This paper presents a method of scalable lossless image compression by means of lossy coding. A progressive decoding capability and a full decoding for the lossless rendition are equipped with the losslessly encoded bit stream. Embedded coding is applied to large-amplitude coefficients in a wavelet transform domain. The other wavelet coefficients are encoded by a context-based entropy coding. The proposed method slightly outperforms JPEG-LS in lossless compression. Its rate-distortion performance with respect to progressive decoding is close to that of JPEG2000. The spatial scalability with respect to resolution is also available.

In this letter, we propose a video traffic model based on a class of stochastic processes, which we call truncated GeoY/G/∞ input processes. Group of picture (GOP) size traces are modeled by truncated GeoY/G/∞ input process with gamma-distributed batch sizes Y and Weibull-like autocorrelation function. With full-length MPEG-4 video traces in QCIF, we run simulations to show that our proposed model estimates packet loss ratios at various traffic loads more accurately than existing modeling methods.

A compact model is proposed for accurately incorporating effects of STI (shallow trench isolation) stress into post-layout simulation by making layout-dependent corrections to SPICE model parameters. The model takes in-plane (longitudinal and transverse) and normal components of the layout-dependent stress into account, and model formulas are devised from physical considerations. Not only can the model handle the shape of the active-area of any MOSFET conforming to design rules, but also considers distances to neighboring active-areas. Extraction of geometrical parameters from the layout can be performed by standard LVS (layout versus schematic) tools, and the corrections can subsequently be back-annotated into the netlist. The paper spells out the complete formulation by presenting expressions for the mobility and the threshold voltage explicitly by way of example. The model is amply validated by comparisons with experimental data from 90 nm- and 65 nm-CMOS technologies having the channel orientations of, respectively, <110> and <100>, both on a (100) surface. The worst-case standard errors turn out to be as small as 1.7% for the saturation current and 8 mV for the threshold voltage, as opposed to 20% and 50 mV without the model. Since device characteristics variations due to STI stress constitute a significant part of what have conventionally been treated as random variations, use of the proposed model could enable one to greatly narrow the guardbands required to guarantee a desired yield, thereby facilitating design closure.

"Dive into the Movie (DIM)" is a name of project to aim to realize a world innovative entertainment system which can provide an immersion experience into the story by giving a chance to audience to share an impression with his family or friends by watching a movie in which all audience can participate in the story as movie casts. To realize this system, several techniques to model and capture the personal characteristics instantly in face, body, gesture, hair and voice by combining computer graphics, computer vision and speech signal processing technique. Anyway, all of the modeling, casting, character synthesis, rendering and compositing processes have to be performed on real-time without any operator. In this paper, first a novel entertainment system, Future Cast System (FCS), is introduced which can create DIM movie with audience's participation by replacing the original roles' face in a pre-created CG movie with audiences' own highly realistic 3D CG faces. Then the effects of DIM movie on audience experience are evaluated subjectively. The result suggests that most of the participants are seeking for higher realism, impression and satisfaction by replacing not only face part but also body, hair and voice. The first experimental trial demonstration of FCS was performed at the Mitsui-Toshiba pavilion of the 2005 World Exposition in Aichi Japan. Then, 1,640,000 people have experienced this event during 6 months of exhibition and FCS became one of the most popular events at Expo.2005.

This paper proposes an accurate modeling method of the copper interconnect cross-section in which the width and thickness dependence on layout patterns and density caused by processes (CMP, etching, sputtering, lithography, and so on) are fully incorporated and universally expressed. In addition, we have developed specific test patterns for the model parameters extraction, and an efficient extraction flow. We have extracted the model parameters for 0.15 µm CMOS using this method and confirmed that 10% τpd error normally observed with conventional LPE (Layout Parameters Extraction) was completely dissolved. Moreover, it is verified that the model can be applied to more advanced technologies (90 nm, 65 nm and 55 nm CMOS). Since the interconnect delay variations due to the processes constitute a significant part of what have conventionally been treated as random variations, use of the proposed model could enable one to greatly narrow the guardbands required to guarantee a desired yield, thereby facilitating design closure.

