• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.1
• /
• pp.21-26
• /
• 2008

It was already realized at a current technological level of home network systems that the systems recognizes a user's simple order and carry out the order in the ubiquitous computing environment. However home is not a simple environment consisting into a large number of family members, so various order and situation would be needed accordingly. From now on we need to reach the technological level to infer that how is the user's behavior patterns and what kinds of service is the fittest to user who belong to the ubiquitous computing environment by using the result of the context interpreter. In this regards, active inferred-model needs to be suggested upgrading user's command into one step more higher level than the simple one adapting diversified feature. This study would like to suggest this active model recognizing context, which is user's environmental information applying basic network and inferring Context-based Service that user wants through the recognized result This study proposes a new method that can infer the user's desire in ubiquitous computing environment. First of all, we define a context as user's information of ubiquitous computing environment situation that user belongs to and we classify the context into 4W1H(Where, Who, When, What) formats. We construct Bayesian network and put the factor of context use as Bayesian network nodes. As a result, we can infer the user's behavior pattern and most proper service for user in the intelligent space from the probabilistic result of Bayesian network.

• Journal of Korea Multimedia Society
• /
• v.24 no.1
• /
• pp.75-94
• /
• 2021

The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1016-1019
• /
• 1996

This paper discribes automobile processes and introduction for process monitoring and control system for engine plant, truck automobile industries using the MES(Manufacturing Execution Systems) functions.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1797-1801
• /
• 2004

In this paper we show the hardware testbed and software simulator of multi function array radar (MFAR). The hardware MFAR is simple and flexible hardware to implement various radar beamforming and detecting algorithms. To overcome the limitation of hardware MFAR, the software simulator is proposed. User can simulate radar under the various environment conditions adjusting the parameter of simulator. User can set environment of radar, such as the location and velocity of target, jammer and the terrain clutter. The radar use various probing pulses and supports two operation mode, surveillance and tracking mode.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.2
• /
• pp.189-200
• /
• 2004

In this paper, we introduce a new soft computing technique that dwells on the ideas of combining fuzzy rules in a fuzzy system with polynomial neural networks (PNN). The PNN is a flexible neural architecture whose structure is developed through the modeling process. Unfortunately, the PNN has a fatal drawback in that it cannot be constructed for nonlinear systems with only a small amount of input variables. To overcome this limitation in the conventional PNN, we employed one of three principal soft computing components such as a fuzzy system. As such, a space of input variables is partitioned into several subspaces by the fuzzy system and these subspaces are utilized as new input variables to the PNN architecture. The proposed soft computing technique is achieved by merging the fuzzy system and the PNN into one unified framework. As a result, we can find a workable synergistic environment and the main characteristics of the two modeling techniques are harmonized. Thus, the proposed method alleviates the problems of PNN while providing superb performance. Identification results of the three-input nonlinear static function and nonlinear system with two inputs will be demonstrated to demonstrate the performance of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.7
• /
• pp.711-717
• /
• 2007

Location information will become increasingly important for future Pervasive Computing applications. Location tracking system of a moving device can be classified into two types of architectures: an active mobile architecture and a passive mobile architecture. In the former, a mobile device actively transmits signals for estimating distances to listeners. In the latter, a mobile device listens signals from beacons passively. Although the passive architecture such as Cricket location system is inexpensive, easy to set up, and safe, it is less precise than the active one. In this paper, we present a passive location system using Cricket Mote sensors which use RF and ultrasonic signals to estimate distances. In order to improve accuracy of the passive system, the transmission speed of ultrasound was compensated according to air temperature at the moment. Upper and lower bounds of a distance estimation were set up through measuring minimum and maximum distances that ultrasonic signal can reach to. Distance estimations beyond the upper and the lower bounds were filtered off as errors in our scheme. With collecting distance estimation data at various locations and comparing each distance estimation with real distance respectively, we proposed an equation to compensate the deviation at each point. Equations for proposed algorithm were derived to calculate relative coordinates of a moving device. At indoor and outdoor tests, average location error and average location tracking period were 3.5 cm and 0.5 second, respectively, which outperformed Cricket location system of MIT.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.10
• /
• pp.968-974
• /
• 2006

We are moving into the era of ubiquitous computing. Ubiquitous Sensor Network (USN) is a base of such computing paradigm, where recognizing the identification and the position of objects is important. For the object identification, RFID tags are commonly used. For the object positioning, use of sensors such as laser and ultrasonic scanners is popular. Recently, there have been a few attempts to apply RFID technology in robot localization by replacing the sensors with RFID readers to achieve simpler and unified USN settings. However, RFID does not provide enough sensing accuracy for some USN applications such as robot navigation, mainly because of its inaccuracy in distance measurements. In this paper, we describe our approach on achieving accurate navigation using RFID. We solely rely on RFID mechanism for the localization by providing coordinate information through RFID tag installed floors. With the accurate positional information stored in the RFID tag, we complement coordinate errors accumulated during the wheel based robot navigation. We especially focus on how to distribute RFID tags (tag pattern) and how many to place (tag granularity) on the RFID tag-floor. To determine efficient tag granularities and tag patterns, we developed a simulation program. We define the error in navigation and use it to compare the effectiveness of the navigation. We analyze the simulation results to determine the efficient granularities and tag arrangement patterns that can improve the effectiveness of RFID navigation in general.

• The Journal of Korea Robotics Society
• /
• v.5 no.3
• /
• pp.240-250
• /
• 2010

A URC, which is a Ubiquitous Robot Companion, provides services to users in ubiquitous computing environments and has advantage of simplifying robot's hardware and software by distributing the complicated functionality of robots to other system. In this paper, we propose SOWL, which is a software architecture for URC robots and a mixed word of SOMAR and CAWL. SOWL keeps the advantages of URC and it also has the loosely-coupled characteristics. Moreover it makes it easy to develop of URC robot software. The proposed architecture is composed of 4 layers: device software, robot software, robot application, and end user layer. Developers of the each layer is able to build software suitable for their requirements by combining software modules in the lower layer. SOWL consists of SOMAR and CAWL engine. SOMAR, which is a middleware for the execution of device software and robot software, is based on service-oriented architecture(SOA) for robot software. CAWL engine is a system to process CAWL which is a context-aware workflow language. SOWL is able to provide a layered architecture for the execution of a robot software. It also makes it possible for developers of the each layer to build module-based robot software.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.11
• /
• pp.1074-1081
• /
• 2007

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.5
• /
• pp.614-621
• /
• 1999

In this paper, the analytical appproaches are presented for jointly determining the profit-miximizing configuration of the fault-tolerance real time modular cell manufacturing system. The transient(time-dependent) analysis of Markovian models is firstly applied to modular cell manufacturing system from a performability viewpoint whose modeling advantage lies in its ability to express the performance that truly matters - the user's perception of it - as well as various performance measures compositely in the context of application. The modular cells are modeled with hybrid decomposition method and then availability measures such as instantaneous availability, interval availability, expected cumulative operational time are evaluated as special cases of performability. In addition to this evaluation, sensitivity analysis of the entire manufacturing system as well as each machining cell is performed, from which the time of a major repair policy and the optimal configuration among the alternative configurations of the system can be determined. Secondly, the recovery policies from the machine failures by computing the minimal number of redundant machines and also from the task failures by computing the minimum number of tasks equipped with detection schemes of task failure and reworked upon failure detection, to meet the timing requirements are optimized. Some numerical examples are presented to demonstrate the effectiveness of the work.