• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1327-1336
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• 2012

In this paper, the dual-faced monopole antenna, which is arranged by numerous rectangular ring patches in sequence for the multi-bands is proposed. The ring type structure of the patch can be increased the bandwidth. Therefore the bandwidth and beam width are improved by using multiple arrayed patches. When the ring type patches are inserted serially, the resonance frequencies are occurred by the current flow from the first ring patch. It is possible because the gap between the patches is very narrow. In addition, if the patches are composed on the same plane as the feed-line, fabrication could be very difficult because the gap between the patches is extremely narrow. The thickness and permittivity of the antenna, moreover, are very important parameters because both sides of the substrate are used. We finally found the optimal thickness and permittivity to generate the coupling effect by simulation. All patches are consisted of 4-steps which the patch size was decreased 85 % by each step. In conclusion, the resonant frequency bands are 1.75~2.6 GHz(850 MHz), 3.24~3.46 GHz(220 MHz), 3.8~4.0 GHz(200 MHz), and 4.4~4.9 GHz(500 MHz).

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.45-55
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• 2009

This study was intended to increase efficiency of traffic flow management on intersection. The result suggested to establish a left-turn at own risk lane to increase efficiency of traffic flow on intersection. The scope of the research was to investigate the geometric structure of a signal-controlled intersection, traffic volume(density) with respect to directions and traffic signal display, and to select a signalling intersection into which a car waiting for a traffic signal enters by adjusting the display sequence of traffic signal. The delay with respect to directions and for the whole intersection was compared for the current situation and an improvement plan. Using TSIS, a traffic analysis package, the traffic situation on an intersection was investigated. Based on the simulation result for Seok-Jeon intersection in Ma-San selected from the field investigation of intersections to which an improvement plans would be applicable, the waiting time in the direction without a entering traffic signal was decreased to be 78.6 seconds per car and that of the direction expecting the increase of waiting time was increased by 4 seconds per car only. It was confirmed that the waiting time for the whole intersection was improved.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.870-881
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• 2020

This paper presents cell ID (cell identity) detection schemes using PSS/SSS (primary synchronization signal/secondary synchronization signal) for 5G NR (new radio) system and evaluates the detection performance. In this paper, we consider two cell ID detection schemes, i.e. two-stage detection and joint detection schemes. The two-stage detection scheme consists of two stages which estimate a channel gain between a transmitter and receiver and detect the PSS and SSS sequences. The joint detection scheme jointly detects the PSS and SSS sequences. In addition, this paper presents coherent and non-coherent combining schemes. The coherent scheme calculates the correlation value for the total length of the given PSS and SSS sequences, and the non-coherent combining scheme calculates the correlation within each group by dividing the total length of the sequence into several groups and then combines them non-coherently. For the detection schemes considered in this paper, the detection error rates of PSS, SSS and overall cell ID are evaluated and compared through computer simulations. The simulation results show that the joint detection scheme outperforms the two-stage detection scheme for both coherent and non-coherent combining schemes, but the two-stage detection scheme can greatly reduce the computational complexity compared to the joint detection scheme. In addition, the non-coherent combining detection scheme shows better performance under the additive white Gaussian noise (AWGN), fixed, and mobile environments.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.81-92
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• 2021

In this study, we investigated the effects of five EMS lumbar back pressure belts produced on an anatomical basis on lumbar spine stabilization. Five core muscles were selected, including the urinal, vertebral column, endotracheal, external abdominal, and large back muscles, and patterns were designed using a conductive fabric considering the appropriate muscle shape and pain-causing points. We experimented with four motions to examine the effects of different EMS abdominal compression belts on lumbar spine stabilization. Five healthy men in their 20s were selected. The selection conditions include no back pain history for the past three months, no restricted movements through pre-inspection, and the muscular strength of the body should belong to the normal grade. Using SLR, the sequence of experimental actions was chosen from the following but not limited to left-hand, body-hand, and back-line forces. Resting between movements lasted for 2 min, and the experiments were conducted after wearing the EMS abdominal pressure belt. Electrical stimulation was applied for 10 min to increase blood flow and muscle activation. The statistics of the experimental results were analyzed for specific differences by conducting the Wilcoxon and Friedman tests with nonparametric tests. The ranking results of each pattern were successfully assessed in the order of 5, 4, 3, 1, 2 for the five patterns, and we could identify slightly more significant results for experimental behavior associated with each muscle movement. Patterns produced based on anatomy showed differentiated effects when electric stimulation was applied to each muscle in different shapes, which could improve the stabilization of the lumbar spine in everyday life or training to the public. Based on these results, subsequent research would focus on developing smart healthcare clothing that is practical in daily life by employing different anatomical mechanisms, depending on the back pain, to utilize trunk-type tights.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Journal of the Korean Geotechnical Society
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• v.22 no.9
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• pp.45-59
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• 2006