In this paper, we investigate minimum mean absolute error (mmae) predictors for lossless image coding. In some prediction-based lossless image coding systems, coding performance depends largely on the efficiency of predictors. In this case, minimum mean square error (mmse) predictors are often used. Generally speaking, these predictors have a problem that outliers departing very far from a regression line are conspicuous enough to obscure inliers. That is, in image compression, large prediction errors near edges cause the degradation of the prediction accuracy of flat areas. On the other hand, mmae predictors are less sensitive to edges and provide more accurate prediction for flat areas than mmse predictors. At the same time, the prediction accuracy of edge areas is brought down. However, the entropy of the prediction errors based on mmae predictors is reduced compared with that of mmse predictors because general images mainly consist of flat areas. In this study, we adopt the Laplacian and the Gaussian function models for prediction errors based on mmae and mmse predictors, respectively, and show that mmae predictors outperform conventional mmse-based predictors including weighted mmse predictors in terms of coding performance.

We have developed a visual entertainment system called "Future Cast" which enables anyone to easily participate in a pre-recorded or pre-created film as an instant CG movie star. This system provides audiences with the amazing opportunity to join the cast of a movie in real-time. The Future Cast System can automatically perform all the processes required to make this possible, from capturing participants' facial characteristics to rendering them into the movie. Our system can also be applied to any movie created using the same production process. We conducted our first experimental trial demonstration of the Future Cast System at the Mitsui-Toshiba pavilion at the 2005 World Exposition in Aichi Japan.

Random variations in Id-Vg characteristics of MOS transistors in an LSI chip are shown to be concisely characterized by using only 3 transistor parameters (Vth, β0, vSAT) in the MOS level 3 SPICE model. Statistical analyses of the transistor parameters show that not only the threshold voltage variation, ΔVth, but also the current factor variation, Δβ0, independently induces Id-variation, and that Δβ0 is negatively correlated with the saturation velocity variation, ΔvSAT. Using these results, we have proposed a simple method that effectively takes the correlation between parameters into consideration when creating statistical model parameters for designing a circuit. Furthermore, we have proposed a sensitivity analysis methodology for estimating the process window of SRAM cell operation taking transistor variability into account. By applying the concise statistical model parameters to the sensitivity analysis, we are able to obtain valid process windows without the large volume of data-processing and long turnaround time associated with the Monte Carlo simulation. The process window was limited not only by ΔVth, but also by Δβ0 which enhanced the failure region in the process window by 20%.

A design methodology optimizing constant-charge-injection programming (CCIP) for assist-gate (AG)-AND flash memories is proposed. Transient circuit simulations using an array-level model including lucky electron model (LEM) current source describing hot electron physics enables a concept design over the whole memory-string in advance of wafer manufacturing. The dynamic programming behaviors of various CCIP sequences, obtained by circuit simulations using the model is verified with the measurement results of 90-nm AG-AND flash memory, and we confirmed that the simulation results sufficiently agree with the measurement, considering the simulation results give optimum bias AG voltage approximately within 0.2 V error. Then, we have applied the model to a conceptual design and have obtained optimum bit line capacitance value and CCIP sequence those are the most important issues involved in high-throughput programming for an AG-AND array.

In this paper, we present and verify a new chip-package co-modeling and simulation approach for a low-noise chip-package hierarchical power distribution network (PDN) design. It is based on a hierarchical modeling to combine distributed circuit models at both chip-level PDN and package-level PDN. In particular, it includes all on- and off-chip parasitic circuit elements in the hierarchical PDN with a special consideration on on-chip decoupling capacitor design and placement inside chip. The proposed hierarchical PDN model was successfully validated with good correlations and subsequent analysis to a series of Z11 and Z21 PDN impedance measurements with a frequency range from 1 MHz to 3 GHz. Using the proposed model, we can analyze and estimate the performance of the chip-package hierarchical PDN as well as can predict the effect of high frequency electromagnetic interactions between the chip-level PDN and the package-level PDN. Furthermore, we can precisely anticipate PDN resonance frequencies, noise generation sources, and noise propagation paths through the multiple levels in the hierarchical PDN.

