• Journal of Digital Convergence
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• v.11 no.9
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• pp.311-318
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• 2013

For face detection techniques, the correctness of detection decreases with different lightings and backgrounds so such requires new methods and techniques. This study has aimed to obtain data for reasoning human emotional information by analyzing the components of the eyes and mouth that are critical in expressing emotions. To do this, existing problems in detecting face are addressed and a detection method that has a high detection rate and fast processing speed good at detecting environmental elements is proposed. This method must detect a specific part (eyes and a mouth) by using Haar-like Feature technique with the application of an integral image. After which, binaries detect elements based on color information, dividing the face zone and skin zone. To generate correct shape, the shape of detected elements is generated by using a bezier curve-a curve generation algorithm. To evaluate the performance of the proposed method, an experiment was conducted by using data in the Face Recognition Homepage. The result showed that Haar-like technique and bezier curve method were able to detect face elements more elaborately.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.395-401
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• 2023

Sound Event Detection (SED) aims to identify not only sound category but also time interval for target sounds in an audio waveform. It is a critical technique in field of acoustic surveillance system and monitoring system. Recently, various models have introduced through Detection and Classification of Acoustic Scenes and Events (DCASE) Task 4. This paper explored how to design optimal parameters of DenseNet based model, which has led to outstanding performance in other recognition system. In experiment, DenseRNN as an SED model consists of DensNet-BC and bi-directional Gated Recurrent Units (GRU). This model is trained with Mean teacher model. With an event-based f-score, evaluation is performed depending on parameters, related to model architecture as well as model training, under the assessment protocol of DCASE task4. Experimental result shows that the performance goes up and has been saturated to near the best. Also, DenseRNN would be trained more effectively without dropout technique.

• Journal of Welding and Joining
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• v.13 no.2
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• pp.42-52
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• 1995

In the evaluation of aging degradation on the structural materials based on the fracture mechanics, the detection and size prediction of defect are very important. Aiming at nondestructive detection and size prediction ol defect with high accuracy and resolution, therefore, an lnduced Current Focusing Potential Drop(ICFPD) technique has been developed. The principle of this technique is to induce a focusing current at an exploratory region by an induction wire flowing an alternating current(AC) that is a constant ampere and frequency. Defects are assessed with the potential drops that are measured the induced current on the surface of metallic material by the potential pick-up pins. In this study, the lCFPD technique was applied for evaluating the location and size of the surface crack and blind crack made in plate specimens, and also for detecting the defects existing in valve, a field component, that were developed by SCC etc. during the service. The results of this present study show that surface crack and blind crack are able to defect with potential drop. these cracks are distinguished with the distribution of potential drop, and the crack depths can be estimated with each normalized potential drop that are parameters estimating the depth of each type crack. In the field component, the defects estimated by experiment result correspond with those in the cutting face of the measuring point within a higher sensitivity.

• Journal of KIISE
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• v.42 no.6
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• pp.713-722
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• 2015

As open-source software (OSS) becomes more widely used, many users breach the terms in the license agreement of OSS, or reuse a vulnerable OSS module. Therefore, a technique needs to be developed for investigating if a binary program includes an OSS module. In this paper, we propose an efficient technique to detect a particular OSS module in an executable program using its function-level features. The conventional methods are inappropriate for determining whether a module is contained in a specific program because they usually measure the similarity between whole programs. Our technique determines whether an executable program contains a certain OSS module by extracting features such as its function-level instructions, control flow graph, and the structural attributes of a function from both the program and the module, and comparing the similarity of features. In order to demonstrate the efficiency of the proposed technique, we evaluate it in terms of the size of features, detection accuracy, execution overhead, and resilience to compiler optimizations.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.26-33
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• 2017

A drone performs a mission through remote control or automatic control, which uses wireless communications technology. Recently the increasing use of drones, the drone signal RF detection is necessary. In this paper, we propose an efficient dron RF detection method through simulations considering Wi-Fi, Bluetooth and dedicated protocol dron communication method in ISM(Industry Science Medical) band.. After configuring an environment where a common terminal and a drone signal are mixed, a general terminal and a drone signal are distinguished from each other by using a RF characteristic according to a dron movement. The proposed drone RF detection method is the WRMD(Windowed RSSI Moving Detection) operation and the Doppler frequency identification method. The simulation environments consist to mixed for two signals and four signals. We analysis the performance to proposed drone RF detection technique thorough detection rate.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.1 s.24
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• pp.24-32
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• 2006

