An overview on the physics and circuit design oriented background of the advanced compact model HICUM is presented. Related topics such as the approach employed for geometry scaling and parameter extraction are briefly discussed. A model hierarchy is introduced, that addresses a variety of requirements encountered during the increasingly complicated task of designing analog and high-frequency circuits.

Embedded systems are used in broad fields. They are one of the indispensable and fundamental technologies in a highly informative society in recent years. As embedded systems are large-scale and complicated, it is prosperous to design and develop a system LSI (Large Scale Integration). The structure of the system LSI has been increasing complexity every year. The degree of improvement of its design productivity has not caught up with the degree of its complexity by conventional methods or techniques. Hence, an idea for the design of a system LSI which has the flow of describing specifications of a system in UML (Unified Modeling Language) and then designing the system in a system level language has already proposed. It is important to establish how to convert from UML to a system level language in specification description or design with the idea. This paper proposes, extracts and verifies transformation rules from UML to SpecC which is one of system level languages. SpecC code has been generated actually from elements in diagrams in UML based on the rules. As an example to verify the rules, "headlights control system of a car" is adopted. SpecC code has been generated actually from elements in diagrams in UML based on the rules. It has been confirmed that the example is executed correctly in simulations. By using the transformation rules proposed in this paper, specification and implementation of a system can be connected seamlessly. Hence, it can improve the design productivity of a system LSI and the productivity of embedded systems.

This paper presents a new model which computes the deformation and the feedback force of high-resolution biomedical volumetric objects consisting of hundreds of thousands of volume elements. The main difficulty in the simulation of these high-resolution volumetric objects is to compute and generate stable feedback force from the objects within a haptic update time (1 msec). In our model, springs are used in order to represent material properties of volume elements and cylinders are used to activate corresponding springs according to the amount of deformation. Unlike in a mass-spring model, springs in our model have constraint conditions. In our model, the deformation is calculated locally and then is propagated outward through object's volume as if a chain is pulled or pushed. The deformed configuration is then used to compute the object's internal potential energy that is reflected to the user. The simple nature of our model allows the much faster calculation of the deformation and the feedback force from the volumetric deformable object than the conventional model (an FEM or a mass-spring model). Experiments are conducted with homogenous and non-homogenous volumetric cubic objects and a volumetric human liver model obtained from CT data at a haptic update rate of 1000 Hz and a graphic update rate of 100 Hz to show that our model can be utilized in the real-time volume haptic rendering. We verify that our model provides a realistic haptic feeling for the user in real time through comparative study.

The aim of this paper is to propose a modeling of corporate knowledge in cyberworlds. An enterprise is considered in the framework of multiagent methodology as a distributed computational system. The Agent-Oriented Abstraction paradigm was proposed earlier to describe in a fully generic way agents and societies of agents. In this paper, we are investigating the application of this paradigm to the abstract modeling of corporate knowledge, extending the scope of traditional knowledge management approaches. We show that such an abstraction mechanism leads to very practical applications for cyberworlds whether on the web or on any other medium. Our approach covers the broader possible scope of corporate knowledge, emphasizing the distributivity and autonomy of agents within cyber systems. This approach can be further used to better simulate and support knowledge management processes.

This paper describes a high-speed D/A converter design for mixed-mode systems. Capacitive coupling induced by inter-chip interconnects and time-variant clock skew between ICs should be considered for mixed-mode systems, and on-chip interconnects should be treated as transmission lines in the circuit simulation as operating speed reaches GHz range. A robust FIFO built in the D/A converter can absorb input data timing variance due to the capacitive coupling and the clock timing skew, the worst-case margin of which is 1.5TCLK. Distributed RLC transmission line models for on-chip interconnects produce accurate simulation results at 1 GHz clock frequency over lumped models. For optimized D/A converter design, behavioral modeling methodology is also presented in this paper. Measurement results verify the accuracy of the on-chip interconnect and behavioral models.

Web browsing task is based on depth-first searching scheme, so that searching relevant information from Web may be very tedious. In this paper, we propose personal browsing assistant system based on user intentions modeling. Before explicitly requested by a user, this system can analyze the prefetched resources from the hyperlinked Webpages and compare them with the estimated user intention, so that it can help him to make a better decision like which Webpage should be requested next. More important problem is the semantic heterogeneity between Web spaces. It makes the understandability of locally annotated resources more difficult. We apply semantic annotation, which is a transcoding procedure with the global ontology. Therefore, each local metadata can be semantically enriched, and efficiently comparable. As testing bed of our experiment, we organized three different online clothes stores whose images are annotated by semantically heterogeneous metadata. We simulated virtual customers navigating these cyberspaces. According to the predefined preferences of customer models, they conducted comparison-shopping. We have shown the reasonability of supporting the Web browsing, and its performance was evaluated as measuring the total size of browsed hyperspace.

