Journal of Satellite, Information and Communications
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v.2
no.2
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pp.64-68
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2007
This paper describes the development of RF front.end equipment of a wide band high precision satellite navigation receiver to be able to receive the currently available GPS navigation signal and the GALILEO navigation signal to be developed in Europe in the near future. The wide band satellite navigation receiver with high precision performance is composed of L - band antenna, RF/IF converters for multi - band navigation signals, and high performance baseband processor. The L - band satellite navigation antenna is able to be received the signals in the range from 1.1 GHz to 1.6 GHz and from the navigation satellite positioned near the horizon. The navigation signal of GALILEO navigation satellite consists of L1, E5, and E6 band with signal bandwidth more than 20 MHz which is wider than GPS signal. Due to the wide band navigation signal, the IF frequency and signal processing speed should be increased. The RF/IF converter has been designed with the single stage downconversion structure, and the IF frequency of 140 MHz has been derived from considering the maximum signal bandwidth and the sampling frequency of 112 MHz to be used in ADC circuit. The final output of RF/IF converter is a digital IF signal which is generated from signal processing of the AD converter from the IF signal. The developed RF front - end has the C/N0 performance over 40dB - Hz for the - 130dBm input signal power and includes the automatic gain control circuits to provide the dynamic range over 40dB.
Park, Sung-chan;Hwang, Kwang-bok;Park, Hee-mun;Choi, Young-kiu;Park, Jin-hyun
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2018.05a
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pp.468-469
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2018
We design CNN(convolutional neural network) which is applicable to steering control system of autonomous vehicle. CNN has been widely used in many fields, especially in image classifications. But CNN has not been applied much to the regression problem such as function approximation. This is because the input of CNN has a multidimensional data structure such as image data, which makes it is not applicable to general control systems. Recently, autonomous vehicles have been actively studied, and many techniques are required to implement autonomous vehicles. For this purpose, many researches have been studied to detect the lane by using the image through the black box mounted on the vehicle, and to get the vanishing point according to the detected lane for control the autonomous vehicle. However, in detecting the vanishing point, it is difficult to detect the vanishing point with stability due to various factors such as the external environment of the image, disappearance of the instant lane and detection of the opposite lane. In this study, we apply CNN for steering control of an autonomous vehicle using a black box image of a car.
IC package marking inspection system using machine vision locates and identifies the target elements from input image, and decides the quality of marking by comparing the extracted target elements with the standard patterns. This paper proposes an adaptive multi-level thresholding (AMLT) method which is suitable for a series of operations such as locating the target IC package, extracting the characters, and detecting the Pinl dimple. It also proposes a dynamic matching unit selection (DMUS) method which is robust to noises as well as effective to catch out the local marking errors. The main idea of the AMLT method is to restrict the inputs of Otsu's thresholding algorithm within a specified area and a partial range of gray values. Doing so, it can adapt to the specific domain. The DMUS method dynamically selects the matching unit according to the result of character extraction and layout analysis. Therefore, in spite of the various erroneous situation occurred in the process of character extraction and layout analysis, it can select minimal matching unit in any environment. In an experiment with 280 IC package images of eight types, the correct extracting rate of IC package and Pinl dimple was 100% and the correct decision rate of marking quality was 98.8%. This result shows that the proposed methods are effective to IC package marking inspection.
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.3
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pp.49-55
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2017
Most motor cases adopt deep drawing products, which are excellent in waterproof functions, concentricity, right angle, and quality. In addition, the blower motor and seat motor, which are installed in the car interior and do not require waterproof function, adopts a multi-forming manufacturing method. The deep drawing process requires an expensive transfer press that can digest approximately 12 processes, such as drawing, trimming and piercing. On the other hand, products can be produced with low investment because the multi-forming method is composed of one multi-forming machine or one multi-forming machine and one press. The multi-forming machine is a high-priced facility that is mostly imported and a bending / shearing process multi-foaming machine, which was developed by domestic small and medium-sized enterprises, is not enough to reduce the production cost. An integral multi - forming machine is used as a limited working method for thin material and small products. A large product and thick material has a high shear load. A large product and thick material has a high shear load and uses a single crank press. After blanking, the worker manually feeds the material to a multi-forming machine. When the bending operation is performed in the multi-forming machine, it is transferred to the press again to calibrate the dimensions. This variance in work processes has resulted in lower cost competitiveness due to the lower productivity, quality issues, and excessive operator input. The aim of this study was to establish a stable and cost - effective production system through bending / shearing process separation and facility automation.
