Accurate values for occurrence probabilities of the template used in the overlapping template matching test included in NIST randomness test suite (NIST SP800-22) have been analyzed. The inaccurate values used in the NIST randomness test suite cause significant difference of pass rate. When the inaccurate values are used and significance level is set to 1%, the experimental mean value of pass rate, which is calculated by use of random number sequences taken from DES (Data Encryption Standard), is about 98.8%. In contrast, our new values derived from a set of recurrence formulas for the NIST randomness test suite give an empirical distribution of pass rate that meets the theoretical binomial distribution. Here, the experimental mean value of pass rate is about 99%, which corresponds to the significance level 1%.

In space division multiplexing with orthogonal frequency division multiplexing (SDM-OFDM) systems, since co-channel interference (CCI) degrades the demodulation performance, CCI suppression is essential. For CCI suppression, the turbo detector using the soft-input soft-output maximum likelihood detector (SISO-MLD) is proposed. Although SISO-MLD can deal with soft information, SISO-MLD updates only a priori information of code bits at each iteration. This prevents the performance to be improved. Meanwhile, a turbo detector with soft cancellation (SC) followed by minimum mean square error (MMSE) filter, in which the variance of the residual interference components as well as a priori information can be updated at each iteration, is well known. However, the performance of SC/MMSE detector is also limited because it is proposed to reduce the computational complexity at the cost of performance degradation. In this paper, we propose an SC-type turbo detector which uses SISO-MLD for SDM-OFDM systems. In our proposed detector, the soft cancellation unit of the SC-type turbo detector is modified to cope with the SISO-MLD. From the simulation results, the proposed SC/MLD provides a better BER performance than the turbo detector using SISO-MLD. Furthermore, the proposed SC/MLD can attain the bit error rate (BER) equivalent to that of the SC/MMSE detector with a smaller computational complexity.

This paper deals with a universal coding problem for a certain kind of multiterminal source coding system that we call the complementary delivery coding system. In this system, messages from two correlated sources are jointly encoded, and each decoder has access to one of the two messages to enable it to reproduce the other message. Both fixed-to-fixed length and fixed-to-variable length lossless coding schemes are considered. Explicit constructions of universal codes and bounds of the error probabilities are clarified via type-theoretical and graph-theoretical analyses.

In this paper, CPW-fed slot antennas using loading metallic strips and a widened tuning stub (CPW-FSLW) which provides wideband operation on the flat, a Λ-shape reflector with horizontal plate that prevents the back radiation and provides the uni-directional radiation are investigated. We observe that the size and shape of the reflector have significant impact on the impedance matching and radiation patterns. By fabricating the CPW-FSLW on the Λ-shape reflector with horizontal plate structure, noticeable enhancements in both radiation pattern and bandwidth are achieved. The antennas are verified both through numerical simulations and also measurements of the experimental prototypes and these confirm the good performance antennas. It is found that the proposed antenna can deliver a measured impedance bandwidth of 64% from 1.6 to 3.1 GHz for VSWR ≤ 2. The antennas are designed to have wideband operation suitable for applications in GSM1800, GSM1900, PCS, IMT-2000 and WLAN bands.

There is an increasing requirement for supporting complex multidimensional queries in Peer-to-Peer systems. In the centralized spatial database world, R-Trees and its variant structures are widely accepted due to their capabilities to manage complex multidimensional queries. In this paper, we propose a new multidimensional indexing structure for P2P systems, called Distributed Hilbert R-Trees (DHR-Trees), in which peers organize themselves into an overlay network, dynamically maintain routing tables with region information and collaboratively execute complex multidimensional queries, such as range query and k-nearest neighbors query, efficiently. DHR-Trees has similar topology to the P-Trees P2P system. The peers' routing tables are enhanced with spatial region information, which allow multidimensional query predicates to be adapted into P2P systems with minor modification. The structure design and two major multidimensional query algorithms are presented. Our experimental results demonstrate that it performs well on range queries and k-nearest neighbors queries with multidimensional data set.

