• Journal of the Society of Naval Architects of Korea
• /
• v.60 no.1
• /
• pp.31-37
• /
• 2023

In the present study, a method of performing cavitation erosion test directly on the anodized surface of the rudder model is proposed, not applying ink or paint on its surface. An image processing technique is newly developed to quantitatively evaluate the erosion damages on the rudder model surface after erosion test. The preprocessing saturation image, image smoothing, adaptive hysteresis thresholding and eroded area detection algorithms are in the image processing program. The rudder cavitation erosion tests are conducted in the rudder deflection angle range of 0° to -4°, which is used to maintain a straight course at the highest speed of the targeted navy ship. In the case of the conventional flat-type full-spade rudder currently being used in the target ship, surface erosion can occur on the model rudder surface in the above rudder deflection angle range. The bubble type of cavitation occurs on rudder surface, which is estimated to be the main reason of erosion damage on the rudder surface.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.240-243
• /
• 2021

Recently, there have been research results of applying Big data and AI technologies to the evaluation and individual learning for education. It is information technology innovations that collect dynamic and complex data, including student personal records, physiological data, learning logs and activities, learning outcomes and outcomes from social media, MOOCs, intelligent tutoring systems, LMSs, sensors, and mobile devices. In addition, e-learning was generated a large amount of learning data in the COVID-19 environment. It is expected that learning analysis and AI technology will be applied to extract meaningful patterns and discover knowledge from this data. On the learner's perspective, it is necessary to identify student learning and emotional behavior patterns and profiles, improve evaluation and evaluation methods, predict individual student learning outcomes or dropout, and research on adaptive systems for personalized support. This study aims to contribute to research in the field of education by researching and classifying machine learning technologies used in anomaly detection and recommendation systems for educational data.

• The Journal of Bigdata
• /
• v.6 no.2
• /
• pp.99-108
• /
• 2021

Recently, unexpected and more advanced cyber medical treat attacks are on the rise. However, in responding to various patterns of cyber medical threat attack, rule-based security methodologies such as physical blocking and replacement of medical devices have the limitations such as lack of the man-power and high cost. As a way to solve the problems, the medical community is also paying attention to artificial intelligence technology that enables security threat detection and prediction by self-learning the past abnormal behaviors. In this study, there has collecting and learning the medical information data from integrated Medical-Information-Systems of the medical center and introduce the research methodology which is to develop the AI-based Net-Working Behavior Adaptive Information data. By doing this study, we will introduce all technological matters of rule-based security programs and discuss strategies to activate artificial intelligence technology in the medical information business with the various restrictions.

• Journal of Smart Tourism
• /
• v.4 no.2
• /
• pp.5-14
• /
• 2024

This study explores the transformative potential of machine learning (ML) and ML-driven data analytics in the hospitality industry. It provides a comprehensive overview of this emerging method, from explaining ML's origins to introducing the evolution of ML-driven data analytics in the hospitality industry. The present study emphasizes the shift embodied in ML, moving from explicit programming towards a self-learning, adaptive approach refined over time through big data. Meanwhile, social media analytics has progressed from simplistic metrics deriving nuanced qualitative insights into consumer behavior as an industry-specific example. Additionally, this study explores innovative applications of these innovative technologies in the hospitality sector, whether in demand forecasting, personalized marketing, predictive maintenance, etc. The study also emphasizes the integration of ML and social media analytics, discussing the implications like enhanced customer personalization, real-time decision-making capabilities, optimized marketing campaigns, and improved fraud detection. In conclusion, ML-driven hospitality data analytics have become indispensable in the strategic and operation machinery of contemporary hospitality businesses. It projects these technologies' continued significance in propelling data-centric advancements across the industry.

• Journal of Biomedical Engineering Research
• /
• v.23 no.3
• /
• pp.253-261
• /
• 2002

A spatially adaptive falter was formulated to imrove PET image qualify and the Performance of the filter was evaluated using simulation and phantom and human PET studies. In the proposed filter. if a pixel was identified as the edge Pixel, the Pixel value was Preserved. Otherwise a Pixel was replaced by the mean of the pixel values weighted by 2:7: 2. A Pixel was identified as the edge Pixel. if it satisfies the following conditions : the number of ADs (absolute difference between center and neighborhood pixels) which is smaller than THl (($pix_max{\times}0.1/log_2(NPM)$, NPM : mean of 6 neighborhood pixels excluding minimum and maximum) is 8-k and the number of ADs which is lager than TH2 ($NPM{\times}0.1$) is k. where k : 2, 3, …, 6. The results of this study demonstrate the superior performance of the Proposed titter compared to Gaussian fitter, weight median filter and subset averaged median filter. The proposed tittering method is simple but effective in increasing uniformity and contrast with minimal degradation of spatial resolution of PET images and thus. is expected to Provide improved diagnositc quality PET images .

• Journal of the Korean Society of Radiology
• /
• v.82 no.6
• /
• pp.1477-1492
• /
• 2021

Purpose Dedicated breast CT is an emerging volumetric X-ray imaging modality for diagnosis that does not require any painful breast compression. To improve the detection rate of weakly enhanced lesions, an adaptive image rescaling (AIR) technique was proposed. Materials and Methods Two disks containing five identical holes and five holes of different diameters were scanned using 60/100 kVp to obtain single-energy CT (SECT), dual-energy CT (DECT), and AIR images. A piece of pork was also scanned as a subclinical trial. The image quality was evaluated using image contrast and contrast-to-noise ratio (CNR). The difference of imaging performances was confirmed using student's t test. Results Total mean image contrast of AIR (0.70) reached 74.5% of that of DECT (0.94) and was higher than that of SECT (0.22) by 318.2%. Total mean CNR of AIR (5.08) was 35.5% of that of SECT (14.30) and was higher than that of DECT (2.28) by 222.8%. A similar trend was observed in the subclinical study. Conclusion The results demonstrated superior image contrast of AIR over SECT, and its higher overall image quality compared to DECT with half the exposure. Therefore, AIR seems to have the potential to improve the detectability of lesions with dedicated breast CT.