In this research, we proposed a two-phase hybrid stock price forecasting model with cointegration tests and artificial neural networks. Using not only the related stocks to the target stock but also the past information as input features in neural networks, the new model showed an improved performance in forecasting than that of the usual neural networks. Firstly in order to extract stocks which have long run relationships with the target stock, we made use of Johansen's cointegration test. In stock market, some stocks are apt to vary similarly and these phenomenon can be very informative to forecast the target stock. Johansen's cointegration test provides whether variables are related and whether the relationship is statistically significant. Secondly, we learned the model which includes lagged variables of the target and related stocks in addition to other characteristics of them. Although former research usually did not incorporate those variables, it is well known that most economic time series data are depend on its past value. Also, it is common in econometric literatures to consider lagged values as dependent variables. We implemented a price direction forecasting system for KOSPI index to examine the performance of the proposed model. As the result, our model had 11.29% higher forecasting accuracy on average than the model learned without cointegration test and also showed 10.59% higher on average than the model which randomly selected stocks to make the size of the feature set same as that of the proposed model.
KIPS Transactions on Software and Data Engineering
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v.6
no.6
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pp.315-320
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2017
Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.
Recently, because credit card crime using a personal credit information is increasing, professionalizing, and spreading the area, the loss occurring from credit card crime is enormous and is difficult to arrest and punish the criminals. At past, crime from forging and counterfeiting the credit card was originated by minority criminals, but at present, the types and appearance of credit card crime is very different to contrasting past crime. The numbers of people using credit card in the middle of 1990's was increasing and barometer of living conditions was evaluated by the number having credit card, therefore this bad phenomenon occurring from credit card crime was affected by abnormal consumption patterns. There is no need emphasizing the importance of personal credit card in this credit society. so, because credit card crime using personal credit card information has a bad effect, and brings the economic loss and harms to individuals, credit card company, and members joining credit card. Credit card crime using personal credit card information means the conduct using another people's credit card information(card number, expiring duration, secret number) that detected by unlawful means. And crime using dishonest means from another people's credit information is called a crime profiting money-making and a crime lending an illegal advance by making false documents. A findings on countermeasures of this study are as follows: Firstly, Diverting user's mind, improving the art of printing, and legitimating password from payment gateway was suggested. Secondly, Complementing input of password, disseminating the system of key-board protection, and promoting legitimations of immediate notification duty was suggested. Thirdly, Certificating the electronic certificates as a personal certificates, assuring the recognition by sense organ of organism, and lessening the ratio of crime occurrence, and restricting the ratio of the credit card crime was suggested.
