In this paper, the problem of identifying a time-varying nonlinear system in an adaptive way was considered, whereby the time-varying second-order Volterra series was employed to model the system and the filtered weighted least squares (FWLS) algorithm was utilized for the fast parameter tracking capability with low computational burden. Finally, the performance of the proposed approach was demonstrated by providing some computer simulation results.

This paper provides an observer-based $H_{\infty}$ controller design method for singular systems with and without time-varying delay by just one LMI condition. The sufficient condition for the existence of controller and the controller design method are presented by perfect LMI (linear matrix inequality) approach. The design procedure involves solving an LMI. The observer-based $H_{\infty}$ controller in the existing results can be constructed from the coupled two or more conditions while the proposed controller design method can be obtained from an LMI condition, which can be solved efficiently by convex optimization. Since the obtained condition can be expressed as an LMI form, all variables including feedback gain and observer gain can be calculated simultaneously by Schur complement and changes of variables. An example is given to illustrate the results.

Recently, Datta at al. [1] have developed a metDattad of obtaining the complete set of stabilizing PI, PID controllers for a given LTI system, in which tDattase are determined by solving a set of linear inequalities parameterized by the proportional(P) gain. In this paper, we provide a note about Dattaw Datta's idea can be extended to the problem of finding all stabilizing PD controllers and about an improved metDattad that allows us to calculate the admissible range of P gain more rigorously. An illustrative example is given.

In this paper, we propose a novel stability criterion and a guideline of controller design for switched linear systems. Unlike existing criterions such as Lie algebraic method and multiple Lyapunov functions method, the proposed criterion can be applied to each individual system without considering an overall system. By applying the proposed criterion to each individual system separately, a state feedback controller can be easily designed. Stability of the overall system is proved by developing a rule to determine non-increasing Lyapunov functions recursively at each switching instant. An illustrative example is given.

The flexible AC transmissions system (FACTS) is the underpinning concept upon which are based promising means to avoid effectively power flow bottlenecks and ways to extend the loadability of existing power transmission networks. This paper proposes a method by which the optimal locations of the FACTS to be installed in power system under cost function. The optimal solution of this type of problem requires large scale nonlinear optimization techniques. We used Lagrange multipliers to solve a nonlinear equation with equality and ineaquality constraints. Case studies on the standard IEEE 14 bus system show that the method can be implemented successfully and that it is effective for determining the optimal location of the FACTS.

This paper considers pulse width modulation (PWM) methods which are used in 3-phase brushless DC motor controller. Due to many disadvantages of bipolar PWM method, unipolar PWM method is mostly used in industrial field. In constant speed control application, the unipolar PWM method shows a good performance of speed control. But in the wide range of speed control application, it shows a poor performance especially when deceleration is needed. So we propose hybrid PWM method that utilizes two PWM methods according to the sign of speed controller output. The simulation and experimental result shows that the proposed method improves a speed control performance of the brushless DC motor which is applied to industrial sewing machines.

In active noise control (ANC) system, the convergence behavior of the Filtered- X Least Mean Square (FXLMS) algorithm may be affected by nonlinear distortion in the secondary path as in the power amplifiers (e.g., saturation), loudspeakers and transducers. This distortion may yields degrading the error reduction performance of the ANC systems. In this paper, the authors of this paper propose a more improved and stable FXLMS algorithm to compensate for the undesirable nonlinearity of the secondary-path, whereby the third-order Volterra model was employed for the identification of the nonlinear secondary-path. In particular, the proposed approach was based on the modification of the conventional FXLMS algorithm. Finally, the simulation results showed that the proposed approach yields better convergence property and more stable performance in the ANC systems.

The sliding mode control law provides a robust solution for general control problems. Most real systems which use a portable hard disk drive have to overcome disturbances and model uncertainties for proper operation. The chattering effect caused from unexpected oscillation can make the system be unstable. Therefore, we propose a robust control algorithm for the nonlinear second order systems with model uncertainties and disturbances. The proposed algorithm is designed following a sliding mode and observer based control. Thus the proposed algorithm has more expanded bounded region of control. Simulation results show the robustness of the proposed controller.

