• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.109-114
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• 2024

Enterprise storage systems that require high data reliability are applying RAID (Redundant Array of Independent Disks) systems to recover from data loss and failure. In particular, RAID 5 ensures space efficiency and reliability by distributing parity across multiple storage devices. However, when storage devices have different capacities, RAID is built based on the smallest capacity storage device, resulting in wasted storage space. Therefore, research is needed to solve this resource management problem. In this paper, we propose a method for RAID grouping of each independent NAND flash memory block in a RAID consisting of SSD (Solid State Disk) with external SSDs as well as internal SSDs. This method is divided into a policy for delivering block information inside SSDs to the RAID system and a policy for RAID grouping of physical addresses delivered from the RAID system. This method allows us to maintain a RAID that does not waste resources when SSDs of different capacities are grouped into RAID5. Finally, we demonstrate the effectiveness of the proposed method through experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.189-196
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• 2024

Frequent false positives alarm from the Intelligent Selective Control System have raised significant concerns. These persistent issues have led to declines in operational efficiency and market credibility among agents. Developing a new model or replacing the existing one to mitigate false positives alarm entails substantial opportunity costs; hence, improving the quality of the training dataset is pragmatic. However, smaller organizations face challenges with inadequate capabilities in dataset collection and refinement. This paper proposes an automatic human pose data collection system centered around a human pose estimation model, utilizing camera-based sensor fusion techniques and edge devices. The system facilitates the direct collection and real-time processing of field data at the network periphery, distributing the computational load that typically centralizes. Additionally, by directly labeling field data, it aids in constructing new training datasets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.77-82
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• 2024

Recent advancements in artificial intelligence (AI) technology have led to an increase in the implementation of AI applications in mobile environments. However, due to the limited resources in mobile devices compared to desktops and servers, there is growing interest in research aimed at efficiently executing AI workloads on mobile platforms. While most studies focus on offloading to edge or cloud solutions to mitigate computing resource constraints, research on the characteristics of file I/O related to storage access in mobile settings remains underexplored. This paper analyzes file I/O traces generated during the execution of deep learning applications in mobile environments and investigates how they differ from traditional mobile workloads. We anticipate that the findings of this study will be utilized to design future smartphone system software more efficiently, considering the file access characteristics of deep learning.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.693-704
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• 2024

Artificial intelligence (AI) technology is actively being applied for the interpretation of medical imaging, such as chest X-rays. AI-based software medical devices, which automatically detect various types of abnormal findings in chest X-ray images to assist physicians in their interpretation, are actively being commercialized and clinically implemented in Korea. Several important issues need to be considered for AI-based detection assistant tools to be applied in clinical practice: the evaluation of performance and efficacy prior to implementation; the determination of the target application, range, and method of delivering results; and monitoring after implementation and legal liability issues. Appropriate decision making regarding these devices based on the situation in each institution is necessary. Radiologists must be engaged as medical assessment experts using the software for these devices as well as in medical image interpretation to ensure the safe and efficient implementation and operation of AI-based detection assistant tools.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.13-18
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• 2024

Recently, reliability has become more important as flash-based storage devices are actively used in cloud servers and data centers. Flash memory chips have limitations in reading/writing, so if writing is concentrated in one location, the chip can no longer be used. To solve this problem and improve reliability, it is necessary to equalize the wear of flash memory chips. However, in order to equalize the wear of flash memory with increasing capacity, the workload increases proportionally. In particular, when searching for a block with the maximum/minimum number of deletions for all blocks of a flash memory chip, the cost increases depending on the capacity of the storage device. In this paper, a random selection method of blocks was applied to solve the previous problem. When k is the randomly selected block, actual experimental results confirmed that searching all blocks with an k value of 4 or more yields similar results.