We present an approach and a web-based system implementation for modeling shapes using real distance functions. The system consists of an applet supporting the HyperFun modeling language. The applet is extended with primitives defined by Euclidean distance from a point to the surface of the shape. Set-theoretic operations (union, intersection, difference) that provide an approximation of the Euclidean distance to a shape built in a constructive way are introduced. Such operations have a controllable error of the exact Euclidean distance to the shape and preserve C1 continuity of the overall function, which is an important condition for further operations and applications. The proposed system should help model various shapes, store them in a concise form, and exchange them easily between different entities on a network. The applet offers also the possibility to export the models defined in the HyperFun language to other formats for raytracing or rapid prototyping.

We have developed a model for circuit-simulation which describes the MOSFET region from pinch-off to drain contact based on the surface potential. The model relates the surface-potential increase beyond the pinch-off point to the channel/drain junction profile by applying the Gauss law with the assumption that the lateral field is greater than the vertical one. Explicit equations for the lateral field and the pinch-off length are obtained, which take the potential increase in the drain overlap region into account. The model, as implemented into a circuit simulator, correctly reproduces measured channel conductance and overlap capacitance for 100 nm pocket-implant technologies as a function of bias condition and gate length.

This paper investigates the effectiveness of the DAEM (Deterministic Annealing EM) algorithm in acoustic modeling for speaker and speech recognition. Although the EM algorithm has been widely used to approximate the ML estimates, it has the problem of initialization dependence. To relax this problem, the DAEM algorithm has been proposed and confirmed the effectiveness in artificial small tasks. In this paper, we applied the DAEM algorithm to practical speech recognition tasks: speaker recognition based on GMMs and continuous speech recognition based on HMMs. Experimental results show that the DAEM algorithm can improve the recognition performance as compared to the standard EM algorithm with conventional initialization algorithms, especially in the flat start training for continuous speech recognition.

This paper describes the modeling of various emotional expressions and speaking styles in synthetic speech using HMM-based speech synthesis. We show two methods for modeling speaking styles and emotional expressions. In the first method called style-dependent modeling, each speaking style and emotional expression is modeled individually. In the second one called style-mixed modeling, each speaking style and emotional expression is treated as one of contexts as well as phonetic, prosodic, and linguistic features, and all speaking styles and emotional expressions are modeled simultaneously by using a single acoustic model. We chose four styles of read speech -- neutral, rough, joyful, and sad -- and compared the above two modeling methods using these styles. The results of subjective evaluation tests show that both modeling methods have almost the same accuracy, and that it is possible to synthesize speech with the speaking style and emotional expression similar to those of the target speech. In a test of classification of styles in synthesized speech, more than 80% of speech samples generated using both the models were judged to be similar to the target styles. We also show that the style-mixed modeling method gives fewer output and duration distributions than the style-dependent modeling method.

An efficient, scalable speech recognition architecture combining topic detection and topic-dependent language modeling is proposed for multi-domain spoken language systems. In the proposed approach, the inferred topic is automatically detected from the user's utterance, and speech recognition is then performed by applying an appropriate topic-dependent language model. This approach enables users to freely switch between domains while maintaining high recognition accuracy. As topic detection is performed on a single utterance, detection errors may occur and propagate through the system. To improve robustness, a hierarchical back-off mechanism is introduced where detailed topic models are applied when topic detection is confident and wider models that cover multiple topics are applied in cases of uncertainty. The performance of the proposed architecture is evaluated when combined with two topic detection methods: unigram likelihood and SVMs (Support Vector Machines). On the ATR Basic Travel Expression Corpus, both methods provide a significant reduction in WER (9.7% and 10.3%, respectively) compared to a single language model system. Furthermore, recognition accuracy is comparable to performing decoding with all topic-dependent models in parallel, while the required computational cost is much reduced.

