Framework technology is one of the promising approaches to reuse effectively software and its key issues are 1) to select the suitable frameworks for the software requirements specification, and 2) to fill the suitable hot spots with application-specific codes (customization). This paper proposes a new technique for automated support of the above issues by using labeled transition systems (LTSs) together with metrics technique. We model the behavior of the frameworks and the system behavior specified in the requirements specification by using two LTSs respectively. By establishing bisimilar relationship between the two LTSs, we check whether the behavior of the framework can match to the requirements and explore how to fill its hot spots. This process is done by means of constructing a graph to extract the bisimilar relationships, and each path of the graph denotes one of the implementations of the requirements by the framework. We attach some measures to the LTS of the framework, such as the number of the hot spots to be filled and the number of the parameters to be set up when filling the corresponding hot spot. These measures are used to estimate developer's efforts in filling the hot spots for each implementation, i.e. for each path of the graph. The result of estimating the efforts guides the developers to select the implementation, and the structure of the application-specific codes to be filled in can be automatically generated from the selected implementation. Furthermore we discuss case studies in the area of Web application, where Struts and Turbine can be used.

This paper proposes a robust fuzzy integral controller for output regulating a class of affine nonlinear systems subject to a bias reference to the origin. First, a common biased fuzzy model is introduced for a class of continuous/discrete-time affine nonlinear systems, such as dc-dc converters, robotic systems. Then, combining an integrator and parallel distributed compensators, the fuzzy integral regulator achieves an asymptotic regulation. Moreover, when considering disturbances or unstructured certainties, a virtual reference model is presented and provides a robust gain design via LMI techniques. In this case, H∞ performances is guaranteed. Note that the information regarding the operational point and bias terms are not required during the controller implementation. Thus, the controller can be applied to a multi-task regulation. Finally, three numerical simulations show the expected results.

Immune system protects living body from various attacks by foreign invades. Based on the immune response principles, we propose an improved lateral interaction artificial immune system model in this paper. Considering that the different epitopes on the surface of antigen can be recognized by a set of different paratopes expressed on the surface of immune cells, we build a neighborhood set that consists of immune cells with different affinities to a certain input antigen. We update all the weights of the immune cells located in neighborhood set according to their affinities. Simulations on noisy pattern recognition illustrate that the proposed artificial immune system model has stronger noise tolerance ability and is more effective at recognizing noisy patterns than that of our previous models.

This letter presents robustness bounds (RBs) for receding horizon controls (RHCs) of uncertain systems. The proposed RBs are obtained easily by solving convex problems represented by linear matrix inequalities (LMIs). We show, by numerical examples, that the RHCs can guarantee robust stabilization for a larger class of uncertain systems than conventional linear quadratic regulators (LQRs).

The homomorphic property of the public key cryptosystem has been exploited in order to achieve asymmetric fingerprinting such that only a buyer can obtain fingerprinted content. However, this requires many computations and a wide-band network channel because the entire uncompressed content must be encrypted based on the public key cryptosystem. In this paper, instead of the homomorphic property, we introduce the management of the enciphering keys for the symmetric cryptosystem. Based on a buyer's identity, a trusted center issues the buyer a partial sequence which is one of the two elements in the entire sequence. Although a merchant shares the entire sequence with the center, he cannot extract the buyer's key sequence from it. Such an information gap enables our protocol to be asymmetric and efficient. For each packet of content, the merchant produces two marked packets that contains a "0" or "1" information bit, and they are enciphered using the two elements from the entire sequence. Subsequently, the buyer obtains the two ciphertexts (the encrypted marked packets) containing the information bits of his identity. Since the merchant does not know the ciphertext decrypted by the buyer, an asymmetric property is achieved. In our protocol, before trade between a buyer and a merchant, the merchant can produce and compress the marked packets; this enables the reduction of both the computational costs for the encryption and the amount of data for transmission. Since only the enciphering operation is performed by a merchant in the on-line protocol, real-time operation may be possible.

The analog IC technology, might sound old-fashioned, is still important for the future wireless systems such as 4G cellular phone systems, broadband wireless networkings, and wireless sensor networkings. The analog features and issues of the scaled CMOS transistor, the basic issue and the technology trend for the ADC as an important building block of wires systems, and the feature of the digital RF architecture proposed recently are reviewed and discussed. Higher speed and lower power consumption are expected for low SNR systems along with the further technology scaling. However, the high SNR system is not realized easily due to a decrease of signal voltage. One of the important technology trends is the digitalization of RF signal to realize the system flexibility, robustness, area shrinking, and TAT shortening.

