In this paper, we present an image compression algorithm using two concepts, subdividing an image matrix and stratifying submatrices into FD-submatrices (feature distribution submatrices). According to the feature distribution and the view that an image can be decomposed into some feature layers, we generate a compression tree by setting up a logic process of decomposition and stratification. To get better compression ratios, the set of submatrices having one and zero as elements, including logic flag sequences is compressed by vector space theory.

In forthcoming home network environment, computation capability will be embedded invisibly in home appliances, sensors, walls, ceilings, and floors. People will conduct various tasks using multiple devices simultaneously without consciousness of using computers. In this paper, first, we propose an application model named Virtual Network Appliance (VNA) model which simplify and expand device utilization. In the model, each device has VNA runtime system and function objects, called VNA components, running on it. A user task is defined in an application called VNA which is a logical appliance consisting of abstract function requirements and a message graph among them. Second, we propose Virtual Plug&Play mechanism which is a dynamic service integration mechanism in VNA model implementation. When a user conducts a task, he/she makes a VNA runtime system on a user-side terminal load a VNA definition appropriate for the task. Virtual Plug&Play dynamically discovers required VNA components and establishes the message graph as defined. Since XML documents are used to describe a VNA, users can share and customize it easily. We call the device integration done by Virtual Plug&Play top-down integration, which existing middleware do not aim at. Finally, we show that Virtual Plug&Play affords practical performance for top-down integration by performance evaluation.

Currently, the most popular model in data compression theory is that of stationary ergodic sources. But there do exist sequences each of which is not emitted from any stationary ergodic source but can be compressed sufficiently by a certain algorithm. We estimate the size of the set of such sequences in terms of Hausdorff dimension.

A method for estimating complex permittivity of a material using a rectangular waveguide with a flange is presented by the finite difference time domain (FDTD) method. An advantage of the present method is that it is not necessary to vary the material structure in order to insert it into the waveguide. Therefore estimation errors related to the dimensions of the material are almost negligible. In this case, fluoridated rubber is chosen as the low-loss material. The comparison of the complex permittivity of the material determined by the present method with FDTD and the conventional waveguide method at 10 GHz is performed. It was confirmed that the present method is effective for estimating the complex permittivity under the condition that the length of the flange is about 50 mm (1.7λ) square.

This paper introduces a new approach based on the geographic nearest neighbors for constructing the Delaunay triangulation (a dual of the Voronoi diagram) of a set of n sites in the plane under the L1 metric. In general, there is no inclusion relationship between the Delaunay triangulation and the octant neighbor graph. We however find that under the L1 metric the octant neighbor graph contains at least one edge of each triangle in the Delaunay triangulation. By using this observation and employing a range tree scheme, we design an algorithm for constructing the Delaunay triangulation (thus the Voronoi diagram) in the L1 metric. This algorithm takes O(n log n) sequential time for constructing the Delaunay triangulation in the L1 metric. This algorithm can easily be parallelized, and takes O(log n) time with O(n) processors on a CREW-PRAM.

Conventional adaptive array antenna processing must access signals on all of the array antenna elements. However, because the low-cost electronically steerable passive array radiator (ESPAR) antenna only has a single-port output, all of the signals on the antenna elements cannot be observed. In this paper, a technique for adaptively controlling the loaded reactances on the passive radiators, thus forming both beam and nulls, is presented for the ESPAR antenna. The adaptive algorithm is based on the steepest gradient theory, where the reactances are sequentially perturbed to determine the gradient vector. Simulations show that the ESPAR antenna can be adaptive. The statistical performance of the output SIR of the ESPAR antenna is also given.