Reliability is an important issue on the digital reactor protection system. This paper presents a Quantitative reliability evaluation method to find out an improvement effect of availability for the digital control module with a fault detection function. It is a reliability evaluation model which considers only the electronics parts ocurring a spurious reactor trip by the FMEA(Failure Mode Effect Analysis). Applying the previous and present methods to the reactor protection system, the availability factors are evaluated and compared.

To meet an increasing demand for high performance in gun dynamic plant, both a precise and a fast response positioning are strongly required for the gun servomechanism control. A mode switching control(MSC) system, which includes a fine stabilizing controller, fast positioning one and a switching function, is widely used to meet this requirement. Stabilization is performed through PID controller, while proximate time optimal servo(PTOS) is used for target designation. Because gun dynamic have large damping comparing to acceleration, PTOS algorithm with damping is newly derived. This paper adopts the initial value compensation method that improve the transient response after switching. Some simulation results are given to show the effectiveness of our scheme.

An $H_2$ servo controller is proposed for networked control systems. The network-induced delay is assumed to be time-varying and vary in the known range. The proposed controller guarantees stability and $H_2$ performance for all time-varying delay in the known range. The proposed controller is verified using a simple networked motor control system.

This paper is concerned with attitude estimation using low cost, small-sized accelerometers and gyroscopes. A two step extended Kalman filter is proposed, which adaptively compensates external acceleration. External acceleration is the main source of estimation error. In the proposed filter, direction of external acceleration is estimated. According to the estimated direction, the accelerometer measurement covariance matrix of the two step extended Kalman filter is adjusted. The proposed algorithm is verified through experiments.

본 논문에서는 이동로봇이 임의의 선행물체를 추종할 때 진행 경로상에 이동장애물이 진입하는 경우 이 장애물을 효과적으로 회피할 수 있는 방법을 제시한다 초음파 센서를 이용하여 이동로봇의 진행경로에 진입하는 이동장애물에 대한 거리 정보와 방향각(Heading Angle)을 구할 수 있다. 이동로봇의 본체 주위에 배치된 16개의 초음파 센서를 이용하여 이동로봇의 전면, 후면 및 측면의 데이터를 얻을 수 있으며 이 정보를 퍼지제어기의 입력으로 사용한다 퍼지제어기는 이러한 입력정보와 제안된 규칙 베이스를 이용하여 이동로봇의 진행방향과 속도를 결정한다. 본 논문에서 제안한 퍼지제어기를 이용한 시뮬레이션을 통해 이동장애물에 대한 효과적인 충돌회피가 수행됨을 보인다.

In this correspondence, an new approach to design a fuzzy controller for system with uncertain output backlash to have good tracking performance is presented. Without using a compensation mechanism or backlash inverse, the fuzzy control mechanism is designed to implicitly compensate the delay effect arising from an uncertain output backlash and to make the output backlash stable without limit cycles. The proposed method designs a model-based fuzzy controller for a one-input one-output linear plant with output backlash. The effectiveness of the designed fuzzy controller is illustrated by the simulation.

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and the floor decreases suddenly, the robot has slip state. First of all, this paper models adhesion characteristics and slip in wheeled robot. Secondly, the paper proposes estimation method of adhesion force coefficient according to slip velocity. In oder to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. The paper proposes an anti-slip control system based on an ordinary disturbance observer, that is, the anti-slip control is achieved by reducing the driving torque enough to give maximum adhesion force coefficient. These procedure is implemented using a Pioneer 2-DXE parameter.

This paper deals with speed control of AC servo motor using a Adaptive fuzzy high gain observer. In this parer, the gain of the observer is properly set up using the fuzzy control and adaptive high gain observer that have a superior transient characteristic and is easy to implement compared the existing method is designed. In order to verify the performance of the Adaptive fuzzy high gain observer which is proposed in this paper, it is compared estimate performance of High-gain Observer and Adaptive High Gain Observer with the computer simulation. Effectiveness of the proposed high gain observer is proved from the experiment to compare the case with a speed sensor to the case with Adaptive fuzzy high gain observer in the speed control of AC servo motor.

