A wireless node is called isolated if it has no links to other nodes. The number of isolated nodes in a wireless network is an important connectivity index. However, most previous works on analytically determining the number of isolated nodes were not based on practical channel models. In this work, we study this problem using a generic probabilistic channel model that can capture the behaviors of the most widely used channel models, including the disk graph model, the Bernoulli link model, the Gaussian white noise model, the Rayleigh fading model, and the Nakagami fading model. We derive the expected number of isolated nodes and further prove that their distribution asymptotically follows a Poisson distribution. We also conjecture that the nonexistence of isolated nodes asymptotically implies the connectivity of the network, and that the probability of connectivity follows the Gumbel function.

In this paper, we give some results towards the conjecture that σ2t+1l-1,2t are the only nonlinear balanced elementary symmetric Boolean functions where t and l are positive integers. At first, a unified and simple proof of some earlier results is shown. Then a property of balanced elementary symmetric Boolean functions is presented. With this property, we prove that the conjecture is true for n=2m+2t-1 where m,t (m>t) are two non-negative integers, which verified the conjecture for a large infinite class of integer n.

This paper presents an architecture of signal-dependent analog-to-digital converter (ADC) based on MINIMAX sampling scheme that allows achieving high data compression rate and power reduction. The proposed architecture consists of a conventional synchronous ADC, a timer and a peak detector. AD conversion is carried out only when input signal peaks are detected. To improve the accuracy of signal reconstruction, MINIMAX sampling is improved so that multiple points are captured for each peak, and its effectiveness is experimentally confirmed. In addition, power reduction, which is the primary advantage of the proposed signal-dependent ADC, is analytically discussed and then validated with circuit simulations.

The imaging of humans using radar is promising for surveillance systems. Although conventional radar systems detect the presence or position of intruders, it is difficult to acquire shape and motion details because the resolution is insufficient. This paper presents a high-resolution human imaging algorithm for an ultra-wideband (UWB) Doppler radar. The proposed algorithm estimates three-dimensional human images using interferometry and, using velocity information, rejects false images created by the interference of body parts. Experiments verify that our proposed algorithm achieves adequate pedestrian imaging. In addition, accurate shape and motion parameters are extracted from the estimated images.

Multihigh-dimensional chaotic systems were reduced to low-dimensional space embedded equations (SEEs), and their macroscopic and statistical properties were investigated using eigen analysis of the moment vector equation (MVE) of the SEE. First, the state space of the target system was discretized into a finite discrete space. Next, an embedding from the discrete space to a low-dimensional discrete space was defined. The SEE of the target system was derived using the embedding. Finally, eigen analysis was applied to the MVE of the SEE to derive the properties of the target system. The geometric increase in the dimension of the MVE with the dimension of the target system was avoided by using the SEE. The pdfs of arbitrary elements in the target nonlinear system were derived without a reduction in accuracy due to dimension reduction. Moreover, since the dynamics of the system were expressed by the eigenvalues of the MVE, it was possible to identify multiple steady states that cannot be done using numerical simulation. This approach can thus be used to analyze the macroscopic and statistical properties of multi-dimensional chaotic systems.

This paper presents efficient secure auction protocols for first price auction and second price auction. Previous auction protocols are based on a generally secure multi-party protocol called mix-and-match protocol based on plaintext equality tests. However, the time complexity of the plaintext equality tests is large, although the mix-and-match protocol can securely calculate any logical circuits. The proposed protocols reduce the number of times the plaintext equality tests is used by replacing them with the Boneh-Goh-Nissim encryption, which enables calculation of 2-DNF of encrypted data.

In this work, we analyze the performance of cognitive amplify-and-forward (AF) relay networks under the spectrum sharing approach. In particular, by assuming that the AF relay operates in the semi-blind mode (fixed-gain), we derive the exact closed-form expressions of the outage probability for the cognitive relaying (no direct link) and cognitive cooperative (with direct link) systems. Simulation results are presented to verify the theoretical analysis.

