The purpose of this paper is to show that a new type of information-theoretic learning method called “potential learning” can be used to detect and extract important tweets among a great number of redundant ones. In the experiment, we used a dataset of 10,000 tweets, among which there existed only a few important ones. The experimental results showed that the new method improved overall classification accuracy by correctly identifying the important tweets.

This paper proposes a blind, inaudible, robust digital-audio watermarking scheme based on singular-spectrum analysis, which relates to watermarking techniques based on singular value decomposition. We decompose a host signal into its oscillatory components and modify amplitudes of some of those components with respect to a watermark bit and embedding rule. To improve the sound quality of a watermarked signal and still maintain robustness, differential evolution is introduced to find optimal parameters of the proposed scheme. Test results show that, although a trade-off between inaudibility and robustness still persists, the difference in sound quality between the original and the watermarked one is considerably smaller. This improved scheme is robust against many attacks, such as MP3 and MP4 compression, and band-pass filtering. However, there is a drawback, i.e., some music-dependent parameters need to be shared between embedding and extraction processes. To overcome this drawback, we propose a method for automatic parameter estimation. By incorporating the estimation method into the framework, those parameters need not to be shared, and the test results show that it can blindly decode watermark bits with an accuracy of 99.99%. This paper not only proposes a new technique and scheme but also discusses the singular value and its physical interpretation.

We introduce the design and deployment of the latest version of the VNode infrastructure, VNode-i. We present new extended VNode-i functions that offer high performance and provide convenient deep programmability to network developers. We extend resource abstraction to the transport network and achieve highly precise slice measurement for resource elasticity. We achieve precise resource isolation for VNode-i. We achieve coexistence of high performance and programmability. We also enhance AGW functions. In addition, we extend network virtualization from the core network to edge networks and terminals. In evaluation experiments, we deploy the enhanced VNode-i on the JGN-X testbed and evaluate its performance. We successfully create international federation slices across VNode-i, GENI, and Fed4FIRE. We also present experimental results on video streaming on a federated slice across VNode-i and GENI. Testbed experiments confirm the practicality of the enhanced VNode-i.

Bistatic multi-input multi-output (MIMO) radar has the capability of measuring the transmit angle from the receiving array, which means the existence of information redundancy and benefits data association. In this paper, a data association decision for bistatic MIMO radar is proposed and the performance advantages of bistatic MIMO radar in data association is analyzed and evaluated. First, the parameters obtained by receiving array are sent to the association center via coordinate conversion. Second, referencing the nearest neighbor association (NN) algorithm, an improved association decision is proposed with the transmit angle and target range as association statistics. This method can evade the adverse effects of the angle system errors to data association. Finally, data association probability in the presence of array directional error is derived and the correctness of derivation result is testified via Monte Carlo simulation experiments. Besides that performance comparison with the conventional phased array radar verifies the excellent performance of bistatic MIMO Radar in data association.

In this paper, a new scheme is presented for ground moving target indication for multichannel high-resolution wide-swath (HRWS) SAR systems with modified reconstruction filters. The conventional steering vector is generalized for moving targets through taking into account the additional Doppler centroid shift caused by the across-track velocity. Two modified steering vectors with symmetric velocity information are utilized to produce two images for the same scene. Due to the unmatched steering vectors, the stationary backgrounds are defocused but they still hold the same intensities in both images but moving targets are blurred to different extents. The ambiguous components of the moving targets can also be suppressed due to the beamforming in the reconstruction procedure. Therefore, ground moving target indication can be carried out via intensity comparison between the two images. The effectiveness of the proposed method is verified by both simulated and real airborne SAR data.

In this paper, we study the problem of a Boolean function can be represented as the sum of two bent functions. This problem was recently presented by N. Tokareva when studying the number of bent functions [27]. Firstly, several classes of functions, such as quadratic Boolean functions, Maiorana-MacFarland bent functions, many partial spread functions etc, are proved to be able to be represented as the sum of two bent functions. Secondly, methods to construct such functions from low dimension ones are also introduced. N. Tokareva's main hypothesis is proved for n≤6. Moreover, two hypotheses which are equivalent to N. Tokareva's main hypothesis are presented. These hypotheses may lead to new ideas or methods to solve this problem. Finally, necessary and sufficient conditions on the problem when the sum of several bent functions is again a bent function are given.

This paper presents an efficient secure auction protocol for M+1st price auction. In our proposed protocol, a bidding price of a player is represented as a binary expression, while in the previous protocol it is represented as an integer. Thus, when the number of players is m and the bidding price is an integer up to p, compared to the complexity of the previous protocol which is a polynomial of m and p, the complexity of our protocol is a polynomial of m and log p. We apply the Boneh-Goh-Nissim encryption to the mix-and-match protocol to reduce the computation costs.

