The objective of this paper is to present a decision support system which uses a computer-based procedure to detect tumor blocks or lesions in digitized medical images. The authors developed a simple method with a low computation effort to detect tumors on T2-weighted Magnetic Resonance Imaging (MRI) brain images, focusing on the connection between the spatial pixel value and tumor properties from four different perspectives: 1) cases having minuscule differences between two images using a fixed block-based method, 2) tumor shape and size using the edge and binary images, 3) tumor properties based on texture values using spatial pixel intensity distribution controlled by a global discriminate value, and 4) the occurrence of content-specific tumor pixel for threshold images. Measurements of the following medical datasets were performed: 1) different time interval images, and 2) different brain disease images on single and multiple slice images. Experimental results have revealed that our proposed technique incurred an overall error smaller than those in other proposed methods. In particular, the proposed method allowed decrements of false alarm and missed alarm errors, which demonstrate the effectiveness of our proposed technique. In this paper, we also present a prototype system, known as PCB, to evaluate the performance of the proposed methods by actual experiments, comparing the detection accuracy and system performance.

Content-Addressable Network (CAN) provides a mechanism that could retrieve objects in a P2P network by maintaining indices to those objects in a fully decentralized manner. In the CAN system, index caching is a useful technique for reducing the response time of retrieving objects. The key points of effective caching techniques are to improve cache hit ratio by actively sharing caches distributed over the P2P network with every node and to reduce a maintenance and/or routing overhead for locating the cache of a requested index. In this paper, we propose a new caching technique based on the notion of proxy-type caching techniques which have been widely used in WWW systems. It can achieve active cache sharing by incorporating the concept of proxy caching into the index access mechanism and locate a closer proxy cache of a requested index with a little routing overhead. By the result of simulations, we conclude that it can improve the response time of retrieving indices by 30% compared with conventional caching techniques.

In this paper, we present the Tangible Media Control System (TMCS), which allows users to manipulate media contents through physical objects in an intuitive way. Currently, most people access digital media contents by exploiting GUI. However, it only provides limited manipulation of the contents. The proposed system, instead of a mouse and a keyboard, adopts two types of tangible objects, i.e. a RFID-enabled object and a tracker-embedded object. The TMCS enables users to easily access and control digital media contents through tangible objects. In addition, it supports an interactive media controller which can be used to synthesize media contents according to users' taste. It also offers personalized contents, which suits users' preferences, by exploiting context such as the users' profile and situational information. Accordingly, the TMCS demonstrates that tangible interfaces with context can provide more effective interfaces to satisfy users' demands. Therefore, the proposed system can be applied to various interactive applications such as multimedia education, entertainment, multimedia editor, etc.

In this paper, we propose multicast technique in order to reduce the required network bandwidth by n times, by merging the adjacent multicasts depending on the number of HENs (Head-End-Nodes) n that request the same video. Allowing new clients to immediately join an existing multicast through patching improves the efficiency of the multicast and offers services without any initial latency. A client might have to download data through two channels simultaneously, one for multicast and the other for patching. Each video stream is divided into blocks which are the same size of multicast grouping interval Im. Blocks then are evenly distributed into different HENs according to their popularity and the order of requests. Only when the playback time exceeds the amount of cached video data, server generates new multicast channel. Since the interval of multicast can be dynamically expanded according to the popularity of videos, it can be reduced the server's workload and the network bandwidth. We adopt the cache replacement strategy as LFU (Least-Frequently-Used) for popular videos, LRU (Least-Recently-Used) for unpopular videos, and the method for replacing the first block of video last to reduce end-to-end latency. We perform simulations to compare its performance with that of conventional multicast. From simulation results, we confirm that the proposed multicast technique offers substantially better performance.

A fully Internet-connected business environment is subject to frequent changes. To ordinary customers, online shopping under such a dynamic environment can be frustrating. We propose a new E-commerce service called the CIGMA to assist online customers under such an environment. The CIGMA provides catalog comparison and purchase mediation services over multiple shopping sites for ordinary online customers. The service is based on up-to-date information by reflecting the frequent changes in catalog information instantaneously. It also matches the desire of online customers for fast response. This paper describes the CIGMA along with its architecture and the implementation of a working prototype.

