As XML is increasingly used for representing and exchanging data, relational database systems have been trying extend their features to handle XML documents XML documents can be stored in a column with XML data type like primitive types. The shredding method, which is one of the traditional methods for storing and managing XML documents in RDBMS, is still useful and viable although it has some drawbacks due to the structural discrepancy between XML and relational databases. This method may be suitable for data-centric XML documents with simple schema. This paper presents the extended version of the Association inlining method that is based on inlined shredding and compares the performance of querying processing to that of XML type method of conventional relational database systems. The experiments showed that in most cases our method resulted in better performance than the other method based on XML data type. This is due to the fact that our shredding method keeps and uses the order and path information of XML documents. The path table has the information of the corresponding table and column for each distinct path and the structure information of the XML document is extracted and stored in data tables.

The standard of evaluating function of speech coder for mobile telecommunication can be shown in channel capacity, noise immunity, encryption, complexity and encoding delay largely. This study is an algorithm to reduce complexity applying to CDMA(Code Division Multiple Access) mobile telecommunication system, which has a benefit of keeping the existing advantage of telecommunication quality and low transmission rate. This paper has an objective to reduce the computing complexity by controlling the frequency band nonuniform during the changing process of LSP(Line Spectrum Pairs) parameters from LPC(Line Predictive Coding) coefficients used for EVRC(Enhanced Variable-Rate Coder, IS-127) speech coders. Its experimental result showed that when comparing the speech coder applied by the proposed algorithm with the existing EVRC speech coder, it's decreased by 45% at average. Also, the values of LSP parameters, Synthetic speech signal and Spectrogram test result were obtained same as the existing method.

The many target-detection methods that use forward-looking infrared (FUR) images can deal with large targets measuring $70{\times}40$ pixels, utilizing their shape features. However, detection small targets is difficult because they are more obscure and there are many target-like objects. Therefore, few studies have examined how to detect small targets consisting of fewer than $30{\times}10$ pixels. This paper presents a small target detection method using clutter rejection with stochastic hypothesis testing for FLIR imagery. The proposed algorithm consists of two stages; detection and clutter rejection. In the detection stage, the mean of the input FLIR image is first removed and then the image is segmented using Otsu's method. A closing operation is also applied during the detection stage in order to merge any single targets detected separately. Then, the residual of the clutters is eliminated using statistical hypothesis testing based on the t-test. Several FLIR images are used to prove the performance of the proposed algorithm. The experimental results show that the proposed algorithm accurately detects small targets (Jess than $30{\times}10$ pixels) with a low false alarm rate compared to the center-surround difference method using the receiver operating characteristics (ROC) curve.

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

Fingerprint verification is being adopted widely to provide positive identification with a high degree of confidence in all practical areas. This popular usage requires reliable methods for matching of these patterns. To meet the latest expectations, the paper presents a pair wise distance histogram method for fingerprint matching. Here, we introduced a randomized algorithm which exploits pair wise distances between the pairs of minutiae, as a basic feature for match. The method undergoes two steps for completion i.e. first it performs the matching locally then global matching parameters are calculated in second step. The proposed method is robust to common problems that fingerprint matching faces, such as scaling, rotation, translational changes and missing points etc. The paper includes the test of algorithm on various randomly generated minutiae and real fingerprints as well. The results of the tests resemble qualities and utility of method in related field.

This paper introduces adaptive PRML (Partial Response Maximum Likelihood) architecture with PR (a,b,c,d,e) channel type for the improved readability of high-density optical discs with capacity greater than 30GB. The proposed PRML architecture consists of an adaptive equalizer, a Viterbi detector and a channel identifier. Detailed description for each component is included. The architecture is implemented in chip and also confirmed its performance on the test board mounting the chip. Test results show that the proposed 5-tap PRML architecture is well operated, and less than $2{\times}10^{-4}$ of BER (Bit Error Rate) is achieved with radial and tangential tilt margin of ${\pm}0.6^{\circ}$ on self-made 30GB BD at 1x speed.

Camera position information from 2D face image is very important for that make the virtual 3D face model synchronize to the real face at view point, and it is also very important for any other uses such as: human computer interface (face mouth), automatic camera control etc. We present an algorithm to detect human face region and mouth, based on special color features of face and mouth in $YC_bC_r$ color space. The algorithm constructs a mouth feature image based on $C_b\;and\;C_r$ values, and use pattern method to detect the mouth position. And then we use the geometrical relationship between mouth position information and face side boundary information to determine the camera position. Experimental results demonstrate the validity of the proposed algorithm and the Correct Determination Rate is accredited for applying it into practice.

