• Journal of Microbiology and Biotechnology
• /
• v.31 no.9
• /
• pp.1323-1329
• /
• 2021

Micro-scale magnetic beads are widely used for isolation of proteins, DNA, and cells, leading to the development of in vitro diagnostics. Efficient isolation of target biomolecules is one of the keys to developing a simple and rapid point-of-care diagnostic. A zinc finger protein (ZFP) is a double-stranded (ds) DNA-binding domain, providing a useful scaffold for direct reading of the sequence information. Here, we utilized two engineered ZFPs (Stx2-268 and SEB-435) to detect the Shiga toxin (stx2) gene and the staphylococcal enterotoxin B (seb) gene present in foodborne pathogens, Escherichia coli O157 and Staphylococcus aureus, respectively. Engineered ZFPs are immobilized on a paramagnetic bead as a detection platform to efficiently isolate the target dsDNA-ZFP bound complex. The small paramagnetic beads provide a high surface area to volume ratio, allowing more ZFPs to be immobilized on the beads, which leads to increased target DNA detection. The fluorescence signal was measured upon ZFP binding to fluorophore-labeled target dsDNA. In this study, our system provided a detection limit of ≤ 60 fmol and demonstrated high specificity with multiplexing capability, suggesting a potential for development into a simple and reliable diagnostic for detecting multiple pathogens without target amplification.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.2
• /
• pp.133-140
• /
• 2016

In active sonar field, a target detection and localization based on a distributed sensor network has been much studied for the underwater surveillance of the coast. Zhou et al. proposed a target localization method utilizing the positions of target-detected sensors in distributed sensor network which consists of detection-only sensors. In contrast with a conventional method, Zhou's method dose not require to estimate the propagation model parameters of detection signal. Also it needs the lower computational complexity, and to transmit less data between network nodes. However, it has large target localization error. So it has been modified for reducing localization error by Ryu. Modified Zhou's method has better estimation performance than Zhou's method, but still relatively large estimation error. In this paper, a target localization method based on modified Zhou's method is proposed for reducing the localization error. The proposed method utilizes the geometry of the positions of target-detected sensors and a line that represents the bearing of target, a line can be found by modified Zhou's method. This paper shows that the proposed method has better target position estimation performance than Zhou's and modified Zhou's method by computer simulations.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.362-369
• /
• 2012

Recently, a target detection based on a distributed sensor network has been much studied in active sonar. Zhou et al. proposed a target localization method using line fitting based on a distributed sensor network which consists of low complexity sensors that only report binary detection results. This method has three advantages relative to ML estimator. First, there is no need to estimate propagation model parameters. Second, the computation is simple. Third, it only use sensors with "detection", which implies less data to be collected by data processing center. However, this method has larger target localization error than the ML estimator. In this paper, a target localization method which modifies Zhou's method is proposed for reducing the localization error. The modified method shows the performance improvement that the target localization error is reduced by 40.7% to Zhou's method in the point of RMSE.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.47 no.6
• /
• pp.27-32
• /
• 2010

77GHz FMCW(Frequency Modulation Continuous Wave) radar system has been used for automotive active safety systems. In typical automotive radar, the moving target detection and clutter cancellation including stationary targets are very important signal processing algorithms. This paper proposed the moving target detection algorithm which improve the detection probability and reduce the false alarm rate. First, the proposed moving target beat-frequency extraction filter is used in order to suppress clutter, and then the data association is applied by using the extracted moving target beat-frequency. Then, the zero-Doppler target is eliminated to remove the rest of clutter.

• Korean Journal of Remote Sensing
• /
• v.40 no.2
• /
• pp.167-177
• /
• 2024

With advancements in satellite technology, interest in target detection and identification is increasing quantitatively and qualitatively. Synthetic Aperture Radar(SAR) images, which can be acquired regardless of weather conditions, have been applied to various areas combined with machine learning based detection algorithms. However, conventional studies primarily focused on the detection of stationary targets. In this study, we proposed a method to identify moving targets using an algorithm that integrates sub-aperture SAR images and cosine similarity calculations. Utilizing a transformer-based deep learning target detection model, we extracted the bounding box of each target, designated the area as a region of interest (ROI), estimated the similarity between sub-aperture SAR images, and determined movement based on a predefined similarity threshold. Through the proposed algorithm, the quantitative evaluation of target identification capability enhanced its accuracy compared to when training with the targets with two different classes. It signified the effectiveness of our approach in maintaining accuracy while reliably discerning whether a target is in motion.

• ETRI Journal
• /
• v.35 no.1
• /
• pp.80-88
• /
• 2013

A passive infrared or pyroelectric infrared (PIR) sensor is mainly used to sense the existence of moving objects in an indoor environment. However, in an outdoor environment, there are often outbreaks of false alarms from environmental changes and other sources. Therefore, it is difficult to provide reliable detection outdoors. In this paper, two algorithms are proposed to reduce false alarms and provide trustworthy quality to surveillance systems. We gather PIR signals outdoors, analyze the collected data, and extract the target features defined as window energy and alarm duration. Using these features, we model target and false alarms, from which we propose two target decision algorithms: window energy detection and alarm duration detection. Simulation results using real PIR signals show the performance of the proposed algorithms.

• Journal of Korea Ship Safrty Technology Authority
• /
• s.38
• /
• pp.69-77
• /
• 2015

If we don't know the intention of altering course of a target ship when being in a head-on or a crossing situation, we may be confused about our decision making to change our course for collision avoidance and be in a danger of collision. In order to solve these problems, we need to develop an automatic detection system on altering course of a target ship for efficient collision avoidance. In this paper, we proposed an early detection system on altering course of a target ship using the steering wheel signal. This system will contribute to the reduction of collision accidents and also be used to the VTS system and the analysis of marine accidents.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.10
• /
• pp.49-54
• /
• 2016

In this paper, the confirmation method of target detection for the vehicle mounted metal detector (MD) has been described. The vehicle mounted MD with the arrayed 6 coils to detect the width of 2.4 m was demonstrated. It is important and necessary to inform the location of the objects detected by the MD. The confirmation method of target detection was verified by using the MD GUI and the analysis of the receive signal processing. The receive signal processing is performed by comparing the threshold and the difference of the signal calibrated at initial location and the signal detected at present location.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.120-124
• /
• 1991

In this paper, we consider the maneuvering detection and target tracking problem in uncertain linear discrete-time systems. The maneuvering detection is based on X$^{2}$ test[2,71, where Kalman filters have been utilized so far. The target tracking is performed by the maneuvering input compensation based on a maximum likelihood estimator. KF has been known to diverge when some modelling errors exist and fail to detect the maneuvering and to track the target in uncertain systems. Thus this paper adopt the FIR filter[l], which is known to be robust to modelling errors, for maneuvering detection and target tracking problem. Various computer simulations show the superior performance of the FIR filter in this problem.

• Journal of Korea Ship Safrty Technology Authority
• /
• s.36
• /
• pp.71-78
• /
• 2014

If we don't know the intention of altering course of a target ship when being in a head-on or a crossing situation, we may be confused about our decision making to change our course for collision avoidance and be in a danger of collision. In order to solve these problems, we need to develop an automatic detection system on altering course of a target ship for efficient collision avoidance. In this paper, we proposed an early detection system on altering course of a target ship using the steering wheel signal. This system will contribute to the reduction of collision accidents and also be used to the VTS system and the analysis of marine accidents.