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This study proposes an intelligent tracking method based on the expectation maximisation approach. To obtain the consistent tracking performance, the observer should maintain contact with the target and continuously update its tracking data. Unfortunately, a significant problem arises from the uncertainty of the target motion. The reasons behind this uncertainty include losses, time-varying noises, external inputs, and others. Above all, a sharp manoeuvre by the arbitrary acceleration input mainly degrades the tracking performance. A variety of techniques were needed and studied to enhance performance levels. This study focuses on acceleration as the cause of the uncertainty and a consistent approximation of the acceleration, leading to highly efficient tracking performance. The EM makes it possible to separate the noise term from the acceleration inputs and the noise components. Finally, a manoeuvring submarine with three-dimensional coordinates is provided as an example to show the effectiveness of the proposed algorithm.

Most of robotic companies develop a control programming of multi-jointed robots, which spend too much time to manually adjust the moving functions of the robots. To solve this problem, we adapt the virtual prototyping (VP) to develop the control program of the robotic behaviors. For software engineers, in order for them to easily program this robot, we also apply metamodel mechanism to convert UML models with virtual prototyping model. We propose the automatic model transformation from the virtual prototyping model to UML models, which will then develop coding based on UML models. To prove our mechanism’s efficiency, we implement Robot to UML Translator (RUT) as our transformation rules with ATLAS transformational language. Lastly, we show experimental validation about the consistency of our proposed technique with an example of multi-joined robot prototype models.

Recently, a photovoltaic energy integrated monitoring system may happen a serious problem with a little error. After constructing the complete solar power monitoring system, this is, a kind of safety-critical system, it should consider how to completely validate it based on requirements of this system. For even code based test coverage in safety critical area, it must achieve 100% of Path and MC/DC coverage on dynamic analysis. To do this, we suggest to automatic test generation on Model Driven Approach to ensure 100% functional requirement coverage using minimal test cases. More important idea is to generate an image (of test case) with an image (of sequence diagram) based on automatic multimedia image translation processing, but not use an algorithmic method in the old fashion. Our approach is focusing on validating the dynamic behaviors of the safety system, which generate test cases based on sequence diagram, that is, use case scenario to design the dynamic behaviors of the solar power monitoring system. As a result, it can validate the safety critical system with minimal test cases.

Requirement-based testing (RBT) is widely known for the efficient testing in the limited resources. However RBT is difficult to generate automatic test cases; thus it needs complex methods. This paper suggests our automatic test case generation for all coverage (statement, condition, decision, condition/decision, modified condition/decision, and multiple condition coverage) based on the model-based testing. To do this, we extend the original control flow graph with multiple conditions for all condition related coverage, which is called multiple conditions control flow graph, and adapt a model transformation using metamodel mechanism for test case generation. As a result, our proposed method successfully applies to the prior test requirement.

In our domestic software industries, it is focused on such a high quality development/ testing process, maturity measurement, and so on. But the real industrial fields are still working on a code-centric development. Most of the existing legacy systems did not keep the design and highly increased the code complexity with more patching of the original codes. To solve this problem, we adopt a code visualization technique which is important to reduce the code complexity among modules. To do this, we suggest a tool chaining method based on the existing open source software tools, which extends NIPA's Software Visualization techniques applied to procedural languages. In addition, it should be refactored to fix bad couplings of the quality measurement indicators within the code visualization. As a result, we can apply reverse engineering to the legacy code, that is, from programming via model to architecture, and then make high quality software with this approach.

This paper presents a new method for tracking a zigzag maneuvering target by compensat- ing for the positional error of the target. The positional difference between the measured and predicted points is separated into acceleration and noise. Fuzzy c-means (FCM) clustering is utilized as an adap- tive method for noise separation. Approximating acceleration is determined by the membership func- tion of the FCM. The approximated acceleration is used to compensate for the tracking error. The pro- cedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

The effort to detect a target conflicts with the covertness in anti-submarine warfare. The underwater detection rate is extremely low and sound waves are the only detection method unlike the airborne operational environment. The data of an underwater target based on noise levels are more difficult to interpret when the acceleration inputs are included. Hence, the authors propose a complementary algorithm for the tracking problem in an active sonar system. The bearing-range data of the target yield the measurement residuals, and the residuals are used as inputs to the clustering method. The clustering method estimates the acceleration and the noise level. The estimates aid in positional compensation and enhance the tracking performance. The fuzzy c-means clustering is utilised for the clustering and maintains the filter sustainable. Finally, some examples are provided to show the effectiveness of the proposed method.

