• Journal of the Korea Society of Computer and Information
• /
• v.11 no.5 s.43
• /
• pp.157-164
• /
• 2006

The Recently, most of Internet attacks are zero-day types of the unknown attacks by Malware. Using already known Misuse Detection Technology is hard to cope with these attacks. Also, the existing information security technology reached the limits because of various attack's patterns over the Internet, as web based service became more affordable, web service exposed to the internet becomes main target of attack. This paper classifies the traffic type over the internet and suggests the Threat Management System(TMS) including the anomaly intrusion detection technologies which can detect and analyze the anomaly sign for each traffic type.

• Korean Journal of Artificial Intelligence
• /
• v.11 no.4
• /
• pp.1-8
• /
• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.

• IE interfaces
• /
• v.18 no.3
• /
• pp.268-276
• /
• 2005

In recent years, the money Laundering crimes are increasing by means of foreign exchange transactions. Our study proposes four scoring models to provide early warning of the laundering in foreign exchange transactions for both inward and outward remittances: logistic regression model, decision tree, neural network, and ensemble model which combines the three models. In terms of accuracy of test data, decision tree model is selected for the inward remittance and an ensemble model for the outward remittance. From our study results, the accumulated number of transaction turns out to be the most important predictor variable. The proposed scoring models deal with the transaction level and is expected to help the bank teller to detect the laundering related transactions in the early stage.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2001.10c
• /
• pp.19-27
• /
• 2001

Early detection of premonitory symptom of slope movement ensures tremendous saving of lives and repair costs from catastrophic disaster. Therefore, it is essential to constantly monitor the performance and integrity of both reinforced and un-reinforced cut slopes. We developed a novel monitoring system by using tension wire sensors. It's advantages are highly sensitivity, simple installation, large displacement measurement, durability of system, capability of remote sensing. Real-time measurement of slope surface movement is shown graphically and it gives a warning when the monitored value exceeds a given threshold level so that any sign of abnormal slope movement can be easily perceived.

• Journal of the Korean Geophysical Society
• /
• v.8 no.3
• /
• pp.137-143
• /
• 2005

Early detection of premonitory symptom of slope movement ensures tremendous saving of lives and repair costs from catastrophic disaster. Therefore, it is essential to constantly monitor the performance and integrity of both reinforced and un-reinforced cut slopes. We developed a novel monitoring system by using tension wire sensors. It's advantages are highly sensitivity, simple installation, large displacement measurement, durability of system, capability of remote sensing. Real-time measurement of slope surface movement is shown graphically and it gives a warning when the monitored value exceeds a given threshold level so that any sign of abnormal slope movement can be easily perceived.

• Journal of Korea Multimedia Society
• /
• v.25 no.6
• /
• pp.833-843
• /
• 2022

Based on the problems of untimely Expressway fire rescue and backward traditional fire rescue methods, an emergency fire fighting and inspection robot riding on expressway guardrail is designed. The overall mechanical structure design of emergency fire fighting and inspection robot riding on expressway guardrail is completed by using three-dimensional design software. The target fire detection is realized by using the target detection algorithm of Yolov5; By selecting a variety of sensors and using the control method of multi algorithm fusion, the basic function of robot on duty early warning is realized, and it has the ability of intelligent fire extinguishing. The BMS battery charging and discharging system is used to detect the real-time power of the robot. The design of the expressway emergency fire fighting and inspection robot provides a new technical means for the development of emergency fire fighting equipment, and improves the reliability and efficiency of expressway emergency fire fighting.