Fairness as defined in wireline network cannot be achieved in wireless packet networks due to the bursty and location-dependent channel errors of wireless link. Channel-state dependent scheduling and compensation mechanism for errored flows are generally employed to improve the fairness in wireless packet scheduling algorithms. Most of the wireless scheduling algorithms, however, have two common significant problems. One problem is that they operate incorrectly unless all flows have the same packet size. This is due to the incorrect lead-and-lag model and the swapping-based rough compensation mechanism of the algorithms. The other problem is the degradation of error-free flow during compensation. The root of the degradation is that the bandwidth for compensation cannot be reserved since it is very difficult to predict. In this paper, we introduce WGPS (Wireless General Processor Sharing) to define fairness in wireless networks and present PWGPS as a packetized algorithm of WGPS. In our method, lead and lag of all flows are defined in terms of virtual time which is flexible enough to deal with packet size differences. Further, compensation is done by increasing the service share of the errored flow to a predetermined amount Δ. This enables the maximum bandwidth for compensation can be estimated and thus reserved. Our method can be proved to achieve improved fairness as compared with the previous scheduling algorithms.

A gradient ascent learning algorithm of the Hopfield neural networks for graph planarization is presented. This learning algorithm uses the Hopfield neural network to get a near-maximal planar subgraph, and increases the energy by modifying parameters in a gradient ascent direction to help the network escape from the state of the near-maximal planar subgraph to the state of the maximal planar subgraph or better one. The proposed algorithm is applied to several graphs up to 150 vertices and 1064 edges. The performance of our algorithm is compared with that of Takefuji/Lee's method. Simulation results show that the proposed algorithm is much better than Takefuji/Lee's method in terms of the solution quality for every tested graph.

In a mobile computing environment, the characteristics of wireless communication and host mobility are important considerations in providing an efficient payment service. Currently, most payment systems were not intended for use in a mobile environment, and as such they inherently possess some inefficient properties. In this paper, we propose a new micropayment system (AMPS), designed for use in a mobile computing environment. AMPS reduces the computational load of mobile hosts by directing operations normally performed by the client to the static portion of the network. With AMPS, a client's request for goods goes to a TTP server, called the AMPS server, using only one message. The client can also be disconnected while the AMPS server deals with the merchant, reducing communication costs and power consumption. User privacy is protected by hiding the details of the payment to the AMPS server. The AMPS server can also provide client anonymity to merchants. Another advantage of AMPS is the provision of transaction atomicity by checking goods and money before forwarding to clients or merchants, and preserving all necessary information for any possible future disputes.

This paper describes a realtime 3D sound localization algorithm to be implemented with the use of a low power embedded DSP. A distinctive feature of this implementation approach is that the audible frequency band is divided into three, in accordance with the analysis of the sound reflection and diffraction effects through different media from a certain sound source to human ears. In the low, intermediate, and high frequency subbands, different schemes of the 3D sound localization are devised by means of an IIR filter, parametric equalizers, and a comb filter, respectively, so as to be run realtime on a low power embedded DSP. This algorithm aims at providing a listener with the 3D sound effects through headphones at low cost and low power consumption.

This paper proposes an automatic system which can perform the entire diagnostic process from the extraction of the liver to the recognition of a tumor. In particular, the proposed technique uses shape information to identify and recognize a lesion adjacent to the border of the liver, which can otherwise be missed. Because such an area is concave like a bay, morphological operations can be used to find the bay. In addition, since the intensity of a lesion can vary greatly according to the patient and the slice taken, a decision on the threshold for extraction is not easy. Accordingly, the proposed method extracts the lesion by means of a Fuzzy c-Means clustering technique, which can determine the threshold regardless of a changing intensity. Furthermore, in order to decrease any erroneous diagnoses, the proposed system performs a 3-D consistency check based on three-dimensional information that a lesion mass cannot appear in a single slice independently. Based on experimental results, these processes produced a high recognition rate above 91%.

This paper proposes a framework for building a customized comparison-shopping system in which the users are allowed to add their own shopping stores dynamically. In this framework, a shopping agent is implemented with a robust inductive learning method that automatically constructs wrappers for semi-structured online stores. During learning, strong biases assumed in many existing systems are weakened so that the real stores with reasonably complex document structures can be handled.