Current literature on input buffer management reveals that, in representative ATM networks under highly bursty traffic conditions, the fuzzy thresholding approach yields lower cell loss rate at the cost of lower throughput. Also, under less bursty traffic, the traditional fixed thresholding approach achieves higher throughput at the expense of higher cell loss rate. The integration of these two properties into practice is termed adaptive dynamic buffer management (ADBM) approach for input buffers and its assessment is the objective of this paper. The argument is that, given that the traffic conditions are constantly changing, to achieve efficiency during actual operation, the network control must dynamically switch, at every ATM switch, under the call processor's control, between the two input buffer management techniques, dictated by the nature of the traffic at the inputs of the corresponding switch. The need to involve the call processor marks the first effort in the literature to dynamically configure input buffer management architectures at the switch fabric level under higher level call processor control. It stems from the fact that the switch fabric operates very fast and cannot engage in complex decision making without incurring stiff penalty. To achieve this goal, the network control needs knowledge of the burstiness of the traffic at the inputs of every ATM switch. The difficulties with this need are two-fold. First, it is not always easy to obtain the traffic model and model parameters for a specific user's call. Second, even where the traffic model and the model parameters are known for a specific user's call, this knowledge is valid only at the source switch where the user interfaces with the network. At all other switches in the network, the cells of the traffic in question interact asynchronously with the cells from other traffic sources and are subject to statistical multiplexing. Thus, to obtain the exact nature of the composite traffic at the inputs of any ATM switch, is a challenge. Conceivably, one may determine the burstiness by counting the number of cells incurred at the inputs of an ATM switch over a defined time interval. The challenge posed by this proposition lies in the very definition of burstiness in that the time interval must approach, in the limit, zero or the resolution of time in the network. To address this challenge, first, a 15-node representative ATM network is modeled in an asynchronous, distributed simulator and, second, simulated on a network of workstations under realistic traffic stimuli. Third, burstiness indices are measured for the synthetic, stochastic traffic at the inputs of every ATM switch as a function of the progress of simulation for different choices of time interval values, ranging from 20,000 timesteps down to 1,000 timesteps. A timestep equals 2.73 µs. Results reveal that consistent burstiness indices are obtained for interval choices between 1,000 and 5,000 timesteps and that a burstiness index of 25, measured at 3,000 timestep interval, constitutes a reasonable and practical threshold value that distinguishes highly bursty traffic that warrants the use of the fuzzy thresholding approach from less bursty traffic that can benefit from the fixed thresholding scheme. A comparative performance analysis of ADBM yields the following. For pure fixed and pure fuzzy thresholding schemes, the throughputs are at 73.88% and 71.53% while the cell drop rates are at 4.31% and 2.44%,respectively. For the ADBM approach, where the input buffer management alternates at each individual ATM switch between the fixed and fuzzy schemes, governed by measured burstiness index threshold of 25 for a 3,000 timestep interval, the throughput is 74.77%, which is higher than even the pure fixed scheme while the cell drop rate is 2.21% that is lower than that of the pure fuzzy scheme. In essence, ADBM successfully integrates the best characteristics of the fuzzy and fixed thresholding schemes.

Synthetic speech usually suffers from bad F0 contour surface. The prediction of the underlying pitch targets robustly relies on the quality of the predicted prosodic structures, i.e. the corresponding sequences of tones and breaks. In the present work, we have utilized a linguistically enriched annotated corpus to build data-driven models for predicting prosodic structures with increased accuracy. We have then used a linear regression approach for the F0 modeling. An appropriate XML annotation scheme has been introduced to encode syntax, grammar, new or already given information, phrase subject/object information, as well as rhetorical elements in the corpus, by exploiting a Natural Language Generator (NLG) system. To prove the benefits from the introduction of the enriched input meta-information, we first show that while tone and break CART predictors have high accuracy when standing alone (92.35% for breaks, 87.76% for accents and 99.03% for endtones), their application in the TtS chain degrades the Linear Regression pitch target model. On the other hand, the enriched linguistic meta-information minimizes errors of models leading to a more natural F0 surface. Both objective and subjective evaluation were adopted for the intonation contours by taking into account the propagated errors introduced by each model in the synthesis chain.

This letter presents a method to simulate a phase-included UWB channel impulse responses for a given indoor channel. In this method we decompose a UWB pulse into a finite number of spectral components. This enables the received signal to be determined by the sum of the convolutions between each spectral component and a corresponding frequency-dependent UWB channel impulse response. The ray-tracing algorithm is applied to calculate the amplitude and the phase of each frequency-dependent channel impulse response. Based on the calculated results, we finally show the simulation of the UWB channel impulse response.

