• Journal of Information Processing Systems
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• v.14 no.1
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• pp.150-161
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• 2018

We propose a novel deep neural network model for detecting human activities in untrimmed videos. The process of human activity detection in a video involves two steps: a step to extract features that are effective in recognizing human activities in a long untrimmed video, followed by a step to detect human activities from those extracted features. To extract the rich features from video segments that could express unique patterns for each activity, we employ two different convolutional neural network models, C3D and I-ResNet. For detecting human activities from the sequence of extracted feature vectors, we use BLSTM, a bi-directional recurrent neural network model. By conducting experiments with ActivityNet 200, a large-scale benchmark dataset, we show the high performance of the proposed DeepAct model.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.30.2-30
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• 2001

As the era of the human friendly robot looms, the intelligent autonomous mobile robots have obtained tremendous interests in recent years. The robots may be service robots for serving human or industrial robots for replacing human. For the coexistance with human, the robots must be able to feel and recognize three dimensional space that human live. In this paper, we propose three dimensional environmental modeling method based on a neural network technique called Growing Neural Gas Network. The purpose of this neural network is to generate a graphical structure which reflects the topology of the input space. Through this method, the robots´ surroundings are autonomously segmented ...

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.364-371
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• 2009

We analyzed romance of the three kingdoms written by Luo Guanzhong by using complex network to compare its properties with those of social network. The three kingdom network has a scale free and hierarchical network properties. Human-human interaction networks are dramatically changing in response to time and space. Due to lack of the dynamic interacting data, the researches only focus to analysis for properties of the statical networks. The romance of the three kingdoms is a Chinese historical novel based upon events from the end of the Han Dynasty, the Three Kingdoms era of China, and the reunification of the land. There are over a thousand characters, over a three thousand human-human interactions, and the dynamic changed in human-human interactions in the historical novel. Here, we introduce that a possible method for analyzing about dynamic changing of the complex network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.998-1013
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• 2013

Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

• The Journal of Korean Medicine
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• v.32 no.1
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• pp.56-66
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• 2011

Background: This was a study to analyze Sanghanron through network theory, as the first attempt to construct network models for systems biomedicine in traditional Korean medicine. For this purpose, we investigated the network structure with priority given to two-node connections between symptoms and herbs of Taeyangbyung compilation in Sanghanron. Purpose: We had three goals in carrying out this study. First, to establish the minimum clinical grouping data sets for symptoms and herbs of Taeyangbyung compilation in Sanghanron. Second, to make index files for the obtained data sets. Third, to generate a network structure for systems biomedicine in this part, and analyze its relationship. Methods: Using MS office Excel and Netminer software, we constructed the minimum clinical grouping data sets and the network for systems biomedicine about symptoms and herbs of Taeyangbyung compilation in Sanghanron, and analyzed its relationship. Results: We established the minimum clinical grouping data sets for symptoms and herbs of Taeyangbyung compilation in Sanghanron, using MS Excel. We constructed a network to structurize our database through two-node connections of Netminer program, and analyzed its relationships. Conclusions: Further research on network model for systems biomedicine between symptoms and herbs for three Yang and three Um(Taeyang, Soyang, Yangmyung, Taeum, Soum, Gualum) disease compilation is necessary.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1421-1429
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• 2017

Human activity recognition has been studied using various sensors and algorithms. Human activity recognition can be divided into sensor based and vision based on the method. In this paper, we proposed an activity recognition system using acceleration sensor and gyroscope sensor in smartphone among sensor based methods. We used Deep Belief Network (DBN), which is one of the most popular deep learning methods, to improve an accuracy of human activity recognition. DBN uses the entire input set as a common input. However, because of the characteristics of different time window depending on the type of human activity, the RBMs, which is a component of DBN, are configured hierarchically by combining them from different time windows. As a result of applying to real data, The proposed human activity recognition system showed stable precision.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.109-112
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• 2006

This paper presents a dialogue interface using the dialogue management system as a method for controlling home appliances in Home Network Services. In order to realize this type of dialogue interface, we first investigated the user requirements for Home Network Services by analyzing the dialogues entered by users. Based on the analysis, we were able to extract 15 user intentions and 22 semantic components. In our study, example dialogues were collected from WOZ (Wizard-of-OZ) environment to implement a reasoning model for generating meaningful responses for example-based dialogue modeling technique. An overview of the Home Network Control System using proposed dialogue interface will be presented. Lastly, we will show that the Dialogue Management System trained with our collected dialogues behaves properly to achieve its task of controlling Home Network appliances by going through the steps of natural language understanding, response reasoning, response generation.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.850-855
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• 1991

In this paper, neural network-based compliance control of telerobot is presented, This is a method to learn the compliance of human behavior and control telerobot using learned compliance. The consistency of human behavior is checked using Lipschitz's condition. The neural compliance model is composed of a multi-layered neural network which mimics the compliant notion of the human operator. The effectiveness of proposed scheme ie verified by a simulation study.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2143-2147
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• 2005

Human-Robot interaction (HRI) has recently become one of the most important issues in the field of robotics. Understanding and predicting the intentions of human users is a major difficulty for robotic programs. In this paper we suggest an interaction method allows the robot to execute the human user's desires in an intelligent room-based domain, even when the user does not give a specific command for the action. To achieve this, we constructed a full system architecture of an intelligent room so that the following were present and sequentially interconnected: decision-making based on the Bayesian belief network, responding to human commands, and generating queries to remove ambiguities. The robot obtained all the necessary information from analyzing the user's condition and the environmental state of the room. This information is then used to evaluate the probabilities of the results coming from the output nodes of the Bayesian belief network, which is composed of the nodes that includes several states, and the causal relationships between them. Our study shows that the suggested system and proposed method would improve a robot's ability to understand human commands, intuit human desires, and predict human intentions resulting in a comfortable intelligent room for the human user.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2771-2773
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• 2005

In network human-robot interaction, human can access services of a robot system through the network The communication is done by interacting with the distributed sensors via voice, gestures or by using user network access device such as computer, PDA. The service organization and exploration is very important for this distributed system. In this paper we propose a new agent-based framework to integrate partners of this distributed system together and help users to explore the service effectively without complicated configuration. Our system consists of several robots. users and distributed sensors. These partners are connected in a decentralized but centralized control system using agent-based technology. Several experiments are conducted successfully using our framework The experiments show that this framework is good in term of increasing the availability of the system, reducing the time users and robots needs to connect to the network at the same time. The framework also provides some coordination methods for the human robot interaction system.