• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.29-34
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• 2021

In this paper, a cylindrical photonic crystal waveguide with a low-index core is first proposed. The core can be filled with air, liquid, or arbitrary dielectric materials. Exact analyses for the electromagnetic field characteristics of guided modes, by using appropriate Bessel functions and applying the boundary conditions, are performed to find out the guiding characteristics of the proposed waveguide. For verification and usage in design and manufacturing process, the computer-calculation of the waveguide transmission characteristics is also performed by applying the rigorous full-vectorial finite difference method. Providing variations of the effective area for the fundamental mode of the designed waveguide with different numbers of cladding layers, ranging from 2.6056 ㎛2 to 5.9673 ㎛2 over the operation wavelength, generally as the core refractive index n1 is higher, the mode area becomes smaller and the result leads to more optimistic effect for nonlinear device applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.41-48
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• 2022

As the COVID-19 situation continues, early childhood are unable to attend early childhood education institutions and are spending more time with their parents at home. Parents are faced with a situation where they have to spend a lot of time at home to teach their children for Korean word learning or play activities. This act as a lot of psychological burden and stress for parents. In order to relieve the psychological burden of parents, the design and implementation of early childhood learning assistant system that can support Korea word education and play activities using artificial intelligence blocks of block coding technique was proposed in this study. The usage of a proposed system can not only reduce the burden on parents for their children's learning, but also can be actively used in the field of early childhood education so many learning effects can be expected.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.319-328
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• 2021

With popularization of services for massive content, the fundamental limitations of TCP/IP networking were discussed and a new paradigm called Information-centric networking (ICN) was presented. In ICN, content is addressed by the content identifier (content name) instead of the location identifier such as IP address, and network nodes can use the cache to store content in transit to directly service subsequent user requests. As the user request can be serviced from nearby network caches rather than from far-located content servers, advantages such as reduced service latency, efficient usage of network bandwidth, and service scalability have been introduced. However, these advantages are determined by how actively content stored in the cache can be utilized. In this paper, we 1) introduce content access schemes in Named-data networking, one of the representative ICN architectures; 2) in particular, review the schemes that allow access to cached content away from routing paths; 3) conduct comparative study on the performance of the schemes using the ndnSIM simulator.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.376-383
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• 2022

The improved performance of computer parts, such as graphic card, CPU, and main board, has led to the need for power supplies with a high power output. The dynamic load profile rapidly changes the usage of power consumption depending on load operations, such as PC power and air conditioner. Under dynamic load profile conditions, power consumption can be classified into maximum, normal, and standby power. Several problems arise in the case of maximum power. Peak power is generated at the system power source in the maximum-power situation. Frequent generation of peak power can cause high-frequency problems and reduce the life of high-pressure parts (especially high-pressure capacitors). For example, when a plurality of PCs are used, system overload occurs due to peak power generation and causes problems, such as power failure and increase in electricity bills due to exceeded contract power. To solve this problem, a system peak power limit/compensation power circuit is proposed for a power supply under dynamic load profile conditions. The proposed circuit detects the system current to determine the power situation of the load. When the system current is higher than the set level, the circuit recognizes that the system current generates peak power and compensates for the load power through a converter using a super capacitor as the power source. Thus, the peak power of loads with a dynamic load profile is limited and compensated for, and problems, such as high-frequency issues, are solved. In addition, the life of high-pressure parts is increased.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.333-344
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• 2022

In a container-based cloud environment, multiple containers can share a graphical processing unit (GPU), and GPU sharing can minimize idle time of GPU resources and improve resource utilization. However, in a cloud environment, GPUs, unlike CPU or memory, cannot logically multiplex computing resources to provide users with some of the resources in an isolated form. In addition, containers occupy GPU resources only when performing GPU operations, and resource usage is also unknown because the timing or size of each container's GPU operations is not known in advance. Containers unrestricted use of GPU resources at any given point in time makes managing resource contention very difficult owing to where multiple containers run GPU tasks simultaneously, and GPU tasks are handled in black box form inside the GPU. In this paper, we propose a container management technique to prevent performance degradation caused by resource competition when multiple containers execute GPU tasks simultaneously. Also, this paper demonstrates the efficiency of container management techniques that analyze and propose the problem of degradation due to resource competition when multiple containers execute GPU tasks simultaneously through experiments.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.5
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• pp.123-136
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• 2021