In a Cognitive Radio system, it is essential to recognize and avoid sources of interference signals. This paper describes a study on a location sensing scheme for interference signals, which utilizes multi-beam phased array antenna for cognitive wireless networks. This paper also elucidates its estimation accuracy of the interference location for the radio communication link using an OFDM signal such as WiMAX. Furthermore, we use the frequency spectrum of the received OFDM interference signal, to create a method that can estimate the propagation status. This spectrum can be monitored by using a software defined radio receiver.

In this paper we propose a discrete program-size dependent software reliability growth model flexibly describing the software failure-occurrence phenomenon based on a discrete Weibull distribution. We also conduct model comparisons of our discrete SRGM with existing discrete SRGMs by using actual data sets. The program size is one of the important metrics of software complexity. It is known that flexible discrete software reliability growth modeling is difficult due to the mathematical manipulation under a conventional modeling-framework in which the time-dependent behavior of the cumulative number of detected faults is formulated by a difference equation. Our discrete SRGM is developed under an existing unified modeling-framework based on the concept of general order-statistics, and can incorporate the effect of the program size into software reliability assessment. Further, we discuss the method of parameter estimation, and derive software reliability assessment measures of our discrete SRGM. Finally, we show numerical examples of discrete software reliability analysis based on our discrete SRGM by using actual data.

This paper presents a study to estimate the composition of an electric load, i.e. to determine the amount of each load class by the direct measurements of the total electric current waveform from instrument reading. Kalman filter algorithm is applied to estimate the electric load composition on a consumer side of a distributed power system. The electric load supplied from the different voltage level by using a non-ideal delta-wye transformer is also studied with consideration of the practical environment for a distributed power system.

Chip-level substrate coupling analysis uses F-matrix computation with slice-and-stack execution to include highly concentrated substrate resistivity gradient. The technique that has been applied to evaluation of device-level isolation structures against substrate coupling is now developed into chip-level substrate noise analysis. A time-series divided parasitic capacitance (TSDPC) model is equivalent to a transition controllable noise source (TCNS) circuit that captures noise generation in a CMOS digital circuit. A reference structure incorporating TCNS circuits and an array of on-chip high precision substrate noise monitors provides a basis for the verification of chip-level analysis of substrate coupling in a given technology. Test chips fabricated in two different wafer processings of 0.30-µm and 0.18-µm CMOS technologies demonstrate the universal availability of the proposed analysis techniques. Substrate noise simulation achieves no more than 3 dB discrepancy in peak amplitude compared to measurements with 100-ps/100-µV resolution, enabling precise evaluation of the impacts of the distant placements of sensitive devices from sources of noise as well as application of guard ring/band structures.

A Verilog-AMS model of a fractional-N frequency synthesizer is presented that is capable of predicting spurious tones as well as noise and jitter performance. The model is based on a voltage-domain behavioral simulation. Simulation efficiency is improved by merging the voltage controlled oscillator (VCO) and the frequency divider. Due to the benefits of Verilog-AMS, the ΔΣ modulator which is incorporated in the synthesizer is modeled in a fully digital way. This makes it accurate enough to evaluate how the performance of the frequency synthesizer is affected by cyclic behavior in the ΔΣ modulator. The spur-minimizing effect of an odd initial condition on the first accumulator of the ΔΣ modulator is verified. Sequence length control and its effect on the fractional-N frequency synthesizer are also discussed. The simulated results are in agreement with prior published data on fractional-N synthesizers and with new measurement results.