Today, it is very important issue to high quality of software issue on huge scale of code and time-to-market. In the industrial fields still developers focuses on Code based development. Therefore we try to consider two points of views 1) improving the general developer the bad development habit, and 2) maintenance without design, documentation and code visualization. To solve these problems, we need to make the code visualization of code. In this paper, we suggest how to visualize the inner structure of code, and also how to proceed improvement of quality with constructing the Tool-Chain for visualizing Java code's inner structure. For our practical case, we applied Object Code with NIPA's SW Visualization, and then reduced code complexity through quantitatively analyzing and visualizing code based on setting the basic module unit, the class of object oriented code.

Recently, in the photovoltaic energy integrated monitoring software system, it has more complex, and accordingly may be possible to occur more errors. In this industrial services, a small error can lead to a huge accident to make the power failures. To completely build this system, it should verify whether it is or not stability of software through measuring the full coverage with generating test cases in detail level based on a message sequence model. In this paper, we apply to verify a system stability of this monitoring system with our previous research such as the automatic test case generation based on UML 2.4.1 message-sequence diagram via cause-effect diagram. With this, we extract automatically test cases on coverage.

For safe software development on the solar integrated monitoring system, it is very important how to identify safe behaviors of the system behaviors. Therefore, it needs to test the system behaviors after the software development. To solve this problem, the existing studies have proposed the use case based test coverage analysis at all software development stages [1]. With this method, we identify the test cases based on priority of the system behaviors. In this paper, we proposes automatic test case extraction method based on state diagram among the use case-based test coverage extraction methods. That is, we can use state diagram for a system behaviors with which generates test cases to validate the system. We show an applicative case on the system behaviors of a solar integrated system with this approach.

This paper proposes a intelligent approach on range decision of figure of merit. Unknown range of the underwater target and the non-fixed signal excess make the uncertainty for the tracking process. Using the input data of signal excess related to the range, we establish the rule of the fuzzy set and the original data acquired by sonar can be transformed to the fuzzified data set. To reduce the error arisen from the unexpected data, we use the new data transformed in fuzzy set. The piecewise relations of the min value, max one, and the mean one are calculated. The three values are used for the expected range of the underwater target. By analysing the fluctuation of the data, we can expect the target’s position and the characteristics of the maneuvering. The examples are presented to show the performance and the effectiveness of the proposed method.

This study proposes a smart tracking model with multiple structures. To achieve optimal performance, an ideal tracking system should maintain contact with the target and constantly update its tracking data. One of the major problems to consider arises from the target motion uncertainty. Although the variance of the overall noise is time-varying and may reduce tracking efficiency, it is difficult to adaptively approximate this uncertainty. To solve these computational problems, a variety of techniques have been studied, and the adaptive interacting multiple model has shown the best result. However, predefined sub-models with different conditions for multiple models are required. Moreover, the acceleration intervals for different acceleration levels should be determined in advance. To alleviate these problems, the authors propose a multiple-structured smart tracking algorithm which properly separates the acceleration from the overall noise by fuzzy c-means clustering. The filter in the algorithm recognises the manoeuvring target as if it does not include the acceleration input, and precisely tracks the target with multiple structures. This study focuses on the acceleration causing the uncertainty and three-dimensional (3D) motion of the real target motion in the tracking problem. Finally, a 3D cruise missile example is provided to show the effectiveness of the proposed algorithm.

Software visualization shows to extract the architecture from source code. With software visualization, we can improve the software quality due to software modularization and also reconfiguration. To do this, we compose of parser, data analyzer, database management system, and visualizer like a tool-chain for realizing the software visualization. In this tool-chain, we develop the parser named xCodeParser that generate the OMG's Abstract Syntax Tree Metamodel (ASTM) for various language such as C, C++ or Java. In this paper, we propose the metamodel based XML databases to save the ASTM files into the repository. The proposed database is able to handle the data which organized metamodel based on XML database. Improving quality through realizing this visualization helps easily to develop high quality software, to increase reusability, and to reduce maintenance cost.