A systematic experimental and modeling study is reported, which characterizes the low-frequency noise spectrum of 100 nm-MOSFETs accurately. Two kinds of measured spectra are observed: 1/f and non-1/f spectra. The non-1/f spectrum is analysed by forward and backward measurements with exchanged source and drain, and shown to be due to a randomly distributed inhomogeneity of the trap density along the channel and within the gate oxide. By averaging the spectra of identical MOSFETs on a wafer the measured non-1/f noise spectra reduce to a 1/f characteristics. On the basis of these measurement data a noise model for circuit simulation is developed, which reproduces the low-frequency noise spectrum with a single model parameter for all gate lengths and under any bias conditions.

This paper proposes a new robust adaptive processing algorithm that is based on the extended least squares (ELS) method with running spectrum filtering (RSF). By utilizing the different characteristics of running spectra between speech signals and noise signals, RSF can retain speech characteristics while noise is effectively reduced. Then, by using ELS, autoregressive moving average (ARMA) parameters can be estimated accurately. In experiments on real speech contaminated by white Gaussian noise and factory noise, we found that the method we propose offered spectrum estimates that were robust against additive noise.

A new analytical approach which reveals relationships between resonator parameters (unloaded Q-factor, coupling coefficient, and loaded Q-factor) and phase noise in microwave negative-resistance oscillators is presented. On the basis of Kurokawa's theory, this approach derives analytical expressions for the phase noise as a function of the resonator parameters (with particular emphasis on the coupling coefficient). Two types of negative-resistance oscillators--classified according to the manner in which the resonator is used in a circuit--are analyzed. These analyses use realistic circuit configurations and design procedures. The passive network connecting the active device and the resonator, which is shown to have important effects on the above-mentioned relationship, is taken into account. Validity of the new approach is verified through harmonic-balance simulations. The presented analytical approach can provide useful guidelines for choosing the resonator parameters, especially the value of the coupling coefficient, when designing microwave negative-resistance oscillators.

This article introduces a novel approach to model phonology and morphosyntax in morpheme unit-based speech recognizers. The proposed methods are evaluated on a Hungarian newspaper dictation task that requires modeling over 1 million different word forms. The architecture of the recognition system is based on the weighted finite-state transducer (WFST) paradigm. The vocabulary units used in the system are morpheme-based in order to provide sufficient coverage of the large number of word-forms resulting from affixation and compounding. Besides the basic pronunciation model and the morpheme N-gram language model we evaluate a novel phonology model and the novel stochastic morphosyntactic language model (SMLM). Thanks to the flexible transducer-based architecture of the system, these new components are integrated seamlessly with the basic modules with no need to modify the decoder itself. We compare the phoneme, morpheme, and word error-rates as well as the sizes of the recognition networks in two configurations. In one configuration we use only the N-gram model while in the other we use the combined model. The proposed stochastic morphosyntactic language model decreases the morpheme error rate by between 1.7 and 7.2% relatively when compared to the baseline trigram system. The proposed phonology model reduced the error rate by 8.32%. The morpheme error-rate of the best configuration is 18% and the best word error-rate is 22.3%.

This paper presents CrtSmile--a CAD tool for the automatic extraction of layout-dependent substrate effects for RF MOSFET modeling. CrtSmile incorporates a new scalable substrate model, which depends not only on the geometric layout information of a transistor (the number of gate fingers, finger width, channel length and bulk contact location), but also on the transistor layout and bulk patterns. We show that this model is simple to extract and has good agreement with measured data for a 0.35 µm CMOS process. CrtSmile reads in the layout information of RF transistors in the CIF/GDSII format, performs a pattern-based layout extraction to recognize the transistor layout and bulk patterns. A scalable layout-dependent substrate model is automatically generated and attached to the standard BSIM3 device model as a sub-circuit for use in circuit simulation. A low noise amplifier is evaluated with the proposed CrtSmile tool, showing the importance of layout effects for RF transistor substrate modeling.

Most traditional board and card games, such as Chess, Chinese Chess, Go, Chinese Mahjong, Hearts, Bridge, etc., share the same playing model: Players play around tables using physical objects such as cards and may hold objects in their own private areas, e.g., players hold cards in their own hands in Bridge. In this paper, this model is called the play-on-table (POT) game model and these games following the model are called POT games. The research of this paper is summarized as follows. First, formalize the definition of the POT game model. Second, present some game systems to allow players to design and play new POT games. Third, prove that these game systems are general for all POT games. Finally, in order to demonstrate the theory, practically implement one of the general game systems that allows players to design and play new POT games in a what-you-see-is-what-you-get (WYSIWYG) manner.