• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.685-691
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• 2023

This study aims to raise awareness of the exposure index according to the Sub-ROI in clinical use by studying the effect of Sub-ROI's change on exposure index and dose during Chest PA examination. In this study, to examine the changes in EI and ESD according to the Sub-ROI setting, the irradiation conditions were set to 120 kVp, 200 mA, 2 mAs, and the SID was fixed to 180cm. Five types of Sub-ROI were used. The average value of EI according to the Sub-ROI's change was 135.58 ± 0.89 in AEC, 100.80 ± 0.80 in VR, 143.43 ± 0.76 in HR, 103.22 ± 0.68 in LS, and 102.79 ± 0.84 in SS. The mean value of ESD was 30.28±0.50 µGy in AEC, 30.16 ± 0.44 µGy in VR, 30.30 ± 0.46 µGy in HR, 30.23 ± 0.46 µGy in LS, and 30.28 ± 0.51 µGy in SS. As a result of this study, based on the AEC mode recommended by the manufacturer, the VR (25.7%), LS (23.9%), and SS (24.2%) modes decreased, and the HR mode increased by 5.7%. However, ESD was not affected by the Sub-ROI's change. Therefore, Sub-ROI may change EI during the Chest PA examination, it is considered that Sub-ROI should be used appropriately when setting protocols in clinical use.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.851-857
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• 2023

The purpose of this study is to investigate the effect of changes in collimation size and sub ROI on exposure index(EI) in hand radiography, present collimation size and EI suitable for average hand size of Koreans, and present the effect of changes in sub ROI on EI. The subjects of this study were hand-wrist phantom, and the exposure conditions were set to 55 kVp, 125, mA, and 6.25 mAs, and source to image receptor distance was applied to 110 cm. Based on the vendor recommended sub-ROI (18.7" × 18.7", 8" × 10", 8" × 7.4", 6" × 7.4")and the textbook's recommended sub-ROI 8" × 10", each obtaining 30 images, and comparing the EI shown in the equipment. The EI according to the change in the size of the collimation were 1663.7±4.52, 8"×10" is 1489.1±4.49, 8"×7.4" is 1716.9±3.00, 6"×7.4" is 168.7±3.66 for each EI, and the average value of each value was statistically significant. The average EI according to the sub ROI change was 1489.1±4.49 for SS, LS was 1694.8±5.19 for AEC, 2052.9±5.96, VR was 1548.3±3.20, and HR was 1663.2±4.33. The appropriate field size considering the hand size of Koreans was found to be 8"×7.4". In addition, when the field size increases based on the generally known field size (8"×10") during hand radiography, the EI value changes from a maximum of 15% to a minimum of 11%, and the sub ROI shape based on sub ROI 'SS' Depending on the change, the EI value increased from a maximum of 37% to a minimum of 3%.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1149-1155
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• 2023

This study aims to investigate the effect of changes in the Sub ROI on exposure index(EI) and to present indicators of changes in EI values that may occur when changing Sub ROI in clinical practice. This study was conducted on a subject of 20 cm of acrylic for a setting similar to abdominal radiography, and the specifications of one acrylic sheet is 20 × 20 × 5 cm. The survey conditions were the same as 80 kVp , 320 mA, 25 ms, SID 110 cm and the Sub ROI obtained 30 images for each type using five types provided by the equipment company. The EI value provided by the equipment and entrance skin exposure(ESE) were compared and analyzed. The mean value of EI according to the change in Sub ROI was 101.18±0.27 for LS, 106.57±0.31 for AEC, 107.74±0.39 for VR, 107.90±0.38 for HR, and 109.72±0.32 for SS (p<0.01). The average value of ESE by sub ROI type (LS, AEC, VR, HR, SS) was measured to be 476.45±1.71 μGy, 476.92±1.48 μGy, 476.14±2.30 μGy, 475.61±1.96 μGy, and 477.14±1.46 μGy, with statistically significant differences (p<0.01). As a result of this study, the EI according to the sub ROI type is based on LS(109.72), which represents the minimum value. AEC increased 5.3%, VR increased 6.4%, HR increased 6.6%, SS increased 8.4%, and overall, increased by about 5.3%. As for the average value of ESE, HR(475.61 μGy)type showed the minimum value, and based on this, AEC increased 0.27%, VR increased 0.11%, LS increased 0.17%, SS increased 0.32%, and overall, increased by about 0.17%.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.143-152
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• 2006

JPEG2000, the standard of still image compression based on wavelet, will be widely used. One of the greatest characteristics of JPEG2000 is to offer ROI(Region-Of-Interest) coding. This is to compress with high quality the region that the user wants better than the other region. JPEG2000 and ROI have different parameters, which are tile size and ROI size, wavelet filter type and ROI shape and its location, codeblock size and number of ROI, number of DWT decomposition level and ROI importance, and number of quality layer and low resolution sub-band importance. In this paper, we shows the correlation of the parameters and ROI coding methods through experiments. This helps an application select the parameters and the methods to meet the application.