This paper presents an intelligent reduction method for external noise. The main idea comes from PSO-FCM (Particle Swam Optimization Fused fuzzy C-Means) clustering. The data of the target is transformed from the antenna coordinates to the vessel one and to the system coordinates. In the conversion, the overall noises hinder observer to get the exact position and velocity of the maneuvering target. While the filter is used for tracking system, unexpected acceleration becomes the main factor which makes the uncertainty. In this paper, the tracking efficiency is improved with the PSO-FCM and the compensation methodology. The acceleration is approximated from the external noise splitted by the proposed clustering method. After extracting the approximated acceleration, the rest in the noise is filtered by the filter and the compensation is added to after that. Proposed tracking method is applicable to the linear model and nonlinear one together. Also, it can do to the on-line system. Finally, some examples are provided to examine the reliability of the proposed method.

This paper presents the smart interacting multiple model (SIMM) using the concept of predicted point and maximum noise level. Maximum noise level means the largest value of the mere noises. We utilize the positional difference between measured point and predicted point as acceleration. Comparing this acceleration with the maximum noise level, we extract the acceleration to recognize the characteristics of the target. To estimate the acceleration, we propose an optional algorithm utilizing the proposed method and the Kalman filter (KF) selectively. Also, for increasing the effect of estimation, the weight given at each sub-filter of the interacting multiple model (IMM) structure is varying according to the rate of noise scale. All the procedures of the proposed algorithm can be implemented by an on-line system. Finally, an example is provided to show the effectiveness of the proposed algorithm.

This paper presents the intelligent tracking method for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. K-means clustering and TS fuzzy system are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by K-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. While calculating expected value, the non-linearity of the maneuvering target is recognized as linear one by dividing acceleration and the capability of Kalman filter is kept in the filtering process. The error for the non-linearity is compensated by approximated acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm. K ey W ords : TS fuzzy system, acceleration, noise, filtering, maneuvering target tracking

The small multi-jointed robots for most education are developed with the way of firmware. But the firmware may be very difficult to develop as gradually increasing throughputs and control routines. Due to limit of firmware we try to use on RTOS, but hard to adapt on the small multi-jointed robots. It would be hard to install RTOS into the small multi-jointed robots because of the size capacity of RTOS, and lack of libraries for control of the particular hardware. Moreover, even its RTOS with many functions causes its to make overheads scheduling, TCB (Task Control Block), and task states. Also to keep maintenance of RTOS, it is composed of components for the whole structure of my proposed RTOS. Additionally, We provided with libraries of servo motor and sensor control and developed RMS (Rate Montonic scheduler) to handle tasks on real time and reduce overheads. Therefore, It is possible to work the fixed priority and task preemptive way. We show one example of the multi-jointed robot installed with my proposed RTOS, which shows to obstacle avoidance and climbing up the slope.

The complicated embedded system for multi-tasking requires RTOS(real-time operating system). It uses the optimal OS and processor to each embedded system on the heterogeneous development environment. This paper is proposed to use UML profile of OS API and Processor Configuration, instead of cross-compiling for developing the heterogeneous embedded system. This reduces the development time and cost through generating the automatic source code with the profile information of each embedded system. We generate and port the code after modeling the two heterogeneous real time operating systems (brickOS and uC/OS-II) and the processors (Hitachi H8 and Intel PXA255) with our proposed profile of the heterogeneous embedded system.

This paper proposes a new approach on nonlinear maneuvering target tracking. In this paper, proposed algorithm is the Kalman filter based on the adaptive interactive multiple model using the concept of predicted impact point and utilize modified Kalman filter regarding the error between measurement position and predicted impact point. The unknown target acceleration is regarded as an additional process noise to the target model, and each sub-model is characterized in accordance with the valiance of the overall process noise which is obtained on the basis of each acceleration interval. To compensate the decreasing performance of Kalman filter in nonlinear maneuver, we construct optional algorithm to utilize proposed method or Kalman filter selectively. To effectively estimate the acceleration during the target maneuvering, the rapid increase of the noise scale is recognized as the acceleration to be used in maneuvering target`s movement equation. And a few examples are presented to show suggested algorithm`s executional potential.