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm is based on EDS (Euclidean Direction Search) algorithm. Generally LMS algorithm has a much slower rate of convergence, but its low computational complexity and robustness make it a representative method of adaptive beamforming. Although the RLS algorithm is known for its fast convergence to the optimal Wiener solution, it still suffers from high computational complexity and poor performance. The proposed EDS algorithm has a rapid convergence better than LMS algorithm, and has a computational more simple complexity than RLS algorithm. In this paper we compared the efficiency of the EDS algorithm with a standard LMS algorithm.

Researches about scheduling distributed real-time systems have some weak points, not scheduling both sporadic and periodic tasks and messages or being unable to guaranteeing the end-to-end constraints due to omitting precedence relations between sporadic tasks. This paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system. It is shown that existing scheduling methods such as Rate Monotonic scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints. So this paper proposes an end-to-end laxity-based priority assignment algorithm which considers the practical laxity of a task and allocates a proper priority to a task.

P2P Systems have grown dramatically in recent years. Now many P2P systems have developed and been confronted by P2P technical challenges. We should consider how to efficiently locate desired resources. In this paper we integrated the existing pure P2P and hybrid P2P model. We try to keep roles of super peer in hybrid and concurrently use pure P2P model for searching resource. In order to improve the existing search mechanism, we present contents-based classification mechanism. Proposed system have the following features. This can forward only query to best peer using RI. Second, it is self-organization. A peer can reconfigure network that it can communicate directly with based on best peer. Third, peers can cluster each other through contents-based classification.

Change of state of Channel between two wireless terminals which is caused by noise and multiple environmental conditions for happens frequently from the Wireles Network. So, When it is like that planning a wireless network protocol or performance analysis, it follows to change of state of time-varying channel and packet the analysis against a transmission efficiency is necessary. In this paper, analyzes transmission time of a packet and a packet in a time-varying and packet based Wireless Network. To reflecte the feature of the time-varying channel, we use a Signal Flow Graph model. From the model the mean of transmission time and the mean of queue length of the packet are analyzed in terms of the packet distribution function, the packet transmission service time, and the PER of the time-varying channel.

In this paper we develop an adaptive interface between video compression and transission protocols to handle QoS fluctuations that are common to mobile communication systems. We consider various generic design alternatives for QoS adaptation and identify 'QoS negotiation' as the most promissing. This method gives the best possibilities to obtain system-wide efficiency. To handle the indued system complexity we apply a design philosophy (called ARC) that separates implementation dependencies by introducing QoS interfaces between system modules. In the ARC phlosophy the implementation details are hidden in the subsystems. To assure efficient adaptation, the QoS must be negotiated between modules. We select the QoS parameters that are both necessary and sufficient for efficient negotiation between the video encoder and protocol modules. We describe the relation between the QoS parameters at the interface and the internal parameters of common video coding methods and protocol elements. Furthermore, we describe a negotiation procedure that allows a system-wide optimum to emerge.

Recently many peoples served multimedia data from Internet. But characteristic of multimedia-object about that effect on weight and transport-time causes Streaming Application is restricted to high-quality-service. This research propose the Quality-of-service(QoS) supporting for Home Gateway that behaving Routing and media platform equipment, using CBQ Scheduling scheme. The QoS Supporting for Multimeda Service that using general Rouging policy is difficult because media platform locate in Home Gateway. Therefore this research propose Routing mechanism to QoS support of media platform located in Gateway using TCP based CBQ Control.

현재 주로 사용되는 네트웍 침입 탐지 기법은, 사람에 의해 분석되고 룰의 형태로 저장된 침입 시그너쳐를 기반으로 침입을 판별하는 것이다. 이러한 방법은 아직 알려지지 않은 침입에 대해 무력하다는 한계를 가진다. 이에 본 연구에서는 사람의 분석과 지식에 의존하지 않는 방법을 제안하여 그러한 한계를 극복하고자 하였다. 침입은 호스트의 컴퓨팅과 네트워킹 자원을 사용할 수 없게 되는 것이라고 볼 때, 네트웍 트래픽과 관련하여 호스트의 자원 사용 상태가 어떻게 변화하는지 미리 알 수 있다면, 해당 침입에 대한 사전지식 없이도 위험에 대비할 수 있다. 본 논문에서는 자원의 가용성 측면에서 호스트 상태를 설명하는 모델을 설계하여, 이 모델이 네트웍 트래픽의 진행에 따라 변화하는 추이를 예측하는 데 사통될 수 있도록 하였다.

