• Structural Monitoring and Maintenance
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• v.2 no.4
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• pp.399-418
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• 2015

Automated damage detection through Structural Health Monitoring (SHM) techniques has become an active area of research in the bridge engineering community but widespread implementation on in-service infrastructure still presents some challenges. In the meantime, visual inspection remains as the most common method for condition assessment even though collected information is highly subjective and certain types of damage can be overlooked by the inspector. In this article, a Frequency Response Functions-based model updating algorithm is evaluated using experimentally collected data from the University of Central Florida (UCF)-Benchmark Structure. A protocol for measurement selection and a regularization technique are presented in this work in order to provide the most well-conditioned model updating scenario for the target structure. The proposed technique is composed of two main stages. First, the initial finite element model (FEM) is calibrated through model updating so that it captures the dynamic signature of the UCF Benchmark Structure in its healthy condition. Second, based upon collected data from the damaged condition, the updating process is repeated on the baseline (healthy) FEM. The difference between the updated parameters from subsequent stages revealed both location and extent of damage in a "blind" scenario, without any previous information about type and location of damage.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.69-72
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• 2018

최근 5G 네트워크의 출현은 전송속도의 진화에 따라 서비스를 확장하고 있는 추세이다. 네트워크에서 사용하는 단말의 수가 증가하며, 단말에서 사용하고 있는 서비스 수는 다양해지고 있다. 이러한 점은 이동성관리 연구가 필수적이며 다양한 기존 연구들이 있다. 하지만 기존 연구에서는 handover delay로 인한 QoE 저하 문제, 활성 링크 수 증가로 인한 패킷 손실 및 네트워크 자원 부족 문제점이 발생을 한다. 이러한 점을 해결하기 위해 단말에서 사용하는 flow 타입을 실시간과 비실시간 서비스로 구별한다. 이동성 요구사항을 필요로 하는 실시간 서비스 앵커를 설정하는 동작과정을 수행하여 라우팅의 경로를 최소화하여 네트워크에서 발생하는 여러 가지 문제점들을 해결한다. 본 논문에서는 수학적 수식을 통한 성능평가를 통해 기존 SDN 기반 이동성관리 보다 제안하는 아이디어가 handover delay 시간을 50% 줄일 수 있다는 점을 확인하였다.

• Journal of Korean Medicine Rehabilitation
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• v.23 no.4
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• pp.83-93
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• 2013

Objectives To present reviews of studies comparing surface-electromyography (SEMG) values between low back pain group and control group. Methods We searched 8 databases including KoreaMed, Google, KISS (Korean studies Information Service System), RISS (Research Information Sharing Service), OASIS (Oriental medicine Advanced Searching Integrated System), Pubmed, Ovid-MEDLINE and EMBASE. After searching, we conducted study selection by using inclusion and exclusion criteria and quality-assessment. We reviewed the selected studies concerning about the subject's measuring position, findings, sensitivities and specificities. Results 27 Studies were searched and reviewed. In static surface electromyography, more muscle activities observed in low back pain subjects than in controls. In dynamic surface electromyography, the low back pain subjects showed more muscle activites during flexion, while the control group showed more muscle activities during extension. Faster muscle fatigue observed in isometric muscle analysis. Conclusions Surface electromyography values will be able to be objective marker for evaluating low back pain. Further research is needed to determine additional unified protocol such as the type of SEMG and its directions.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.231-236
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• 2012

For real-time wireless sensor network applications, it is essential to provide different levels of quality of service (QoS) such as reliability, low latency, and fault-tolerant traffic control. To meet these requirements, an (m,k)-firm based real-time routing protocol has been proposed in our prior work, including a novel local transmission status indicator called local DBP (L_DBP). In this paper, a fault recovery scheme for (m,k)-firm real-time streams is proposed to improve the performance of our prior work, by contributing a delay-aware forwarding candidates selection algorithm for providing restricted redundancy of packets on multipath with bounded delay in case of transmission failure. Each node can utilize the evaluated stream DBP (G_DBP) and L_DBP values as well as the deadline information of packets to dynamically define the forwarding candidate set. Simulation results show that for real-time service, it is possible to achieve both reliability and timeliness in the fault recovery process, which consequently avoids dynamic failure and guarantees meeting the end-to-end QoS requirement.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.40-40
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• 2009

