• Journal of Korean Society of Steel Construction
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• v.21 no.2
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• pp.193-201
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• 2009

Structural design of most nonprismatic Pre-Engineered Building Systems (PEBS) is performed using optimizing software developed in foreign countries. In this study, a structural optimizing software for the design of 3-D structures of nonprismatic PEBS is developed according to the allowable stress design method of AISC2005 and KBC. Optimizing structural design with nonprismatic members is carried out by repeating the process of structural analysis and member design to minimize the weight of a structure. According to the optimizing design results of 2-D and 3-D structures with nonprismatic members, there are considerable steel savings in designing structures with nonprismatic H-shaped built-up sections rather than with H-shaped rolled sections. When H-shaped built-up sections were used, the weight of the structural steel was reduced when AISC2005 specification rather than AISC1898 was used in the design. It is therefore concluded that utilizing the new AISC2005 specification is safer in preventingweb buckling because the height of a member is designed to be small despite some differences depending on the structural type.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.327-335
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• 2007

A new optimization scheme and some key techniques are proposed in the development of a vehicle glass drop design software system. The key issues of the design system are how to regenerate the glass surface and make the vehicle glass drop down along the glass channels. To resolve these issues, a parameterized model was created at first, in which the optimizing method and Knowledge Fusion techniques were adopted the optimized process was then written into the glass drop design system by coding with C language and UGS/Open Application Programme Interface functions etc. Therefore, the designer or engineer can simulate the process of glass dropping along the channels to assess the potential interference between glass and door accessory by using this software system. All of the testing results demonstrate the validity of the optimizing scheme, and the parametric design software effectively solves the key issues on development of the door accessory package.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.4
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• pp.135-142
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• 2023

Recently, many companies are using public cloud services or building their own data center because digital transformation is expanding. The software-defined storage is a key solution for storing data on the cloud platform and its use is expanding worldwide. Software-defined storage has the advantage of being able to virtualize and use all storage resources as a single storage device and supporting flexible scale-out. On the other hand, since the size of an object is variable, an imbalance occurs in the use of the disk and may cause a failure. In this study, a method of redistributing objects by optimizing disk weights based on storage state information was proposed to solve the imbalance problem of disk use, and the experimental results were presented. As a result of the experiment, it was confirmed that the maximum utilization rate of the disk decreased by 10% from 89% to 79%. Failures can be prevented, and more data can be stored by optimizing the use of disk.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4081-4098
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• 2022

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.17-26
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• 1989

This paper is concerned with forecasting the existing number of errors in the computer software and optimizing the stopping time of the software test based upon the forecasted number of errors. The most commonly used models have assessed software reliability under the assumption that the software failure late is proportional to the current fault content of the software but invariant to time since software faults are independents of others and equally likely to cause a failure during testing. In practice, it has been observed that in many situations, the failure rate decrease. Hence, this paper proposes a mathematical model to describe testing situations where the failure rate of software limearly decreases proportional to testing time. The least square method is used to estimate parameters of the mathematical model. A cost model to optimize the software testing time is also proposed. In this cost mode two cost factors are considered. The first cost is to test execution cost directly proportional to test time and the second cost is the failure cost incurred after delivery of the software to user. The failure cost is assumed to be proportional to the number of errors remained in the software at the test stopping time. The optimal stopping time is determined to minimize the total cost, which is the sum of test execution cast and the failure cost. A numerical example is solved to illustrate the proposed procedure.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.74-80
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• 2023

Currently, hardware companies such as Oculus, Samsung, and HTC are producing virtual reality devices, and game software development companies are developing or servicing VR games using these devices. Accordingly, the VR game market is expected to continue to grow in the future. However, in order for the VR game market to become active, various problems raised during game development and service must be resolved. This paper investigates solutions to problems raised during the development and service of VR games, such as cyber sickness, risk of injury due to environmental restrictions during play, and reconnection induction problems. Cybersickness can be alleviated by utilizing multiple GPUs for each display processing to achieve higher frame rates and optimizing play space design. Environmental constraints during play can be mitigated by optimizing space design, and the problem of inducing reconnection can be solved by continuously providing the motivation and purpose used in existing game methods. Through this, we were able to apply it to develop VR content that can be played continuously.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.841-846
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• 2006

This paper presents a numerical approach to optimizing vehicle fuel economy in a higway bus. The method described is based on using a commercial software vehicle simulation to identify the relative efficiency of each of the vehicle systems, such as the engine hardware, engine software calibration, transmission, cooling system and ancillary drives. The simulation-based approach offers a detailed understanding of which vehicle systems are underperforming and by how much the vehicle fuel economy can be improved if those systems are brought up to best-in-class performance. In this way, the optimum vehicle fuel economy can be provided to the vehicle customer. A further benefit is that the simulation requires only a minimum number of vehicle testing for initial validation, with all subsequent field test cycles performed in software, thereby reducing development time and cost for the manufacturer.

• Steel and Composite Structures
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• v.6 no.5
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• pp.417-433
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• 2006

In this paper, a non-linear structural analysis software with pro-processing and post-recessing function is proposed by the author. The software incorporating the functions of the structural analysis and geometrical design of Tensegrity structures. Using this software, Cable Dome is analyzed as a prototype, a comprehensive study on the structural behavior of Tensegrity domes is presented in detail. Design methods of Tensegrity domes were proposed. Based on the analysis, optimizing design was performed. Several new Tensegrity domes with different geometrical design scheme are proposed, the structural analysis of the new schemes is also conducted. The analysis result shows that the proposed new forms of the Tensegrity domes are reasonable for practical applications.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2088-2097
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• 1999

We propose the software framework construction method that increases reusability through use case extraction and structuring of software system's dynamic behavior of which identifying behavior patterns from software domain models. Most behavior models do not provide a consistent modeling technique for harmonizing user's heterogeneous requirements, and not yet prepared to a detailed optimizing technique for redevelopment and maintenance. Therefore, we need a software reuse framework to support consistency and reusability of existing development models using use cases with functional characteristics. a lattice model is used to this approach for structuring use cases, and the reuse process that can be driven to reusable components is introduced in this paper,.