Because robot hardware architecture generally is consisted of a few sensors and motors connected to the central processing unit, this type of structure is led to time consuming and unreliable system. For analysis, one of the fundamental difficulties in real-time system is how to be bounded the time behavior of the system. When a distributed control network controls the robot, with a central computing hub that sets the goals for the robot, processes the sensor information and provides coordination targets for the joints. If the distributed system supposed to be connected to a control network, the joints have their own control processors that act in groups to maintain global stability, while also operating individually to provide local motor control. We try to analyze the architecture of network-based humanoid robot's leg part and deal with its application using the CAN(Controller Area Network) protocol.

Personal robot consist of various modules that have independent functions. Because personal robot has requirement that support various construction for user's tendency. Therefore, Middleware mechanism at support not only personal robot's main functional element but also embedded modules functional elements is required. Each module have various heterogeneous network interfaces and variable services and variables. Therefore, Middleware must support these various network interfaces. This paper, pointed in Controller Area Network(CAN) inreface that usually used in embedded system for control. For connect various heterogeneous network interfaces (Ethernet, RS232 etc..), it is necessary to modify bagic CAN frame format. And also make some kind of BUS topology for CAN network.

Personal Robot System being developed is designed to module-based system architecture for supporting internal devices have variable system platforms, environments, networks. For supporting development environment, integrating remote services, managing the interoperation among internal modules on this system design, a well-designed object oriented middleware is needed significantly. There are already some middlwares like DCOM, CORBA, UPnP, JINI, OSGi, etc. But they have some limitations to applying to Personal Robot in variable side view. We are researching for a suitable design scheme to require low system resources, to guarantee realtime services as possible, and to implement easily. In this paper, we suggest a middleware architecture have goals that are simple, light, and object oriented, so that can be used at diversity devices in Personal Robot System.

Personal Robot System in developing, have a module architecture, each module are connected through variety network system like ethernet, WLAN (802.11), IEEE 1394 (firewire), bluetooth, CAN, or RS-232C. In developing personal robot system. We think that the key of robot performance is interoperablity among modules. Each network protocol are well connected in the view of network system for the interoperability. So we make a bridging architecture that can routing converting, and transporting packets with matching each network's properties. Furthermore, we suggest a advanced design scheme for realtime / non-realtime and control signal (short, requiring hard-realtime) / multimedia data (large, requiring soft-realtime).

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult to the PID gains suitably lots of researches have been reported with respect to turning schemes of PID gains. A Neural Network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal is convergence speed progress about applied gain of PID controller using the neural networks.

We become an industry information society which is advanced to the altitude with the today. The information to be loading various goods each other together at a circumstance environment is increasing extremely. The restriction recognizes the data of many Quantity and it follows because the human deals the task to classify. The development of a mathematical formulation for solving a problem like this is often very difficult. But Artificial intelligent systems such as neural networks have been successfully applied to solving complex problems in the area of pattern recognition and classification. So, in this paper a neural network approach is used to recognize and classification problem was broken into two steps. The first step consist of using a neural network to recognize the existence of purpose pattern. The second step consist of a neural network to classify the kind of the first step pattern. The neural network leaning algorithm is to use error back-propagation algorithm and to find the weight and the bias of optimum. Finally two step simulation are presented showing the efficacy of using neural networks for purpose recognition and classification.

This paper estimates Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter ${\rho}$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter estimate criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one.

Linear Programming(LP) is the term used for defining a wide range of optimization problems in which the objective function to be minimized or maximized is linear in the unknown variables and the constraints are a combination of linear equalities and inequalities. LP problems occur in many real-life economic situations where profits are to be maximized or costs minimized with constraint limits on resources. While the simplex method introduced in a later reference can be used for hand solution of LP problems, computer use becomes necessary even for a small number of variables. Problems involving diet decisions, transportation, production and manufacturing, product mix, engineering limit analysis in design, airline scheduling, and so on are solved using computers. This technique is called Sequential Linear Programming (SLP). This paper describes LP's problems and solves a LP's problems using the neural networks.

