Chang-Won Jeong

TMO-Based Object Group Framework for Supporting Distributed Object Management and Real-Time Services

In this paper, we present a TMO-based object group framework that can support the distributed object group management and the real-time scheduling services on distributed real-time computing environments. These environments have some difficulties for managing lots of distributed objects and providing the timing constraints to real-time objects. For simultaneously solving these problems, we design a TMO object group framework that can manage as a grouping unit of the distributed TMO objects in order to reduce their own complicated managements and interfaces among individual objects without modifying the ORB itself. The TMO object as real-time object, defines the object having real-time property developed from Dream Laboratory at UC at Irvine. The TMO object group we suggested contains several components reflected the object grouping concepts and real-time service requirements analyzed by referring OMG CORBA specifications. To construct our TMO object group framework, we designed the TMO object group structure, and described the functional class diagram with representing relationships among components. We also explained the detailed functional definitions and interactions between the components from the following 2 points of views; object management service by the Dynamic Binder object for selecting an appropriate one out of objects with the same property, and the real-time scheduling service by the Scheduler object and the Real-Time Manager object. We finally verified the results produced by using the known algorithms like the Binding Priority algorithm and the EDF algorithm to see whether a distributed object management service and a real-time service can adapt on the suggested framework.

Identification of Fuzzy Inference System Based on Information Granulation

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with “conventional” evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some “conventional” fuzzy models already encountered in the literature.

Mobile Collaboration Framework for u-Healthcare Agent Services and Its Application Using PDAs

In this paper, we suggested a mobile collaboration framework based on distributed object group framework (DOGF). This paper focuses on the use of this framework to support mobile collaboration. Therefore, we improved the existing work and apply it to the construction of u-healthcare agent services. For supporting mobile collaboration, we divided into two agent types such as the stationary and the moving-typed agents according to the function of mobile devices. The data collected by sensors attached on arbitrary spaces can be shared by 2-typed agents or a home server, and exchanged with each other using the Push and Pull methods. For managing this information, the DOGF provides functions of object group management, storing information and security services to our mobile collaboration framework via defined application interfaces. The agent for executing service functions of mobile devices and an integrated monitoring system on home server are implemented by using TMO scheme. And we used the TMOSM for interactions between distributed components. Finally, we showed via GUI the executablility of healthcare application supporting for medical work in hospitals on our mobile collaboration framework.

GA-based Feed-forward Self-organizing Neural Network Architecture and Its Applications for Multi-variable Nonlinear Process Systems

In this paper, we introduce the architecture of Genetic Algorithm (GA) based Feed-forward Polynomial Neural Networks (PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN leads to the selection of preferred nodes (PNs) with optimal parameters available within the PNN. To evaluate the performance of the GA-based PNN, experiments are done on a model by applying Medical Imaging System (MIS) data to a multi-variable software process. A comparative analysis shows that the proposed GA-based PNN is modeled with higher accuracy and more superb predictive capability than previously presented intelligent models.

Development of a Mini-Mobile Digital Radiography System by Using Wireless Smart Devices

The current technologies that trend in digital radiology (DR) are toward systems using portable smart mobile as patient-centered care. We aimed to develop a mini-mobile DR system by using smart devices for wireless connection into medical information systems. We developed a mini-mobile DR system consisting of an X-ray source and a Complementary Metal–Oxide Semiconductor (CMOS) sensor based on a flat panel detector for small-field diagnostics in patients. It is used instead of the systems that are difficult to perform with a fixed traditional device. We also designed a method for embedded systems in the development of portable DR systems. The external interface used the fast and stable IEEE 802.11n wireless protocol, and we adapted the device for connections with Picture Archiving and Communication System (PACS) and smart devices. The smart device could display images on an external monitor other than the monitor in the DR system. The communication modules, main control board, and external interface supporting smart devices were implemented. Further, a smart viewer based on the external interface was developed to display image files on various smart devices. In addition, the advantage of operators is to reduce radiation dose when using remote smart devices. It is integrated with smart devices that can provide X-ray imaging services anywhere. With this technology, it can permit image observation on a smart device from a remote location by connecting to the external interface. We evaluated the response time of the mini-mobile DR system to compare to mobile PACS. The experimental results show that our system outperforms conventional mobile PACS in this regard.

