• Journal of Information Technology Services
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• v.11 no.sup
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• pp.165-176
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• 2012

Context-Awareness system provides an appropriate service to user by recognizing situation from surrounding environment. There are many successful studies on this framework, but still has some limitations. In this paper, we are describing a context-awareness middleware that can enhance the limitation of the previous approaches. We first defined a new concept of context-awareness environment as a social intelligence. This concept implies that intelligent objects can make relationships, can aware of situation from surrounding environment, and can collaborate to accomplish a given task. The significance of the study is as follows. First, the system is capable of multi context-awareness since it is designed with a structure that supports multiple lines of reasoning. Second, the system is capable of context planning by adapting AI planning mechanism. Third, the system is capable of making the intelligent objects as a group for collaboration, and provides adaptive service to user. We have developed a prototype of the system and tested with a virtual scenario.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.420-428
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• 2016

In this paper, we investigate the scheduling and power allocation for coordinated multi-point transmission in downlink long term evolution advanced (LTE-A) systems, where orthogonal frequency division multiple-access is used. The proposed scheme jointly optimizes user selection, power allocation, and modulation and coding scheme (MCS) selection to maximize the weighted sum throughput with fairness consideration. Considering practical constraints in LTE-A systems, the MCSs for the resource blocks assigned to the same user need to be the same. Since the optimization problem is a combinatorial and non-convex one with high complexity, a low-complexity algorithm is proposed by separating the user selection and power allocation into two subproblems. To further simplify the optimization problem for power allocation, the instantaneous signal-to-interference-plus-noise ratio (SINR) and the average SINR are adopted to allocate power in a single cell and multiple coordinated cells, respectively. Simulation results show that the proposed scheme can improve the average system throughput and the cell-edge user throughput significantly compared with the existing schemes with limited feedback.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.33-43
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• 2022

In this paper, we propose an ensemble model facilitated by multi-channel palm images with attention U-Net models and pretrained convolutional neural networks (CNNs) for establishing a contactless palm-based user identification system using conventional inexpensive camera sensors. Attention U-Net models are used to extract the areas of interest including hands (i.e., with fingers), palms (i.e., without fingers) and palm lines, which are combined to generate three channels being ped into the ensemble classifier. Then, the proposed palm information-based user identification system predicts the class using the classifier ensemble with three outperforming pre-trained CNN models. The proposed model demonstrates that the proposed model could achieve the classification accuracy, precision, recall, F1-score of 98.60%, 98.61%, 98.61%, 98.61% respectively, which indicate that the proposed model is effective even though we are using very cheap and inexpensive image sensors. We believe that in this COVID-19 pandemic circumstances, the proposed palm-based contactless user identification system can be an alternative, with high safety and reliability, compared with currently overwhelming contact-based systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3A
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• pp.172-178
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• 2012

This paper studies the application of a fuzzy-ARTMAP (FAM) neural network to multi-user detector (MUD) for direct sequence (DS)-code division multiple access (CDMA) system. This method shows new solution for solving the problems, such as complexity and long training, which is found when implementing the previously developed neural-basis MUDs. The proposed FAM based MUD is fast and easy to train and includes capabilities not found in other neural network approaches; a small number of parameters, no requirements for the choice of initial weights, automatic increase of hidden units, no risk of getting trapped in local minima, and the capabilities of adding new data without retraining previously trained data. In simulation studies, binary signals were generated at random in a linear channel with Gaussian noise. The performance of FAM based MUD is compared with other neural net based MUDs in terms of the bit error rate.

• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.299-311
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• 2005

This article introduces developing trends of an "Ubiquitous Interface" as an access method for use of various network resources, such as public wireless networks and un-licensed wireless networks in ubiquitous sensor network environments, without troublesome settings or operations by users. "Ubiquitous Interface" is include a relatively wide sense meaning not only physical interface of specified device or between processors, but anything method for access USN. These "Ubiquitous Interface" able to provide seamless services that adapt autonomously to the user's movements and changes in the state of wireless resources. Recently, strongly recommended candidates are RFID, NFC, Multi-mode mobile terminal, Wearable computer and OSGi for integrated digital home networking system as a future ubiquitous interface. These candidates are have to have flexibility and multiple physical communication channel for seamless service hand over and serve easy connection at huge USN to user. And, must have flexible software structure and multi-functional middleware. Consequently, for more enhance performance of an ubiquitous interface and developing, need more structured and integrated future plan.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3089-3091
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• 1999

To control IWR-III Biped Waking Robot, those complex modules are necessary that concurrent control multi-axes servo motors, PID & Feedforward gain tuning, initial value calibration, display current status of system, user interface for emergency safety and three-dimensional rendering graphic visualization. It is developed for various-type gait $data^{[1]}$ and for control modes (i.e open/closed loop and pulse/velocity/torque control) that Integrated Control Enviroment with GUI( Graphic User Interface) consist of time-buffered control part using MMC (Multi-Motion Controller) and 3D simulation part using DirectX graphic library.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.261-271
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• 2009

Due to the recent rise of a need for 3 dimensional geospatial information on urban areas, general interest in aerial multi-view cameras has been on an increase. The conventional geospatial information system depends solely upon vertical images, while the multi-view camera is capable of taking both vertical and oblique images taken from multiple directions, thus making it easier for the user to interpret the object. Through our research we developed a prototype of a multi-view camera system that includes a camera system, GPS/INS, a flight management system, and a control system. We also studied and experimented with the camera viewing angles, the synchronization of image capture, the exposure delay, the data storage that must be considered for the development of the multi-view camera system.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.21-26
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• 2009

A sensor system capable of automatically recognize activities would allow many potential Ubiquitous applications. This paper presents a new system for recognizing the activities of daily living(ADL) like walking, running, standing, sitting, lying etc. The system based on the state-dependent motion analysis using Tri-Accelerometer and Zigbee tag. Two accelerometers are used for the classification of body and hand activities. Classification of the environment and instrumental activities is performed based on the hand interaction with an object ID using.

• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.428-438
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• 2013

The requirement for high performance visualization of engineering analysis of digital products is increasing since the size of the current analysis problems is more and more complex, which needs high-performance codes as well as high performance computing systems. On the other hand, different companies or customers do not have all the facilities or have difficulties in accessing those computing resources. In this paper, we present a multi-view supporting VR/AR system for providing supercomputing-based engineering analysis services. The proposed system is designed to provide different views supporting VR/AR visualization services depending on the requirement of the customers. It provides a sophisticated VR rendering directly dependent on a supercomputing resource as well as a remotely accessible AR visualization. By providing multi-view centric analysis services, the proposed system can be more easily applied to various customers requiring different levels of high performance computing resources. We will show the scalability and vision of the proposed approach by demonstrating illustrative examples with different levels of complexity.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.962-971
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• 2013

In this paper, we propose a method to infer the user's behavior and situation through collected data from multi-sensor equipped with a smart clothing and it was implemented as a smart-phone App. This smart-clothes is able to monitor wearer users' health condition and activity levels through the gyro, temp and acceleration sensor. Sensed vital signs are transmitted to a bluetooth-enabled smart-phone in the smart-clothes. Thus, users are able to have real time information about their user condition, including activities level on the smart-application. User context reasoning and behavior determine is very difficult using multi-sensor depending on the measured value of the sensor varies from environmental noise. So, the reasoning and the digital filter algorithms to determine user behavior reducing noise and are required. In this paper, we used Multi-black Filter and SVM processing behavior for 3-axis value as a representative value of one.