data at at mid-latitude stations. First, we found no similar increase in Daejeon GPS TEC when the sudden enhancements of Anyang NmF2 occurred. Second, we investigated NmF2's observed at other ionosonde stations that use the same ionosonde model and auto-scaling program as the Anyang ionosonde. We found similar enhancements of NmF2 at these ionosonde stations. Moreover, the analysis of ionograms from Athens and Rome showed that there were sporadic-E layers with high electron density during the enhancements in NmF2. The auto-scaling program (ARTIST 4.5) used seems to recognize sporadic-E layer echoes as a F2 layer trace, resulting in the erroneous critical frequency of F2 layer (foF2). Other versions of the ARTIST scaling program also seem to produce similar erroneous results. Therefore we conclude that the sudden enhancements of NmF2 in Anyang data were due to the misrecognition of sporadic-E echoes as a F-layer by the auto-scaling program. We also noticed that although the scaling program flagged confidence level (C-level) of an ionogram as uncertain when a sporadic-E layer occurs, it still automatically computed erroneous foF2's. Therefore one should check the confidence level before using long term ionosonde data that were produced by an auto-scaling program.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.102-105
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• 2017

최근 네트워크 서비스 관리의 복잡성을 줄이기 위해 새로운 네트워크 인프라가 등장하고 있다. NFV(Network Function Virtualization) 기술은 하드웨어 기반의 네트워크 장비에 가상화를 적용하여, 유연성 있는 네트워크 서비스를 제공한다. 네트워크 서비스는 Firewall, Parental Control (PC)과 같은 일련의 VNF (Virtual Network Function)로 구성된다. NFV 기술을 기존의 네트워크 환경과 통합시키는 경우 해결해야 할 난제가 존재한다. 기존 네트워크는 복잡성이 요구되며 많은 양의 트래픽을 다루어야 한다. 사용자가 요청한 네트워크 서비스의 높은 트래픽 로드로 인해 패킷 손실이 발생할 수 있다. 본 논문에서는 Zabbix 모니터링 시스템을 활용해 VNF 로드 기반의 Auto-scaling을 제안한다. 이를 통해 네트워크 서비스의 자원 효율성을 향상시키고 패킷 손실 비율을 줄일 수 있다.

• KNOM Review
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• v.23 no.2
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• pp.1-10
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• 2020

Network Function Virtualization (NFV) is a key technology of 5G networks that has the advantage of enabling building and operating networks flexibly. However, NFV can complicate network management because it creates numerous virtual resources that should be managed. In NFV environments, service function chaining (SFC) composed of virtual network functions (VNFs) is widely used to apply a series of network functions to traffic. Therefore, it is required to dynamically allocate the right amount of computing resources or instances to SFC for meeting service requirements. In this paper, we propose Deep Q-Networks (DQN)-based auto-scaling to operate the appropriate number of VNF instances in SFC. The proposed approach not only resizes the number of VNF instances in SFC composed of multi-tier architecture but also selects a tier to be scaled in response to dynamic traffic forwarding through SFC.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.73-82
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• 2022

Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

• Journal of Korean Society of Transportation
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• v.4 no.1
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• pp.12-27
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• 1986

This study examined user preferences toward transportation modes in Seoul. Two multidimensional scaling models, the ideal point and vector models, were applied to data on mode preferences of 114 adults in the metropolitan area. While both models produced fairly similar results, the vector model performed slightly better than the other in terms of interpretability of the results. The transport attributes elicited are comfort, flexibility, travel cost, travel time, privacy, and safety; among which comfort is salient most. The comfort variable is a multi-faceted attribute in nature. The variations of attribute preferences are most significant between the gender groups as well as worker/nonworker groups. In particular, male workers, female workers and female nonworkers form three distinctive market segments. An unidimensional scaling of the preference data reveals that subway, auto-driver, and subscription bus modes are preferred most, whereas motorcycle and bicycle least. The other modes of express bus, taxt, auto-passenger, bus and walk rank intermediately. An examination of how preference orders vary among modal groups hints that users align their stated attitudes to their choice in order to reduce cognitive dissonance.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.123-128
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• 1992

This paper presents an autotuning algorithm of scaling factor in order to improve system performance. We define the scaling factor of fuzzy controller as a function of error and error change. This function is tuned by the output of performance evaluation level utilizing the error of overshoot and rising time. Simulation results show that the proposed algorithm has good tuning performance for a system with parameter change.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.36-43
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• 1999

This paper proposes a new hybrid genetic algorithm for auto-tuning fuzzy controllers improving the performance. In general, fuzzy controllers use pre-determined moderate membership functions, fuzzy rules, and scaling factors, by trial and error. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a hybrid genetic algorithm. The object of the proposed algorithm is to promote search efficiency by the hybrid optimization technique. The proposed hybrid genetic algorithm is based on both the standard genetic algorithm and a modified gradient method. If a maximum point is not be changed around an optimal value at the end of performance during given generation, the hybrid genetic algorithm searches for an optimal value using the the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algoritms. Simulation results verify the validity of the presented method.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.126-129
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• 1997

This paper propose a new hybrid genetic algorithm for auto-tunig auzzy controller improving the performance. In general, fuzzy controller used pre-determine d moderate membership functions, fuzzy rules, and scaling factors, by trial and error. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controller, using hybrid genetic algorithms. The object of the proposed algorithm is to promote search efficiency by overcoming a premature convergence of genetic algorithms. Hybrid genetic algorithm is based on genetic algorithm and modified gradient method. Simulation results verify the validity of the presented method.