• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.113-118
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• 2011

In this paper, we develop a speaker gender classification technique using collaborative sensor fusion for use in a wireless sensor network. The distributed sensor nodes remove the unwanted input data using the BER(Band Energy Ration) based voice activity detection, process only the relevant data, and transmit the hard labeled decisions to the fusion center where a global decision fusion is carried out. This takes advantages of power consumption and network resource management. The Bayesian sensor fusion and the global weighting decision fusion methods are proposed to achieve the gender classification. As the number of the sensor nodes varies, the Bayesian sensor fusion yields the best classification accuracy using the optimal operating points of the ROC(Receiver Operating Characteristic) curves_ For the weights used in the global decision fusion, the BER and MCL(Mutual Confidence Level) are employed to effectively combined at the fusion center. The simulation results show that as the number of the sensor nodes increases, the classification accuracy was even more improved in the low SNR(Signal to Noise Ration) condition.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.1
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• pp.165-174
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• 2004

This research develops a technique which uses energy dissipation ratio in order to monitor the structural health on real time basis. For real-time monitoring, we employ the NExT and the ERA which enable us to obtain real-time data. Energy dissipation ratio is calculated from those data only with the damping and natural frequency of the structure, and from the calculated values we develop an algorithm (Energy dissipation method) which decides the damage degree of structure. The Energy dissipation method developed in this research is proved to be valid by comparison with other methods like the eigenparameter method and the MAC. Especially this method enables us to save measuring time and data which are the most important in real-time monitoring, and its use of the ambient vibration also makes it easy to monitor the whole structure and its damage points.

• Journal of Yeungnam Medical Science
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• v.37 no.2
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• pp.90-97
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• 2020

Background: To minimize damage to the ovarian reserve, it is necessary to evaluate the follicular density in the ovarian tissue surrounding endometriosis on preoperative imaging. The purpose of the present study was to evaluate the usefulness of subtraction pelvic magnetic resonance imaging (MRI) to detect ovarian reserve. Methods: A subtracted T1-weighted image (^subT1WI) was obtained by subtracting unenhanced T1WI from contrast-enhanced T1WI (^ceT1WI) with similar parameters in 22 patients with ovarian endometriosis. The signal-to-noise ratio (SNR) in ovarian endometriosis, which was classified into the high signal intensity and iso-to-low signal intensity groups on the T2-weighted image, was compared to that in normal ovarian tissue. To evaluate the effect of contrast enhancement, a standardization map was obtained by dividing ^subT1WI by ^ceT1WI. Results: On visual assessment of 22 patients with ovarian endometriosis, 16 patients showed a high signal intensity, and 6 patients showed an iso-to-low signal intensity on T1WI. Although SNR in endometriosis with a high signal intensity was higher than that with an iso-to-low signal intensity, there was no difference in SNR after the subtraction (13.72±77.55 vs. 63.03±43.90, p=0.126). The area of the affected ovary was smaller than that of the normal ovary (121.10±22.48 vs. 380.51±75.87 ㎟, p=0.002), but the mean number of pixels in the viable remaining tissue of the affected ovary was similar to that of the normal ovary (0.53±0.09 vs. 0.47±0.09, p=0.682). Conclusion: The subtraction technique used with pelvic MRI could reveal the extent of endometrial invasion of the normal ovarian tissue and viable remnant ovarian tissue.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.108-113
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• 2007

The classification of fingerprint images is to classify fingerprint images into varies fingerprint types, it is very important in automatic fingerprint recognition. In this paper, a new singular points detection technique was presented. A direction uniform measure is defined to describe the changes of direction fields in a certain neighborhood of fingerprint images. Singular points can be detected by adopting the measure. It should be pointed out that singular points in accurate positions would be obtained in this ways. And an improved Poincare exponential algorithm is presented to identify core points and triangle points. In this paper. making use of 102 experimental fingerprint images datas and attained 7.8% classification errors. This was better than experimental result of abstract [9]. It is possible to use on-line fingerprint images classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1992-1998
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• 2007

It is important to obtain conn cytodiagnosis to classify background, cytoplasm, and nucleus from the diagnostic image. This study mose an algorithm that detects and classifies carcinoma cells of the uterine cervix in Pap smear using features of cervical cancer. It applies Median filter and Gaussian filter to get noise-removed nucleus area and also applies Kapur method in binarization of the resultant image. We apply 8-directional contour tracking algorithm and stretching technique to identify and revise clustered cells that often hinder to obtain correct analysis. The resulted nucleus area has distinguishable features such as cell size, integration rate, and directional coefficient from normal cells so that we can detect and classify carcinoma cells successfully. The experiment results show that the performance of the algorithm is competitive with human expert.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1696-1702
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• 2008