In this paper, we presented geometric CAD watermarking scheme for Architectural design drawings using line, arc, and circle components to prevent infringement of copyright from unlawfulness reproductions and distribution. The conventional CAD watermarking scheme can be applied to both line and arc components. But the proposed scheme consists of line, arc and circle watermarking schemes for three basic components of CAD design. After extracting line, arc and circle components from designed drawing, the watermark is embedded into the length of Line component, the angle of arc component, and the radius of circle component considering the robustness against various geometric transformations. The embedding strengths in each component are determined to be preserving the transparency of the watermark. By experimental result, we confirmed the robustness and the invisibility of embedded watermarks in several conversions of architectural design drawing.

In this paper, we introduced our designed TDMA (Time Division Multiple Access) based MAC (Medium Access Control) protocol for Home Networks called HomeTDMA. We have implemented and tested it in a test bed using crossbow motes and TinyOS. We also have compared HomeTDMA and CSMA (Carrier Sense Multiple Access) in terms of space and time complexity, channel access time, delivery success ratio, and throughput. Based on our results, HomeTDMA has an advantage over CSMA on channel access time, throughput and delivery success ratioIn the case of complexity, HomeTDMA is more complex compared to CSMA. Thus, CSMA is more appropriate in wireless sensor networks (WSNs) where memory, energy, and throughput are important parameters to be considered. However, HomeTDMA has a natural advantage of collision free medium access and is very promising for home networks where a reliable transmission or data transfer and congestion control is highly preferred.

To realize the wireless packet scheduler which efficiently considers both the effect of adaptive modulation and coding (AMC) scheme due to variable wireless communication channel information from physical layer and the QoS differentiation of multimedia services from internet protocol (IP) layer, this paper proposes a new downlink AMC-based priority queuing (APQ) scheduler which combines AMC scheme and service priority method in multimedia services at the same time. The result of numerical analysis shows that the proposed APQ algorithm plays a role in increasing the number of services satisfying the mean waiting time requirements per each service in multimedia services because the APQ scheme allows the mean waiting time of each service to be reduced much more than existing packet scheduler having only user selection processor.

Wireless Mesh Networks aim to attain large connectivity with minimum performance degradation, as network size is increase. As such, scalability is one of the main characteristics of Wireless Mesh Networks that differentiates it from other wireless networks. This characteristic creates the need for bandwidth efficiency strategies to ensure that network performance does not degrade as the size of the network increase. Several researches have been done to realize mesh networks. However, the researches conducted were mostly focused on a per TCP/IP layer basis. Also, the studies on bandwidth efficiency and bandwidth improvement are usually dealt with as separate issues. This paper aims to simultaneously study bandwidth efficiency and improvement. Aside from optimizing the bandwidth given a fixed capacity, the capacity is also increased using results of physical layer studies. In this paper, the capacity is improved by using the concept of non-overlapping channels for wireless communication. A channel allocation scheme is conceptualized to choose the transmission channel that would optimize the network performance parameters with consideration of chosen Quality of Service (QoS) parameters. Network utility maximization is used to optimize the bandwidth after channel selection. Furthermore, a routing scheme is proposed using the results of the network utilization method and the channel allocation scheme to find the optimal path that would maximize the network gain.

In this paper, we study the problem of load balancing routing in clustered-based wireless mesh network in order to enhance the overall network throughput. We first address the problems of cluster allocation in wireless mesh network to achieve load-balancing state. Due to the complexity of the problem, we proposed a simplified algorithm using gradient load-balancing model. This method searches for a localized optimal solution of cluster allocation instead of solving the optimal solution for overall network. To support for load-balancing algorithm and reduce complexity of topology control, we also introduce limited broadcasting between two clusters. This mechanism maintain shortest path between two nodes in adjacent clusters while minimizing the topology broadcasting complexity. The simulation experiments demonstrate that our proposed model achieve performance improvement in terms of network throughput in comparison with other clustering methods.