• 한국환경농학회:학술대회논문집
• /
• 2009.07a
• /
• pp.228-239
• /
• 2009

The observations on climate change show a clear increase in the temperature of the Earth's surface and the oceans, a reduction in the land snow cover, and melting of the sea ice and glaciers. The effects of climate change are likely to include more variable weather, heat waves, increased mean temperature, rains, flooding and droughts. The threat of climate change and global warming on human and animal health is now recognized as a global issue. This presentation is described an overview of the latest scientific knowledge on the impact of climate change on zoonotic diseases. Climate strongly affects agriculture and livestock production and influences animal diseases, vectors and pathogens, and their habitat. Global warming are likely to change the temporal and geographical distribution of infectious diseases, including those that are vector-borne such as West Nile fever, Rift Valley fever, Japanese encephalitis, bluetongue, malaria and visceral leishmaniasis, and other diarrheal diseases. The distribution and prevalence of vector-borne diseases may be the most significant effect of climate change. The impact of climate change on the emergence and re-emergence of animal diseases has been confirmed by a majority of countries. Emerging zoonotic diseases are increasingly recognized as a global and regional issue with potential serious human health and economic impacts and their current upward trends are likely to continue. Coordinated international responses are therefore essential across veterinary and human health sectors, regions and countries to control and prevent emerging zoonoses. A new early warning and alert systems is developing and introducing for enhancing surveillance and response to zoonotic diseases. And international networks that include public health, research, medical and veterinary laboratories working with zoonotic pathogens should be established and strengthened. Facing this challenging future, the long-term strategies for zoonotic diseases that may be affected by climate change is need for better prevention and control measures in susceptible livestock, wildlife and vectors in Korea. In conclusion, strengthening global, regional and national early warning systems is extremely important, as are coordinated research programmes and subsequent prevention and control measures, and need for the global surveillance network essential for early detection of zoonotic diseases.

• Journal of Korean Society of Environmental Engineers
• /
• v.34 no.12
• /
• pp.828-834
• /
• 2012

The ecotoxicity detection device for preliminary test (Test jig) was manufactured to develop the biological early warning system using Vibrio fischeri. In this study, the ecotoxicity detection charateristics of the Test jig was investigated for 6 heavy metals (Cr, Zn, Pb, Cd, Cu and Hg). It was observed that relative luminescence unit (RLU) of Vibrio fischeri constantly decreased by the concentrations of the tested heavy metals. In contrast with other heavy metals, RLUs of Pb and Hg constantly decreased even at low concentrations. RLU of Hg drastically decreased when its concentration increased from 0.13 mg/L to 0.25 mg/L. $EC_{50}$ values of Cr, Zn, Pb and Cd gradually decreased with exposure time, whereas there was no significant change in $EC_{50}$ values of Cu and Hg with time. On the other hand, $EC_{50}$ values between the Test jig and Reference device were compared to evaluate the ecotoxicity detection performance of the Test jig. No big difference was found in $EC_{50}$ vlaues between the two devices, indicating that the Test jig could be applied as the ecotoxicity detection device for heavy metals.

• IMMUNE NETWORK
• /
• v.24 no.2
• /
• pp.12.1-12.17
• /
• 2024

Exosomes are double phospholipid membrane vesicles that are synthesized and secreted by a variety of cells, including T cells, B cells, dendritic cells, immune cells, are extracellular vesicles. Recent studies have revealed that exosomes can play a significant role in under both physiological and pathological conditions. They have been implicated in regulation of inflammatory responses, immune response, angiogenesis, tissue repair, and antioxidant activities, particularly in modulating immunity in autoimmune diseases (AIDs). Moreover, variations in the expression of exosome-related substances, such as miRNA and proteins, may not only offer valuable perspectives for the early warning, and prognostic assessment of various AIDs, but may also serve as novel markers for disease diagnosis. This article examines the impact of exosomes on the development of AIDs and explores their potential for therapeutic application.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.21 no.2
• /
• pp.147-157
• /
• 2018

There are increasing demands to provide early warning against intruding drones and cope with potential threats. Commercial anti-drone systems are mostly based on simple target detection by radar reflections. In real scenario, however, it becomes essential to obtain drone radar signatures so that hostile targets are recognized in advance. We present experimental test results that micro-Doppler radar signature delivers partial information on multi-rotor platforms and exhibits limited performance in drone recognition and classification. Afterward, we attempt to generate high resolution profile of flying drone targets. To this purpose, wide bands radar signals are employed to carry out inverse synthetic aperture radar(ISAR) imaging against moving drones. Following theoretical analysis, experimental field tests are carried out to acquire real target signals. Our preliminary tests demonstrate that high resolution ISAR imaging provides effective measures to detect and classify multiple drone targets in air.