Robotic systems operating in the real-world have to cope with unforeseen events by determining appropriate decisions based on noisy or partial knowledge. In this respect high functional robots are equipped with many sensors and actuators and run multiple processing modules in parallel. The resulting complexity is even further increased in case of cooperative multi-robot systems, since mechanisms for joint operation are needed. In this paper a complete and modular framework that handles this complexity in multi-robot systems is presented. It provides efficient exchange of generated data as well as a generic scheme for task execution and robot coordination.

A new signature scheme of MPKC is proposed. It is created by perturbing a traditional encryption scheme in two ways. The proposed perturbation polynomials successfully reinforce the Matsumoto-Imai cryptosystem This new signature scheme has a structure very difficult to cryptanalyze. Along with the security against algebraic attacks, its security against existing attacks is discussed. The experimental data imply that the scheme can create a both lightweight and secure signature system.

The linear Piece In Hand (PH, for short) matrix method with random variables was proposed in our former work. It is a general prescription which can be applicable to any type of multivariate public-key cryptosystems for the purpose of enhancing their security. Actually, we showed, in an experimental manner, that the linear PH matrix method with random variables can certainly enhance the security of HFE against the Grobner basis attack, where HFE is one of the major variants of multivariate public-key cryptosystems. In 1998 Patarin, Goubin, and Courtois introduced the plus method as a general prescription which aims to enhance the security of any given MPKC, just like the linear PH matrix method with random variables. In this paper we prove the equivalence between the plus method and the primitive linear PH matrix method, which is introduced by our previous work to explain the notion of the PH matrix method in general in an illustrative manner and not for a practical use to enhance the security of any given MPKC. Based on this equivalence, we show that the linear PH matrix method with random variables has the substantial advantage over the plus method with respect to the security enhancement. In the linear PH matrix method with random variables, the three matrices, including the PH matrix, play a central role in the secret-key and public-key. In this paper, we clarify how to generate these matrices and thus present two probabilistic polynomial-time algorithms to generate these matrices. In particular, the second one has a concise form, and is obtained as a byproduct of the proof of the equivalence between the plus method and the primitive linear PH matrix method.

This paper presents an adaptive maximum power point tracking (MPPT) algorithm. The aim is to dynamically adjust the step length for updating duty ratio (or operating voltage) so as to make full utilization of the output power of photovoltaic (PV) systems, even under the rapidly changing atmospheric conditions. To this end, the average slope in terms of voltage and power is exploited for reducing the harmful effect of noise and error (incurred in measurement or quantization) on the slope. Also, a statistical decision-making scheme is employed for reliably deciding the time instant at which atmospheric conditions actually change. Empirical study has adduced grounds for its dominance over existing references.

The proportionate normalized least mean square algorithm (PNLMS) greatly improves the convergence of the sparse impulse response. It exploits the shape of the impulse response to decide the proportionate step gain for each coefficient. This is not always suitable. Actually, the proportionate step gain should be determined according to the difference between the current estimate of the coefficient and its optimal value. Based on this idea, an approach is proposed to determine the proportionate step gain. The proposed approach can improve the convergence of proportionate adaptive algorithms after a fast initial period. It even behaves well for the non-sparse impulse response. Simulations verify the effectiveness of the proposed approach.

In a society preoccupied with gradual erosion of electronic privacy, loss of privacy in the current Domain Name System is an important issue worth considering. In this paper, we first review the DNS and some security & privacy threats to make average users begin to concern about the significance of privacy preservation in DNS protocols. Then, by an careful survey of four noise query generation based existing privacy protection approaches, we analyze some benefits and limitations of these proposals in terms of both related performance evaluation results and theoretic proofs. Finally, we point out some problems that still exist for research community's continuing efforts in the future.

Inductive theorem proving plays an important role in the field of formal verification of systems. The rewriting induction (RI) is a method for inductive theorem proving proposed by Reddy. In order to obtain successful proofs, it is very important to choose appropriate contexts (such as in which direction each equation should be oriented) when applying RI inference rules. If the choice is not appropriate, the procedure may diverge or the users have to come up with several lemmas to prove together with the main theorem. Therefore we have a good reason to consider parallel execution of several instances of the rewriting induction procedure, each in charge of a distinguished single context in search of a successful proof. In this paper, we propose a new procedure, called multi-context rewriting induction, which efficiently simulates parallel execution of rewriting induction procedures in a single process, based on the idea of the multi-completion procedure. By the experiments with a well-known problem set, we discuss the effectiveness of the proposed procedure when searching along various contexts for a successful inductive proof.

We propose a character size optimization technique to reduce the number of EB shots of multi-column-cell (MCC) lithographic systems in which transistor patterns are projected with multiple column cells in parallel. Each and every column cell is capable of projecting patterns with character projection (CP) and variable shaped beam (VSB) methods. Seeking the optimal character size of characters contributes to minimizing the number of EB shots and reducing the fabrication cost for ICs. Experimental results show that the character size optimization achieved 70.6% less EB shots in the best case with an available electron beam (EB) size. Our technique also achieved 40.6% less EB shots in the best case than a conventional character sizing technique.

