• The Plant Pathology Journal
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• v.39 no.5
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• pp.504-512
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• 2023

After transitioning from periodic to model-based control policy for fire blight blossom infection, it is crucial to provide the timing of field application with easy and accurate information. To assess the risk of blossom infection, Maryblyt was employed in 31 sites across apple-producing regions nationwide, including areas prone to fire blight outbreaks, from 2021 to 2023. In 2021 and 2023, two and seven sites experienced Blossom Infection Risk-Infection warning occurrences among 31 sites, respectively. However, in 2022, most of the sites observed Blossom Infection Risk-Infection from April 25 to 28, highlighting the need for blossom infection control. For the comparison between the two model-based control approaches, we established treatment 1, which involved control measures according to the Blossom Infection Risk-Infection warning and treatment 2, aimed at maintaining the Epiphytic Infection Potential below 100. The analysis of control values between these treatments revealed that treatment 2 was more effective in reducing Blossom Infection Risk-Infection and the number of days with Epiphytic Infection Potential above 100, with respective averages of 95.6% and 93.0% over the three years. Since 2022, the implementation of the K-Maryblyt system and the deployment of Automated Weather Stations capable of measuring orchard weather conditions, with an average of 10 stations per major apple fire blight county nationwide, have taken place. These advancements will enable the provision of more accurate and timely information for farmers based on fire blight models in the future.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1472-1479
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• 2024

Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware components to ensure a reliable and safe physical power production and supply. Renewable Energy Sources (RESs) add uncertainty to energy demand that can be dealt with flexible operation (e.g., load-following) of CPES; at the same time, scenarios that could result in severe consequences due to both component stochastic failures and aging of the cyber system of CPES (commonly overlooked) must be accounted for Operation & Maintenance (O&M) planning. In this paper, we make use of Deep Reinforcement Learning (DRL) to search for the optimal O&M strategy that, not only considers the actual system hardware components health conditions and their Remaining Useful Life (RUL), but also the possible accident scenarios caused by the failures and the aging of the hardware and the cyber components, respectively. The novelty of the work lies in embedding the cyber aging model into the CPES model of production planning and failure process; this model is used to help the RL agent, trained with Proximal Policy Optimization (PPO) and Imitation Learning (IL), finding the proper rejuvenation timing for the cyber system accounting for the uncertainty of the cyber system aging process. An application is provided, with regards to the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED).

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.2
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• pp.151-158
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• 2024

Microalgae are aquatic microorganisms capable of photosynthetic growth using water, carbon dioxide and sunlight, and can replace petroleum for transportation. It is receiving great attention as a potential next-generation biological resource. The microalgae biodiesel production process is largely based on the development of highly efficient strains and mass production. It consists of cultivation, harvesting, oil extraction, fuel conversion and by-product utilization. Currently, microalgae diesel is 3-5 times more expensive than petroleum diesel. However, with the optimization of each element technology and the development of integrated systems, not only biofuels, but also industrial materials, wastewater treatment, and greenhouse gases As application expands to various fields such as abatement, the timing of commercialization may be brought forward. Oil prices have recently fallen due to the influence of sail gas. Although there has been a significant drop, global warming is an urgent challenge for current and future generations. In particular, Korea, which does not have oil resources, We must always prepare for political environmental changes, high oil prices, and energy crises. In this paper, the need for eco-friendly biofuel for carbon dioxide conversion. In addition to research trends, domestic and international research trends, and economic prospects, the concept of microalgae and the element technologies of the biodiesel production process are briefly discussed introduced.

• Clinical Endoscopy
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• v.57 no.4
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• pp.424-433
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• 2024

Colonic stent placement is a commonly used bridging strategy for surgery in patients with obstructive colorectal cancer. The procedure involves the placement of a self-expandable metallic stent (SEMS) across the obstructive lesion to restore intestinal patency and alleviate the symptoms of obstruction. By allowing patients to receive surgery in a planned and staged manner with time for preoperative optimization and bowel preparation, stent placement may reduce the need for emergency surgery, which is associated with higher complication rates and poorer outcomes. This review focuses on the role of colon stenting as a bridge to surgery in the management of obstructive colorectal cancer. SEMS as a bridge to surgery for left-sided colon cancer has been demonstrated to be particularly useful; however, further research is needed for its application in cases of right-sided colon cancer. Colon stent placement also has limitations and potential complications including stent migration, re-obstruction, and perforation. However, the timing of curative surgery after SEMS placement remains inconclusive. Considering the literature to date, performing surgery at an interval of approximately 2 weeks is considered appropriate. Therefore, colonic stent placement may be an effective strategy as a bridge to surgery in patients with obstructive colorectal cancer.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.1-9
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• 2004

In this paper, we proposed a hardware(H/W) structure which can compress and recontruct the input image in real time operation and implemented it into a FPGA platform using VHDL(VHSIC Hardware Description Language). All the image processing element to process both compression and reconstruction in a FPGA were considered each of them was mapped into a H/W with the efficient structure for FPGA. We used the DWT(discrete wavelet transform) which transforms the data from spatial domain to the frequency domain, because use considered the motion JPEG2000 as the application. The implemented H/W is separated to both the data path part and the control part. The data path part consisted of the image processing blocks and the data processing blocks. The image processing blocks consisted of the DWT Kernel for the filtering by DWT, Quantizer/Huffman Encoder, Inverse Adder/Buffer for adding the low frequency coefficient to the high frequency one in the inverse DWT operation, and Huffman Decoder. Also there existed the interface blocks for communicating with the external application environments and the timing blocks for buffering between the internal blocks. The global operations of the designed H/W are the image compression and the reconstruction, and it is operated by the unit or a field synchronized with the A/D converter. The implemented H/W used the 54％(12943) LAB(Logic Array Block) and 9％(28352) ESB(Embedded System Block) in the APEX20KC EP20K600CB652-7 FPGA chip of ALTERA, and stably operated in the 70MHz clock frequency. So we verified the real time operation. that is. processing 60 fields/sec(30 frames/sec).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1139-1144
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• 2008