Sleeping situation monitoring system in ubiquitous environments

In recent years, because of the development of ubiquitous technology in health care, research is actively progress. We describe a sleeping situation monitoring system, created to support home healthcare services. We discuss the method we used to develop the system and how to use the sleep activity monitor to support home health care. Information about the sleeping situation is collected from motion detection, sound, and vibration sensors. And this information is based on real-time processing, we used the TMO (Time-trigger and Message-trigger Object) schema and TMOSM (TMO Support Middleware) into the development software environment of the healthcare application. To verify the practical use of sleeping situation information as recorded by the system discussed in this paper, we relate an example of the monitoring of a sleeping situation using our system, and we describe the results of an experimental evaluation.

The development of a medical image information system environment using data synchronization based on cloud computing

This paper describes the medical image information system environment for medical image share. The external interface of this system used a cloud service and we adapted the devices for connections with PACS and smart devices. One problem with this type of approach is the accumulated network latency that can arise from such a deployment. For this reason, we suggested a medical image information system environment using data synchronization methods. Our approach is designed as synchronization methods using detection of creation image data on components of system. Also, we used the cloud computing environment, which reduced the number of high-latency image transmissions. Finally, we show the data synchronization process of the system with imaging application services based on a cloud-computing service. Also, we evaluated the response time to compare to mobile PACS. The experimental results show that our system outperforms mobile PACS. As results, our approach is shown to deliver on par or even better results.

Dedicated mobile volumetric cone-beam computed tomography for human brain imaging: A phantom study

BACKGROUND Mobile computed tomography (CT) with a cone-beam source is increasingly used in the clinical field. Mobile cone-beam CT (CBCT) has great merits; however, its clinical utility for brain imaging has been limited due to problems including scan time and image quality. OBJECTIVE The aim of this study was to develop a dedicated mobile volumetric CBCT for obtaining brain images, and to optimize the imaging protocol using a brain phantom. METHODS The mobile volumetric CBCT system was evaluated with regards to scan time and image quality, measured as signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), spatial resolution (10% MTF), and effective dose. Brain images were obtained using a CT phantom. RESULTS The CT scan took 5.14 s at 360 projection views. SNR and CNR were 5.67 and 14.5 at 120 kV/10 mA. SNR and CNR values showed slight improvement as the x-ray voltage and current increased (p < 0.001). Effective dose and 10% MTF were 0.92 mSv and 360 μ m at 120 kV/10 mA. Various intracranial structures were clearly visible in the brain phantom images. CONCLUSIONS Using this CBCT under optimal imaging acquisition conditions, it is possible to obtain human brain images with low radiation dose, reproducible image quality, and fast scan time.

Performance of mobile digital X-ray fluoroscopy using a novel flat panel detector for intraoperative use

BACKGROUND Technologies employing digital X-ray devices are developed for mobile settings. OBJECTIVE To develop a mobile digital X-ray fluoroscopy (MDF) for intraoperative guidance, using a novel flat panel detector to focus on diagnostics in outpatient clinics, operating and emergency rooms. METHODS An MDF for small-scale field diagnostics was configured using an X-ray source and a novel flat panel detector. The imager enabled frame rates reaching 30 fps in full resolution fluoroscopy with maximal running time of 5 minutes. Signal-to-noise (SNR), contrast-to-noise (CNR), and spatial resolution were analyzed. Stray radiation, exposure radiation dose, and effective absorption dose were measured for patients. RESULTS The system was suitable for small-scale field diagnostics. SNR and CNR were 62.4 and 72.0. Performance at 10% of MTF was 9.6 lp/mm (53 μ m) in the no binned mode. Stray radiation at 100 cm and 150 cm from the source was below 0.2 μ Gy and 0.1 μ Gy. Exposure radiation in radiography and fluoroscopy (5 min) was 10.2 μ Gy and 82.6 mGy. The effective doses during 5-min-long fluoroscopy were 0.26 mSv (wrist), 0.28 mSv (elbow), 0.29 mSv (ankle), and 0.31 mSv (knee). CONCLUSIONS The proposed MDF is suitable for imaging in operating rooms.

Construction of Dynamic Medical Information System for Digital Hospital Environments

AbstractThe distribution of healthcare information via cloud-based hospital information systems has been increasing in recent years. Because these systems can disseminate sensitive healthcare information to various smart devices, their security approaches must be carefully studied. In addition, research is required to ensure that patients are being properly notified about changes in their medical treatments. Therefore, in this paper, we propose a dynamic medical information system for digital hospital environments. For this purpose, we design a system that can securely distribute existing digital hospital data, including medical images and patient record information. In order to classify the providing services, we divide them into two types—synchronization and security. We suggest a dynamic authentication method to access medical information. Moreover, the proposed system provides Digital Imaging and Communications in Medicine (DICOM) file synchronization between system environments. We confirm the usefulness of the application based on experimental results.