In software testing, cause-effect graph assures coverage criteria of 100% functional requirements with minimum test case. The existing test case generation from cause-effect graph implements the algorithmic approach. It has disadvantages to modify the entire program if the input model is different. In contrast, model transformation approach can flexibly implement with even a different input models. In the future, we need to study the method of automatic generation of test cases from UML Diagram. It is possible to generate the test case when mapping between cause-effect graph and UML diagram. In this paper, as a first research step, we propose the method to generate test cases from cause-effect graph based on model transformation. To implement the proposed method, we write the rules of model transformation with ATLAS Transformation Language (ATL), and execute the rules in development environment of Eclipse. The implemented tool of the proposed method can be easily extended by rewriting with the mapping rule between cause-effect graph and UML diagram. We just define the relationship between each models to generate the test case.

For the covertness in modern anti-submarine warfare (ASW), a sonar system has been evolved to the bi-static type. However, it is difficult to get the recognizable error coefficients at any time with clear mathematical definition for the sonar model. To resolve the dynamics accompanied with the error component, we should deal with heterogeneous, complementary fusion of information in order to enable robust target detection, classification, localization, and tracking. In the tracking point of view, we concentrate on the increment of tracking error occurred from the target's maneuvering owing to the acceleration. From the measurement residual, compensating acceleration by merging the filter with fuzzy c-means (FCM) clustering is proposed. Finally, a example is provided to show the effectiveness of the proposed algorithm.

It popularly uses Simulink to design embedded system on Model oriented design platform, and to simulate dynamic system for multi-domain simulation. So, Electrics Telecommunication Research Institute (ETRI) is researching for model transformation from Simulink model to ECML model for Cyber Physical Systems Project. This paper shows how to transform Simulink model to ECML model. We propose an automatic transformation method to transform ECML model from Simulink model based on model transformation technique that is very useful mechanism for heterogeneous model. And, we also design each metamodel of Simulink and ECML. With these metamodels of them, it easily execute model transformation even with models of any vendor’s tools.

Existing TV remote controls using relative coordinates have some difficulties in selecting various types of IPTV content. This paper proposes an absolute coordinates based remote control to make the selection of IPTV channels more convenient. It uses a laser pointer to point at an IPTV, a camera mounted the remote control to locate the spot pointed at, and control software to calculate the absolute coordinates of the spot pointed to on the screen.

Real financial transactions take place on a consecutive real-time serialization. They are carried out as dynamic transaction chains along with various related systems rather than with just one system. This paper suggests a process that generates a test case for the verification of such consecutive real-time transaction system. The suggested process generates a test case through mechanism applied with UML and ECA (Event/Condition/Action) rules. Through analyzing transactions, we generate UML modeling, then maps UML with ECA rules, which creates an ECA-decision table. A test scenario is generated with this table. That is, the test scenario is modeled from an ECA diagram based on the consecutive transaction chains, which generate a test case.

The current smart phone applications are developed subordinately to its platform. In other words, applications are developed according to its own unique platform by each relevant vender, such as Cocoa for Apple, Android for Google and Windows Mobile for Microsoft. This paper suggests adapting the whole process of MDD (Model Driven Development) for the development of heterogeneous smart applications. Our proposed MDD is composed of Model-to-Model Transformation, which separates the independent from the dependent platform and transforms the independent model to the dependent model through rules on model transformation, and Model-to-Text Transformation, which forms codes from each dependent model. Model, metamodel and model transformation language are required to achieve Model-to-Model Transformation while model, metamodel and code template are needed for Model-to-Text Transformation. UML model, UML metamodel, ATL model transformation language and Acceleo code generation language also are adapted MDD in smart phone development environment. This paper also mentions a case of applying MDD in SnakePlus game.

In the conventional tests, test case is generated in the design stage. However, actual test can be executed after its embodiment. As there is as much time difference between the design and execution of the test, the errors in the designs of test and software are checked out late. This paper is proposing the test case generation method so as automatic test can be carried out in the virtual simulation environment. The method proposed generates the test case automatically based on the state diagram and executes it in the virtual simulator. It can reduce the time difference between the design and execution of test, accordingly, to find out the error in the test case and problems in the design promptly. As a result, it can identify the error in the beginning stage of software development and save the time and expense need for the development.