Mobile devices, such as cellular phones and car navigation systems, are essential to daily life. People acquire necessary information and preferred content over communication networks anywhere, anytime. However, usability issues arise from the simplicity of user interfaces themselves. Thus, a recommendation of content that is adapted to a user's preference and situation will help the user select content. In this paper, we describe a method to realize such a system using Bayesian networks. This user-adapted mobile system is based on a user model that provides recommendation of content (i.e., restaurants, shops, and music that are suitable to the user and situation) and that learns incrementally based on accumulated usage history data. However, sufficient samples are not always guaranteed, since a user model would require combined dependency among users, situations, and contents. Therefore, we propose the LK method for modeling, which complements incomplete and insufficient samples using knowledge data, and CPT incremental learning for adaptation based on a small number of samples. In order to evaluate the methods proposed, we applied them to restaurant recommendations made on car navigation systems. The evaluation results confirmed that our model based on the LK method can be expected to provide better generalization performance than that of the conventional method. Furthermore, our system would require much less operation than current car navigation systems from the beginning of use. Our evaluation results also indicate that learning a user's individual preference through CPT incremental learning would be beneficial to many users, even with only a few samples. As a result, we have developed the technology of a system that becomes more adapted to a user the more it is used.

This study presents several optimization approaches for the MPEG-2/4 Audio Advanced Coding (AAC) Low Complexity (LC) encoding and decoding processes. Considering the power consumption and the peripherals required for consumer electronics, this study adopts the TI OMAP5912 platform for portable devices. An important optimization issue for implementing AAC codec on embedded and mobile devices is to reduce computational complexity and memory consumption. Due to power saving issues, most embedded and mobile systems can only provide very limited computational power and memory resources for the coding process. As a result, modifying and simplifying only one or two blocks is insufficient for optimizing the AAC encoder and enabling it to work well on embedded systems. It is therefore necessary to enhance the computational efficiency of other important modules in the encoding algorithm. This study focuses on optimizing the Temporal Noise Shaping (TNS), Mid/Side (M/S) Stereo, Modified Discrete Cosine Transform (MDCT) and Inverse Quantization (IQ) modules in the encoder and decoder. Furthermore, we also propose an efficient memory reduction approach that provides a satisfactory balance between the reduction of memory usage and the expansion of the encoded files. In the proposed design, both the AAC encoder and decoder are built with fixed-point arithmetic operations and implemented on a DSP processor combined with an ARM-core for peripheral controlling. Experimental results demonstrate that the proposed AAC codec is computationally effective, has low memory consumption, and is suitable for low-cost embedded and mobile applications.

An on-chip Charged Device Model (CDM) ESD protection method for RF ICs is proposed in a 0.13 µm RF process and evaluated by using very fast Transmission Line Pulse (vf-TLP) system. Key design parameters such as triggering voltage (Vt1) and the oxide breakdown voltage from the vf-TLP measurement are used to design input ESD protection circuits for a RF test chip. The characterization and the behavior of a Low Voltage Triggered Silicon Controlled Rectifier (SCR) which used for ESD protection clamp under vf-TLP measurements are also reported. The results measured by vf-TLP system showed that the triggering voltage decreased and the second breakdown current increased in comparison with the results measured by a standard 100 ns TLP system. From the HBM/ CDM testing, the RF test chip successfully met the requested RF ESD withstand level, HBM 1 kV, MM 100 V and CDM 500 V.

We try to use a computer algebra system Mathematica as a test case generation system. In test case generation, we generally need to solve equations and inequalities. The main reason why we take Mathematica is because it has a built-in function to solve equations and inequalities. In this paper, we deal with both black-box testing and white-box testing. First, we show two black-box test case generation procedures described in Mathematica. The first one is based on equivalence partitioning. Mathematica explicitly shows a case that test cases do no exist. This is an advantage in using Mathematica. The second procedure is a modification of the first one adopting boundary value analysis. For implementation of boundary value analysis, we give a formalization for it. Next, we show a white-box test case generation procedure. For this purpose, we also give a model for source programs. It is like a control flow graph model. The proposed procedure analyzes a model description of a program.

File systems make use of the buffer cache to enhance their performance. Traditionally, part of DRAM, which is volatile memory, is used as the buffer cache. In this paper, we consider the use of of Non-Volatile RAM (NVRAM) as a write cache for metadata of the file system in embedded systems. NVRAM is a state-of-the-art memory that provides characteristics of both non-volatility and random byte addressability. By employing NVRAM as a write cache for dirty metadata, we retain the same integrity of a file system that always synchronously writes its metadata to storage, while at the same time improving file system performance to the level of a file system that always writes asynchronously. To show quantitative results, we developed an embedded board with NVRAM and modify the VFAT file system provided in Linux 2.6.11 to accommodate the NVRAM write cache. We performed a wide range of experiments on this platform for various synthetic and realistic workloads. The results show that substantial reductions in execution time are possible from an application viewpoint. Another consequence of the write cache is its benefits at the FTL layer, leading to improved wear leveling of Flash memory and increased energy savings, which are important measures in embedded systems. From the real numbers obtained through our experiments, we show that wear leveling is improved considerably and also quantify the improvements in terms of energy.