This paper is to analyze the effectiveness of multistatic sonar network based on detection performance. The multistatic sonar network is a distributed detection system that places a source and multi-receivers apart. So it needs a detection technique that relates to decision rule and optimization of sonar system to improve the detection performance. For this we propose a data fusion procedure using Bayesian decision and optimal sensor arrangement by optimizing a bistatic sonar. Also, to analyze the detection performance effectively, we propose the environmental model that simulates a propagation loss and target strength suitable for multistatic sonar networks in real surroundings. The effectiveness analysis on the multistatic sonar network confirms itself as a promising tool for effective allocation of detection resources in multistatic sonar system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.2
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• pp.99-106
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• 2003

Intrusions pose a serious security risk in a network environment. For detecting the intrusion effectively, many researches have developed data mining framework for constructing intrusion detection modules. Traditional anomaly detection techniques focus on detecting anomalies in new data after training on normal data. To detect anomalous behavior, Precise normal Pattern is necessary. This training data is typically expensive to produce. For this, the understanding of the characteristics of data on network is inevitable. In this paper, we propose to use clustering and association rules as the basis for guiding anomaly detection. For applying entropy to filter noisy data, we present a technique for detecting anomalies without training on normal data. We present dynamic transaction for generating more effectively detection patterns.

• ETRI Journal
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• v.28 no.3
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• pp.355-363
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• 2006

This paper presents a low-cost RF parameter estimation technique using a new RF built-in self-test (BIST) circuit and efficient DC measurement for 4.5 to 5.5 GHz low noise amplifiers (LNAs). The BIST circuit measures gain, noise figure, input impedance, and input return loss for an LNA. The BIST circuit is designed using $0.18\;{\mu}m$ SiGe technology. The test technique utilizes input impedance matching and output DC voltage measurements. The technique is simple and inexpensive.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.455-467
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• 2017

When performing target detection using hyperspectral imagery, a feature extraction process is necessary to solve the problem of redundancy of adjacent spectral bands and the problem of a large amount of calculation due to high dimensional data. This study proposes a new band selection method using the $L_{2,1}$-norm regression model to apply the feature selection technique in the machine learning field to the hyperspectral band selection. In order to analyze the performance of the proposed band selection technique, we collected the hyperspectral imagery and these were used to analyze the performance of target detection with band selection. The Adaptive Cosine Estimator (ACE) detection performance is maintained or improved when the number of bands is reduced from 164 to about 30 to 40 bands in the 350 nm to 2500 nm wavelength band. Experimental results show that the proposed band selection technique extracts bands that are effective for detection in hyperspectral images and can reduce the size of the data without reducing the performance, which can help improve the processing speed of real-time target detection system in the future.

• Journal of the Korean Wood Science and Technology
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• v.24 no.3
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• pp.18-27
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• 1996

The feasibility of using stress-wave technique in the transverse direction for the assessment of early stages of decay was investigated using compression test specimens having different annual ring orientations subjected to decay by Tyromyces palustris for various time intervals. Decay detection, quantitative assessment of decay, and the prediction of residual strength of decayed wood with less than five percent weight loss can be feasible using stress-wave parameters (wave velocity, wave impedance, and stress-wave elasticity) and their percent reduction due to decay, measured by stress-wave technique in the transverse direction. The use of stress-wave technique in the transverse direction for the application of this technique to structural members in service is desirable, when considering the easiness of attachment of accelerometers of stress-wave measuring device on the surface of members and also accurate detection of localized decayed areas. In stress-wave technique in the transverse direction, stress-wave parameters measured were different according to the angles between wave propagation path and annual ring, due to the anisotropy of wood structure. Therefore, it is recommended to use percent reduction in stress-wave parameters instead of stress-wave parameters. This evaluation method using percent reduction in stress-wave parameters is ideal when it is impossible to observe annual ring orientation on the transverse surface of wood.