• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.67-73
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• 2010

In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1176-1194
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• 2018

The object classification using the images' contents is a big challenge in computer vision. The superpixels' information can be used to detect and classify objects in an image based on locations. In this paper, we proposed a methodology to detect and classify the image's pixels' locations using enhanced bag of words (BOW). It calculates the initial positions of each segment of an image using superpixels and then ranks it according to the region score. Further, this information is used to extract local and global features using a hybrid approach of Scale Invariant Feature Transform (SIFT) and GIST, respectively. To enhance the classification accuracy, the feature fusion technique is applied to combine local and global features vectors through weight parameter. The support vector machine classifier is a supervised algorithm is used for classification in order to analyze the proposed methodology. The Pascal Visual Object Classes Challenge 2007 (VOC2007) dataset is used in the experiment to test the results. The proposed approach gave the results in high-quality class for independent objects' locations with a mean average best overlap (MABO) of 0.833 at 1,500 locations resulting in a better detection rate. The results are compared with previous approaches and it is proved that it gave the better classification results for the non-rigid classes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.27-34
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• 2013

Mobile robot has the exploration function in order to perform its own task. Robot exploration can be used in many applications such as surveillance, rescue and resource detection. The workspace that robots performed in was complicated or quite wide, the multi search using the several mobile robots was mainly used. In this paper, we proposed a scheme that all areas are searched for by using one robot. The method to be proposed extract a area that can be explored in the workspace then the robot investigates the area and updates the map at the same time. The explored area is saved as a hybrid map that combines the nice attributes of the grid and topological maps. The robot can produce the safe navigation route without the obstacles by using hybrid map. The proposed hybrid map uses less memory than a grid map, but it can be used for complete coverage with the same efficiency of a topological map. Experimental results show that the proposed scheme can generate a map of an environment with only 6% of the memory that a grid map requires.

• Progress in Superconductivity
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• v.10 no.1
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• pp.60-67
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• 2008

We present domestic efforts for superconducting fault current limiter (SFCL) application in the Korea Electric Power Corporation (KEPCO) grid and pending points at issue. KEPCO's decision to upgrade the 154 kV/22.9 kV main transformer from 60 MVA to 100 MVA cast a problem of high fault current in the 22.9 kV distribution lines. The grid planners supported adopting an SFCL to control the fault current. This environment friendly to SFCL application must be highly dependent upon the successful development of SFCL having specifications that domestic utility required. The required conditions are (1) small size of not greater than twice of 22.9 kV gas insulated switch-gear (GIS), (2) sustainability of current limitation without the line breaking by circuit breakers (CB) for maximum 1.5 seconds. Also, optionally, recommended is (3) the reclosing capability. Conventional resistive SFCLs do not meet (1) $\sim$ (3) all together. A hybrid SFCL is an excellent solution to meet the conditions. The hybrid SFCL consists of HTS SFCL components for fault detection and line commutation, a fast switch (FS) to break the primary path, and a limiter. This characteristic structure not only enables excellent current limiting performances and the reclosing capability, but also allows drastic reduction of HTS volume and small size of the cryostat, resulting in economic feasibility and compactness of the equipment. External current limiter also enables long term limitation since it is far less sensitive to heat generation than HTS. Semi-active operation is another advantage of the hybrid structure. We will discuss more pending points at issues such as maintenance-free long term operation, small size to accommodate the in-house substation, passive and active control, back-up plans, diagnosis, and so on.

