• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.633-638
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• 2006

We investigated the importance and efficiency of active and passive exploration on the recognition of objects in a variety of virtual environments (VEs). In this study, 54 participants (19 males and 35 females) were randomly allocated into one of two navigation conditions (active and passive navigation). The 3D visual display was presented through HMD and participants used joysticks to navigate VEs. The VEs consisted of exploring four rooms (library, office, lounge, and conference room), each of which had 15 objects. 'Active navigation' was performed by allowing participants to self-pace and control their own navigation within a predetermined time limitation for each room. 'Passive navigation' was conducted by forced navigation of the four rooms in random order. Total navigation duration and objects for both navigations were identical. After navigating VEs, participants were asked to recognize the objects that had been in the four rooms. Recognition for objects was measured by response time and the percentage of correct, false, hit, and miss responses. Those in the active navigation condition had a significantly higher percentage of hit responses (t (52) = 4.000 p < 0.01), and a significantly lower percentage of miss responses (t (52) = -3.763, p < 0.01) in object recognition than those in the passive condition. These results suggest that active navigation plays an important role in spatial cognition as well as providing a better explanation about the efficiency of learning in a 3D-based program.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.209-214
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• 2018

Today is the era of artificial intelligence. With the development of artificial intelligence, machines have begun to impersonate various human characteristics today. Chatbot is one instance of this interactive artificial intelligence. Chatbot is a computer program that enables to conduct natural conversations with people. As mentioned above, Chatbot conducted conversations in text, but Chatbot, in this study evolves to perform commands based on speech-recognition. In order for Chatbot to perfectly emulate a human dialogue, it is necessary to analyze the sentence correctly and extract appropriate response. To accomplish this, the sentence is classified into three types: objects, actions, and preferences. This study shows how objects is analyzed and processed, and also demonstrates the possibility of evolving from an elementary model to an advanced intelligent system. By this study, it will be evaluated that speech-recognition based Chatbot have improved order-processing time efficiency compared to text based Chatbot. Once this study is done, speech-recognition based Chatbot have the potential to automate customer service and reduce human effort.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.743-748
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• 2007

Recently, various types of camera mouse are developed using the image processing. The camera mouse showed limited performance compared to the traditional optical mouse in terms of the response time and the usability. These problems are caused by the mismatch between the size of the monitor and that of the active pixel area of the CMOS Image Sensor. To overcome these limitations, we designed a new input device that uses the face recognition as well as the speech recognition simultaneously. In the proposed system, the area of the monitor is partitioned into 'n' zones. The face recognition is performed using the web-camera, so that the mouse pointer follows the movement of the face of the user in a particular zone. The user can switch the zone by speaking the name of the zone. The multimodal mouse is analyzed using the Keystroke Level Model and the initial experiments was performed to evaluate the feasibility and the performance of the proposed system.

• International Journal of Contents
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• v.16 no.1
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• pp.75-86
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• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.517-523
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• 2010

In this paper, we proposed an algorithm to detect aggressive driving status by analysing six kinds of driving patterns, which was achieved by comparing for the feature vectors using mahalanobis distance. The first step is to construct feature matrix of $6{\times}2$ size using frequency response of the time-series accelerometer data. Singular value decomposition makes it possible to find the dominant eigenvalue and its corresponding eigenvector. We use the eigenvector as the feature vector of the driving pattern. We conducted real experiments using three drivers to see the effects of recognition. Although there exists differences from individual drivers, we showed that driving patterns can be recognized with about 80% accuracy. Further research topics will include the development of aggressive driving warning system by improving the proposed technique and combining with post-processing of accelerometer signals.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.264-269
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• 2005

Advances in sensors, actuators, and computers and developments In information systems offer unprecedented opportunities to implement highly ambitious automation, control and decision strategies. There are also new challenges and demands for control and automation in modern industrial practices. There is a growing need for an active participation from the information systems in industrial, manufacturing and process industry environments because currently there are many control problems. This paper provides pattern recognition to the monitoring system for solvent manufacturing process and shows performance in real-time response with multiple input signals. Data is teamed by a multilayer feedforward network trained by error-backpropagation. The two kinds of test results show that the trained network has the ability to show the current system status with different input data sets.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.370-377
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• 2018

Focus level has been important mental state in user study. Cardiac response has been related to focus and less clarified. The study was to determine cardiac parameters for recognizing focus level. The sixty participants were asked to play shooting game designed to control two focus levels. Electrocardiogram was measured during task. The parameters of time domain and frequency domain were determined from ECG. As a result of independent t-test, RRI, SDNN, rMSSD and pNN50 of time domain indicator were statistically significant in recognizing focus level. LF, HF, lnLF and lnHF of frequency domain were observed to be significant indicator. The rule base for recognition has been developed by the combination of RRI, rMSSD and lnHF. The rule base has been verified from another sixty data samples. The recognition accuracy were 95%. This study proposed significant cardiac indicators for recognizing focus level. The results provides objective measurement of focus in user interaction design in the fields of contents industry and service design.

• Fire Science and Engineering
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• v.34 no.3
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• pp.35-42
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• 2020

The accurate prediction of fire detector activation time is required to ensure the reliability of fire modeling during the safety assessment of performance-based fire safety design. The main objective of this study is to determine the activation temperature and the response time index (RTI) of a fixed heat detector, which are the main input factors of a fixed-temperature heat detector applied to the fire dynamics simulator (FDS), a typical fire model. Therefore, a fire detector evaluator, which is a fire detector experimental apparatus, was applied, and 10 types of domestic fixed-temperature heat detectors were selected through a product recognition survey. It was found that there were significant differences in the activation temperature and RTI among the detectors. Additionally, the detector activation time of the FDS with the measured DB can be predicted more accurately. Finally, the DB of the activation temperature and RTI of the fixed-temperature heat detectors with reliability was provided.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.16-24
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• 2011

The vehicle electronic control system is being developed as the legal and social demand for ensuring driver's safety is rising. The various Driver Assistance Systems with various sensors such as radars, camera, and lasers are in practical use because of the falling price of hardware and the high performance of sensor and processer. In the preceding study of this research, the program was developed to recognize the experiment vehicle's driving lane and the cars nearby or approaching the experiment vehicle throughout the images taken by CCD camera. In addition, the 'dangerous driving analysis program' which is Vision System basis was developed to analyze the cause and consequence of dangerous driving. However, the Vision system developed in the previous studyhad poor recognition rate of lane and vehicles at the time of passing a tunnel, sunrise, or sunset. Therefore, through mounting the brightness response algorithm to the Vision System, the present study is aimed to analyze the causes of driver's dangerous driving clearly by improving the recognition rate of lane and vehicle, regardless of when and where it is.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.585-594
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• 2007

The back propagation algorithm took a long time to learn the input patterns and was difficult to train the additional or repeated learning patterns. So Aleksander proposed the binary neural network which could overcome the disadvantages of BP Network. But it had the limitation of repeated learning and was impossible to extract a generalized pattern. In this paper, we proposed a dynamic 3 dimensional Neuro System which was consisted of a learning network which was based on weightless neural network and a feedback module which could accumulate the characteristic. The proposed system was enable to train additional and repeated patterns. Also it could be produced a generalized pattern by putting a proper threshold into each learning-net's discriminator which was resulted from learning procedures. And then we reused the generalized pattern to elevate the recognition rate. In the last processing step to decide right category, we used maximum response detector. We experimented using the MNIST database of NIST and got 99.3% of right recognition rate for training data.