• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.342-348
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• 2021

For the characterization or failure analysis of electronic devices such as PCB (printed circuit boards), the most common method is the measurement of voltage waveforms with an oscilloscope. However, because there are many types of problems that cannot be detected by voltage waveform analysis, several other methods such as X-ray transmission, infrared imaging, or eddy current measurement have been applied for these analyses. However, these methods have also been limited to general analyses because they are partially useful in detecting physical defects, such as disconnections or short circuits. Fundamentally current waveform measurements during the operation of electronic devices need to be performed, however, commercially available current sensors have not yet been developed, particularly for applications in highly integrated PCB products with sub-millimeter fine pitch. In this study, we developed a highly sensitive PHR (planar hall resistance) magnetic sensor for application in highly integrated PCBs. The developed magnetic sensor exhibited sufficient features of an ultra-small size of less than 340 ㎛, magnetic field resolution of 10 nT, and current resolution of 1 mA, which can be applicable for PCB analyses. In this work, we introduce the development process of the magnetic sensing probe and its characteristic results in detail, and aim to extend this pin-type current probe to applications such as current distribution imaging of PCBs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.605-616
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• 2021

While malwares must be accurately identifiable from arbitrary programs, existing studies using classification techniques have limitations that they can only be applied to limited samples. In this work, we propose a method to utilize API call frequency to detect and classify malware families from arbitrary programs. Our proposed method defines a rule that checks whether the call frequency of a particular API exceeds the threshold, and identifies a specific family by utilizing the rate information on the corresponding rules. In this paper, decision tree algorithm is applied to define the optimal threshold that can accurately identify a particular family from the training set. The performance measurements using 4,443 samples showed 85.1% precision and 91.3% recall rate for family detection, 97.7% precision and 98.1% reproduction rate for classification, which confirms that our method works to distinguish malware families effectively.

• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.247-260
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• 2021

While it is an important element of clothing construction, research has so far been very limited on the similarities between virtual and real clothing in terms of the type of neckline. The purpose of this study is to verify the similarity, accuracy of virtualization, and actuality of neckline, which all play an important role in individual impressions and image formation, and require considerable modification when fitting real samples. A total of 5 neckline models were selected through the analysis of dress composition textbooks. The selected designs were then planned and manufactured in muslin. The specimen clothes were then tested on a female model in her 20s. 2 kinds of virtual bodies were created in order to compare the real and the virtual dressing. The first virtual body was made through an Artec 3D Eva scan of the model, and the other was made by entering the model's measurements in a CLO 3D program. A visual image of the front, side, and back image of both the real and virtual dressing were subsequently collected. The collected images were then evaluated by 20 professional fashion workers who checked the similarity between the real and the virtual versions. The current study found that the similarity between the actual and virtual wearing of the five neckline designs with reality appeared higher with the virtual wearing image using the 3D-scanned body. The results of this study could provide further information on the selection of appropriate avatars to clothing companies that check the fit of clothing by utilizing 3D virtualized programs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1690-1698
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• 2018

Recent advances in ICT technology have transformed many of our daily lives and attracted a lot of attention to personal health. Heart beat measurement that reflects cardiac activities has been used in various fields such as exercise evaluation and psychological state evaluation for a long time, but its utilization method is limited due to its differentiation from clinical electrocardiogram. Therefore, in this study, we could observe the change of the measured signal according to the change of the distance and the position of the measuring electrodes which are non-standard electrode configuration. Based on the electric dipole model of the heart, correlation with clinical electrocardiogram could be confirmed by synthesizing multiple surface potentials measured with a shorter electrode distance than standard one. From the electromagnetic point of view, the distance between the measuring electrodes corresponds to the distance that the electric potential by the cardiac electric dipole moves, and the electric potential measured at the body surface is proportional to the moving distance of the electric potential. Therefore, it is preferable to make the distance between electrodes as long as possible, and to position the measuring electrode close to the ventricle rather than the atrium. In addition, it was found that standard electrocardiographic waveforms could be synthesized by using arithmetic sum of multiple measuring electrodes due to the relationship of electrical dipole vectors, which is obtained by dividing and positioning a plurality of measuring electrodes on a reference electrode line, such as Lead-I, Lead-II direction. Also, we obtained a significant Pearson correlation coefficient ($r=0.9113{\pm}0.0169$) as a result of synthetic experiments on four subjects.