Content Distribution Networks (CDNs) are highly advanced architectures for networks on the Internet, providing low latency, scalability, fault tolerance, and load balancing. One of the most important issues to realize these advantages of CDNs is dynamic content allocation to deal with temporal load fluctuation, which provides mirroring of content files in order to distribute user accesses. Since user accesses for content files change over time, the content files need to be reallocated appropriately. In this paper, we propose a cost-effective content migration method called the Step-by-Step (SxS) Migration Algorithm for CDNs, which can dynamically relocate content files while reducing transmission cost. We show that our method maintains sufficient performance while reducing cost in comparison to the conventional shortest-path migration method. Furthermore, we present six life cycle models of content to consider realistic traffic patterns in our simulation experiments. Finally, we evaluate the effectiveness of our SxS Migration Algorithm for dynamic content reconfiguration across time.

Given the limited channel capacity in wireless LANs, it is important to achieve high throughput and good fairness through medium access control (MAC) schemes. Although many schemes have been proposed to enhance throughput or fairness of the original IEEE 802.11 standard, they either fail to consider both throughput and fairness, or to do so with complicated algorithms. In this paper, we propose a new MAC scheme that dynamically optimizes each active node's backoff process. The key idea is to enable each node to adjust its Contention Window (CW) to approach the optimal one that will maximize the throughput. Meanwhile, when the network enters into steady state in saturated case, i.e., under heavy traffic load, all the nodes will maintain approximately identical CWs, which guarantees fair share of the channel among all nodes. A distinguishing feature of this scheme is the use of an index called average channel idle interval for optimizing the backoff process without estimating the number of active nodes in networks. We show through theoretical analysis that the average channel ideal interval can represent current network traffic load and indicate the optimal CW. Moreover, since it can be obtained through direct measurement, our scheme eliminates the need for complicated estimation of the number of active nodes as required in previous schemes, which makes our schemes simpler and more reliable when network traffic changes frequently. Through simulation comparison with previous schemes, we show that our scheme can greatly improve the throughput no matter the network is in saturated or non-saturated case, while maintaining good fairness.

In the future network, optical technology will play a stronger role not only for transmission but also for switching. Optical burst switching (OBS) emerged as a promising switching paradigm. It brings together the complementary strengths of optics and electronics. This paper presents the design and implementation of an overlay mode burst-switched photonic network testbed, including its architecture, protocols, algorithms and experiments. We propose a flexible "transceiver + forwarding" OBS node architecture to perform both electronic burst assembly/disassembly and optical burst forwarding. It has been designed to provide class of service (CoS), wavelength selection for local bursts, and transparency to cut-through bursts. The functional modules of OBS control plane and its key design issues are presented, including signaling, routing, and a novel scheduling mechanism with combined contention resolution in space and wavelength domains. Finally, we report the experimental results on functional verification, performance analysis and service demonstration.

Deflection routing is one of the promising approaches to resolve contention in the optical burst switching networks. In the conventional deflection routing scheme, optical bursts may be unable to traverse the route evaluated to select an outgoing link because of the contention at succeeding downstream transit nodes. As a result, the optical bursts may traverse a different route resulting in a long distance or decreased performance. This paper proposes a deflection routing scheme that considers the possibility of the contention at downstream nodes. This scheme utilizes the "expected route distance" instead of the static route distance toward a destination node. The expected route distance considers the possibility of contention at each downstream transit node and is calculated using measured link blocking probabilities at each downstream transit node. The selection priority of each outgoing link is given dynamically based on its expected route distance toward a destination node. By considering the possibility of contention at downstream nodes, a routing scheme with high performance can be realized. The loss rate of optical bursts is improved when an imbalanced load is applied to the network, and the loss rate of optical bursts is also improved when the network includes links with extremely different distances.