We propose a simple configuration for colorless and directionless (CD) reconfigurable optical add/drop multiplexers that enables ultra-low contention add/drop operation to be achieved. In the configuration, we apply a combination of multiple small-port-count CD add/drop banks (CD banks) and round-robin CD bank assignment. Evaluation results show that the proposed configuration can substantially reduce intra-node contention rate, which is less than 0.1%. We also find that the proposed configuration can improve the utilization efficiency of wavelength resources and transponders. We discuss the mechanism of how the proposed configuration reduces intra-node contention by analyzing the status of wavelength assignments in direction ports and CD banks.

A novel optical high order quadrature amplitude modulation (QAM) transmission system for high-speed short links is described. Dual-polarization (DP) QAM and twin local lights are generated from one light source in the system, and these lightwaves are simultaneously transmitted via standard single mode fiber. The receiver can be constructed simply because it does not require a coherent light source under wavelength control. The system enables a 3.1 Gbaud DP-16-QAM signal to be successfully demodulated after 80-km transmission without using an optical dispersion compensator. It also achieves high tolerance against phase noise in the signal light source.

This paper presents an adaptive interference-aware receiver for multiuser multiple-input multiple-output (MU-MIMO) downlink systems in wireless local area network (WLAN) systems. The MU-MIMO downlink technique is one of the key techniques that are newly applied to WLAN systems in order to support a very high throughput. However, the simultaneous communication of several users causes inter-user interference (IUI), which adversely affects receivers. Therefore, in order to prevent IUI, a precoding technique is defined at the transmitter based on feedback from the receiver. Unfortunately, however, the receiver still suffers from interference, because the precoding technique is prone to practical errors from the feedback quantization and subcarrier grouping scheme. Whereas ordinary detection schemes are available to mitigate such interference, such schemes are unsuitable because of their low performance or high computational complexity. In this paper, we propose an switching algorithm based on the norm ratio between an effective channel matrix for the desired signal and that of the interfering signals. Simulation results based on the IEEE 802.11ac standard show that the proposed algorithm can achieve near-optimal performance with a 70% reduction in computational complexity.

To substantially alleviate the human blockage problem in mmWave communications, this paper proposes a proactive handover system based on human blockage prediction using RGB and depth (RGB-D) cameras. The proposed scheme uses RGB-D camera images to estimate the mobility of pedestrians and to predict when blockage will occur. On the basis of this information, the proposed system transfers a mobile station (STA) communicating with one wireless BS (base station) to another BS before human blockage occurs and thus avoids blockage-induced throughput degradation. This paper presents performance modeling of both proactive handover scheme and reactive handover scheme which is based on the received power level. A numerical evaluation reveals conditions under which the proactive handover scheme achieves higher spectral efficiency compared to reactive scheme. In addition, using IEEE 802.11ad-based wireless local area network (WLAN) devices, a testbed for implementing the proposed system is built. The innovative experimental results demonstrate that the proactive handover system can considerably reduce the duration of human blockage-induced degradation of throughput performance relative to the reactive scheme.

This paper proposes an opamp-free solution to implement single-phase-clock controlled noise shaping in a SAR ADC. Unlike a conventional noise shaping SAR ADC, the proposal realizes noise shaping by charge redistribution, which is a passive technique. The passive implementation has high power efficiency. Meanwhile, since the proposal maintains the basic architecture and operation method of a traditional SAR ADC, it retains all the advantages of a SAR ADC. Furthermore, noise shaping helps to improve the performance of SAR ADC and relaxes its non-ideal effects. Designed in a 65-nm CMOS technology, the prototype realizes 58-dB SNDR based on an 8-bit C-DAC at 50-MS/s sampling frequency. It consumes 120.7-µW power from a 0.8-V supply and achieves a FoM of 14.8-fJ per conversion step.

In the classical computation theory, the language of a system features the computational behavior of the system but it does not distinguish the determinism and nondeterminism of actions. However, Milner found that the determinism and nondeterminism affect the interactional behavior of interactive systems and thus the notion of language does not features the interactional behavior. Therefore, Milner proposed the notion of (weak) bisimulation to solve this problem. With the development of internet, more and more interactive systems occur in the world, such as electronic trading system. Security is one of the most important topics for these systems. We find that different security policies can also affect the interactional behavior of a system, which exactly is the reason why a good policy can strengthen the security. In other words, two interactive systems with different security policies are not of an equivalent behavior although their functions (or business processes) are identical. However, the classic (weak) bisimulation theory draws an opposite conclusion that their behaviors are equivalent. The notion of (weak) bisimulation is not suitable for these security-oriented interactive systems since it does not consider a security policy. This paper proposes the concept of secure bisimulation in order to solve the above problem.