This paper deals with a characteristic of the so-called effective boundary condition for a plane wave scattering from periodic surfaces with perfect conductivity. The perturbation solution with all orders is explicitly given under the effective boundary condition. It is newly found that such a perturbation solution satisfies the optical theorem under the exact boundary condition. A comparison between such a perturbation solution and a reference solution for the exact boundary condition by other methods is performed. Then, the validity of such a perturbation solution is concretely discussed.

This letter proposes a multiple symbol differential detection (MSDD) with majority decision method for differentially coded quadrature phase-shift keying (DQPSK) in Rician fading channels. The proposed method shows better BER performance than the conventional MSDD. Simulation results show that the proposed MSDD with a majority decision method improves the system's BER performance for DQPSK signals under the AWGN channel and it approaches asymptotically the theoretical BER performance of coherent detection. Furthermore, the proposed method shows better BER performance under the Rician fading channel with large frequency offsets especially for the range of C/M > 12 dB in comparison with the conventional MSDD.

This paper proposes a lattice-reduction-aided MIMO-OFDM receiver with virtual channels; the receiver enables an increase in the downlink transmission speed for a user where the number of transmit antennas is considerably higher than that of the receive antennas. However, the receiver has a higher computational complexity than conventional lattice-reduction-aided MIMO receivers. Accordingly, we also propose novel techniques to reduce the computational complexity for the lattice-reduction-aided MIMO receivers with virtual channels. The proposed MIMO receiver achieves superior performance in 102 MIMO-OFDM systems. Furthermore, the proposed techniques are shown to reduce the computational complexity to approximately 40% of the original configuration in the 102 MIMO-OFDM systems.

As the number of new malware has increased explosively, traditional malware detection approaches based on pattern matching have been less effective. Therefore, it is important to develop a detection method which relies on not signatures but characteristic behaviors of malware. Recently, malware authors have been embedding functions for countermeasure against malware analyses and detections into malware. Accordingly, modern malware often changes their runtime behaviors in each execution to tolerate against malware analyses and detections. For example, when malware copies itself on a file system, it can randomly determine its file name for avoiding the detections. Another example is that when malware tries to connect its command and control server, it randomly chooses a domain name from a hard-coded domain name list to avoid being blocked by a static blacklist of malicious domain names. We assume that such evasive behaviors are unnecessary for benign software. Therefore the behaviors can be the clues to distinguish malware from benign software. In this paper, we propose a novel behavior-based malware detection method which focuses attention on such characteristics. Our proposed method conducts dynamic analysis on an executable file multiple times in same sandbox environment so as to obtain plural lists of API call sequences and plural traffic logs, and then compares the lists and the logs to find the difference between the multiple executions. In the experiments with 5,697 malware samples and 819 benign software samples, we can detect about 70% malware samples and the false positive rate is about 1%. In addition, we can detect about 50% malware samples which were not detected by each Anti-Virus Software engine. Therefore we confirm the possibility the proposed method may be able to improve the accuracy of malware detection utilizing in combination with other existing methods.

In this paper, a wide input range CMOS multi-mode active rectifier is presented for a magnetic resonant wireless battery charging system. The configuration is automatically changed with respect to the magnitude of the input AC voltage. The output voltage of the multi-mode rectifier is sensed by a comparator. Furthermore, the mode of the multi-mode rectifier is automatically selected by switches among the original rectifier mode, 1-stage voltage multiplier mode, and 2-stage voltage multiplier mode. In the original rectifier, the range of the rectified output DC voltage is from 9 V to 19 V for an input AC voltage from 10 V to 20 V. In the multi-mode rectifier, the input-range is wider compared to the original rectifier by 5 V. As a result, the rectified output DC voltage ranges from 7.5 V to 19 V for an input AC voltage from 5 V to 20 V. The proposed multi-mode rectifier is fabricated in a 0.35 µm CMOS process with an active area of around 2500 µm 1750 µm. When the magnitude of the input AC voltage is 10 V, the power conversion efficiency is about 94%.

This paper presents a new span-based dependency chart parsing algorithm that models the relations between the left and right dependents of a head. Such relations cannot be modeled in existing span-based algorithms, despite their popularity in dependency corpora. We address this problem through ternary-span combination during the subtree derivation. By modeling the relations between the left and right dependents of a head, our proposed algorithm provides a better capability of coordination disambiguation when the conjunction is annotated as the head of the left and right conjuncts. This eventually leads to state-of-the-art performance of dependency parsing on the Chinese data of the CoNLL shared task.