Finger language is a typical tool for deaf persons. But learning the finger language for non-handicapped persons is very difficult. To overcome these difficulties, a new communication method using visual function is developed recently. Even though the developed system uses the visual function, it needs expensive equipments such as camera and computer. To be used in the real environments, the cost of equipments is a critical factor. If the recognition system for the finger language can be developed with low price equipments, the system can be used in the notebook or cellular phone. The image captured by PC camera was processed by preprocessing algorithm. To recognize the finger language, the resulting image was divide into $5{\times}5$ sections. The recognition system uses a similarity method and position information. The simulation results shows the effectiveness of the proposed algorithm.

In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on size, angle, and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value(255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking parameters.

Automatic license plate recognition (LPR) is one of the critical techniques of the intelligent transportation system (ITS), in which license plate location plays an important role. In this paper, through surveying the international existing techniques, a new method for locating license plate is proposed: utilize row scan method to locate up and down boundary of the plate; and based on the location of up and down boundary, take advantage of the feature of plate area to locate left and right boundary of the plate. The tests of using the proposed algorithms have been conducted. The experimental results show that the proposed approaches are reasonable and accurate.

Histogram Equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. In this paper, We propose the advanced contrast enhancement method using genetic algorithm. We propose a novel objective criterion for enhancement, and attempt finding the best image according to the respective criterion. Due to the high complexity of the enhancement criterion proposed, we employ a Genetic Algorithm. We compared our method with other enhancement techniques, like Global Histogram Equalization and Partially Overlapped Sub-Block Histogram Equalization(POSHE).

Biometrics consist of technologies that support automatic identification or verification of identity based on behavioral or physical traits. Biometrics can authenticate identities since they measure unique individual characteristics including fingerprints, hand geometry, iris, hand vascular patterns and facial characteristics. we review the state of the hand vascular patterns identification technology and compare other competitive authentication technologies such as cryptography, electronic signature and PKI.

Biometrics are best defined as measurable physiological and behavioral characteristics that can be utilized to verify the identity of an individual. Biometric technologies will continue to improve, becoming even more accurate and reliable as technology evolves. In this paper, we review the state of the hand vascular patterns identification technology and analyse the opportunities and threats of the technology in the markets.

Wearable input device that can make free-space typewriting possible is introduced. We named this device as $SCURRY^{TM}$. To measure the angular velocity of hand and the acceleration rates at the ends of fingers, we buried MEMS inertial sensors in this keyboard. We processed sensor signals to get the information on hand movement and finger-click motion. With this signal processing, apparent finger movements were depicted over the virtual keyboard shown on output device of a target computing system. In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger clicking of $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click part, and cross-talk avoidance part. The experiments were conducted to verify the effectiveness and efficiency of the proposed algorithms.

Recently, we are getting to interest in a user friendly machine. The emotion is one of most important conditions to be familiar with people. The machine uses sound or image to express or recognize the emotion. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.

As e-mail is becoming increasingly important in every day life activity, mail users spend more and more time organizing and classifying the e-mails they receive into folder. Many existing recommendation systems or text classification are mostly focused on recommending the products for the commercial purposes or web documents. So this study aims to apply these application to e-mail more necessary to users. This paper suggests a dynamic recommendation agent system based on Rule Filtering Component recommending the relevant category to enable users directly to manage the optimum classification when a new e-mail is received as the effective method for E-Mail Management. Moreover we try to improve the accuracy as eliminating the limits of misclassification that can be key in classifying e-mails by category. While the existing Bayesian Learning Algorithm mostly uses the fixed threshold, we prove to improve the satisfaction of users as increasing the accuracy by changing the fixed threshold to the dynamic threshold. We designed main modules by rule filtering component for enhanced scalability and reusability of our system.

The advanced technology called Telematics appeared with the development of automobile industries and IT technologies. In Telematics it is important to offer good quality information to the car which loads the terminal, so in this paper, for this, we propose the intelligent information service method using artificial intelligence(A. I.). In this paper, through the concept of multi-agent, we represent Telematics system and show the interaction between information service center and a terminal for smooth information service. Finally, we mention the way that Telematics should persue for the enhancement of information service.