• Korean Journal of Cognitive Science
• /
• v.16 no.4
• /
• pp.305-322
• /
• 2005

Watermarking is a widely employed method tn protecting copyright of a digital image, the owner's unique image is embedded into the original image. Strengthened level of watermark insertion would help enhance its resilience in the process of extraction even from various distortions of transformation on the image size or resolution. However, its level, at the same time, should be moderated enough not to reach human visibility. Finding a balance between these two is crucial in watermarking. For the algorithm for watermarking, the predefined strength of a watermark, computed from the physical difference between the original and embedded images, is applied to all images uniformal. The mean brightness or contrast of the surrounding images, other than the absolute brightness of an object, could affect human sensitivity for object detection. In the present study, we examined whether the detectability for watermark noise might be attired by image statistics: mean brightness and contrast of the image. As the first step to examine their effect, we made rune fundamental images with varied brightness and control of the original image. For each fundamental image, detectability for watermark noise was measured. The results showed that the strength ot watermark node for detection increased as tile brightness and contrast of the fundamental image were increased. We have fitted the data to a regression line which can be used to estimate the strength of watermark of a given image with a certain brightness and contrast. Although we need to take other required factors into consideration in directly applying this formula to actual watermarking algorithm, an adaptive watermarking algorithm could be built on this formula with image statistics, such as brightness and contrast.

• Journal of Biomedical Engineering Research
• /
• v.25 no.4
• /
• pp.261-268
• /
• 2004

Osteoporosis is a clinical condition in which the amount of bone tissue is reduced and the likelihood of fracture is increased. It is known that the electrical property of the bone is related to its density, and, in particular, the electrical resistance of the bone decreases as the bone loss increases. This implies that the electrical property of bone may be an useful parameter to diagnose osteoporosis, provided that it can be readily measured. The study attempted to evaluate the electrical conductivity of bone using a technique of electrical impedance tomography (EIT). It nay not be easy in general to get an EIT for the bone due to the big difference (an order of 2) of electrical properties between the bone and the surrounding soft tissue. In the present study, we took an adaptive mesh regeneration technique originally developed for the detection of two phase boundaries and modified it to be able to reconstruct the electrical conductivity inside the boundary provided that the geometry of the boundary was given. Numerical simulation was carried out for a tibia phantom, circular cylindrical phantom (radius of 40 mm) inside of which there is an ellipsoidal homeogenous tibia bone (short and long radius are 17 mm and 15 mm, respectively) surrounded by the soft tissue. The bone was located in the 15 mm above from the center of the circular cross section of the phantom. The electrical conductivity of the soft tissue was set to be 4 mS/cm and varies from 0.01 to 1 ms/cm for the bone. The simulation considered measurement errors in order to look into its effects. The simulated results showed that, if the measurement error was maintained less than 5 %, the reconstructed electrical conductivity of the bone was within 10 % errors. The accuracy increased with the electrical conductivity of the bone, as expected. This indicates that the present technique provides more accurate information for osteoporotic bones. It should be noted that tile simulation is based on a simple two phase image for the bone and the surrounding soft tissue when its anatomical information is provided. Nevertheless, the study indicates the possibility that the EIT technique may be used as a new means to detect the bone loss leading to osteoporotic fractures.

• Journal of Digital Convergence
• /
• v.10 no.9
• /
• pp.1-13
• /
• 2012

This study aims to analyze actual conditions of the present national defense information network operation, the structure and management of the system, communication lines, security equipments for the lines, the management of network and software, stored data and transferred data and even general vulnerable factors of our army tactical C4I system. Out of them, by carrying out an extensive analysis of the army tactical C4I system, likely to be the core of future information warfare, this study suggested plans adaptive to better information security, based on the vulnerable factors provided. Firstly, by suggesting various information security factor technologies, such as VPN (virtual private network), IPDS (intrusion prevention & detection system) and firewall system against virus and malicious software as well as security operation systems and validation programs, this study provided plans to improve the network, hardware (computer security), communication lines (communication security). Secondly, to prepare against hacking warfare which has been a social issue recently, this study suggested plans to establish countermeasures to increase the efficiency of the army tactical C4I system by investigating possible threats through an analysis of hacking techniques. Thirdly, to establish a more rational and efficient national defense information security system, this study provided a foundation by suggesting several priority factors, such as information security-related institutions and regulations and organization alignment and supplementation. On the basis of the results above, this study came to the following conclusion. To establish a successful information security system, it is essential to compose and operate an efficient 'Integrated Security System' that can detect and promptly cope with intrusion behaviors in real time through various different-type security systems and sustain the component information properly by analyzing intrusion-related information.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.328-334
• /
• 2012

Continuous fetal heart beat monitoring has assisted clinicians in assuring fetal well-being during antepartum and intrapartum. Fetal heart rate (FHR) is an important parameter of fetal health during pregnancy. The Doppler ultrasound is one of very useful methods that can non-invasively measure FHR. Although it has been commonly used in clinic, inaccurate heart rate reading has not been completely resolved.. The objective of this study is to improve detection algorithm of FHR from Doppler ultrasound signal with simple method. We modified autocorrelation function to enhance signal periodicity and adopted adaptive window size and shifted for data segment to be analysed. The proposed method was applied to real measured data, and it was verified that beat-to-beat FHR estimation result was comparable with the reference fetal ECG data. This simple and effective method is expected to be implemented in the embedded system.