In this paper, for an odd prime p such that p≡3 mod 4, odd n, and d=(pn+1)/(pk+1)+(pn-1)/2 with k|n, the value distribution of the exponential sum S(a,b) is calculated as a and b run through $mathbb{F}_{p^n}$. The sequence family $mathcal{G}$ in which each sequence has the period of N=pn-1 is also constructed. The family size of $mathcal{G}$ is pn and the correlation magnitude is roughly upper bounded by $(p^k+1)sqrt{N}/2$. The weight distribution of the relevant cyclic code C over $mathbb{F}_p$ with the length N and the dimension ${ m dim}_{mathbb{F}_p}mathcal{C}=2n$ is also derived.

With the proliferation of smart grids and the construction of various electric IT systems and networks, a next-generation substation automation system (SAS) based on IEC 61850 has been agreed upon as a core element of smart grids. However, research on security vulnerability analysis and quantification for automated substations is still in the preliminary phase. In particular, it is not suitable to apply existing security vulnerability quantification approaches to IEC 61850-based SAS because of its heterogeneous characteristics. In this paper, we propose an IEC 61850-based SAS network modeling and evaluation approach for security vulnerability quantification. The proposed approach uses network-level and device groupings to categorize the characteristic of the SAS. In addition, novel attack scenarios are proposed through a zoning scheme to evaluate the network model. Finally, an MTTC (Mean Time-to-Compromise) scheme is used to verify the proposed network model using a sample attack scenario.

This paper proposes the synchronization control method for two different unified chaotic systems with unknown mismatched parameters using sum of squares method. Previously, feedback-linearizing and stabilization terms were used in the controller for the synchronization problem. However, they used just a constant matrix as a stabilization control gain, whose performance is shown to be valid only for a linear model. Thus, we propose the novel control method for the synchronization of the two different unified chaotic systems with unknown mismatched parameters via sum of squares method. We design the stabilization control input which is of the polynomial form by sum of squares method and also the adaptive law for the estimation of the unknown mismatched parameter between the master and slave systems. Since we can use the polynomial control input which is dependent on the system states as the stabilization controller, the proposed method can have better performance than the previous methods. Numerical simulations for both uni-directional and bi-directional chaotic systems show the validity and advantage of the proposed method.

This paper introduces a radio frequency identification (RFID) tag for urination detection. The proposed tag is embedded into paper diapers in order to detect the patient's urination immediately. For this tag, we designed an RFID tag antenna at 950MHz, which matches the impedance of the associated integrated circuit (IC) chip. In addition, we calculate the antenna characteristics and measure the reflection coefficient (S11) and radiation pattern of the antenna. The results show that this system can be used to detect urination.

Natural language (NL) requirements are usually human-centric and therefore error-prone and inaccurate. In order to improve the 3Cs of natural language requirements, namely Consistency, Correctness and Completeness, in this paper we propose a systematic pattern matching approach supporting both NL requirements modeling and inconsistency, incorrectness and incompleteness analysis among requirements. We first use business process modeling language to model NL requirements and then develop a formal language — Workflow Patterns-based Process Language (WPPL) — to formalize NL requirements. We leverage workflow patterns to perform two-level 3Cs checking on the formal representation based on a coherent set of checking rules. Our approach is illustrated through a real world financial service example — Global Equity Trading System (GETS).

In this paper, for an odd prime p, new quaternary sequences of even period 2p with ideal autocorrelation property are constructed using the binary Legendre sequences of period p. For the new quaternary sequences, two properties which are considered as the major characteristics of pseudo-random sequences are derived. Firstly, the autocorrelation distribution of the proposed quaternary sequences is derived and it is shown that the autocorrelation values of the proposed quaternary sequences are optimal. For both p≡1 mod 4 and p≡3 mod 4, we can construct optimal quaternary sequences while only for p≡3 mod 4, the binary Legendre sequences can satisfy ideal autocorrelation property. Secondly, the linear complexity of the proposed quaternary sequences is also derived by counting non-zero coefficients of the discrete Fourier transform over the finite field Fq which is the splitting field of x2p-1. It is shown that the linear complexity of the quaternary sequences is larger than or equal to p or (3p+1)/2 for p≡1 mod 4 or p≡3 mod 4, respectively.

Orthogonal arrays have important applications in statistics and computer science, as well as in coding theory. In this letter, a new construction method of symmetric orthogonal arrays of strength t is proposed, which is a concatenation of two orthogonal partitions according to a latin square. As far as we know, this is a new construction of symmetric orthogonal arrays of strength t, where t is a given integer. Based on the different latin squares, we also study the enumeration problem of orthogonal partitions, and a lower bound on the count of orthogonal partitions is derived.

