Sangki Kim

Comparison of intrathecal fentanyl and sufentanil in low-dose dilute bupivacaine spinal anaesthesia for transurethral prostatectomy

BACKGROUND The administration of low-dose bupivacaine can limit the distribution of spinal block to reduce adverse haemodynamic effects. Intrathecal opioids can enhance analgesia in combination with subtherapeutic doses of local anaesthetics. We aimed at comparing the efficacy of intrathecal fentanyl and sufentanil with low-dose diluted bupivacaine for transurethral prostatectomy (TURP) in elderly patients. METHODS Seventy patients undergoing TURP were randomly allocated into two groups. Group F (n=35) received fentanyl 25 microg+bupivacaine 0.5% (0.8 ml)+normal saline 0.3 ml and Group S (n=35) received sufentanil 5 microg+bupivacaine 0.5% (0.8 ml)+normal saline 0.7 ml--in total, bupivacaine 0.25% (1.6 ml) intrathecally. Onset and duration of the sensory block, the degree of the motor block, side-effects, and the perioperative analgesic requirements were assessed. RESULTS The median peak level of the sensory block was significantly higher in Group S than in Group F (P=0.049). Group S required fewer perioperative analgesics than Group F (P=0.008). The time to the first analgesic request was longer in Group S (P=0.025). There were no differences between the groups for the onset and recovery time of the sensory block, degree of the motor block, quality of anaesthesia, or adverse effects. CONCLUSIONS Low-dose diluted bupivacaine with fentanyl 25 microg or sufentanil 5 microg can provide adequate anaesthesia without haemodynamic instability for TURP in elderly patients. However, sufentanil was superior to fentanyl in the quality of the spinal block produced.

Biometric Image Authentication using Watermarking

In this paper, we propose an invertible authentication watermarking algorithm which can detect block-wise malicious manipulations in biometric images. Our method uses an invertible watermark that can also detect manipulated area simultaneously. Virtually all watermarking schemes introduce a small amount of irrecoverable distortion in original biometric images. But our new method is invertible in the sense that, if the data is deemed authentic, distortion due to authentication can be removed if it becomes necessary to obtain the original biometric image. In our method two watermarks are embedded into biometric image. The first one is based on the conventional method which can completely remove the distortion due to authentication if the data is deemed authentic. The second one can detect the block-wise malicious manipulation using the cyclic redundancy check (CRC) concept in the image block. Our proposed method can classify a test image into two types; authentic, and manipulated. Also, this technique provides cryptographic strength when verifying image integrity because the probability of making an undetectable modification to the image can be directly related to a secure cryptographic element, such as a hash function

Robust Face Recognition by Fusion of Visual and Infrared Cues

This paper proposes a robust face recognition method by fusing images acquired from visual and infrared (IR) sensors. Although current 2D image face recognition systems have reached a certain level of maturity, the performance of these systems has been limited by external conditions such as pose, expression and illumination. To alleviate some of these problems, infrared sensor based methods have been suggested. These methods showed very good performance when used in illumination variation environments. However, one of the main drawbacks of using IR sensors for recognition is that they are very sensitive to ambient temperatures. To solve this problem, we suggest a face recognition method that fuses both visual and IR techniques. We developed a visual and IR face image database with photographs taken under a wide range of imaging conditions. With this database, we are able to produce full combinations of comparative experiments in the field of face recognition. Our experiments showed that when using both modalities, results are far better in terms of recognition performance than when using only one modality. The overall average performance was observed to have improved under all imaging conditions

Design of Open APIs for Personalized IPTV Service

With the broadcasting and network convergences, IPTV which is a broadcasting service using IP network, becomes popular as a new business model. The IPTV service supports the user-interactive and personalized broadcasting service. However, it is difficult to serve the IPTV services to the universal user terminals in the heterogeneous network environment. In this paper, we study the service scenarios for the personalized broadcasting services under open network environments and extend the Parlay X Web service structure for the personalized EPG, NDR and target advertisement services from the service scenarios. For these three services, we specify open APIs based on Parlay X for open network environments. Based on these open network environments for the personalized broadcasting services, it is possible to provide new business model to the network operators, to reduce the duplicable investment in new business by defining the roles of each service provider and to develop the various and inventive services through the third party application service. We also implement the prototype system for open APIs based on the extended Parlay X Web service structure which are named personalized EPG, NDR and target advertisement.