• Investigative Magnetic Resonance Imaging
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• v.23 no.1
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• pp.38-45
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• 2019

Purpose: To demonstrate the high-resolution numerical simulation of the respiration-induced dynamic $B_0$ shift in the head using generalized susceptibility voxel convolution (gSVC). Materials and Methods: Previous dynamic $B_0$ simulation research has been limited to low-resolution numerical models due to the large computational demands of conventional Fourier-based $B_0$ calculation methods. Here, we show that a recently-proposed gSVC method can simulate dynamic $B_0$ maps from a realistic breathing human body model with high spatiotemporal resolution in a time-efficient manner. For a human body model, we used the Extended Cardiac And Torso (XCAT) phantom originally developed for computed tomography. The spatial resolution (voxel size) was kept isotropic and varied from 1 to 10 mm. We calculated $B_0$ maps in the brain of the model at 10 equally spaced points in a respiration cycle and analyzed the spatial gradients of each of them. The results were compared with experimental measurements in the literature. Results: The simulation predicted a maximum temporal variation of the $B_0$ shift in the brain of about 7 Hz at 7T. The magnitudes of the respiration-induced $B_0$ gradient in the x (right/left), y (anterior/posterior), and z (head/feet) directions determined by volumetric linear fitting, were < 0.01 Hz/cm, 0.18 Hz/cm, and 0.26 Hz/cm, respectively. These compared favorably with previous reports. We found that simulation voxel sizes greater than 5 mm can produce unreliable results. Conclusion: We have presented an efficient simulation framework for respiration-induced $B_0$ variation in the head. The method can be used to predict $B_0$ shifts with high spatiotemporal resolution under different breathing conditions and aid in the design of dynamic $B_0$ compensation strategies.

• Korean Journal of Materials Research
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• v.28 no.11
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• pp.680-684
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• 2018

We investigate the effect of light intensity and wavelength of a solar cell device using photoconductive atomic force microscopy(PC-AFM). A $POCl_3$ diffusion doping process is used to produce a p-n junction solar cell device based on a polySi wafer, and the electrical properties of prepared solar cells are measured using a solar cell simulator system. The measured open circuit voltage($V_{oc}$) is 0.59 V and the short circuit current($I_{sc}$) is 48.5 mA. Moreover, the values of the fill factors and efficiencies of the devices are 0.7 and approximately 13.6 %, respectively. In addition, PC-AFM, a recent notable method for nano-scale characterization of photovoltaic elements, is used for direct measurements of photoelectric characteristics in limited areas instead of large areas. The effects of changes in the intensity and wavelength of light shining on the element on the photoelectric characteristics are observed. Results obtained through PC-AFM are compared with the electric/optical characteristics data obtained through a solar simulator. The voltage($V_{PC-AFM}$) at which the current is 0 A in the I-V characteristic curves increases sharply up to $18W/m^2$, peaking and slowly falling as light intensity increases. Here, $V_{PC-AFM}$ at $18W/m^2$ is 0.29 V, which corresponds to 59 % of the average $V_{oc}$ value, as measured with the solar simulator. Furthermore, while the light wavelength increases from 300 nm to 1,100 nm, the external quantum efficiency(EQE) and results from PC-AFM show similar trends at the macro scale but reveal different results in several sections, indicating the need for detailed analysis and improvement in the future.

• The Plant Pathology Journal
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• v.34 no.6
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• pp.544-554
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• 2018