In orthogonal frequency-division multiplex access (OFDMA) downlink systems, the carrier-frequency offset (CFO) between the multiple transceivers introduces inter-carrier interference (ICI). In this letter, we propose an iterative precoding scheme to suppress the ICI due to CFO. This scheme is applied at the transmitter, and can jointly cancel the ICI for all the receivers. Moreover, by the studies of the convergence behavior of the iterations, a sufficient condition for the convergence is presented. The theoretical analysis and simulation results both show that this iterative scheme is equivalent to the zero-forcing (ZF) scheme in function, but with much lower complexity.

Due to the limited resources of sensor nodes, an energy-efficient routing algorithm of Wireless Sensor Networks is considered as one of the most important issues in improving network lifetime. To resolve this issue, several routing algorithms have been suggested, but the published studies have mainly focused on minimizing distances between sensor nodes or the number of hops. These researches have also assumed that all the sensor nodes participate in the sensing task. In this paper, we propose a new cluster head selection algorithm focusing on both the density of sensor nodes and sensing-awareness that has not been considered yet in other existing researches on cluster-based routing scheme. In the real sensor network environment, only a part of sensor nodes participates in data reporting, so consideration of sensing-awareness in a routing algorithm will have effect on network efficiency. Moreover, the density of sensor nodes that has resulted from geographical location of sensor nodes can be an important factor in cluster head selection. The simulation results show that the proposed algorithm, by considering these 2 factors simultaneously, reduces energy consumption and enhances network lifetime.

Behavioral synthesis, which automatically synthesizes an RTL circuit from a sequential program, is one of promising technologies to improve the design productivity. This paper proposes a function call optimization method in behavioral synthesis from large sequential programs with a number of functions. We formulate the optimization problem using integer linear programming. Our experimental results show the reduction in the circuit area by up to 44.6%, compared with a traditional method.

This letter proposes a sliding window method with iterative tuning for channel estimation of UWB signals. The iterative tuning scheme, which is based on multiple iterations of least mean square (LMS) algorithm, is utilized for modifying the output of the conventional sliding window channel estimator. By using this, the proposed method is more flexible due to the tradeoff between the processing time and accuracy, which makes it more suitable for practical UWB wireless communications. Simulations are also provided for demonstrating the validation of the proposed method.

This study investigates a new transmission method of light from a point source in a multimode graded-index fiber. The position of the point source is arranged along with a mode pattern to precisely determine the location of an output point image. Propagation performance is observed in an experiment and estimated by simulation.

We propose, in this article, the Hierarchical Behavior-Knowledge Space as an extension of Behavior-Knowledge Space. Hierarchical BKS utilizes ranked level individual classifiers, and automatically expands its behavioral knowledge in order to satisfy given reliability requirement. From the statistical view point, its decisions are as optimal as those of original BKS, and the reliability threshold is a lower bound of estimated reliability. Several comparisons with original BKS and unanimous voting are shown with some experiments.

The size-dependent array problem is a problem with systolic arrays such that the size of systolic arrays limits the size of calculations, which in a do-loop structure controls how many times it is repeated and how deep the nesting loops are. A systolic array cannot deal with larger calculations. For the size-dependent array problem, a spiral systolic array has been studied so far. It has non-adjacent connections between PEs, such as loop paths for sending data back so that data flows over the array independently of its own size. This paper takes an approach to the problem without non-adjacent connections. This paper discusses systolic messy arrays for infinite iterative algorithms so that they are independent from the size of calculations. First a systolic messy array called two-square shape is introduced then the properties of two-square shape are summarized: memory function, cyclic addition, and cyclic multiplication. Finally a way of building systolic messy arrays that calculate infinite iterative algorithms is illustrated with concrete examples such as an arithmetic progression, a geometric progression, N factorial, and Fibonacci numbers.

Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.

Assessment of discovered patterns is an important issue in the field of knowledge discovery. This paper presents an evaluation method that utilizes citation (reference) information to assess the quality of discovered document relations. With the concept of transitivity as direct/indirect citations, a series of evaluation criteria is introduced to define the validity of discovered relations. Two kinds of validity, called soft validity and hard validity, are proposed to express the quality of the discovered relations. For the purpose of impartial comparison, the expected validity is statistically estimated based on the generative probability of each relation pattern. The proposed evaluation is investigated using more than 10,000 documents obtained from a research publication database. With frequent itemset mining as a process to discover document relations, the proposed method was shown to be a powerful way to evaluate the relations in four aspects: soft/hard scoring, direct/indirect citation, relative quality over the expected value, and comparison to human judgment.