With the rapid spread of information and ubiquitous access of browsers, flash crowds, a sudden, unanticipated surge in the volume of request rates, have become the bane of many Internet websites. This paper models and presents FCAN, an adaptive network that dynamically optimizes the system structure between peer-to-peer (P2P) and client-server (C/S) configurations to alleviate flash crowds effect. FCAN constructs P2P overlay on cache proxy server layer to distribute the flash traffic from origin server. It uses policy-configured DNS redirection to route the client requests in balance, and adopts strategy load detection to monitor and react the load changes. Our preliminary simulation results showed that the system is overall well behaved, which validates the correctness of our design.

In this brief, a chaotic Jerk system is presented. This was obtained by converting the Van der Pol architecture into a third order differential equation, and, after the state-space representation was obtained, adding one innovation term and modifying some proportional parameters. Using Lyapunov exponents, Poincare maps, Fourier spectrum analysis and numerical experiments, we confirm the chaotic nature of the proposed Jerk system. Experimental results are also included.

A hybrid evolutionary neuro-fuzzy system (HENFS) is proposed in this paper, where the weighted Gaussian function (WGF) is used as the membership function for improved premise construction. With the WGF, different types of the membership functions (MFs) can be accommodated in the rule base of HENFS. A new hybrid algorithm of random optimization (RO) algorithm incorporated with the least square estimation (LSE) is presented. Based on the hybridization of RO-LSE, the proposed soft-computing approach overcomes the disadvantages of other widely used algorithms. The proposed HENFS is applied to chaos time series identification and industrial process modeling to verify its feasibility. Through the illustrations and comparisons the impressive performances for unknown system identification can be observed.

In iterative software development methodology, a version control system is used in order to record and manage modification histories of products such as source codes and models described in diagrams. However, conventional version control systems cannot manage the models as a logical unit because the systems mainly handle source codes. In this paper, we propose a version control technique for handling diagrammatical models as logical units. Then we illustrate the feasibility of our approach with the implementation of version control functions of a meta-CASE tool that is able to generate a modeling tool in order to deal with various diagrams.

Recently, system level design languages (SLDL), which can describe both hardware and software aspects of the design, are receiving attention. Mixed-signal extensions of SLDL enable current discrete-oriented SLDLs to describe and simulate not only digital systems but also digital-analog mixed-signal systems. The synchronization between discrete and continuous behaviors is widely regarded as a critical part in the extensions. In this paper, we present an event-driven synchronization mechanism for both timed and untimed system level designs through which discrete and continuous behaviors are synchronized via AD events and DA events. We also demonstrate how the synchronization mechanism can be incorporated into the kernel of SLDL, such as SpecC. In the extended kernel, a new simulation cycle, the AMS cycle, is introduced. Three case studies show that the extended SpecC-based system level design environment using our synchronization mechanism works well with timed/untimed mixed-signal system level description.

An RF adaptive array antenna (RF-AAA) configured with variable capacitors is proposed. This antenna system can control the power combining ratio and phase value of received signals. In this paper, we focus on the diversity effects of RF-AAA. First, we show the design methodology of the combiner circuit to realize the effective combining. Second, the perturbation method and the steepest gradient method are compared for the optimization algorithms to provide fast convergence and suboptimum solutions among the variable circuit constants. Finally, in simulation, we show the RF-AAA can achieve diversity antenna gains of 7.7 dB, 10.9 dB and 12.6 dB for 2-branch, 3-branch and 4-branch configuration, respectively, which have higher performance than the selection combining.

This paper studies the robustness of message masking communication over noisy channels using modified chaotic systems. First, the modified chaotic systems are introduced with a higher capability of transmitting messages than typical chaotic systems. Then, assuming an ideal channel, the chaotic message masking scheme is derived which achieves asymptotic convergence or dead-beat performance for recovering messages. Next, considering the case of noisy channels, an H∞ performance and an L2-gain optimal noise rejection are achieved by solving linear matrix inequality (LMI) problems. Furthermore, the ultimate bound of synchronization error and recovered message error can be adjusted by both design gains and the system parameter of the modified chaos. Using the proposed method, the bit-error-ratio and noise tolerance are improved. Finally, numerical simulations and DSP experiments are carried out to verify the theoretical derivations.