Construction firms have long sought success in the global construction market through diversifying revenue sources and project portfolios. The volume of international contracts has contributed to firms' sustained growth by mitigating the impact of the domestic market's cyclical nature. In spite of the importance of international construction, the uncertainty and dynamic changes surrounding global construction pose serious threats to global contactors. Over the last decade, the international construction industry has changed drastically in many ways, particularly including financial resource diversity, competition rules for the selection of contractors, and the terms of delivery systems requiring more competent total service providers. This paper investigates the important changes for global contractors through various documentation analysis as well as in-depth interviews with industry experts. This paper then analyzes the common strategies and lessons obtained from the cases of leading global contractors that have sustained their growth in the competitive global construction during the last decade. In addition, the authors further analyzed the comparisons between those firms and Korean contractors to discern any difference in sustaining their growth in the competitive market. It was found that those leading firms were quite proactive and responsive to changing markets by diversifying their market revenues to stabilize their revenue structure and enhancing their competency through a wide range of 'business convergence'. In addition, they significantly increased their upstream/downstream functional capabilities; hence becoming more competent service providers, able to grow in these rapidly changing market conditions. Finally, this paper benchmarks the critical strategies that support growth, which in turn can provide a strategic guideline for expansion into the global construction market.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.8
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• pp.432-444
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• 2004

In this paper, we construct the TMO-based object group model on distributed environment, and analyze and evaluate the executability for distributed real-time service of our object group model by developing the distributed real-time application simulator applying the model. The Time-triggered Message-triggered Object(TMO) is a real-time server object having real-time property itself. The TMO-based object group is defined as a set of objects which logically reconfigured the physically distributed one or more TMOs on network by a given distributed application. For supporting group management of the server objects, the TMO-based object group we suggested provides the functions which register and withdraw the solver objects as a group member to an arbitrary object group, and also provides the functions which insert and delete the access rights of server objects from clients. Also, our model was designed and implemented to support the appropriate object selection and dynamic binding service for a single TMO as well as the duplicated TMOs, and to support the real-time scheduling service for the clients which are requesting the service. Finally, we developed the Defence System against Invading Enemy Planes(DSIEP) simulator as a practical example of distributed real-time application by applying our model, and evaluated the adaptability of distributed service strategies for the group components and the executability of real-time services that the TMO-based object group model provides.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.94-104
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• 2020

Currently media consumption over fixed/mobile Internet is mostly conducted by adaptive media streaming technology such as DASH (Dynamic Adaptive Streaming over HTTP), which is an ISO/IEC MPEG (Moving Picture Experts Group) standard, or some other technologies similar to DASH. All these heavily depend on the HTTP caches that ISPs (Internet Service Providers) are obliged to provide sufficiently to make sure fast enough Web services. As a result, as the number of media streaming users increases, ISPs' burden for HTTP cache has been greatly increased rather than CDN (Content Delivery Network) providers' server burden. Hence ISPs charge traffic cost to CDN providers to compensate for the increased cost of HTTP caches. Recently in order to reduce the traffic cost of CDN providers, P2P (Peer-to-Peer)-assisted DASH system was proposed and a peer selection algorithm that maximally reduces CDN provides' traffic cost was investigated for this system. This algorithm, however, tends to concentrate the burden upon the selected peer. This paper proposes a new peer selection algorithm that distributes the burden among multiple peers while maintaining the proper reduction level of the CDN providers' cost. Through implementation of the new algorithm in a Web-based media streaming system using WebRTC (Web Real-Time Communication) standard APIs, it demonstrates its effectiveness with experimental results.

• Journal of KIISE:Software and Applications
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• v.34 no.5
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• pp.431-446
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• 2007

Executable composite Web services are selected by binding a given abstract workflow with the specific Web services that satisfy given QoS requirements. Considering the rapidly increasing number of Web services and their highly dynamic QoS environment, the fast selection of composite services is important. This paper presents a method for quality driven comosite Web services selection based on a workflow partition strategy. The proposed method partitions an abstract workflow into two sub-workflows to decrease the number of candidate services that should be considered. The QoS requirement is also decomposed for each partitioned workflow. Since the decomposition of a QoS requirement is based on heuristics, the selection might fail to find composite Web services. To avoid such a failure, the tightness of a QoS requirement is defined and a workflow is determined to be partitioned according to the tightness. A mixed integer linear programming is utilized for the efficient service selection. Experimental results show that the success rate of partitioning is above 99%. Particularly, the proposed method performs faster and selects composite services whose qualities are not significantly different (less than 5%) from the optimal one.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.