In this correspondence, we devise a new method for constructing a ternary column sequence set of length 3m+1-1 form ternary sequences of period 3m-1 with ideal autocorrelation, and the ternary LCZ sequence set of period 3n-1 is constructed by using the column sequence set when (m+1)|n. In addition, the method is popularized to the p-ary LCZ sequence. The resultant LCZ sequence sets in this paper are optimal with respect to the Tang-Fan-Matsufuji bound.

Internet behavior is becoming more complex due to ever-changing networking technologies and applications. Thus, understanding and controlling the complex behavior of the Internet are important for designing future networks. One of the complex behaviors of the Internet is traffic dynamics. Previous studies revealed that flow control in the transport layer affects the traffic dynamics of the Internet. However, it is not clear how the topological structure impacts traffic dynamics. In this paper, we investigate packet delay dynamics and traffic fluctuation in ISP router-level topologies where the degree distribution exhibits a power-law nature, and the nodes interact via end-to-end feedback control functionality. We show the packet delay dynamics of the BA topologies generated by the Barabasi-Albert (BA) model and the ISP router-level topologies. Simulation results show that the end-to-end delay distributions exhibit a heavy tail in the TCP model. Moreover, the number of links with highly fluctuating queue length increases dramatically compared to that in the stop-and-wait model. Even in this case, the high-modularity structures of the ISP topologies reduce the number of highly fluctuating links compared with the BA topologies.

A Superconcentrator is a directed acyclic graph with specific properties. The existence of linear-sized supercentrator has been proved in [4]. Since then, the size has been decreased significantly. The best known size is 28N which is proved by U. Schöning in [8]. Our work follows their construction and proves a smaller size superconcentrator.

An exponential regression-based model with stochastic intensity is developed to describe the software reliability growth phenomena, where the software testing metrics depend on the intensity process. For such a generalized modeling framework, the common maximum likelihood method cannot be applied any more to the parameter estimation. In this paper, we propose to use the pseudo maximum likelihood method for the parameter estimation and to seek not only the model parameters but also the software reliability measures approximately. It is shown in numerical experiments with real software fault data that the resulting software reliability models based on four parametric approximations provide the better goodness-of-fit performance than the common non-homogeneous Poisson process models without testing metric information.

The minimized assumption generation has been recognized as an important improvement of the assume-guarantee verification method in order to generate minimal assumptions. The generated minimal assumptions can be used to recheck the whole component-based software at a lower computational cost. The method is not only fitted to component-based software but also has a potential to solve the state space explosion problem in model checking. However, the computational cost for generating the minimal assumption is very high so the method is difficult to be applied in practice. This paper presents an optimization as a continuous work of the minimized assumption generation method in order to reduce the complexity of the method. The key idea of this method is to find a smaller assumption in a sub-tree of the search tree containing the candidate assumptions using the depth-limited search strategy. With this approach, the improved method can generate assumptions with a lower computational cost and consumption memory than the minimized method. The generated assumptions are also effective for rechecking the systems at much lower computational cost in the context of software evolution. An implemented tool supporting the improved method and experimental results are also presented and discussed.

Discrete-Time fractional Brownian motion (DFBM) and its increment process, called discrete-time fractional Gaussian noise (DFGN), are usually used to describe natural and biomedical phenomena. These two processes are dominated by one parameter, called the Hurst exponent, which needs to be estimated in order to capture the characteristics of physical signals. In the previous work, a variance estimator for estimating the Hurst exponent directly via DFBM was provided, and it didn't consider point selection for linear regression. Since physical signals often appear to be DFGN-type, not DFBM-type, it is imperative to first transform DFGN into DFBM in real applications. In this paper, we show that the variance estimator possesses another form, which can be estimated directly via the autocorrelation functions of DFGN. The above extra procedure of transforming DFGN into DFBM can thus be avoided. On the other hand, the point selection for linear regression is also considered. Experimental results show that 4-point linear regression is almost optimal in most cases. Therefore, our proposed variance estimator is more efficient and accurate than the original one mentioned above. Besides, it is also superior to AR and MA methods in speed and accuracy.