This paper presents a novel data compression method for testing integrated circuits within the framework of pattern run-length coding. The test set is firstly divided into 2n-length patterns where n is a natural number. Then the compatibility of each pattern, which can be an external type, or an internal type, is analyzed. At last, the codeword of each pattern is generated according to its analysis result. Experimental results for large ISCAS89 benchmarks show that the proposed method can obtain a higher compression ratio than existing ones.

Based on sample-pair refinement and local optimization, this paper proposes a high-accuracy and quick matting algorithm. First, in order to gather foreground/background samples effectively, we shoot rays in hybrid (gradient and uniform) directions. This strategy utilizes the prior knowledge to adjust the directions for effective searching. Second, we refine sample-pairs of pixels by taking into account neighbors'. Both high confidence sample-pairs and usable foreground/background components are utilized and thus more accurate and smoother matting results are achieved. Third, to reduce the computational cost of sample-pair selection in coarse matting, this paper proposes an adaptive sample clustering approach. Most redundant samples are eliminated adaptively, where the computational cost decreases significantly. Finally, we convert fine matting into a de-noising problem, which is optimized by minimizing the observation and state errors iteratively and locally. This leads to less space and time complexity compared with global optimization. Experiments demonstrate that we outperform other state-of-the-art methods in local matting both on accuracy and efficiency.

A specification for digital cinema systems which deal with movies digitally from production to delivery as well as projection on the screens is recommended by DCI (Digital Cinema Initiative), and the systems based on this specification have already been developed and installed in theaters. The parameters of the systems that play an important role in determining image quality include image resolution, quantization bit depth, color space, gamma characteristics, and data compression methods. This paper comparatively discusses a relation between required bit depth and gamma quantization using both of a human visual system for grayscale images and two color difference models for color images. The required bit depth obtained from a contrast sensitivity function against grayscale images monotonically decreases as the gamma value increases, while it has a minimum value when the gamma is 2.9 to 3.0 from both of the CIE 1976 L* a* b* and CIEDE2000 color difference models. It is also shown that the bit depth derived from the contrast sensitivity function is one bit greater than that derived from the color difference models at the gamma value of 2.6. Moreover, a comparison between the color differences computed with the CIE 1976 L* a* b* and CIEDE2000 leads to a same result from the view point of the required bit depth for digital cinema systems.

In this paper, a stochastic asymptotic stabilization method is proposed for deterministic input-affine control systems, which are randomized by including Gaussian white noises in control inputs. The sufficient condition is derived for the diffusion coefficients so that there exist stochastic control Lyapunov functions for the systems. To illustrate the usefulness of the sufficient condition, the authors propose the stochastic continuous feedback law, which makes the origin of the Brockett integrator become globally asymptotically stable in probability.

A method of calculating the top event probability of a fault tree, where dynamic gates and repeated events are included and the occurrences of basic events follow nonexponential distributions, is proposed. The method is on the basis of the Bayesian network formulation for a DFT proposed by Yuge and Yanagi [1]. The formulation had a difficulty in calculating a sequence probability if components have nonexponential failure distributions. We propose an alternative method to obtain the sequence probability in this paper. First, a method in the case of the Erlang distribution is discussed. Then, Tijms's fitting procedure is applied to deal with a general distribution. The procedure gives a mixture of two Erlang distributions as an approximate distribution for a general distribution given the mean and standard deviation. A numerical example shows that our method works well for complex systems.

In a sign-magnitude representation of binary lattice codevectors, only a few least significant bit-planes are constrained due to the structure of the lattice, while there is no restriction on other more significant bit-planes. Hence, any convenient bit-plane coding method can be used to encode the lattice codevectors, with modification required only for the lattice-defining, least-significant bit-planes. Simple encoding methods for the lattice-defining bit-planes of the D4, RE8, and Barnes-Wall 16-dimensional lattices are described. Simulation results for the encoding of a uniform source show that standard bit-plane coding together with the proposed encoding provide about the same performance as integer lattice vector quantization when the bit-stream is truncated. When the entire bit-stream is fully decoded, the granular gain of the lattice is realized.

As mobile multimedia services expand, user behavior will become more diverse and the control of service quality from the user's perspective will become more important in service design. The quality of the network is one of the critical factors determining mobile service quality. However, this has mainly been evaluated in objective physical terms, such as delay reduction and bandwidth expansion. It is less common to use a human-centered design viewpoint when improving network performance. In this paper, we discuss ways to improve the quality of web services using time-fillers that actively address the human factors to improve the subjective quality of a mobile network. A field experiment was conducted, using a prototype. The results of the field experiment show that time-fillers can significantly decrease user dissatisfaction with waiting, but that this effect is strongly influenced by user preferences concerning content. Based on these results, we discuss the design requirements for effective use of time-fillers.