• Journal of Life Science
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• v.14 no.1
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• pp.26-31
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• 2004

Redox factor-1 (Ref-1), known as a redox regulator, controls the DNA binding of AP-1 and is activated in HT29 colon cancer cells by hypoxia in vitro. REF-1 also increases tile DNA binding affinity of Hypoxia-inducible Factor-lalpha$ (HIF-lalpha$), HIF-like Factor (HLF) and early growth response-1 (Egr-1) which induce expression of the genes involved in angiogenesis, so that we speculate that REF-1 may play a role in hypoxia-induced angiogenesis. In this research we tried to detect novel proteins interacting with REF-1 using Yeast two-hybrid system using full-length REF-1 cDNA as bait. As result of such screening we detected 3 positive clones. DNA sequencing and GeneBank search revealed that one of the clones contained the same sequences as M.musculus cDNA for tioredoxin.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.914-925
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• 1998

This paper considers the evaluation of the hybrid acquistion perdformance for the pilot signal in the direct sequence code division multiple access(DS/CDMA) forward link. the hybrid acquisition is introduced by the combination of two schemes, the parallel and serial acquisions. The mean acquisition time of the proposed scheme is derived to consider both the best case(the correct code-phase offsets are included i one subset) and the worst case(the correct code-phase offsets exist at the boundary of two subsets), which are cause by the distribution of the correct code-phase offsets in the subset. Expressions for the detection, false alarm, and miss probabilities are derived for the case of multiple correct code-phase offsets and multipath Rayleigh fading channel. Numerical results present the hybrid acquistion performance with repect to design parameters such as postdetectio integration length in the search and verification modes, subset size, and number of I/Q noncoherent correlators, and compare the hybrid acquistion with the parallel acquistion in terms of the minimum acquistion time under the same hardware complexity.

• Korean Journal of Weed Science
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• v.15 no.3
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• pp.206-213
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• 1995

Glyphosate(N-[phosphonomethyl]glycine) applied to the assimilate-exporting leaves(i.e. third old leaf) of tomato(Lycopersicon esculentum Mil var. Moneymaker). Herbicide binding protein, QB protein(D1), has been immunoblotted using the antibodies raised against the hybrid-protein expressed by a part of spinach psb A gene cloned in frame with the 3'end of lac Z gene to allow expression of the ${\beta}$-galactosidase(EC 3.21.23) in Escherichia coli. Glyphosate has an effect on a turnover of D1 within photosystem II of thylakoid membrane. The dysfunction of D1 protein within light harvesting complex(LHC-II) seems to be a pleiotropic effect of glyphosate.

• Journal of the Korean Geosynthetics Society
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• v.22 no.1
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• pp.67-74
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• 2023

In order to monitor the stability of slopes, research on data-based slope failure prediction and early warning is increasing. However, most papers overlook the quality of data. Poor data quality can cause problems such as false alarms. Therefore, this paper proposes a two-step hybrid approach consisting of rules and machine learning models for quality control of data collected from slopes. The rule-based has the advantage of high accuracy and intuitive interpretation, and the machine learning model has the advantage of being able to derive patterns that cannot be explicitly expressed. The hybrid approach was able to take both of these advantages. Through a case study, the performance of using the two methods alone and the case of using the hybrid approach was compared, and the hybrid method was judged to have high performance. Therefore, it is judged that using a hybrid method is more appropriate than using the two methods alone for data quality control.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1307-1312
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• 2023

In this paper, we propose a hybrid camera system that combines cameras with different focal lengths and LiDAR (Light Detection and Ranging) sensors to address the core components of autonomous driving perception technology, which include object recognition and distance measurement. We extract objects within the scene and generate precise location and distance information for these objects using the proposed hybrid camera system. Initially, we employ the YOLO7 algorithm, widely utilized in the field of autonomous driving due to its advantages of fast computation, high accuracy, and real-time processing, for object recognition within the scene. Subsequently, we use multi-focal cameras to create depth maps to generate object positions and distance information. To enhance distance accuracy, we integrate the 3D distance information obtained from LiDAR sensors with the generated depth maps. In this paper, we introduce not only an autonomous vehicle platform capable of more accurately perceiving its surroundings during operation based on the proposed hybrid camera system, but also provide precise 3D spatial location and distance information. We anticipate that this will improve the safety and efficiency of autonomous vehicles.