• Journal of ILASS-Korea
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• v.29 no.3
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• pp.147-154
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• 2024

This study explores the rate of injection (ROI) and injection quantities of a solenoid-type high-pressure injector under varying conditions by integrating experimental methods with machine learning (ML) techniques. Experimental data for fuel injection were obtained using a Zeuch-based HDA Moehwald injection rate measurement system, which served as the foundation for developing a machine learning model. An artificial neural network (ANN) was employed to predict the ROI, ensuring accurate representation of injection behaviors and patterns. The present study examines the impact of ambient conditions, including chamber temperature, chamber pressure, and injection pressure, on the transient profiles of the ROI, quasi-steady ROI, and injection duration. Results indicate that increasing the injection pressure significantly increases ROI, with chamber pressure affecting its initial rising peak. However, the chamber temperature effect on ROI is minimal. The trained ANN model, incorporating three input conditions, accurately reflected experimental measurements and demonstrated expected trends and patterns. This model facilitates the prediction of various ROI profiles without the need for additional experiments, significantly reducing the cost and time required for developing injection control systems in next-generation aero-engine combustors.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2418-2425
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• 2021

Monazite is a phosphate mineral that contains thorium (Th) and rare earth elements. The Th concentration in monazite can be as high as 500 ppm, and it has the potential to be used as fuel in the nuclear power system. Therefore, this study aimed to conduct the techno-economic analysis (TEA) of Th extraction in the form of thorium oxide (ThO₂) from monazite. Th can be extracted from monazite through an alkaline fusion method. The TEA of ThO₂ production studied parameters, including raw materials, equipment costs, total plant direct and indirect costs, and direct fixed capital cost. These parameters were calculated for the production of 0.5, 1, and 10 ton ThO₂ per batch. The TEA study revealed that the highest production cost was ascribed to installed equipment. Furthermore, the highest return on investment (ROI) of 21.92% was achieved for extraction of 1 ton/batch of ThO₂, with a payback time of 4.56 years. With further increase in ThO₂ production to 10 ton/batch, the ROI was decreased to 5.37%. This is mainly due to a significant increase in the total capital investment with increasing ThO₂ production scale. The minimum unit production cost was achieved for 1 ton ThO₂/batch equal to 335.79 $/Kg ThO₂.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.63-71
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• 2009

In this study, we propose a revised dynamic ROI (Region-of-Interest) coding method in which the focused ROI is automatically extracted without help from users during the recovery process of low DOF (Depth-of-Field) JPEG2000 image. The proposed method creates edge mask information using high frequency sub-band data on a specific level in DWT (Discrete Wavelet Transform), and then identifies the edge code block for a high-speed ROI extraction. The algorithm scans the edge mask data in four directions by the unit of code block and identifies the edge code block simply and fastly using a edge threshold. As the results of experimentation applying for Implicit method, the proposed method showed the superiority in the side of speed and quality comparing to the existing methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.27-34
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• 2006

In this paper, we propose a combined region-based image retrieval system using EHD(Edge Histogram Descriptor) and CLD(Color Layout Descriptor) of MPEG-7 descriptors. The combined descriptor can efficiently describe edge and color features in terms of sub-image regions. That is, the basic unit for the selection of the region-of-interest (ROI) in the image is the sub-image block of the EHD, which corresponds to 16 (i.e., $4{\times}4)$ non-overlapping image blocks in the image space. This implies that, to have a one-to-one region correspondence between ELE and CLD, we need to take an $8{\times}8$ inverse DCT (IDCT) for the CLD. Experimental results show that the proposed retrieval scheme can be used for image retrieval with the ROI based image retrieval for MPEG-7 indexed images.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.282-294
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• 2017

In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

• Agribusiness and Information Management
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• v.1 no.2
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• pp.23-42
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• 2009

As technology develops, more advanced technologies involving GPS, GIS, RFID and sensor networks have been adopted in agriculture sector for u-Farm. However, technology adoptions have been evaluated as ineffective. Farmers and agri-business have low level of understanding on technology so it is not efficiently utilized. This study introduces a case of RFID/sensor networks of mushroom farm as a u-Farm case study, focusing on developing a framework for analysis of u-Farm investment returns. RFID and sensor networks improve real-time production control, processing management, and traceability. Integration of RFID and sensor networks leads to innovation into the mushroom farm, reducing labor cost, increasing productivity, and improving quality of the mushroom. The ROI which is used as an indicator of performance indicator is 413%.