Packet classification has become one of the most important application techniques in network security since the last decade. The technique involves a traffic descriptor or user-defined criteria to categorize packets to a specific forwarding class which will be accessible for future security handling. To achieve fast packet classification, we propose a new scheme, Hierarchical Cross-Producting. This approach simplifies the classification procedure and decreases the distinct combinations of fields by hierarchically decomposing the multi-dimensional space based on the concept of telescopic search. Analogous to the use of telescopes with different powers**, a multiple-step process is used to search for targets. In our scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into recursive searching for matching subspaces. The required storage of our scheme could be significantly reduced since the distinct field specifications of subspaces is manageable. The performance are evaluated based on both real and synthetic filter databases. The experimental results demonstrate the effectiveness and scalability of the proposed scheme.

In this paper, we describe a verification environment which is based on a constrained random layered testbench using SystemVerilog OOP. As SystemVerilog OOP technique does not allow multiple inheritance, we adopt SystemC to design components of a verification environment which employ multiple inheritance. Then SystemC design unit is linked to a SystemVerilog-based verification environment using SystemVerilog DPI and ModelSim macro. Employing multiple inheritance of SystemC makes the design phase of verification environment simple and easy through source code reusability without corruption due to multi-level single inheritance.

Cyclic delay diversity (CDD) is a simple technique to intentionally increase frequency selectivity of channels for orthogonal frequency division multiplexing (OFDM). This letter evaluates the performance of post-FFT fine frequency estimation scheme for OFDM-based FM system using CDD. A new and accurate mean square error expression of the fine frequency estimator is derived in the CDD-based OFDM system, and simulation results are provided to verify our analysis.

A new adaptive algorithm is proposed by introducing some modifications to the recursive least squares (RLS) algorithm. Except for the noise variance, the proposed algorithm does not require any statistics or knowledge of the desired signal, thus, it is suitable for adaptive filtering for channel estimation in code division multiple access (CDMA) systems in cases where the standard RLS approach cannot be used. A theoretical analysis demonstrates the convergence of the proposed algorithm, and simulation results for CDMA channel estimation show that the proposed algorithm outperforms existing channel estimation schemes.

In the last decade, the technique of packet classification has been widely deployed in various network devices, including routers, firewalls and network intrusion detection systems. In this work, we improve the performance of packet classification by using multiple hash tables. The existing hash-based algorithms have superior scalability with respect to the required space; however, their search performance may not be comparable to other algorithms. To improve the search performance, we propose a tuple reordering algorithm to minimize the number of accessed hash tables with the aid of bitmaps. We also use pre-computation to ensure the accuracy of our search procedure. Performance evaluation based on both real and synthetic filter databases shows that our scheme is effective and scalable and the pre-computation cost is moderate.

Effective countermeasures against explosive increase in healthcare expenditures are urgently needed. A paradigm shift in healthcare is called for, and academics and governments worldwide are working hard on the application of information and communication technologies (ICT) as a feasible and effective measure for reducing medical cost. The more prevalent the disease and the easier disease outcome can be improved, the more efficient is medical ICT in reducing healthcare cost. Hypertension and diabetes mellitus are such examples. Chronic heart failure is another disease in which patients may benefit from ICT-based medical practice. It is conceivable that daily monitoring of hemodynamics together with appropriate treatments may obviate the expensive hospitalization. ICT potentially permit continuous monitoring with wearable or implantable medical devices. ICT may also help accelerate the development of new therapeutic devices. Traditionally effectiveness of treatments is sequentially examined by sacrificing a number of animals at a given time point. These inefficient and inaccurate methods can be replaced by applying ICT to the devices used in chronic animal experiments. These devices allow researchers to obtain biosignals and images from live animals without killing them. They include implantable telemetric devices, implantable telestimulation devices, and imaging devices. Implanted rather than wired monitoring and stimulation devices permit experiments to be conducted under even more physiological conditions, i.e., untethered, free-moving states. Wireless communication and ICT are indispensible technologies for the development of such telemetric and telestimulation devices.

In this letter, we develop an anycast-based emergency service for healthcare wireless sensor networks. The new service could operate with sensors to detect and activate an alarm system based on predefined conditions that are specific to the patient and the disease. The new service is implemented on 802.15.4 ZigBee which usually has large control overhead and long transmission times. To improve the service performance, our service identifies the closest emergency service provider to alleviate the control overhead and achieve immediate assistance when a patient requests for an emergency service. We also increase the reliability of packet transmission by using a Recovery Point scheme. Our simulations and experiment demonstrate that our scheme is efficient and feasible for healthcare wireless sensor networks.