RPC (Remote Procedure Call)-based Graphics Processing Unit (GPU) virtualization technology is one of the technologies for sharing GPUs with multiple user virtual machines. However, in a cloud environment, unlike CPU or memory, general GPUs do not provide a resource isolation technology that can limit the resource usage of virtual machines. In particular, in an RPC-based virtualization environment, since GPU tasks executed in each virtual machine are performed in the form of multi-process, the lack of resource isolation technology causes performance degradation due to resource competition. In addition, the GPU memory competition accelerates the performance degradation as the resource demand of the virtual machines increases, and the fairness decreases because it cannot guarantee equal performance between virtual machines. This paper, in the RPC-based GPU virtualization environment, analyzes the performance degradation problem caused by resource contention when the GPU memory requirement of virtual machines exceeds the available GPU memory capacity and proposes a GPU memory management technique to solve this problem. Also, experiments show that the GPU memory management technique proposed in this paper can improve the performance of GPGPU tasks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1078-1090
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• 2022

The distribution patterns of battery usage time data per battery level are able to affect the performance of estimating battery remaining time in mobile devices. Outliers may mainly affect the estimation performance of statistical regression methods. In this paper, we propose a software framework that detects and processes outliers to improve the estimation performance of statistical regression methods. The proposed framework first detects outliers that degrade the estimation performance. The proposed framework replaces outliers with smoothed data. The difference between an outlier and its replaced data will be properly distributed into individual data. Finally, individual data are reinforced to improve the estimation performance. The numerical results obtained by experimenting the proposed framework confirmed that it yielded good performance of estimating battery remaining time.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.259-268
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• 2022

With prosperous usage of cloud services to improve management efficiency due to the explosive increase in data volume, various cryptographic techniques are being applied in order to preserve data privacy. In spite of the vast computing resources of cloud systems, decrease in storage efficiency caused by redundancy of data outsourced from multiple users acts as a factor that significantly reduces service efficiency. Among several approaches on privacy-preserving data deduplication over encrypted data, in this paper, the research results for improving efficiency of encrypted data deduplication using trusted execution environment (TEE) published in the recent USENIX ATC are analysed in terms of security and efficiency of the participating entities. We present a way to improve the stability of a key-managing server by integrating it with individual clients, resulting in secure deduplication without independent key servers. The experimental results show that the communication efficiency of the proposed approach can be improved by about 30% with the effect of a distributed key server while providing robust security guarantees as the same level of the previous research.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1388-1395
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• 2009

In March 2007, Korea's Ministry of Construction & Transportation (MOCT) established "Guidelines on the Computerization and Use of Geotechnical Investigation Results," which took effect as official instructions. The 2007 Geotechnical Information DB Construction Project is underway as a model project for a stable geotechnical information distribution system based on the MOCT guidelines, accompanied by user education on the geotechnical data distribution system. This study introduces a geotechnical data entry system characterized by the standardization of the geotechnical investigation form, the standardization of metadata for creating the geotechnical data to be distributed, and the creation of borehole space data based on the world geodetic system according to the changes in the national coordinate system, to define a unified DB structure and the items for the geotechnical data entry system and to computerize the field geotechnical investigation results using the MOCT guidelines. In addition, the present operating status of the geotechnical data entry system and entry data processing statistics are introduced through an analysis of the model project, and the problems of the project are analyzed to suggest improvements. Education on, and the implementation of, the model project for the geotechnical data entry system, which was developed via the standardization of the geotechnical investigation results form and the metadata for institutions showed that most users can use the system easily. There were problems, however, including those related to the complexity of metadata creation, partial errors in moving to the borehole data window, partial recognition errors in the installation program for different computer operating systems, etc. Especially, the individual standard form usage and the specificity of the person who enters the geotechnical information for the Korea National Housing Corporation, among the institutions under MOCT, required partial improvement of the geotechnical data entry system. The problems surfaced from this study will be promptly addressed in the operation and management of the geotechnical data DB center in 2008.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.85-92
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• 2023

Deep learning applications are increasingly being leveraged for disease detection tasks in medical imaging modalities such as X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). Most data-centric deep learning challenges necessitate the use of supervised learning methodologies to attain high accuracy and to facilitate performance evaluation through comparison with the ground truth. Supervised learning mandates a substantial amount of image and label sets, however, procuring an adequate volume of medical imaging data for training is a formidable task. Various data augmentation strategies can mitigate the underfitting issue inherent in supervised learning-based models that are trained on limited medical image and label sets. This research investigates the enhancement of a deep learning-based rib fracture segmentation model and the efficacy of data augmentation techniques such as left-right flipping, rotation, and scaling. Augmented dataset with L/R flipping and rotations(30°, 60°) increased model performance, however, dataset with rotation(90°) and ⨯0.5 rescaling decreased model performance. This indicates the usage of appropriate data augmentation methods depending on datasets and tasks.