Although the PKl-based user authentication solution has been widely used, the security of it can be deteriorated by a simple password. This is because a long and random private key may be protected by a short and easy-to-remember password. To handle this problem, many biometric-based user authentication solutions have been proposed. However, protecting biometric data is another research issue because the compromise of the biometric data will be permanent. In this paper, we present an implementation to improve the security of the typical PKI-based authentication by protecting the private key with a fingerprint. Compared to the unilateral authentication provided by the typical biometric-based authentication, the proposed solution can provide the mutual authentication. In addition to the increased security, this solution can alleviate the privacy issue of the fingerprint data by conglomerating the fingerprint data with the private key and storing the conglomerated data in a user-carry device such as a smart card. With a 32-bit ARM7-based smart card and a Pentium 4 PC, the proposed fingerprint-based PKI authentication can be executed within 1.3second.

One-way hash chains are important cryptographic primitives and have been used as building blocks of various cryptographic applications. Advantages of one-way hash chains are their simplicity and efficiency for generation based on low-powered processors with short time. However, a drawback of one-way hash chains is their difficulty of control to compute interval values of one-way hash chains. That is, when hash values in one-way hash chain are used as encryption keys, if one hash value is compromised, then the attacker can compute other encryption keys from the compromised hash value. Therefore, direct use of one-way hash chains as encryption keys is limited to many cryptographic applications, such as pay per view system and DRM system. In this paper, we propose a new concept which is called interval hash chain using a hash function. In particular, proposed hash chains are made for only computing interval hash values by using two different one-way hash chains. The proposed scheme can be applied to contents encryption scheme for grading and partially usable contents in DRM system.

In these days, Disaster Management Systems have still put emphasis on its recovery more than the prevention of disaster events. However, the countermeasure of restoration has limitations to prevent the caused loss because the disasters often happen and are massive. Therefore, we propose a disaster prevention system for supporting the safe urban. In this paper, we try to construct a real-time monitoring system to prevent disaster events using new technologies such as Wireless Sensor Networks (WSN) and Geographic Information System (GIS). As a prototype to simulate the fire disasters on real-time, we construct gas sensors and temperature sensors. Our system consists of a WSN system to collect data of the gas and temperature sensors and to monitor the situation information. Our contribution is to provide a prototype application to prevent the disasters from the fire by constructing a WSN system with gas and temperature sensors.

In this paper, we introduce the sharable and reusable learning objects which are suitable for XML Web services in e-learning systems. These objects are extracted from the principles of pedagogical paradigms for reusable learning units. We call them LIO (Learning Item Object) objects. Existing models, such as Web-hosted and ASP-oriented service model, are difficult to cooperate and integrate among the different kinds of e-learning systems. So we developed the LIO objects that are suitable for XML Web services. The reusable units that are extracted from pedagogical paradigms are tutorial item, resource, case example, simulation, problems, test, discovery and discussion. And these units correspond to the LIO objects in our learning object model. As a result, the proposed model is that learner and instruction designer should increase the power of understanding about learning contents that are based on pedagogical paradigms. By using XML Web services, this guarantees the integration and interoperation of the different kinds of e-learning systems in distributed environments and so educational organizations can expect the cost reduction in constructing e-learning systems.

Paik Nam-June is known as a Video Artist. Video is a presentation tool with the feature of recordability. However, it is not only a video which has been applied as an art presentation tool by him. Nevertheless, the existing researches fail to notice the aesthetic concept which is shown as the rest contents or forms, as they focus on the media features of Paik Nam-June's video. Therefore, this article aims at contemplating the art world of Paik Nam-June with its contents as 'visualization of music' and its form as 'hypermediacy' Therefore, 1. Sound is shown as the visualization of music, with the direct influence of absolute hollowness and noise of John Cage, originated from Zen Buddhism, while the foundation of it is known to be from the liberation of dissonance of Arnold Schoenberg and creative impromptu of shamanic sound. 2. The from of TVs influence of the orchestra, originated from Culture of a dining table in Korean. and indicated hypermediacy 3. Paik Nam-June indicated 'Text-interpretation' us to text analytics of 'how to read', rather than the question of 'what to tell' by intermedia as the visualization of music & hypermediacy.

The paper focuses on a new 'learning ecology' that is evolving and the challenges that educators must confront. It looks at e-learning as not just another add-on, but a technology that is transforming our educational institutions. How teaching and learning is conceptualized and experienced to generate a determined community of inquiry that integrates social, cognitive, and teaching presence in a manner that will take full advantage of the distinctive assets of e-learning is discussed. Likewise, the possibility of mobile learning is put forward.