There are several methods for generating multi-fractal time series, but the origin of the multi-fractality is not discussed so far. This paper deals with the multi-fractality analysis of time series in an artificial stock market generated by multi-agent systems based on the Genetic Programming (GP) and its applications to feature extractions. Cognitive behaviors of agents are modeled by using the GP to introduce the co-evolutionary (social) learning as well as the individual learning. We assume five types of agents, in which a part of the agents prefer forecast equations or forecast rules to support their decision making, and another type of the agents select decisions at random like a speculator. The agents using forecast equations and rules usually use their own knowledge base, but some of them utilize their public (common) knowledge base to improve trading decisions. For checking the multi-fractality we use an extended method based on the continuous time wavelet transform. Then, it is shown that the time series of the artificial stock price reveals as a multi-fractal signal. We mainly focus on the proportion of the agents of each type. To examine the role of agents of each type, we classify six cases by changing the composition of agents of types. As a result, in several cases we find strict multi-fractality in artificial stock prices, and we see the relationship between the realizability (reproducibility) of multi-fractality and the system parameters. By applying a prediction method for mono-fractal time series as counterparts, features of the multi-fractal time series are extracted. As a result, we examine and find the origin of multi-fractal processes in artificial stock prices.

We present a linear-time algorithm for treating collision response of articulated rigid bodies in physically based modeling. By utilizing the topology of articulated rigid bodies and the property of linear equations, our method can solve in linear time the system of linear equations that is crucial for treating collision response.

We survey traffic matrix models, whose elements represent the traffic demand between source-destination pair nodes. Modeling the traffic matrix is useful for multilayer Traffic Engineering (TE) in IP optical networks. Multilayer TE techniques make the network so designed flexible and reliable. This is because it allows reconfiguration of the virtual network topology (VNT), which consists of a set of several lower-layer (optical) paths and is provided to the higher layer, in response to fluctuations (diurnal) in traffic demand. It is, therefore, important to synthetically generate traffic matrices as close to the real ones as possible to maximize the performance of multilayer TE. We compare several models and clarify their applicability to VNT design and control. We find that it is difficult in practice to make an accurate traffic matrix with conventional schemes because of the high cost for data measurement and the complicated calculations involved. To overcome these problems, we newly introduce a simplified traffic matrix model that is practical; it well mirrors real networks. Next, this paper presents our developed server, the IP Optical TE server. It performs multilayer TE in IP optical networks. We evaluate the effectiveness of multilayer TE using our developed IP Optical server and the simplified traffic matrix. We confirm that multilayer TE offers significant CAPEX savings. Similarly, we demonstrate basic traffic control in IP optical networks, and confirm the dynamic control of the network and the feasibility of the IP Optical TE server.

In order to prepare the health care industry for an increasingly aging society, a ubiquitous health care infrastructure is certainly needed. In a ubiquitous computing environment, it is important that all applications and middleware should be executed on an embedded system. To provide personalized health care services to users anywhere and anytime, a context-aware framework should convert low-level context to high-level context. Therefore, ontology and rules were used in this research to convert low-level context to high-level context. In this paper, we propose context modeling and context reasoning in a context-aware framework which is executed on an embedded wearable system in a ubiquitous computing environment for U-HealthCare. The objective of this research is the development of the standard ontology foundation for health care services and context modeling. A system for knowledge inference technology and intelligent service deduction is also developed in order to recognize a situation and provide customized health care service. Additionally, the context-aware framework was tested experimentally.

We developed a comprehensive simulation system for evaluating satellite-based navigation services in highly built-up areas; the system can accommodate Global Positioning System (GPS) multipath effects, as well as line-of-sight (LOS) and dilution of position (DOP) issues. For a more realistic simulation covering multipath and diffracted signal propagations, a 3D-ray tracing method was combined with a satellite orbit model and three-dimensional (3D) geographic information system (GIS) model. An accuracy estimation model based on a 3D position determination algorithm with a theoretical delay-locked loop (DLL) correlation computation could measure the extent to which multipath mitigation improved positioning accuracy in highly built-up areas. This system could even capture the multipath effect from an invisible satellite, one of the greatest factors in accuracy deterioration in highly built-up areas. Further, the simulation results of satellite visibility, DOP, and multipath occurrence were mapped to show the spatial distribution of GPS availability. By using object-oriented programming, our simulation system can be extended to other global navigation satellite systems (GNSSs) simply by adding the orbital information of the corresponding GNSS satellites. We demonstrated the applicability of our simulation system in an experimental simulation for Shinjuku, an area of Tokyo filled with skyscrapers.