Tree task structures occur frequently in many applications where parallelization may be desirable. We present a formal treatment of non-preemptively scheduling task trees on distributed memory multiprocessors and show that the fundamental problems of scheduling (i) a task tree in absence of any inter-task communication on a fixed number of processors and (ii) a task tree with inter-task communication on an unbounded number of processors are NP-complete. For task trees that satisfy certain constraints, we present an optimal scheduling algorithm. The algorithm is shown optimal over a wider set of task trees than previous works.

An important goal in communication theory is to construct good minimum squared Euclidean distance (MSED) codes for transmission over additive white Gaussian noise (AWGN) channels. In this paper, a new construction method for the M-ary phase-shift-keyed (M-PSK) codes over the ring structure ZM, the ring of integers modulo M, with a good minimum Euclidean distance, is proposed. The proposed codes are linear when multiple coset leaders are considered. The characteristics and performance levels of the newly constructed codes are analyzed for code length up to n 8. It is found that the proposed codes compare favorably with Piret's codes and Graeffe's method codes on Gaussian channels in terms of decoding complexity, coding gain, and error performance.

A complex coefficient filter obtained by directly exchanging several reactance elements included in a real coefficient BPF for imaginary valued resistors is described. By using the proposed method, we obtain four varieties of complex coefficient filters. The stability problem is examined.

A digit-recurrence algorithm for cube rooting is proposed. In cube rooting, the digit-recurrence equation of the residual includes the square of the partial result of the cube root. In the proposed algorithm, the square of the partial result is kept, and the square, as well as the residual, is updated by addition/subtraction, shift, and multiplication by one or two digits. Different specific versions of the algorithm are possible, depending on the radix, the digit set of the cube root, and etc. Any version of the algorithm can be implemented as a sequential (folded) circuit or a combinational (unfolded) circuit, which is suitable for VLSI realization.

Using the chirped grating with temperature control, we demonstrated the adaptive dispersion compensation at 40 Gbit/s RZ transmission. The simple monitoring of the 40 GHz frequency component enables us to automatic control of the adaptive dispersion compensator.

In this paper, we present deterministic parallel algorithms for the convex hull of sorted points and their application to a related problem. The algorithms are proposed for the coarse grained multicomputer (CGM) model. We first propose a cost optimal parallel algorithm for computing the problem with a constant number of communication rounds for n/p p2, where n is the size of an input and p is the number of processors. Next we propose a cost optimal algorithm, which is more complicated, for n/p pε, where 0 < ε < 2. From the above two results, we can compute the convex hull of sorted points with O(n/p) computation time and a constant number of communication rounds for n/p pε, where ε > 0. Finally we show an application of our convex hull algorithms. We solve the convex layers for d lines in O((n log n)/p) computation time with a constant number of communication rounds. The algorithm is also cost optimal for the problem.

Adaptation of software components to the requirements is one of the key concerns in Component Based Software Development (CBSD). In this paper, we propose a formal approach to compose component based systems which are adaptable to the requirements. We focus on the functional aspects of software components and requirements, which are expressed in S-sorted functions. Those S-sorted functions are transformed into Colored Petri Nets (CPN) models in order to evaluate connectivity between the components, and to evaluate adaptability of composed systems to the requirements. The connectivity is measured based on colors or data types in CPN, while the adaptability is measured based on functional equivalency. We introduce simple glue codes to connect the components each other. The paper focuses on business applications, however the proposed approach can be applied to any other domains as far as the functional adaptability is concerned.

This paper proposes a bandwidth allocation scheme which improves degradation of communication quality due to handoffs in mobile multimedia networks. In general, a multimedia call consists of several component calls. For example, a video phone call consists of a voice call and a video call. In realistic environments, each component call included in one multimedia call may have different requirements for quality-of-service (QoS) from each other, and priorities among these component calls often exist with respect to importance for communications. When the available bandwidth is not enough for a handoff call, the proposed scheme eliminates a low priority component call and defers bandwidth allocation for a component call whose delay related QoS is not strict. Moreover, in the allocation, the scheme gives priority to new calls and handoff calls over a deferred call and also performs bandwidth reallocation to eliminated component calls. By computer simulation, we evaluate the performance such as call dropping probability and show effectiveness of the proposed scheme.