End-User Driven Service Creation for Converged Service of Telecom and Internet

Convergence and user-centricity are the leading trends in telecom network. The service creation scheme is changing to realize these trends. This paper describes the end-user driven service creation method for converged service over telecom and Internet domain. The proposed SCE fulfills the general SCE requirements and also comes up with the network trend to user-centricity and the network evolution towards convergence. The advantage of our approach comes from web based service creation and execution environment to satisfy end-users requirements and encourage users participation. Using our SCE, end- users can create their own service applications and use them anytime and anywhere through their personal devices.

An Efficient Context Model for Fast Responsiveness of Context-Aware Services in Mobile Networks

In order to provide context-aware services, context modeling is one of the most important tasks. Ontology has been widely accepted for the context modeling but it brings some overheads in the process of reasoning large-scale and dynamic information. In mobile networks, especially, ontology should be verified to be applicable for Context-aware Services since real-time responsiveness for large scale moving users is highly required to be guaranteed. This paper proposes an efficient context model to overcome the limitation of ontology. For the purpose, we design a conceptual context model and compare the processing time of the context-aware mobile service system implying the three different context modeling approaches - ontology, database, and proposed hybrid modeling. As the result of performance evaluations, the proposed hybrid model shows faster processing time among them and lesser affected by the major metrics of mobile services - changeability and number of users - than the two existing models. Based on the experimental results, we expect that the proposed hybrid model is very useful and efficient for fast responsiveness to support Context-aware Services for large scale users in mobile networks.

Fingertips detection and tracking based on active shape models and an ellipse

Detecting and tracking fingertips are significant techniques for recognizing hand gestures. Many patterns and skin color information are used to extract and trace features [1, 2]. However, to find correct shapes is difficult and there is limitation to express the diversity of models. In this paper, we describe a method of detecting and tracking fingertips based on Active Shape Models (ASMs) and an ellipse equation. ASM is an effective tool to obtain features of a specific object in images by using a trained model. The ellipse equation helps a template follow the object without skin color information. We show how well fingertips are extracted and traced through some experiments.

Efficient offering Service Creation Experience Environment for Open Service

Today, developers can create new services by simple mouse clicks on the tools. This shows SCE is becoming smart that means more automatic and requires less human interaction. IT developers who may not have the specific knowledge of telecommunication network can create open services. For that, the scope of SCE is becoming wider. These days, SCE required more than just simplifying and fast service creation. SCE needs to explain explicitly how to be used and make developers to understand well the outcome. This paper shows the efficient offering methods of open service creation experience environment

TMN-based intelligent network number portability service management system using CORBA

Local number portability (LNP) is an intelligent network (IN) service, which provides end users the ability to change local telephone service providers without changing their telephone numbers. LNP is a key service for increasing competition in the local telephone marketplace. To implement LNP, a number portability administration center (NPAC) is needed to manage the LNP databases. Service providers also must implement the carrier-level system and update their existing IN components to provide LNP. In this paper, we present our work on applying the TMN and CORBA technology to the service management of the intelligent network, particularly the LNP. We propose a TMN-based LNP system architecture and present a design and implementation of a NPAC service management system using CORBA.

Higher order knowledge management platform for the personalized services in next generation networks

We propose higher order knowledge management platform (HKMP) that can support to provide the personalized services for the end users by means of evolving lower order network knowledge. HKMP helps 3rd party service providers to create personalized services considering users context through the open interfaces for providing higher order knowledge. In this paper, we classify lower order network knowledge and build ontology to represent them including user profiles and users preference. Furthermore, we propose the efficient algorithms of leaner and recommender to evolve higher order knowledge in HKMP. Finally, we simulated to evaluate the precision of proposed algorithms with data sets of UCI depository. As the result of evaluation, we expect that the HKMP would be an essential component for providing personalized services in next generation networks.