This paper analyzes automation surprises in human-machine systems with time information. Automation surprises are phenomena such that the underlying machine's behavior diverges from user's intention and may lead to critical situations. Thus, designing human-machine systems without automation surprises is one of fundamental issues to achieve reliable user interaction with the machines. In this paper, we focus on timed human-machine interaction and address their formal aspects. The presented framework is essentially an extension of untimed human-machine interaction and will cover the previously proposed methodologies. We employ timed automata as a model of human-machine systems with time information. Modeling the human-machine systems as timed automata enables one to deal with not only discrete behavior but also time constraints. Then, by introducing the concept of timed simulation of the machine model and the user model, conditions which guarantee the nonexistence of automation surprises are derived. Finally, we construct a composite model in which a machine model and a user model evolve concurrently and show that automation surprises can be detected by solving a reachability problem in the composite model.

This paper proposes novel methods to provide intelligence for characters in fighting action games by using neural networks. First, how a character learns basic game rules and matches against randomly acting opponents is considered. Since each action takes more than one time unit in general fighting action games, the results of a character's action are exposed not immediately but several time units later. We evaluate the fitness of a decision by using the relative score change caused by the decision. Whenever the scores of fighting characters are changed, the decision causing the score change is identified, and then the neural network is trained by using the score difference and the previous input and output values which induced the decision. Second, how to cope more properly with opponents that act with predefined action patterns is addressed. The opponents' past actions are utilized to find out the optimal counter-actions for the patterns. Lastly, a method in order to learn moving actions is proposed. To evaluate the performance of the proposed algorithm, we implement a simple fighting action game. Then the proposed intelligent character (IC) fights with the opponent characters (OCs) which act randomly or with predefined action patterns. The results show that the IC understands the game rules and finds out the optimal counter-actions for the opponents' action patterns by itself.

The module-wise dynamic voltage and frequency scaling (MDVFS) scheme is applied to a single-chip H.264/MPEG-4 audio/visual codec LSI. The power consumption of the target module with controlled supply voltage and frequency is reduced by 40% in comparison with the operation without voltage or frequency scaling. The consumed power of the chip is 63 mW in decoding QVGA H.264 video at 15 fps and MPEG-4 AAC LC audio simultaneously. This LSI keep operating continuously even during the voltage transition of the target module by introducing the newly developed dynamic de-skewing system (DDS) which watches and control the clock edge of the target module.

Acoustic modeling in speech recognition uses very little knowledge of the speech production process. At many levels our models continue to model speech as a surface phenomenon. Typically, hidden Markov model (HMM) parameters operate primarily in the acoustic space or in a linear transformation thereof; state-to-state evolution is modeled only crudely, with no explicit relationship between states, such as would be afforded by the use of phonetic features commonly used by linguists to describe speech phenomena, or by the continuity and smoothness of the production parameters governing speech. This survey article attempts to provide an overview of proposals by several researchers for improving acoustic modeling in these regards. Such topics as the controversial Motor Theory of Speech Perception, work by Hogden explicitly using a continuity constraint in a pseudo-articulatory domain, the Kalman filter based Hidden Dynamic Model, and work by many groups showing the benefits of using articulatory features instead of phones as the underlying units of speech, will be covered.

We propose two sequence design schemes for an overloaded space-time spreading system with multiple antennas. One scheme is for a system in which the amplitude of user signals needs not be adjusted and provides tradeoffs between the user capacity and diversity order. This scheme has a certain similarity to time-sharing, but its performance is further improved by time-diversity. Another is to achieve full diversity order by varying user signal amplitudes. The diversity orders of the respective schemes are theoretically proved and their performances are demonstrated by simulation.

Properties of the quantum noise and the optical feedback noise in blue-violet InGaN semiconductor lasers were measured in detail. We confirmed that the quantum noise in the blue-violet laser becomes higher than that in the near-infrared laser. This property is an intrinsic property basing on principle of the quantum mechanics, and is severe subject to apply the laser for optical disk with the small consuming power. The feedback noise was classified into two types of "low frequency type" and "flat type" basing on frequency spectrum of the noise. This classification was the same as that in the near infra-red lasers.

We propose a new receiving method for an information-providing system that uses LED-based traffic lights as the transmitter. We analyzed the improvements obtained when 2-dimentional image sensor replaced the conventional single-element photodiode. First, we discuss the maximum receiver's field of view (FOV) when using the 2-dimentional image sensor at a particular focal length. We analyzed the best vertical inclination for both lanes and quantified the improvements in terms of the enhancement of received signal-noise ratio (SNR) when different numbers of pixels were applied. Our results indicate that using more pixels increases the received SNR and the service area becomes wider compared to the conventional single-element system. Consequently, receivable information within the service area also increased. We also found that the optimum number of pixels to accomplish a reliable communication system is 5050 because performance degradation occured with a larger number of pixels.