In this paper, we propose an automatic generation method of transaction level(TL) model from algorithmic model to verify system specification fast and effectively using virtual platform. The TL virtual platform including structural properties such as timing, synchronization and real-time is one of the effective verification frameworks. However, whenever change system specification or HW/SW mapping, we must rebuild virtual platform and additional design/verification time is required. And the manual description is very time-consuming and error-prone process. To solve these problems, we build TL library which consists of basic components of virtual platform such as CPU, memory, timer. We developed a set of design/verification tools in order to generate a virtual platform automatically. Our tools generate a virtual platform which consists of embedded real-time operating system (RTOS) and hardware components from an algorithmic modeling. And for communication between HW and SW, memory map and device drivers are generated. The effectiveness of our proposed framework has been successfully verified with a Joint Photographic Expert Group (JPEG) and H.264 algorithm. We claim that our approach enables us to generate an application specific virtual platform $100x{\tims}1000x$ faster than manual designs. Also, we can refine an initial platform incrementally to find a better HW/SW mapping. Furthermore, application software can be concurrently designed and optimized as well as RTOS by the generated virtual platform

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.112-119
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• 2008

Today, A matter of concern of home network technology increase. The standard of communication between home network devices are required. IEEE 802.1 AVB(Audio/Video Bridging) specifies transmission method for time-sensitive data between these devices using Ethernet in bridged local area networks. IEEE 802.1 AVB and IEEE 1588 PTP(Precision Time Protocol) have various message type for grandmaster selection and synchronize the devices. These messages bring on complexity protocol. We propose a method that uses Single TimeSync frame in order to the problem. Our proposal is appropriate process complexity and low transmission delay for home network by using the TimeSync frame. Furthermore, after all devices are adjusted to the single TimeSync frame, a resource reservation, a forwarding and queueing rule are needed for a time-sensitive application.

• Journal of Computing Science and Engineering
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• v.1 no.1
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• pp.56-73
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• 2007

Demands have been growing in safety-critical application fields for producing networked real-time embedded computing (NREC) systems together with acceptable assurances of tight service time bounds (STBs). Here a service time can be defined as the amount of time that the NREC system could take in accepting a request, executing an appropriate service method, and returning a valid result. Enabling systematic composition of large-scale NREC systems with STB certifications has been recognized as a highly desirable goal by the research community for many years. An appealing approach for pursuing such a goal is to establish a hard-real-time (HRT) component model that contains its own STB as an integral part. The TMO (Time-Triggered Message-Triggered Object) programming scheme is one HRT distributed computing (DC) component model established by the first co-author and his collaborators over the past 15 years. The TMO programming scheme has been intended to be an advanced high-level RT DC programming scheme that enables development of NREC systems and validation of tight STBs of such systems with efforts far smaller than those required when any existing lower-level RT DC programming scheme is used. An additional goal is to enable maximum exploitation of concurrency without damaging any major structuring and execution approaches adopted for meeting the first two goals. A number of previously untried program structuring approaches and execution rules were adopted from the early development stage of the TMO scheme. This paper presents new concrete justifications for those approaches and rules, and also discusses new extensions of the TMO scheme intended to enable further exploitation of concurrency in NREC system design and programming.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.468-470
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• 2002

We have designed X-ray detection system and multi-channel data acquisition system for Spiral CT application. X-ray detection system consists of scintillator and photodiode. Scintillator converts X-ray into visible light. Photodiode converts visible light into electrical signal. The multi-channel data acquisition system consists of analog, digital, master and backplane board. Analog board detects electrical signal and amplifies signal by 140dB. Digital board consists of MUX(Multiplex) which routes multi-channel analog signal to preamplifier, and ADC(Analog to Digital Converter) which converts analog signal into digital signal. Master board supplies the synchronized clock and transmits the digital data to image reconstructor. Backplane provides electrical power, analog output and clock signal. The system converts the projected X-ray signal over the detector array with large gain, samples the data in each channel sequentially, and the sampled data are transmitted to host computer in a given time frame. To meet the timing limitation, this system is very flexible since it is implemented by FPGA(Field Programmable Gate Array). This system must have a high-speed operation with low noise and high SNR(signal to noise ratio), wide dynamic range to get a high resolution image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2232-2240
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• 2015

Recently in the field of Big Data, there is a trend of collecting and reprocessing the existing data such as products having high interest of customers and past purchase details to be utilized for the analysis of transaction propensity of users(product recommendations, sales forecasts, etc). Studies related to the propensity of previous users has limitations on its range of subjects and investigation timing and difficult to make predictions on detailed products with lack of real-time thus there exists difficult disadvantages of introducing appropriate and quick sales strategy against the trend. This paper utilizes the machine learning algorithm application to analyze the transaction propensity of users. As a result of applying the machine learning algorithm, it has demonstrated that various indicators which can be deduced by detailed product were able to be extracted.