Emotion recognition between human and human is done compositely using various features that are face, voice, gesture and etc. Among them, it is a face that emotion expression is revealed the most definitely. Human expresses and recognizes a emotion using complex and various features of the face. This paper proposes hybrid feature extraction for emotions recognition from facial expression. Hybrid feature extraction imitates emotion recognition system of human by combination of geometrical feature based extraction and color distributed histogram. That is, it can robustly perform emotion recognition by extracting many features of facial expression.

In this paper, a new method which is based on mathematics is proposed for the obstacle-avoidance and path-planning (OAPP) of robotics in unknown environment. The robot just knows the start point and the goal point. The robot is represented by a circle(not a point) whose radius is one. After being sensed, the obstacles are represented by some mathematic functions and when avoiding the obstacles, the robot path will be generated autonomously. Along this path, the robot can get the goal point at last. The simulation results show that the proposed method works very well.

This paper mainly deals with the dynamic walking of a biped robot. At first, in order to walk in various environments, it is desirable to adapt to such ground conditions with a suitable foot motion, and maintain the stability of the robot by a smooth hip motion. A method to plan a walking pattern consisting of a foot trajectory and a hip trajectory is presented. The effectiveness of the proposed method is illustrated by simulation results. Secondly, the paper brings forward a balance control technique based on off-line walking pattern with real-time modification. At last, the concept of Zero Moment Point (ZMP) is used to evaluate dynamic stability.

This paper presents an algorithm in which a feature map is built and localization of a mobile robot is carried out for indoor environments. The algorithm proposes an approach which extracts scale-invariant features of natural landmarks from a pair of stereo images. The feature map is built using these features and updated by merging new landmarks into the map and removing transient landmarks over time. And the position of the robot in the map is estimated by comparing with the map in a database by means of an Extended Kalman filter. This algorithm is implemented and tested using a Pioneer 2-DXE and preliminary results are presented in this paper.

It is known that Global Positioning System(GPS) is the most efficient navigation system because it provides precise position information on the all areas of Earth regardless of metrology. Until now, the size of GPS receivers has become smaller and the performance of receivers has become higher. So receivers provide the position information of not only static system but also dynamic system. Usually, users make similar movement trajectory according to their life pattern and it is possible to build up efficient database by collecting only the repeated users' position. Because position information calculated by the receiver is erroneous about 10-30m within 5% error tolerance, the position information is oscillated even on the same area. In this paper, we propose the system that can estimate whether users are out of trajectory or in dangerous situation by soft-computing method.

Although most of the people have studied English for a long time, their English conversation capability is low. When we provide them portable conversational-type English learners by the application of computer and information process technology, such portable learners can be used to enhance their English conversation capability by their conventional conversation exercises. The core technology to develop such learner is the development of a voice recognition and synthesis module under an embedded environment. This paper deals with voice recognition and synthesis, prototype of the learner module using a DSP(Digital Signal Processing) chip for voice processing, voice playback function, flash memory file system, PC download function using USB ports, English conversation text function by the use of SMC(Smart Media Card) flash memory, LCD display function, MP3 music listening function, etc. Application areas of the prototype equipped with such various functions are vast, i.e. portable language learners, amusement devices, kids toy, control by voice, security by the use of voice, etc.

The battery charge/discharge process, the final step of the secondary battery production process, requires real-time precision controls for improving both lifetime and performance of the battery cell. In this paper, we present embedded system design for precision control of the secondary battery charge/discharge production process using low power embedded processor based on embedded linux. This system receive charge/discharge command from the main server through ethernet. Compared to existing charge/discharge control system, our design makes low cost and precision control system possible.

In this paper, we design the memory tester chip playing an important role in the memory tester as central parts. Memory tester has the sixteen inner instructions to control the test sequence and the address and data signals to DUT. These instructions are saved in memory with each block such as sequencer and pattern generator. Sequencer controls the test sequence according to instructions saved in the memory. And Pattern generator generates the address and data signals according to instructions saved in the memory, too. We can use these chips for various functional test of memory.

The patent analysis of GPS technologies is performed by using a patent mapping method. The number of U.S.,Japanese and Korean patent applications are 1,819, 1,715 and 1,277 cases respectively. U.S and Japanese patents are mainly composed of hardware technologies. But, Korean patents are mainly composed of service technologies.