With the technology scaling down, leakage power becomes an important part of total power consumption. The relatively large leakage current weakens the energy recovery capability of adiabatic circuits and reduces its superiority, compared with static CMOS circuits in the field of low-power design. In this paper, we rebuild three types of adiabatic circuits (2N2N2P, IPAL and DCPAL) based on FinFET devices to obtain a large leakage power reduction by rationally utilizing the different operating modes of FinFET devices (SG, LP, and IG). A 16-bit adiabatic adder has been investigated to demonstrate the advantages of FinFET adiabatic circuits. The Predictive Technology Model (PTM) is used for 32-nm bulk MOSFET and FinFET devices and all of the simulations are based on HSPICE. The results evince the proposed FinFET adiabatic circuits have a considerable reduction (more than 60% for SG mode FinFET and more than 80% for LP mode FinFET) of power consumption compared with the bulk MOSFET ones. Furthermore, the FinFET adiabatic circuits also have higher limiting frequency of clock source and better noise immunity.

This paper proposes a method for evaluating visual differences caused by decimation. In many applications it is important to evaluate visual differences of two different images. There exist many image assessment methods that utilize the model of the human visual system (HVS), such as the visual difference predictor (VDP) and the Sarnoff visual discrimination model. In this paper, we extend and elaborate on the conventional image assessment method for the purpose of evaluating the visual difference caused by the image decimation. Our method matches actual human evaluation more and requires less computational complexity than the conventional method.

In the next generation mobile network, the demand for high data rate transmission will require an increase in the transmission power if the current mobile cellular network architecture is used. Multihop networks are considered to be a key solution to this problem. However, a new resource allocation algorithm is also required for the new network architecture. In this paper, we propose a resource allocation scheme for a parallel relay 2-hop OFDMA virtual cellular network (VCN) which can be applied in a multiuser environment. We evaluate, by computer simulation, the ergodic channel capacity of the VCN using the proposed algorithm, and compare the results with those of the conventional single hop network (SHN). In addition, we analyze the effect of the location of the relay wireless ports on the ergodic channel capacity of the VCN. We also study the degree of fairness of the VCN, using the proposed scheme, compared with that of the SHN. For low transmission power, the simulation results show: a) the VCN can provide a better ergodic channel capacity and a better degree of fairness than the SHN, b) the distance ratio for which the ergodic channel capacity of the VCN is maximal can be found in the interval 0.20.3, c) the ergodic channel capacity of the VCN remains better than that of the SHN as the number of users increases, and d) as the distance between the relay WPs and the base station increases, the channel capacity of VCN approaches that of the SHN.

The mining problem over data streams has recently been attracting considerable attention thanks to the usefulness of data mining in various application fields of information science, and sequence data streams are so common in daily life. Therefore, a study on mining sequential patterns over sequence data streams can give valuable results for wide use in various application fields. This paper proposes a new framework for mining novel interesting sequential patterns over a sequence data stream and a mining method based on the framework. Assuming that a sequence with small time-intervals between its data elements is more valuable than others with large time-intervals, the novel interesting sequential pattern is defined and found by analyzing the time-intervals of data elements in a sequence as well as their orders. The proposed framework is capable of obtaining more interesting sequential patterns over sequence data streams whose data elements are highly correlated in terms of generation time.

Multi-label classification allows a sample to belong to multiple classes simultaneously, which is often the case in real-world applications such as text categorization and image annotation. In multi-label scenarios, taking into account correlations among multiple labels can boost the classification accuracy. However, this makes classifier training more challenging because handling multiple labels induces a high-dimensional optimization problem. In this paper, we propose a scalable multi-label method based on the least-squares probabilistic classifier. Through experiments, we show the usefulness of our proposed method.

Spectral subtraction (SS) is an additive noise removal method which is derived in an extensive framework. In spectral subtraction, it is assumed that speech and noise spectra follow Gaussian distributions and are independent with each other. Hence, noisy speech also follows a Gaussian distribution. Spectral subtraction formula is obtained by maximizing the likelihood of noisy speech distribution with respect to its variance. However, it is well known that noisy speech observed in real situations often follows a heavy-tailed distribution, not a Gaussian distribution. In this paper, we introduce a q-Gaussian distribution in the non-extensive statistics to represent the distribution of noisy speech and derive a new spectral subtraction method based on it. We found that the q-Gaussian distribution fits the noisy speech distribution better than the Gaussian distribution does. Our speech recognition experiments using the Aurora-2 database showed that the proposed method, q-spectral subtraction (q-SS), outperformed the conventional SS method.