In adaptive motion estimation, spatial-temporal correlation based motion type inference has been recognized as an effective way to guide the motion estimation strategy adjustment according to video contents. However, the complexity and the reliability of those methods remain two crucial problems. In this paper, a motion vector field model is introduced as the basis for a new spatial-temporal correlation based motion type inference method. For each block, Full Search with Adaptive Search Window (ASW) and Three Step Search (TSS), as two search strategy candidates, can be employed alternatively. Simulation results show that the proposed method can constantly reduce the dynamic computational cost to as low as 3% to 4% of that of Full Search (FS), while remaining a closer approximation to FS in terms of visual quality than other fast algorithms for various video sequences. Due to its efficiency and reliability, this method is expected to be a favorable contribution to the mobile video communication where low power real-time video coding is necessary.

When video data are transmitted via the network, the quality of video data must be carefully chosen to be best under the condition that the transmission is not influenced by other internet services. They often use the simulcast type, which uses independent streams that are stored and transmitted for the quality, considering implementation, when they select the video quality. On the other hand, we had already proposed the scalable structure, which consists of base and enhancement data, but when they require the high quality video, these data are combined using the transcoding methods. In this paper, we propose the video contents delivery methods with scalable transcoding, in which users can update the quality of video data even after the transmission by base data and differential data. In order to reduce the total time of not only users' access time, but also watching time, we compare simulcast method with proposed methods in the total content utilization time using a video contents access model, and evaluate required transcoding time to reduce the waiting time of users.

The widespread use of the Internet raises issues regarding intellectual property. After content is downloaded, no further protection is provided on that content. DRM (Digital Rights Management) technologies were developed to ensure secure management of digital processes and information. In this paper, we present a multilevel content distribution model of which we present formal descriptions.

Multicasting is a remarkable technology that can effectively provide point-to-multipoint communications. The multicast communication can substantially decrease traffic in a network and thus save network resources and transmission costs. If multicasting is applied to a content delivery system, however, the transmission speed must be set to the lowest one among the available capacities of links on the multicast tree for all client terminals to receive the contents simultaneously. This type of problem is especially serious for heterogeneous networks. This paper studies effective content delivery systems for non-real-time point-to-multipoint services over heterogeneous environments and proposes an adaptive delivery system to select multicasting and store-and-forward transferring data streams. The results obtained by computer simulation show that our proposed system can reduce delivery time and that it is scalable to large networks and robust against variations in network size as well as environmental heterogeneities.

Over the past few years, there has been significant interest in content-aware routing that use the information found in the payload of packets to provide intelligent request distribution. As these content-aware routing mechanisms have become an increasingly important building block for Internet service providers, the network behavior and effectiveness of such mechanisms are unclear. In this paper we analyze the network dynamic of a busy Web site with the content-aware routing mechanism. We find that some unique characteristics of Web traffic may limit the effectiveness of the content-aware switching. Based on these observations, we also propose solutions to remedy these deficiencies.

CDN (Content Delivery Networks) improves end-user performance by replicating web contents on a group of geographically distributed servers. However, repeatedly keeping the entire replica of the original objects into many content servers consumes too much server resource. This problem becomes more serious for the large-sized objects such as streaming media, e.g. high quality video. In this paper, we therefore propose an efficient replication method for layered video streams in CDN, which can reduce user response delays and storage costs simultaneously. Based on an analytical formulation of the cooperative replication of layers and segments of each video stream, we derive a replication algorithm which solves next three problems quantitatively. (1) How many servers should be selected to replicate a given video stream? (2) For a single video stream, how many layers and segments should be stored in a given server? (3) After selecting a group of servers for each video stream, how do we allocate the replication priority (i.e. order) to each server? Simulation results verify that the proposed algorithm efficiently resolves the above problems and provides much better performance than conventional methods.

The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.

