• Convergence Security Journal
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• v.12 no.6
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• pp.31-37
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• 2012

Today, the core technology of an automobile is becoming to IT-based convergence system technology. To cope with many kinds of situations and provide the convenience for drivers, various IT technologies are being integrated into automobile system. In this paper, we propose an convergence system, which is called Augmented Driving System (ADS), to provide high safety and convenience of drivers based on image information processing. From imaging sensor, the image data is acquisited and processed to give distance from the front car, lane, and traffic sign panel by the proposed methods. Also, a converged interface technology with camera for gesture recognition and microphone for speech recognition is provided. Based on this kind of system technology, car accident will be decreased although drivers could not recognize the dangerous situations, since the system can recognize situation or user context to give attention to the front view. Through the experiments, the proposed methods achieved over 90% of recognition in terms of traffic sign detection, lane detection, and distance measure from the front car.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.1-13
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• 2011

In order to create an intelligent autonomous agent in virtual world, we need a sophisticated design for perception, recognition, judgement and behavior. We develop the perception and recognition functions for such an autonomous agent. Our perception mechanism identifies lines based on differences in color, the primitive visible data, and exploits those lines to grasp shapes and regions in the scene. We develop an inferencing algorithm that can infer the original shape from a damaged or partially hidden shape using its characteristics from the ontology in order to intelligently recognize the perceived shape. Several individually recognized 2D shapes and their spatial relations form 3D shapes and those 3D shapes in turn constitute a scene. Each 3D shape occupies its respective region, and an agent analyzes the associated objects and relevant scenes to recognize things and phenomena. We also develop a mechanism by which an agent uses this recognition function to accumulate and use her knowledge on the scene in the historical context. We implement these functions presented above against an example situation to demonstrate their sophistication and realism.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.27-33
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• 2010

In this study, we conducted the classification experiments with GMM (Gaussian Mixture Model) from combining the extracted features by using microphone, Gyro sensor and Acceleration sensor in 9 different environment types. Existing studies of Context Aware wanted to recognize the Environment situation mainly using the Environment sound data with microphone, but there was limitation of reflecting recognition owing to structural characteristics of Environment sound which are composed of various noises combination. Hence we proposed the additional application methods which added Gyro sensor and Acceleration sensor data in order to reflect recognition agent's movement feature. According to the experimental results, the method combining Acceleration sensor data with the data of existing Environment sound feature improves the recognition performance by more than 5%, when compared with existing methods of getting only Environment sound feature data from the Microphone.

• Journal of Platform Technology
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• v.8 no.4
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• pp.11-19
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• 2020

In an autonomous driving environment, dynamic recognition of objects is essential as the situation changes in real time. In addition, as the number of sensors and control modules built into an autonomous vehicle increases, the amount of data the central control unit has to process also rapidly increases. By minimizing the output data from the sensor, the load on the central control unit can be reduced. This study proposes a dynamic object recognition algorithm solely using the embedded processor on a LiDAR sensor. While there are open source algorithms to process the point cloud output from LiDAR sensors, most require a separate high-performance processor. Since the embedded processors installed in LiDAR sensors often have resource constraints, it is essential to optimize the algorithm for efficiency. In this study, an embedded processor based object recognition algorithm was developed for autonomous vehicles, and the correlation between the size of the point clouds and processing time was analyzed. The proposed object recognition algorithm evaluated that the processing time directly increased with the size of the point cloud, with the processor stalling at a specific point if the point cloud size is beyond the threshold

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.91-96
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• 2022

At the current camera-based technology level, sensor-based basic life pattern recognition technology has to suffer inconvenience to obtain accurate data, and commercial band products are difficult to collect accurate data, and cannot take into account the motive, cause, and psychological effect of behavior. the current situation. In this paper, radar technology for life pattern recognition is a technology that measures the distance, speed, and angle with an object by transmitting a waveform designed to detect nearby people or objects in daily life and processing the reflected received signal. It was designed to supplement issues such as privacy protection in the existing image-based service by applying it. For the implementation of the proposed system, based on TI IWR1642 chip, RF chipset control for 60GHz band millimeter wave FMCW transmission/reception, module development for distance/speed/angle detection, and technology including signal processing software were implemented. It is expected that analysis of individual life patterns will be possible by calculating self-management and behavior sequences by extracting personalized life patterns through quantitative analysis of life patterns as meta-analysis of living information in security and safe guards application.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.326-341
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• 2020