A garbage collector relieves programmers from manual memory management and improves productivity and program reliability. However, there are many other finite system resources that programmers must manage by themselves, such as sockets and database connections. Growing resource leaks can lead to performance degradation and even program crashes. This paper presents the automatic resource collection approach called Resco (RESource COllector) to tolerate non-memory resource leaks. Resco prevents performance degradation and crashes due to resource leaks by two steps. First, it utilizes monitors to count resource consumption and request resource collections independently of memory usage when resource limits are about to be violated. Second, it responds to a resource collection request by safely releasing leaked resources. We implement Resco based on a Java Virtual Machine for Java programs. The performance evaluation against standard benchmarks shows that Resco has a very low overhead, around 1% or 3%. Experiments on resource leak bugs show that Resco successfully prevents most of these programs from crashing with little increase in execution time.

Given an integer n-dimensional lattice basis, the random sampling reduction was proven to find a short vector in arithmetic steps with an integer k, which is freely chosen by users. This paper introduces new random sampling reduction using precomputation techniques. The computation cost is almost independent of the lattice dimension number. The new method is therefore especially advantageous to find a short lattice vector in higher dimensions. The arithmetic operation number of our new method is about 20% of the random sampling reduction with 200 dimensions, and with 1000 dimensions it is less than 1% ( 1/130) of that of the random sampling reduction with representative parameter settings under reasonable assumptions.

In this letter, we analyze the outage performance of cognitive spectrum sharing in two-way relaying systems. We derive expressions of outage probability for the primary and secondary network over independent but not necessarily identically distributed (i.n.i.d.) Rayleigh fading channels. Monte Carlo simulations are presented to verify the theoretical analyses.

Existing salient object detection methods either simply use a threshold to detect desired salient objects from saliency map or search the most promising rectangular window covering salient objects on the saliency map. There are two problems in the existing methods: 1) The performance of threshold-dependent methods depends on a threshold selection and it is difficult to select an appropriate threshold value. 2) The rectangular window not only covers the salient object but also contains background pixels, which leads to imprecise salient object detection. For solving these problems, a novel saliency threshold-free method for detecting the salient object with a well-defined boundary is proposed in this paper. We propose a novel window search algorithm to locate a rectangular window on our saliency map, which contains as many as possible pixels belonging the salient object and as few as possible background pixels. Once the window is determined, GrabCut is applied to extract salient object with a well-defined boundary. Compared with existing methods, our approach doesn't need any threshold to binarize the saliency map and additional operations. Experimental results show that our approach outperforms 4 state-of-the-art salient object detection methods, yielding higher precision and better F-Measure.

We propose a new analytical method for a composite dielectric grating embedded with conducting strips using scattering factors in the shadow theory. The scattering factor in the shadow theory plays an important role instead of the conventional diffraction amplitude. By specifying the relation between scattering factors and spectral-domain Green's functions, we derive expressions of the Green's functions directly for unit surface electric and magnetic current densities, and apply the spectral Galerkin method to our formulation. From some numerical results, we show that the expressions of the Green's functions are valid, and analyze scattering characteristics by composite gratings.

This paper deals with reflection and transmission of a TE plane wave from a one-dimensional random slab with slanted fluctuation by means of the stochastic functional approach. By starting with a generalized representation of the random wavefield from a two-dimensional random slab, and by using a manner for slanted anisotropic fluctuation, the corresponding random wavefield representation and its statistical quantities for one-dimensional cases are newly derived. The first-order incoherent scattering cross section is numerically calculated and illustrated in figures.

It is important to characterize the distributional property and the long-range dependency of traffic arrival processes in modeling Internet traffic. To address this problem, we propose a long-range dependent traffic model using the unbounded Johnson distribution. Using the proposed model, a sequence of traffic rates with the desired four quantiles and Hurst parameter can be generated. Numerical studies show how well the sequence of traffic rates generated by the proposed model mimics that of the real traffic rates using a publicly available Internet traffic trace.