• Journal of IKEEE
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• v.28 no.3
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• pp.321-328
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• 2024

The growth of the multimedia industry has led to the advent of digital devices utilizing images of varying resolutions. Accordingly, it is essential to adapt the resolution of the source image to match with the resolutions of the target digital device, while ensuring that the quality of the input image is preserved throughout this process. In this paper, we propose the implementation of a hardware system that performs image scaling using interpolation algorithms. The bicubic interpolation algorithm is employed as the interpolation algorithm, as it produces the highest quality image among the three most common methods. Each interpolated axis in the image can be operated independently to achieve asymmetric scaling in any desired ratio. The hardware of the proposed scaler satisfies real-time processing and is implemented with less memory resources than the previously studied hardware using the time allocation method, showing that it is a suitable structure for the hardware of the scaler.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.4
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• pp.421-429
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• 2000

In present, ATM integrated switching system has been developed to a mixed modules that complexed switching system including maintenance, operation based on B-ISDN/LAN service and plug-in module, , which runs on workstation computer system. Meanwhile, workstation has HMI operation system feature including file system management, time management, graphic processing, TMN agent function. The workstation has communicated with between ATM switching module and clients. This computer system architecture has much burden messages communication among processes or processor. These messages communication consume system resources which are socket, message queue, IO device files, regular files, and so on. Therefore, in this paper we proposed new performance modeling with this system architecture. We will analyze the system bottleneck and improve system performance. In addition, in the future, the system has many additional features should be migrated to workstation system, we need previously to evaluate system bottleneck and redesign it. In performance model, we use queueing network model and the simulation package is used PDQ and C-program.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.63-69
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• 2014

For the safety messages in IEEE 802.11p vehicles network environment(WAVE), strict periodic beacon broadcasting requires status advertisement to assist the driver for safety. WAVE standards apply multiple radios and multiple channels to provide open public road safety services and improve the comfort and efficiency of driving. Although WAVE standards have been proposed multi-channel multi-radio, the standards neither consider the WAVE multi-radio environment nor its effect on the beacon broadcasting. Most of beacon broadcasting is designed to be delivered on only one physical device and one control channel by the WAVE standard. also conflict-free channel assignment of the fewest channels to a given set of radio nodes without causing collision is NP-hard, even with the knowledge of the network topology and all nodes have the same transmission radio. Based on the latest standard IEEE 802.11p and IEEE 1609.4, this paper proposes an interference aware-based channel assignment algorithm with Nash bargaining solution that minimizes interference and increases throughput with wireless mesh network, which is deigned for multi-radio multi-cahnnel structure of WAVE. The proposed algorithm is validated against numerical simulation results and results show that our proposed algorithm is improvements on 8 channels with 3 radios compared to Tabu and random channel allocation algorithm.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.21-29
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• 2016

Cell segmentation is an important but time-consuming and laborious task in biological image analysis. An automated, robust, and fast method is required to overcome such burdensome processes. These needs are, however, challenging due to various cell shapes, intensity, and incomplete boundaries. A precise cell segmentation will allow to making a pathological diagnosis of tissue samples. A vast body of literature exists on cell segmentation in microscopy images [1]. The majority of existing work is based on input images and predefined feature models only - for example, using a deformable model to extract edge boundaries in the image. Only a handful of recent methods employ data-driven approaches, such as supervised learning. In this paper, we propose a novel data-driven cell segmentation algorithm for bright-field microscopy images. The proposed method minimizes an energy formula defined by two dictionaries - one is for input images and the other is for their manual segmentation results - and a common sparse code, which aims to find the pixel-level classification by deploying the learned dictionaries on new images. In contrast to deformable models, we do not need to know a prior knowledge of objects. We also employed convolutional sparse coding and Alternating Direction of Multiplier Method (ADMM) for fast dictionary learning and energy minimization. Unlike an existing method [1], our method trains both dictionaries concurrently, and is implemented using the GPU device for faster performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.106-116
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• 2011

USN(Ubiquitous Sensor Network) environment permits us to access whatever information we want, whenever we want. The technologies to provide a basement to these environments premise an accurate location establishment. Especially, ITS(Intelligent Transportation Systems) is easily constructed by applying USN technology. Localization can be categorized as either Range-based or Range-free. Range-based is known to be not suitable for the localization based on sensor network, because of the irregularity of radio propagation and the additional device requirement. The other side, Range-free is much appropriated for the resource constrained sensor network because it can actively locate by means of the communication radio. But, generally the location accuracy of Range-free is low. Especially, it is very low in a low-density environment. So, these two methods have both merits and demerits. Therefore, it requires a new method to be able to improve tracking accuracy by combining the two methods. This paper proposes the tracking scheme based on range-hybrid, which can markedly enhance tracking accuracy by effectively using the information of surrounding nodes and the RSSI(Received Signal Strength Indication) that does not require additional hardware. Additionally, we present a method, which can improve the accuracy of vehicle tracking by adopting the prediction mechanism. Simulation results show that our method outperforms other methods in the transportation simulation environment.