• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.243-249
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• 2020

Event detection in wireless sensor networks is a key requirement in many applications. Acoustic sensors are one of the most frequently used sensors for event detection in sensor networks, but they are sensitive and difficult to handle because they vary greatly depending on the environment and target characteristics of the sensor field. In this paper, we propose a learning-based improvement of CFAR algorithm for increasing node-level event detection performance in acoustic sensor networks, and verify the effectiveness of the designed algorithm by comparing and evaluating the event detection performance with other algorithms. Our experimental results demonstrate the superiority of the proposed algorithm by increasing the detection accuracy by more than 45.16% by significantly reducing false positives by 7.97 times while slightly increasing the false negative compared to the existing algorithm.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.518-523
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• 2012

This paper presents new coherent and non-coherent detection methods for the IEEE 802.15.4a low-rate ultra-wideband physical layer with forward error correction (FEC) coding techniques. The coherent detection method involving channel estimation is based on the correlation characteristics of the preamble signal. A coherent receiver uses novel iterated selective-rake (IT-SRAKE) to detect 2-bit data in a non-line-of-sight channel. The non-coherent detection method that does not involve channel estimation employs a 2-bit data detection scheme using modified transmitted reference pulse cluster (M-TRPC) methods. To compare the two schemes, we have designed an IT-SRAKE receiver and a MTRPC receiver using an IEEE 802.15.4a physical layer. Simulation results show the performance of IT-SRAKE is better than that of the M-TRPC by 3-9 dB.

• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.7-12
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• 2019

Significant progress has been made recently in detection of highly sensitive volatile organic compounds (VOCs) using chemical sensors. Combined with the progress in design of micro sensors array and electronic nose systems, these advances enable new applications for detection of extremely low concentrations of breath-related VOCs. State of the art detection technology in turn enables commercial sensor systems for health care applications, with high detection sensitivity and small size, weight and power consumption characteristics. We have been developing an intelligent electronic nose system for detection of VOCs for healthcare breath analysis applications. This paper reviews our contribution to monitoring of respiratory diseases and to diabetic monitoring using an intelligent electronic nose system for detection of low concentration VOCs using breath analysis techniques.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.864-871
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• 2002

Acoustic emission(AE) technique has been applied to not only mechanical property testing but also on-line monitoring of the entire structure or a limit zone only. Although several AE devices have already been developed for on-line monitoring, the price of these systems is very high and it is difficult for the field to apply yet. In this study, we developed a specially designed PC-based leak detection system using A/D board. In this paper, AE technique has been applied to detect leak for heat exchanger by analyzing the characteristics of signal obtained from leak. It was confirmed that the characteristics of the signal generated by the turbulence of gas in the heat exchanger is narrow band signal having between 130-250kHz. Generally, the amplitude of leak signal is increased as the leak size increasing, but showed no significant change at frequency characteristic. Leak source location can be found by determining for the paint of highest signal amplitude by comparing with several fixed sensors. In this paper, AE results are compared with the PC-based leak detection system using A/D board.

• Journal of the Korean earth science society
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• v.36 no.5
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• pp.437-446
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• 2015

Many edge detection methods, based on horizontal and vertical derivatives, have been introduced to provide us with intuitive information about the horizontal distribution of a subsurface anomalous body. Understanding the characteristics of each edge detection method is important for selecting an optimized method. In order to compare the characteristics of the individual methods, this study applied each method to synthetic magnetic data created using homogeneous prisms with different sizes, the numbers of bodies, and spacings between them. Seven edge detection methods were comprehensively and quantitatively analyzed: the total horizontal derivative (HD), the vertical derivative (VD), the 3D analytic signal (AS), the title derivative (TD), the theta map (TM), the horizontal derivative of tilt angle (HTD), and the normalized total horizontal derivative (NHD). HD and VD showed average good performance for a single-body model, but failed to detect multiple bodies. AS traced the edge for a single-body model comparatively well, but it was unable to detect an angulated corner and multiple bodies at the same time. TD and TM performed well in delineating the edges of shallower and larger bodies, but they showed relatively poor performance for deeper and smaller bodies. In contrast, they had a significant advantage in detecting the edges of multiple bodies. HTD showed poor performance in tracing close bodies since it was sensitive to an interference effect. NHD showed great performance under an appropriate window.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.456-460
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• 2020

In this research, a radiation detection backpack to be used discreetly or by a wide range of users was developed using array silicon-photomultiplier (SiPM) and CsI (Tl), and its characteristics were evaluated. The R-squared value, which indicates the responsiveness of a detector based on the signal intensity, was determined to be 0.981, indicating a good linear responsivity. The energy resolutions for gamma radiation energies of Co-57 (122 keV), Ba-133 (356 keV), Cs-137 (662 keV), and Co-60 (1332 keV) were found to be 13.40, 10.50, 6.77, and 3.16%, respectively. These results confirm good energy resolution characteristics. Furthermore, in the case of mixed sources, the gamma radiation peaks were readily distinguishable, and the R-squared value for energy linearity was calculated to be 0.999, demonstrating an exceptional energy linearity. Further research based on the results of this study would enable the commercialization of lightweight SiPM-based wireless radiation detection backpacks that can be used for longer durations by replacing the photomultiplier tube, which is mainly used as the optical sensor in existing radiation detection backpacks.

• Journal of IKEEE
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• v.18 no.4
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• pp.456-462
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• 2014

Scintillators were polished in four steps using polishing paper, to reduce the optical loss occurring at their cross section when radiation detectors are fabricated with plastic scintillators. We studied the correlation between the polishing steps and detection efficiency and assessed the detection characteristics that are dependent in the polishing steps. Our results showed that the detection efficiency increased by approximately 7.75 times for a detector that used a scintillator polished in four steps, compared to a detector that used an depolished scintillator. For detectors fabricated using scintillators polished in different steps, better detection characteristics were obtained in terms of the activity, distance, and location of radiation, compared to detectors fabricated with an depolished scintillator.

• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.188-194
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• 2004

With a remarkable advance in CMOS (complimentary metal-oxide-semiconductor) process technology, a variety of vision sensors with signal processing circuits for complicated functions are actively being developed. Especially, as the principles of signal processing in human retina have been revealed, a series of vision chips imitating human retina have been reported. Human retina is able to detect the edge and motion of an object effectively. The edge detection among the several functions of the retina is accomplished by the cells called photoreceptor, horizontal cell and bipolar cell. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge and motion detection. The designed vision chip was fabricated using $0.6{\mu}m$ CMOS process and the characteristics were measured. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• Journal of the Korean Institute of Navigation
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• v.22 no.4
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• pp.59-67
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• 1998

A quick and automatic detection with no harm to the goods is very important task for improving quality control, process control and labour reduction. In real fields of industry, defect detection is mostly accomplished by skillful workers. A narrow band eliminating spatial filter having characteristics of removing the specified spatial frequency is developed by the author, and it is proved that the filter has an excellent ability for on-line and real time detection of surface defect. By the way,. this spatial filter shows a ripple phenominum in filtering characteristics. So, it is necessary to remove the ripple component for the improvement of filter gain, moreover efficiency of defect detection. The spatial filtering method has a remarkable feature which means that it is able to set up weighting function for its own sake, and which can to obtain the best signal relating to the purpose of the measurement. Hence, having an eye on such feature, theoretical analysis is carried out at first for optimal design of narrow band eliminating spatial filter, and secondly, on the basis of above results spatial filter is manufactured, and finally advanced effectiveness of spatial filter is evaluated experimentally.