A MANET(Mobile Ad-hoc Network) is a multi-hop routing protocol formed by a collection without the intervention of infrastructure. So the MANET also depended on the property as like variable energy, high degree of mobility, location environments of nodes etc. Generally the various clustering technique and routing algorithm would have proposed for improving the energy efficiency. One of the popular approach methods is a cluster-based routing algorithm using in MANET. In this paper, we propose an algorithm techniques which is TICC (Time Interval Clustering Control) based on energy value in property of each node for solving cluster problem. It provides improving cluster energy efficiency how can being node manage to order each node's energy level. TICC could be able to manage the clustering, re-configuration, maintenance and detection of Node in MANET. Furthermore, the results of modeling shown that Node's energy efficiency and lifetime are improved in MANET.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.49-61
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• 2006

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.131-131
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• 2019

최근 기후변화와 여름철 고온 등으로 인한 녹조현상, 각종 사고로 인한 화학물질 및 유류 유출 등 수질오염과 관련된 사회적 관심이 높아지고 있다. 특히, 화학사고로 인한 유해화학물질 유출은 접촉시 인체에 악영향을 끼치며, 대기 수질 토양을 오염시키고 주변 농작물의 변색이나 괴사를 유발하는 등 발생 시 적절한 조치와 대응이 필요하다. 환경부에서는 유해화학물질 유출사고로 인한 국민건강 및 환경상의 위해를 예방하기 위해 화학물질관리법과 화학물질 등록 및 평가에 관한 법률을 제정하여 유해화학물질을 관리하고 사고에 대응하고 있다. 그러나, 화학사고 발생 시 현장인력에 의존해 공장 인근의 먼지, 악취 등을 감시하거나 화학물질의 유출이 우려되는 곳에 제한적으로 검출센서를 설치해 사고를 감시하고 있으나 미설치 지역에 대한 능동적 탐지가 어렵고, 공간적 분포 탐지가 불가능하여 초동 대응에 한계가 있다. 한편 최근 초분광 영상을 활용하여 물질 고유의 특성을 분석함으로써 토지피복, 식생, 수질 등의 식별에 활용되고 있어 화학물질 감지 가능성도 보여주고 있다. 하지만, 초분광 센서를 활용한 하천의 화학물질 감지를 위한 연구는 아직 미비한 실정이다. 이에 본 연구에서는 우선 유해화학물질의 일종인 황산, 염화티오닐, 톨루엔을 대상으로 지점 분광복사계로 촬영하여 각각의 화학물질이 갖는 분광특성을 수집하여 초분광 영상으로 상호 구분이 가능한 지 확인하고자 하였다. 이상치 검출 및 신뢰도 높은 자료를 구축하기 위해 다회 반복촬영하였으며 반사도의 표준화를 위해 백색판을 동시에 측정하고 이를 정규화하여 분광 라이브러리를 구축한 결과, 대상 화학물질 별 식별이 가능하다는 결과를 도출하였다. 이러한 가능성에 기반하여 추가적인 유해화학물질 분광 라이브러리 데이터베이스를 구축하면, 사고물질의 식별 및 농도를 즉각적으로 확인하고 실시간 모니터링에 적용하여 신속하게 화학사고 발생여부 감지 및 대응에 활용될 것으로 기대한다.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.1-9
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• 2017

Recently, the DDoS attack using the amplifier method makes it difficult to distinguish the normal traffic from the normal server and it is difficult to detect even the attack detection. Since the SSDP protocol is a common protocol widely used in IoT devices, it is used as a DDoS amplification attack. In this paper, we analyze the reflector attack of SSDP which is one of the DDoS and suggest a technical proposal to detect and defend against the attack by managing the Mac address of each device. Also, we propose a control structure to protect the reflection attack of SSDP in Home IoT. The efficiency of the proposed system has been verified by performing an experimental attack on the virtual environment.

• Journal of the Optical Society of Korea
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• v.17 no.6
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• pp.548-558
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• 2013

In this work, laser induced breakdown spectroscopy (LIBS) is used to investigate soil samples collected from different desert areas of Riyadh city in Saudi Arabia. Both qualitative analysis and plasma parameters are studied via the observed LIBS spectra. These experiments have been done using a Spectrolaser-7000 system with 50 mJ fundamental wavelength of Nd:YAG laser and detection delay time of 1 microsecond. Many spectral lines are highly resolved for many elements like Al, Fe, Mg, Si, Mn, Na, Ca and K. The electron temperatures Te and electron densities Ne, for the constituent of generated LIBS plasma, are determined for all the collected samples. It is found that both Te and Ne vary from one desert area to other. This variation is due to the change of the elemental concentration in different desert areas that affects the sample's matrices. Time dependent measurements have also been performed on the soil samples. While the signal-to-base ratio (SBR) reached its optimal value at 1 microsecond, the plasma parameters Ne and Te reach values of $4{\times}10^{17}cm^{-3}$ and 9235 K, respectively, at 2.5 microsecond. The later indicate that the plasma cooling processes are slow in comparison to the previously observed results for metallic samples. The observed results show also that in the future it is possible to enhance the exploitation of LIBS in the remote on-line environmental monitoring application, by following up only the values of Ne and Te for one element of the soil desert sample using an optical fiber probe.