Nonpoint source pollution has become a concern for water quality in the Han River system, especially during the high runoff events during the monsoon season. The patterns in nonpoint source runoff the relationships with land use, rainfall intensity, and stream nutrients concentrations were surveyed in 19 streams in the Han River watershed. The results show that the magnitude of NPS inputs of nutrients and sediment in the Han River watershed are of a serious concern. In the South Han River watershed, event mean concentrations (EMC) for biochemical oxygen demand (BOD), suspended sediment (SS), dissolved organic carbon (DOC), dissolved total phosphorus (DTP), total nitrogen (TN) Nitrate ($NO_3$-N) and total phosphorus (TP) were $1.94mg{\cdot}L^{-1},\;251mg{\cdot}L^{-1},\;2.75mg{\cdot}L^{-1},\;0.076mg{\cdot}L^{-1},\;2.82mg{\cdot}L^{-1},\;2.40mg{\cdot}L^{-1}$ and $0.232mg{\cdot}L^{-1}$, respectively. In the North Han River watershed, EMCs for BOD, SS, DOC, DTP, TN, $NO_3$-N and TP were $1.34mg{\cdot}L^{-1},\;172mg{\cdot}L^{-1},\;2.63mg{\cdot}L^{-1},\;0.032mg{\cdot}L^{-1},\;1.97mg{\cdot}L^{-1},\;1.55mg{\cdot}L^{-1}$ and $0.148mg{\cdot}L^{-1}$, respectively. The specific export coefficients of nutrient and sediments were much higher than those of other reports. Our study also found that the proportion of agricultural field area was significantly correlated with the EMCs for nutrients. Therefore, efforts to reduce NPS loading must focus on agricultural practices in the watershed. The relationships between land use and nutrient and sediment export found in this study can be used to derive estimates of runoff coefficients for agricultural field and as input data for modeling works and to develop total maximum daily load and best management practices in the Han River watershed.
The sustainability of conventional agriculture which is characterized by input dependent and ecologically simplified food production system is vague. Chemicals and present practices used in agriculture are not only costly but also have widespread implications on human and animal health, food quality and safety and environmental quality. Thus there is a need for alternative farming practices to sustain food production for the escalating population and conserve environment for future generations. The present research scenario in the area of plant microbe interactions for maintaining sustainable agriculture suggests that the level of internal regulation in agro-ecosystems is largely dependent on the level of plant and microbial diversity present in the soil. In agro-ecosystems, biodiversity performs a variety of ecological services beyond the production of food, including recycling of nutrients, regulation of microclimate and local hydrological processes, suppression of undesirable organisms and detoxification of noxious chemicals. Controlling the soil microflora to enhance the predominance of beneficial and effective microorganisms can help improve and maintain soil chemical and physical properties. The role of beneficial soil microorganisms in sustainable productivity has been well construed. Some plant bacteria referred to as plant growth-promoting rhizobacteria (PGPR) can contribute to improve plant growth, nutrient uptake and microbial diversity when inoculated to plants. Term PGPR was initially used to describe strains of naturally occurring non-symbiotic soil bacteria have the ability to colonize plant roots and stimulate plant growth PGPR activity has been reported in strains belonging to several other genera, such as Azotobacter, Azospirillum, Arthrobacter Bacillus, Burkhokderia, Methylobacterium, and Pseudomonas etc. PGPR stimulate plant growth directly either by synthesizing hormones such as indole acetic acid or by promoting nutrition, for example, by phosphate solubilization or more generally by accelerating mineralization processes. They can also stimulate growth indirectly, acting as biocontrol agents by protecting the plant against soil borne fungal pathogens or deleterious bacteria. Present review focuses on some recent developments to evolve strategies for better biotechnological exploitation of PGPR's.
The purpose of this research is to analyze the performance of national R&D projects and to find out measures to improve the performance indicators, focusing on energy HRD projects. The main analysis target is 86 energy manpower projects supported since 2010. The performance indicators of the energy HRD projects are related to the research capacity, the number of emission workers, industry-university linkage, job creation and so on, and analyzed by using the 11 indicators of human resource performance index called KPI index. As a result of analyzing the attainment level of the proposed target by task, the index with the highest achievement level is the corporation linkage rate, and the index with the lowest achievement level is the participating company employment. As a result of examining the effects of job creation in company - linked activities, it was found that the greater the number of participating companies in the business, the greater the employment creation effect of the number of internships. As a result of the above analysis, the following policy alternatives are proposed. First, it is necessary to consider adding indicators that can express the quality performance of the business and performance indicators that can express actual business linkages. Second, it is necessary to strengthen the management of differentiated performance indicators according to policy performance targets and major target groups. Third, it is necessary to improve information input and accumulation system along with improvement of performance index.
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