Tomato (Solanum lycopersicum) production in Ghana is limited by the root-knot nematode (Meloidogyne incognita, and yield losses over 70% have been experienced in farmer fields. Major management strategies of the root-knot nematode (RKN), such as rotation and nematicide application, and crop rotation are either little efficient and harmful to environments, with high control cost, respectively. Therefore, this study aims to examine morphometric variations of RKN populations in Ghana, using principal component analysis (PCA), of which the information can be utilized for the development of tomato cultivars resistant to RKN. Ninety (90) second-stage juveniles (J2) and 16 adult males of M. incognita were morphometrically characterized. Six and five morphometric variables were measured for adult males and second-stage juveniles (J2) respectively. Morphological measurements showed differences among the adult males and second-stage juveniles (J2). A plot of PC1 and PC2 for M. incognita male populations showed clustering into three main groups. Populations from Asuosu and Afrancho (Group I) were more closely related compared to populations from Tuobodom and Vea (Group II). There was however a single nematode from Afrancho (AF4) that fell into Group III. Biplots for male populations indicate, body length, DEGO, greatest body width, and gubernaculum length serving as variables distinguishing Group 1 and Group 2 populations. These same groupings from the PCA were reflected in the dendogram generated using Agglomerative Hierarchical Clustering (AHC). This study provides the first report on morphometric characterisation of M. incognita male and juvenile populations in Ghana showing significant morphological variation.

• Current Optics and Photonics
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• v.3 no.1
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• pp.46-53
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• 2019

Monte Carlo simulations were performed for a three-dimensional tissue model with and without an embedded large vessel, to understand how varying vessel geometry affects surface light distribution. Vessel radius was varied from 1 to 5 mm, and vessel depth from 2 to 10 mm. A larger difference in surface fluence rate was observed when the vessel's radius increased. For vessel depth, the largest difference was seen at a depth of approximately 4 mm, corresponding to human wrist region. When the vessel was placed at depths greater than 8 mm, very little difference was observed. We also tested the feasibility of using two source-detector pairs, comprising two detectors distinctly spaced from a common source, to noninvasively measure blood-scattering changes in a large vessel. High sensitivity to blood-scattering changes was achieved by placing the near detector closer to the source and moving the far detector away from the source. However, at longer distances, increasing noise levels limited the sensitivity of the two-detector approach. Our results indicate that the approach using two source-detector pairs may have potential for quantitative measurement of scattering changes in the blood while targeting large vessels near the human wrist region.

• Korean Journal of Materials Research
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• v.29 no.5
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• pp.336-341
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• 2019

The gas adsorption isotherm requires accurate measurement for the analysis of porous materials and is used as an index of surface area, pore distribution, and adsorption amount of gas. Basically, adsorption isotherms of porous materials are measured conventionally at 77K and 87K using liquid nitrogen and liquid argon. The cold volume calibration in this conventional method is done simply by splitting a sample cell into two zones (cold and warm volumes) by controlling the level sensor in a Dewar filled with liquid nitrogen or argon. As a result, BET measurement for textural properties is mainly limited to liquefied gases (i.e. $N_2$ or Ar) at atmospheric pressure. In order to independently investigate other gases (e.g. hydrogen isotopes) at cryogenic temperature, a novel temperature control system in the sample cell is required, and consequently cold volume calibration at various temperatures becomes more important. In this study, a cryocooler system is installed in a commercially available BET device to control the sample cell temperature, and the automated cold volume calibration method of temperature variation is introduced. This developed calibration method presents a reliable and reproducible method of cryogenic measurement for hydrogen isotope separation in porous materials, and also provides large flexibility for evaluating various other gases at various temperature.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.47-53
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• 2021

The article deals with the problems of application of microwave methods in systems of geoecological monitoring of natural environments and resources of the agro-industrial complex. It is noted that the methods of microwave radiometry make it possible, by the power of the measured intrinsic radio-thermal radiation of the atmosphere, when solving inverse problems using empirical and semi-empirical models, to determine such parameters of the atmosphere as thermodynamic temperature, humidity, water content, moisture content, precipitation intensity, and the presence of different fractions of clouds.In addition to assessing the meteorological parameters of the atmosphere and the geophysical parameters of the underlying surface based on the data of microwave radiometric measurements, it is possible to promptly detect and study pollution of both the atmosphere and the earth's surface. A technique has been developed for the analysis of sources of measurement error and their numerical evaluation, because they have a significant effect on the accuracy of solving inverse problems of reconstructing the values of the physical parameters of the probed media.To analyze the degree of influence of the limited spatial selectivity of the antenna of the microwave radiometric system on the measurement error, we calculated the relative measurement error of the ratio of radio brightness contrasts in two angular directions. It has been determined that in the system of geoecological monitoring of natural environments, the effect of background noise is maximal with small changes in the radiobrightness temperature during angular scanning and high sensitivity of the receiving equipment.