Based on theoretical background of Situational Theory of Problem Solving(STOPS), we have examined the role of STOPS variables on a group of online public in their issue recognition and communicative behavior on Korea's nationwide civil boycott movement of Japanese goods. Results from 524 survey cases from a Korea's major online community show that two independent variables(Problem Recognition, Referent Criterion) revealed positive in their effect on mediating variable(Situational Motivation in Problem Solving). Situational Motivation also revealed positive in its effect on six dependent variables(Information Forefending, Information Permitting, Information Forwarding, Information Sharing, Information Seeking, Information Attending) of Communicative Behavior. Involvement Recognition and Constraint Recognition revealed positive without proper statistical significance. As a result, study on the case of online public in Korea supports STOPS theory as high-level of Problem Recognition and Referent Criterion effects on Communicative Behavior in positive way via Situational Motivation. Implications from the findings have discussed and proposed suggestions for government public relations and further studies.

• Journal of the Korean association of regional geographers
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• v.16 no.1
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• pp.59-75
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• 2010

This study analyzed on the recognition characteristics of high school students in Seoul about the factors influencing the land value. The results are as follows; First, when the factors influencing the land value was divided into 'the factors related with the publicly assessed land value' and 'the unrelated factors.' Students recognized that the former had more influence on the land value than the latter. Second, students recognized that 'the relative factors of land' had more influence on the land value than 'the absolute factors of land'. Third, as a result of checking how much five evaluation criterions influence on the recognition characteristics about the factors influencing the land value, the distance to major facilities had the most influence on the recognition, while the situation of land use had the weakest one. Among 13 factors, the distance from the convenience facilities was most influential and the shape of the land was least influential. Fourth, there was a gap between recognition of choosing the highest land value areas and the lowest land value areas and recognition of degree that the factor influencing the land value had an effect on the land value. Lastly, when the result of recognition about factors influencing the land value and the land value ranking was compared with the result of the co-relation between the land value and factors influencing the land value of the real region, either similar or different results were shown.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• The Journal of the Convergence on Culture Technology
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• v.1 no.2
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• pp.71-75
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• 2015

Smart City for establishing mutual communication for next-generation digital signage technology attracting attention in the tele screen service is being spread. In recent years, the state of the surrounding circumstances of the user-to-user information such as situation-based, bi-directional communication by collecting and analyzing the possible interactive tele-screen services. This study suggests the value of smart city services platform, standardization trends, domestic, and international marketability analysis information. Tele-screen service technology is able to be a high-level administrative services, and further domestic e-government technology can be spread all over the world.

• Korean Journal of Organic Agriculture
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• v.12 no.3
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• pp.303-316
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• 2004

Recently, with the improvement of national income, the increase of int e rest in the consumers, health, and the enhancement of recognition of environment the demands of environmental-friendly agricultural products(EFAPs) are on the rise rapidly. The demand in the market for EFAPs increases rapidly, and the sales amount increases by 30~40% every year. But, it is in situation that the EFAPs arc not distributed well between the producers and consumers now. That is, the producers of EFAPs can not End th e ir markets. And, the consumers do not trust the EFAPs. Also, it is in situation that it is difficult to promote the demand because of relatively higher prices than the general agricultural products. To solve these problems, it may be summed up as follows. First, it needs to reduce the distribution cost by the construction of stable supply basis. Second, it needs to improve the distribution system of EFAPs. Third, it needs to enhance the differentiation and improve the consumers, reliability. Fourth, it needs to make in brand and extend the various publicities. Fifth, it needs to construct the supporting system and enhance the cooperation with the related institutions. Sixth, it needs to End new demand and introduce the procurement system by the government.