For a microstrip antenna (MSA) with a ring-shaped slot on formed on the ground plane, downsizing the microstrip patch and expanding the circularly polarized bandwidth have been achieved successfully. The dimensions of the patch are 6.8 mm7.4 mm and the minimum axial ratio (AR) of 0.6 dB is obtained at 6.1 GHz. In addition, its AR is less than 3 dB at the relative bandwidth of 3.5%. The bandwidth of the proposed MSA is twice that of conventional single-feeding circularly polarized MSAs; however, its size is only half that of conventional MSAs.

Ethical and legal requirements have made accessibility a crucial feature in any information systems. This paper presents a content adaptation framework, based on the MPEG-21 standard, to help low-vision users have better accessibility to visual contents. We first present an overview of MPEG-21 Digital Item Adaptation (DIA) and the low-vision description tool which enables interoperable content adaptation. This description tool lists seven low-vision symptoms, namely loss of fine detail, lack of contrast, central vision loss, peripheral vision loss, hemianopia, light sensitivity, and need of light. Then we propose a systematic contrast-enhancement method to improve the content visibility for low-vision users, focusing on the first two symptoms. The effectiveness of the low-vision description tool and our adaptation framework is verified by some experiments with an adaptation test-bed. The major advantages of the proposed approach include 1) support of a wide range of low-vision conditions, and 2) customized content adaptation to specific characteristics of each user.

In this paper, we propose a low complexity realization method for compensating for nonlinear distortion. Generally, nonlinear distortion is compensated for by a linearization system using a Volterra kernel. However, this method has a problem of requiring a huge computational complexity for the convolution needed between an input signal and the 2nd-order Volterra kernel. The Simplified Volterra Filter (SVF), which removes the lines along the main diagonal of the 2nd-order Volterra kernel, has been previously proposed as a way to reduce the computational complexity while maintaining the compensation performance for the nonlinear distortion. However, this method cannot greatly reduce the computational complexity. Hence, we propose a subband linearization system which consists of a subband parallel cascade realization method for the 2nd-order Volterra kernel and subband linear inverse filter. Experimental results show that this proposed linearization system can produce the same compensation ability as the conventional method while reducing the computational complexity.

This study employs secret codes and secret keys based on the elliptic curve to construct an elliptic curve cryptosystem with a dynamic access control system. Consequently, the storage space needed for the secret key generated by an elliptic curve dynamic access control system is smaller than that needed for the secret key generated by exponential operation built on the secure filter (SF) dynamic access control system. Using the elliptic curve to encrypt/decrypt on the secure filter improves the efficiency and security of using exponential operation on the secure filter in the dynamic access control system. With the proposed dynamic elliptic curve access control system, the trusted central authority (CA) can add/delete classes and relationships and change the secret keys at any time to achieve an efficient control and management. Furthermore, different possible attacks are used to analyze the security risks. Since attackers can only obtain the general equations for the elliptic curve dynamic access control system, they are unable to effectively perform an elliptic curve polynomial (ECP) conversion, or to solve the elliptic curve discrete logarithm problem (ECDLP). Thus, the proposed elliptic curve dynamic access control system is secure.

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.

Orthogonal frequency division multiplexing (OFDM) is an attractive technique to accomplish wired or wireless broadband communications. Since it has been adopted as the terrestrial digital-video-broadcasting standard in Europe, it has also subsequently been embedded into many broadband communication standards. Many techniques for frame timing and frequency synchronization of OFDM systems have been studied as a result of its increasing importance. We propose a new technique of simultaneously synchronizing frame timing and frequency utilizing matched filters. First, a new short preamble consisting of short sequences multiplied by a DBPSK coded sequence is proposed. Second, we show that the new short preamble results in a new structure for matched filters consisting of a first matched filter, a DBPSK decoder, and a second matched filter. We can avoid the adverse effects of carrier frequency offset (CFO) when frame timing is synchronized because a DBPSK decoder has been deployed between the first and second matched filters. In addition, we show that the CFO can be directly estimated from the peak value of matched filter output. Finally, our simulation results demonstrate that the proposed scheme outperforms the conventional schemes.