The research on driverless cars has been making much progress lately. In this paper, we propose a new traffic control system without traffic lights at an intersection. We assume a system with fully autonomous driverless cars, and infrastructure to avoid collision completely. When automobiles approach an intersection, they communicates with the access point in both random access mode and polling mode, and the movement of the automobiles will be coordinated by the infra structure (access point). Traffic congestion is very difficult to predict and deal with because it is a function of many unknown factors such as number of cars, weather, road conditions, accidents, etc. The proposed algorithm is designed for urban road networks to ease the congestion, and make it more predictable at the same time. A key idea of this paper is that IEEE 802.11 DCF/PCF mechanisms are used to control traffic flow for driverless cars when there are no traffic lights at an intersection. The algorithm uses the concept of contention/contention-free period of IEEE 802.11 to find a balance between the efficiency of traffic flow and the fairness between users.

In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.

We present attacks on the generalized Feistel schemes, where each round function consists of a subkey XOR, S-boxes, and then a linear transformation (i.e. a Substitution-Permutation (SP) round function). Our techniques are based on rebound attacks. We assume that the S-boxes have a good differential property and the linear transformation has an optimal branch number. Under this assumption, we firstly describe known-key distinguishers on the type-1, -2, and -3 generalized Feistel schemes up to 21, 13 and 8 rounds, respectively. Then, we use the distinguishers to make several attacks on hash functions where Merkle-Damgård domain extender is used and the compression function is constructed with Matyas-Meyer-Oseas or Miyaguchi-Preneel hash modes from generalized Feistel schemes. Collision attacks are made for 11 rounds of type-1 Feistel scheme. Near collision attacks are made for 13 rounds of type-1 Feistel scheme and 9 rounds of type-2 Feistel scheme. Half collision attacks are made for 15 rounds of type-1 Feistel scheme, 9 rounds of type-2 Feistel scheme, and 5 rounds of type-3 Feistel scheme.

This study proposes an improved per-survivor-processing (PSP) scheme to tackle the phase error issue in the convolutionally coded OFDM systems. The proposed approach takes advantage of the trellis structure of the convolutional codes to compensate the symbol-time-offset (STO) caused phase error in frequency domain. Unlike the traditional PSP scheme which simply estimates the phase error by using a state-based horizontal process, the proposed approach develops an extra state-wise vertical process which selects the most likely phase estimate as the survival phase in each trellis stage and then accordingly align the phase of all states to this survival phase before moving to next trellis stage of the PSP scheme. With the vertical process, the resultant phase estimate is more reliable than that of the conventional PSP scheme and hence improve the accuracy in data decoding. Computer simulations confirm the validity of the proposed approach.

A low-complexity method for angle estimation in Multiple-input multiple-output radar (MIMO) radar is presented. In this approach, the signal subspace can be spanned by the orthogonal vectors which are obtained by Multi-stage Wiener Filter (MSWF), then the ESPRIT method can be used to estimate direction of departures (DODs) and direction of arrivals (DOAs). Compared with the conventional ESPRIT algorithm, the proposed method does not involve estimation of the covariance matrix and its eigen-decomposition, which alleviates remarkably the computational complexity. Moreover, the proposed method achieves the similar angle estimation performance. Simulation results are presented to verify the efficiency of the proposed method.

Out-of-vocabulary (OOV) words create serious problems for automatic speech recognition (ASR) systems. Not only are they miss-recognized as in-vocabulary (IV) words with similar phonetics, but the error also causes further errors in nearby words. Language models (LMs) for most open vocabulary ASR systems treat OOV words as a single entity, ignoring the linguistic information. In this paper we present a class-based n-gram LM that is able to deal with OOV words by treating each of them individually without retraining all the LM parameters. OOV words are assigned to IV classes consisting of similar semantic meanings for IV words. The World Wide Web is used to acquire additional data for finding the relation between the OOV and IV words. An evaluation based on adjusted perplexity and word-error-rate was carried out on the Wall Street Journal corpus. The result suggests the preference of the use of multiple classes for OOV words, instead of one unknown class.

There are many roles to play in the bug fixing process in open source software development. A developer called “Committer”, who has a permission to submit a patch into a software repository, plays a major role in this process and holds a key to the successfulness of the project. Despite the importance of committer's activities, we suspect that sometimes committers can make mistakes which have some consequences to the bug fixing process (e.g., reopened bugs after bug fixing). Our research focuses on studying the consequences of each committer's activities to this process. We collected each committer's historical data from the Eclipse-Platform's bug tracking system and version control system and evaluated their activities using bug status in the bug tracking system and commit log in the version control system. Then we looked deeper into each committer's characteristics to see the reasons why some committers tend to make mistakes more than the others.