Contents industry is growing into a versatile area whose contents can be embodied through not only traditional media such as theater and TV, but also new ones such as the internet, mobile unit, PDA, DMP, etc. In addition, highly advanced computer technology and contents are harmoniously combined for image development featuring multi-channels, which produces various contents, and thus, creating synergy effects with other key industries such as IT, strengthens the domestic economy as an industry of value expansion and new high value items. To this end, this study is to present development plans that are highly productive and valued to domestic contents development companies. For this, the focus was put on the fact that concurrent engineering, which is the mechanism bringing very beneficial effects to existing analog product development processes, and the team system have significant, positive effect on the company productiveness and competitive market values among digital contents related companies, especially contents businesses.

This paper describes a top-down behavior planning framework in a simulation game from personality to real life action selection. The combined behavior creating system is formed by five levels of specification, which are personality definition, motivation extraction, emotion generation, decision making and action execution. Along with the data flowing process in our designed framework, NPC selects actions autonomously to adapt to the dynamic environment information resulting from active agents and human players. Furthermore, we illuminate applying Gaussian probabilistic distribution to realize character's behavior changeability like human performance. To elucidate the mechanism of the framework, we situated it in a restaurant simulation game.

The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents an efficient rough set based anomaly detection method that can effectively identify a group of especially harmful internal attackers - masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on this, the used pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function with the age of the user profile. The performance of the proposed scheme is evaluated by using a simulation. Simulation results demonstrate that the anomalies are well detected by the proposed scheme that considers the age of user profiles.

In this paper, we propose a wireless location-based routing algorithm which uses the location information of its neighbor nodes and a destination node. At first, the proposed routing algorithm forwards a packet to the X direction by selecting a closest node to its destination as a next hop in terms of the X coordinate until the packet reaches closely to the packet's destination. Then the packet is forwarded to the Y direction by selecting a closest node to its destination in terms of the Y coordinate. We use a back off mechanism in case that a next hop cannot be found using the proposed routing algorithm, which resolves loops while forwarding. The experimental results show that the proposed routing algorithm performs well like the existing routing algorithms Ad hoc On-demand Distance Vector and Greedy Perimeter Stateless Routing. It is expected to use the proposed routing algorithm in the digital battlefield of military environments and survival games of commercial environments.

The imprecise computation technique ensures that all time-critical tasks produce their results before their deadlines by trading off the quality of the results for the computation time requirements of the tasks. In the imprecise computation, most scheduling problems of satisfying both 0/1 constraints and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. In the previous studies, the reasonable strategies of scheduling tasks with the 0/1 constraints on uniprocessors and multiprocessors for minimizing the total error are proposed. But, these algorithms are all off-line algorithms. Then, in the on-line scheduling, NORA(No Off-line tasks and on-line tasks Ready upon Arrival) algorithm can find a schedule with the minimum total error. In NORA algorithm, EDF(Earliest Deadline First) strategy is adopted in the scheduling of optional tasks. On the other hand, for the task system with 0/1 constraints, NORA algorithm may not suitable any more for minimizing total error of the imprecise tasks. Therefore, in this paper, an on-line algorithm is proposed to minimize total error for the imprecise real-time task system with 0/1 constraints. This algorithm is suitable for the imprecise on-line system with 0/1 constraints. Next, to evaluate performance of this algorithm, a series of experiments are done. As a consequence of the performance comparison, it has been concluded that IOSMTE(Imprecise On-line Scheduling to Minimize Total Error) algorithm proposed in this paper outperforms LOF(Longest Optional First) strategy and SOF(Shortest Optional First) strategy for the most cases.

Location-based services are a recent concept that integrates a mobile device's location with other information in order to provide added value to a user. Although Location-based Services provide users with comfortable information, it is a complex task to manage and share heterogeneous and numerous data in decentralized environments. In this paper, we propose the Semantic LBS Model as one of the solution to resolve the problem. The Semantic LBS Model is a LBS middleware model that includes an ontology-based data model for LBS POI information and its processing mechanism based on Semantic Web technologies. Our model enables POI information to be described and retrieved over various domain-specific ontologies based on our proposed POIDL ontology. This mechanism provide rich expressiveness, interoperability, flexibility in describing and using information about POls, and it can enhance POI retrieval services.