The successful performance of any numerical geotechnical simulation depends on the accuracy and efficiency of the numerical implementation of constitutive model used to simulate the stress-strain (constitutive) response of the soil. The corner stone of the numerical implementation of constitutive models is the numerical integration of the incremental form of soil-plasticity constitutive equations over a discrete sequence of time steps. In this paper a well known two-surface soil plasticity model is implemented using a generalized implicit return mapping algorithm to arbitrary convex yield surfaces referred to as the Closest-Point-Projection method (CPPM). The two-surface model describes the nonlinear behavior of coarse-grained materials by incorporating a bounding surface concept together with isotropic and kinematic hardening as well as fabric formulation to account for the effect of fabric formation on the unloading response. In the course of investigating the performance of the CPPM integration method, it is proven that the algorithm is an accurate, robust, and efficient integration technique useful in finite element contexts. It is also shown that the algorithm produces a consistent tangent operator $\frac{d\sigma}{d\varepsilon}$ during the iterative process with quadratic convergence rate of the global iteration process.

• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.17-30
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• 2009

Underground construction such as tunneling can induce damages on the surrounding rock mass, due to the stress concentration of in situ stresses and excessive energy input during construction sequence, such as blasting. The developed damage on the rock mass can have substantial influence on the mechanical and hydraulic behaviors of the rock masses around a tunnel. In this study, investigation on the generation of damage around an opening in a jointed rock model under biaxial compression condition was conducted. The joint dip angles employed are 30, 45, and 60 degrees to the horizontal, and the synthetic rock mass was made using early strength cement and water. From the biaxial compression test, initiation and propagation of tensile cracks at norm to the joint angle were found. The propagated tensile cracks eventually developed rock blocks, which were dislodged from the rock mass. Furthermore, the propagation process of the tensile cracks varies with joint angle: lower joint angle model shows more stable and progressive tensile crack propagation. The development of the tensile crack can be explained under the hypothesis that the rock segment encompassed by the joint set is subjected to the developing moment, which can be induced by the geometric irregularity around the opening in the rock model. The experiment results were simulated by using discrete element method PFC 2D. From the simulation, as has been observed from the test, a rock mass with lower joint angle produces wider damage region and rock block by tensile cracks. In addition, a rock model with lower joint angle shows progressive tensile cracks generation around the opening from the investigation of the interacted tensile cracks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.247-259
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• 2000

This paper introduces a new technique that reduces the search times and Improves the accuracy of motion estimation using high temporal and spatial correlation of motion vector. Instead of using the fixed first search Point of previously proposed search algorithms, the proposed method finds more accurate first search point as to compensating searching area using high temporal and spatial correlation of motion vector. Therefore, the main idea of proposed method is to find first search point to improve the performance of motion estimation and reduce the search times. The proposed method utilizes the direction of the same coordinate block of the previous frame compared with a block of the current frame to use temporal correlation and the direction of the adjacent blocks of the current frame to use spatial correlation. Based on these directions, we compute the first search point. We search the motion vector in the middle of computed first search point with two fixed search patterns. Using that idea, an efficient adaptive predicted direction search algorithm (APDSA) for block matching motion estimation is proposed. In the experimental results show that the PSNR values are improved up to the 3.6dB as depend on the Image sequences and advanced about 1.7dB on an average. The results of the comparison show that the performance of the proposed APDSA algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the FS (Full Search) algorithm. Simulation results also show that the performance of the APDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS algorithm.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.6 no.2
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• pp.81-92
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• 2001

According to analyses of high-resolution seismic profiles (air gun, sparker, and SBP) and a deep-drill core(YSDP 105) in the mid-eastern Yellow Sea, stratigraphic and geoacoustic models have been established and seismo-acoustic modeling has been fulfilled using ray tracing of finite element method. Stratigraphic model reflects seismo-, litho-, and chrono-stratigraphic sequences formed under a significant influence of Quaternary glacio-eustatic sea-level fluctuations. Each sequence consists of terrestrial to very-shallow-marine coarse-grained lowstand systems tract and tidal fine-grained transgressive to highstand systems tract. Based on mean grain-size data (121 samples) of the drill core, bulk density and P-wave velocity of depositional units have been inferred and extrapolated down to a depth of the recovery using the Hamilton's regression equations. As goo-acoustic parameters, the 121 pairs of bulk density and P-wave velocity have been averaged on each unit of the stratigraphic model. As a result of computer ray-tracing simulation of the subsurface strata, we have found that there are complex ray paths and many acoustic-shadow zones owing to the presence of irregular layer boundaries and low-velocity layers.