Based on a reverse converter algorithm derived from the New Chinese Remainder Theorem I, an algorithm for sign detection of RNS {2n-1, 2n, 2n+1} is presented in this paper. The hardware of proposed algorithm can be implemented using two n-bit additions and one (n+1)-bit comparator. Comparing with the previous paper, the proposed algorithm has reduced the number of additions used in the circuit. The experimental results show that the proposed circuit achieves 17.3% savings in area for small moduli and 10.5% savings in area for large moduli on an average, with almost the same speed. The power dissipations obtain 12.6% savings in average.

In this letter, we propose a GRid-based Indexing scheme on Multiple channels (GRIM) for processing spatial window queries in non-flat wireless spatial data broadcasting. When the clients access both popular and regular items simultaneously, GRIM provides the clients with improved access time by broadcasting popular items separately from regular ones in units of grid cells over multiple channels. Simulations show that the proposed GRIM outperforms the existing indexing scheme in terms of the access time.

IEEE 802.15.4 based devices are a key component for mobile and pervasive computing. However, their small dimensions and reduced resources, together with the intrinsic properties of wireless communication, make it difficult to evaluate such networked systems through real-world trials. In this paper we present an emulation testbed intended for the evaluation of IEEE 802.15.4 networked systems. The testbed builds on the generic framework of the wireless network testbed QOMB, and adds IEEE 802.15.4 network, processor and sensing emulation functionality. We validated the testbed through a series of experiments carried out both through real-world trials in a smart home environment, and through emulation experiments on our testbed. Our results show that one can accurately, and in real time, execute IEEE 802.15.4 network applications on our testbed in an emulated environment that reproduces closely the real scenario.

The impact and benefits of infrastructure support are shown by introducing an achievable throughput scaling law of a ultra-wide band (UWB) ad hoc network in which m base stations (BSs) are regularly located. The existing multi-hop scheme consisting of two variants, with and without BS help, is utilized with a slight modification. Our result indicates that the derived throughput scaling depends on the path-loss exponent due to the power-limited characteristics for all operating regimes examined. Furthermore, it is shown that the total throughput scales linearly with parameter m as m is larger than a certain level. It thus turns out the use of infrastructure is also helpful in improving the throughput scaling of UWB networks in some conditions.

A novel long-term sub-band entropy (LT-SubEntropy) measure, which uses improved long-term spectral analysis and sub-band entropy, is proposed for voice activity detection (VAD). Based on the measure, we can accurately exploit the inherent nature of the formant structure on speech spectrogram (the well-known as voiceprint). Results show that the proposed VAD is superior to existing standard VAD methods at low SNR levels, especially at variable-level noise.

In this paper, we discuss the stochastic modeling for operational software reliability measurement, assuming that the testing environment is originally different from the user operation one. In particular, we introduce the concept of systemability which is defined as the reliability characteristic subject to the uncertainty of the field operational environment into the model. First we introduce the environmental factor to consistently bridge the gap between the software failure-occurrence characteristics during the testing and the operation phases. Then we consider the randomness of the environmental factor, i.e., the environmental factor is treated as a random-distributed variable. We use the Markovian imperfect debugging model to describe the software reliability growth phenomena in the testing and the operation phases. We derive the analytical solutions of the several operational software reliability assessment measures which are given as the functions of time and the number of debuggings. Finally, we show several numerical illustrations to investigate the impacts of the consideration of systemability on the field software reliability evaluation.

This letter proposes a monopole multi-sector antenna with dielectric cylinder, and shows some results of simulations that examined the antenna characteristics. The dependency of radiation characteristics on relative permittivity εr shows the lens effect with increase of εr. Furthermore, the characteristics of the proposed antenna are improved by optimizing the termination conditions at the quiescent antennas. The backlobe level is lower than -10 dB. Also, the vertical HPBW and the conical HPBW are around 70.5° and 63.4°, respectively. The optimization improved the actual gain by 2 dB. It is found that the diameter of the proposed antenna is 1/3rd that of the conventional one.