• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.961-968
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• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.211-218
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• 1998

The demand prediction becomes an essential mean to utilize efficiently finite traffic facilities and to provide the optimized schedules for transportation system. The demand prediction is one of the critical complex management schemes for distibuting resources of transportation service by means of computer system. The construction of a prediction model is based on data granulization, followed by processing the raw input data and evaluating the predicted output values. A large number of economic-social parameters are also to be implemented in conventional prediction models which are only based on a sequence of past data. The proposed prediction models are classified by static and dynamic characteristics and its performances are evaluated utilizing computer simulation.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.541-550
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• 2012

Objective: The aim of this study is to suggest a notation method for three-dimensional hand gesture. Background: To match intuitive gestures with commands of products, various studies have tried to derive gestures from users. In this case, various gestures for a command are derived due to various users' experience. Thus, organizing the gestures systematically and identifying similar pattern of them have become one of important issues. Method: Related studies about gesture taxonomy and notating sign language were investigated. Results: Through the literature review, a total of five elements of static gesture were selected, and a total of three forms of dynamic gesture were identified. Also temporal variability(reputation) was additionally selected. Conclusion: A notation method which follows a combination sequence of the gesture elements was suggested. Application: A notation method for three dimensional hand gestures might be used to describe and organize the user-defined gesture systematically.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.439-444
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• 2011

As construction projects have been getting larger and more complex, a single individual or organization cannot have complete knowledge or the abilities to handle all matters. Collaborative practices among heterogeneous individuals, which are temporarily congregated to carry out a project, are required in order to accomplish project objectives. These organizational knowledge creation processes of project teams should be understood from the active and dynamic viewpoint of how they create information and knowledge rather than from the passive and static input-process-output sequence. To this end, agent-based modeling and simulation which is built from the ground-up perspective can provide the most appropriate way to systematically investigate them. In this paper, agent-based modeling and simulation as a research method and a medium for representing theory is introduced. To illustrate, an agent-based simulation of the evolution of collaboration in large-scale project teams from a game theory and social network perspective is presented.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.8
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• pp.782-791
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• 1991

In the fields of pattern recognition such as speech recognition, several new techniques using Artifical Neural network Models have been proposed and implemented. In particular, the Multilayer Perception Model has been shown to be effective in static speech pattern recognition. But speech has dynamic or temporal characteristics and the most important point in implementing speech recognition systems using Artificial Neural Network Models for continuous speech is the learning of dynamic characteristics and the distributed cues and contextual effects that result from temporal characteristics. But Recurrent Multilayer Perceptron Model is known to be able to learn sequence of pattern. In this paper, the results of applying the Recurrent Model which has possibilities of learning tedmporal characteristics of speech to phoneme recognition is presented. The test data consist of 144 Vowel+ Consonant + Vowel speech chains made up of 4 Korean monothongs and 9 Korean plosive consonants. The input parameters of Artificial Neural Network model used are the FFT coefficients, residual error and zero crossing rates. The Baseline model showed a recognition rate of 91% for volwels and 71% for plosive consonants of one male speaker. We obtained better recognition rates from various other experiments compared to the existing multilayer perceptron model, thus showed the recurrent model to be better suited to speech recognition. And the possibility of using Recurrent Models for speech recognition was experimented by changing the configuration of this baseline model.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.546-549
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• 1999

For the safty driving of an automobile which is become individual requisites, a new Neural Network algorithm which recognized the load vehicles in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed 1-D LIPN hardware has been composed and various experiments with static and dynamic signals have been implmented.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2130-2133
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• 2003

For real-time recognizing of the load vehicles a new Neural Network algorithm is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a Processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through severa simulation experiments, real time reconstruction nonlinear image information is Processed. 1-D hardware has been composed and various experi with static and dynamic signals have implemented.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.293-301
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• 2017

Most new products not only suddenly disappear in the market but also quickly cannibalize older products. Under such a circumstance, retailers may have too much stock, and customers may be faced with difficulties discovering products suitable to their preferences among short life cycle products. To address these problems, recommender systems are good solutions. However, most previous recommender systems had difficulty in reflecting changes in customer preferences because the systems employ static customer preferences. In this paper, we propose a recommendation methodology that considers dynamic customer preferences. The proposed methodology consists of dynamic customer profile creation, neighborhood formation, and recommendation list generation. For the experiments, we employ a mobile image transaction dataset that has a short product life cycle. Our experimental results demonstrate that the proposed methodology has a higher quality of recommendation than a typical collaborative filtering-based system. From these results, we conclude that the proposed methodology is effective under conditions where most new products have short life cycles. The proposed methodology need to be verified in the physical environment at a future time.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.6
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• pp.120-136
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• 2016

This study, views the color of scenery not as a static state, but rather as a continuous sequence of perceptions that incorporates the concept of time. This study derived techniques to quantitatively analyze the flow and data from this sequence. By utilizing this, urban color trends can be based on openness. This is very close to what would be experienced by an actual viewer: it extracted color data and visual amount from frames at 2-second intervals by shooting a video of the color sequence of the city as seen from both the left and right sides from the inside of the monorail (line 3 of the Daegu urban railway). These images were classified by color group, brightness, chroma, high chroma distribution derived techniques such as openness of space, brightness level, clarity level, high-chroma distribution and code, advantage of visual amount, dominant factor exposure, hot and cold color image and dynamic of sequence rhythm. During the derived sequence, the data determines the openness in the visual amount of sky and it was found that the tendency of the colors of the city was opening regression analysis. The more colorful the city is opening the brightness is lowered, the chroma increased slightly, cold colors significantly increased, which also had a very deep relationship with Lynch enclosed proportion, color change of the city trends through the actual scenery could grasp in more detail.

• Progress in Medical Physics
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• v.15 no.1
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• pp.1-8
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• 2004

Patient dose verification is one of the most Important responsibilities of the physician in the treatment delivery of radiation therapy. For the task, it is necessary to use an accurate dosimeter that can verify the patient dose profile, and it is also necessary to determine the physical characteristics of beams used in intensity modulated radiation therapy (IMRT) The Beam Intensity Scanner (BInS) System is presented for the dosimetric verification of the two dimensional photon beam. The BInS has a scintillator, made of phosphor Terbium-doped Gadolinium Oxysulphide (Gd$_2$O$_2$S:Tb), to produce fluorescence from the irradiation of photon and electron beams. These fluoroscopic signals are collected and digitized by a digital video camera (DVC) and then processed by custom made software to express the relative dose profile in a 3 dimensional (3D) plot. As an application of the BInS, measurements related to IWRT are made and presented in this work. Using a static multileaf collimator (SMLC) technique, the intensity modulated beam (IMB) is delivered via a sequence of static portals made by controlled leaves. Thus, when static subfields are generated by a sequence of abutting portals, the penumbras and scattered photons of the delivered beams overlap in abutting field regions and this results in the creation of “hot spots”. Using the BInS, inter-step “hot spots” inherent in SMLC are measured and an empirical method to remove them is proposed. Another major MLC technique in IMRT, the dynamic multileaf collimator (DMLC) technique, has different characteristics from SMLC due to a different leaf operation mechanism during the irradiation of photon and electron beams. By using the BInS, the actual delivered doses by SMLC and DMLC techniques are measured and compared. Even if the planned dose to a target volume is equal in our experimental setting, the actual delivered dose by DMLC technique is measured to be larger by 14.8% than that by SMLC, and this is due to scattered photons and contaminant electrons at d$_{max}$.