In this paper, we present a hierarchical multi-chip architecture which employs fully digital and word-parallel associative memories based on Hamming distance. High capacity scalability is critically important for associative memories since the required database capacity depends on the various applications. A multi-chip structure is most efficient for the capacity scalability as well as the standard memories, however, it is difficult for the conventional nearest-match associative memories. The present digital implementation is capable of detecting all the template data in order of the exact Hamming distance. Therefore, a hierarchical multi-chip structure is simply realized by using extra register buffers and an inter-chip pipelined priority decision circuit hierarchically embedded in multiple chips. It achieves fully chip- and word-parallel Hamming distance search with no throughput decrease, additional clock latency of O(log P), and inter-chip wires of O(P) in a P-chip structure. The feasibility of the architecture and circuit implementation has been demonstrated by post-layout simulations. The performance has been also estimated based on measurement results of a single-chip implementation.

Color histograms are effective for representing color visual features. However, the high dimensionality of feature vectors results in high computational cost. Several transformations, including singular value decomposition (SVD) and principal component analysis (PCA), have been proposed to reduce the dimensionality. In PCA, the dimensionality reduction is achieved by projecting the data to a subspace which contains most of the variance. As a common observation, the PCA basis function with the lowest frquency accounts for the highest variance. Therefore, the PCA subspace may not be the optimal one to represent the intrinsic features of data. In this paper, we apply independent component analysis (ICA) to extract the features in color histograms. PCA is applied to reduce the dimensionality and then ICA is performed on the low-dimensional PCA subspace. The experimental results show that the proposed method (1) significantly reduces the feature dimensions compared with the original color histograms and (2) outperforms other dimension reduction techniques, namely the method based on SVD of quadratic matrix and PCA, in terms of retrieval accuracy.

Most of system-on-chips (SOCs) have many memory cores. Diagnosis is often used to improve the yield of memories. Memory cores usually represent a significant portion of the chip area and dominate the yield of the chip. Memory diagnosis thus is one of key techniques for improving the yield and quality of SOCs. Content addressable memories (CAMs) are important components in many SOCs. In this paper we propose a three-phase diagnosis procedure for binary CAMs (BCAMs). The user can distinguish different types of BCAM-specific comparison and RAM faults and locate the faulty cells with the procedure. A March-like fault identification algorithm is also proposed. The algorithm can distinguish different types of faults--including typical RAM faults and BCAM-specific comparison faults. The algorithm requires 15N Read/Write operations and 2(N + B) Compare operations for an N B-bit BCAM. Analysis results show that the algorithm has 100% diagnostic resolution for the target faults.

In this paper, we propose a new content delivery platform on the ITS (Intelligent Transport Systems) road-vehicle communication system on the basis of ROF (Radio over Fiber). The platform is strongly motivated by the ROF communication system capabilities of (1) broadband access, (2) integrated multiple service transmission interface, and (3) simultaneous use of a single and downsized vehicle terminal shared among multiple services based on a multi-mode software radio system. Content is delivered on per reservation basis, as is carefully envisaged as a primary service which is subjected to immaturity of early ITS road-vehicle communication systems, and is provided in limited service areas such as parking on main highways. After the reservation, requested content is stored in a cache connected to a ROF local station via optical fiber. At the designated time, the content is delivered from the cache to a target terminal by way of the ROF local station at high-speed. It can also be done by moving the content from the cache to another cache depending on the target terminal location in a flexible and reliable manner, even if the target terminal could not reach the place at the time designated in the reservation. Such flexibility and reliability are required for consequent practical application, and are provided using information given in the reservations. We implement a preliminary system to evaluate the proposed platform from the viewpoints of (1) processing time from logging into the system for a reservation to delivering content to the target terminal and (2) amount of control traffic required for the delivery. The results show that the proposed platform in which content is delivered from a cache connected with a ROF local station distributed geographically is effective. We also evaluate content delivery throughput using the system connected with an actual ROF local station, and show that the effective throughput is 40 Mbps and the proposed platform is a promising ITS service platform. The paper concludes by discussing future study toward realizing a more promising and practical system.