In this paper, we propose an overloaded multiple-input multiple-output (MIMO) signal detection scheme with slab decoding and lattice reduction (LR). The proposed scheme firstly splits the transmitted signal vector into two parts, the post-voting vector composed of the same number of signal elements as that of receive antennas, and the pre-voting vector composed of the remaining elements. Secondly, it reduces the candidates of the pre-voting vector using slab decoding and determines the post-voting vectors for each pre-voting vector candidate by LR-aided minimum mean square error (MMSE)-successive interference cancellation (SIC) detection. From the performance analysis of the proposed scheme, we derive an upper bound of the error probability and show that it can achieve the full diversity order. Simulation results show that the proposed scheme can achieve almost the same performance as the optimal ML detection while reducing the required computational complexity.

In this paper, a multi-data and multi-ACK verified selective forwarding attacks (SFAs) detection scheme is proposed for containing SFAs. In our scheme, each node (in addition to the nodes in the hotspots area) generates multiple acknowledgement (ACK) message for each received packet to confirm the normal packet transmission. In multiple ACK message, one ACK is returned along the data forwarding path, other ACKs are returned along different routing paths, and thus malicious nodes can be located accurately. At the same time, source node send multiple data routing, one is primary data routing, the others are backup data routing. Primary data is routed to sink directly, but backup data is routed to nodes far from sink, and then waits for the returned ACK of sink when primary data is routed to sink. If a node doesn't receive the ACK, the backup data is routed to sink, thus the success rate of data transmission and lifetime can be improved. For this case, the MDMA scheme has better potential to detect abnormal packet loss and identify suspect nodes as well as resilience against attack. Theoretical analysis and experiments show that MDMA scheme has better ability for ensuring success rate of data transmission, detecting SFA and identifying malicious nodes.

Network Intrusion Detection Systems (NIDS) are deployed to protect computer networks from malicious attacks. Proper evaluation of NIDS requires more scrutiny than the evaluation for general network appliances. This evaluation is commonly performed by sending pre-generated traffic through the NIDS. Unfortunately, this technique is often limited in diversity resulting in evaluations incapable of examining the complex data structures employed by NIDS. More sophisticated methods that generate workload directly from NIDS rules consume excessive resources and are incapable of running in real-time. This work proposes a novel approach to real-time workload generation for NIDS evaluation to improve evaluation diversity while maintaining much higher throughput. This work proposes a generative grammar which represents an optimized version of a context-free grammar derived from the set of strings matching to the given NIDS rule database. The grammar is memory-efficient and computationally light when generating workload. Experiments demonstrate that grammar-generated workloads exert an order of magnitude more effort on the target NIDS. Even better, this improved diversity comes at much smaller cost in memory and speeds four times faster than current approaches.

A novel rendering algorithm with a best-matching patch is proposed to address the noise artifacts associated with Monte Carlo renderings. First, in the sampling stage, the representative patch is selected through a modified patch shift procedure, which gathers homogeneous pixels together to stay clear of the edges. Second, each pixel is filtered over a discrete set of filters, where the range kernel is computed using the selected patches. The difference between the selected patch and the filtered value is used as the pixel error, and the single filter that returns the smallest estimated error is chosen. In the reconstruction stage, pixel colors are combined with features of depth, normal and texture to form a cross bilateral filter, which highly preserves scene details while effectively removing noise. Finally, a heuristic metric is calculated to allocate additional samples in difficult regions. Compared with state-of-the art methods, the proposed algorithm performs better both in visual image quality and numerical error.

In this paper, the average symbol error probability (SEP) performance of decode-and-forward (DF) relaying mobile-to-mobile (M2M) systems with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated. The moment generating function (MGF) method is used to derive exact SEP expressions, and the analysis is verified via simulation. The optimal power allocation problem is investigated. Performance results are presented which show that the fading coefficient, number of cascaded components, relative geometrical gain, number of antennas, and power allocation parameter have a significant effect on the SEP.

The bug reports expressed in natural language text usually suffer from vast, ambiguous and poorly written, which causes the challenge to the duplicate bug reports detection. Current automatic duplicate bug reports detection techniques have mainly focused on textual information and ignored some useful factors. To improve the detection accuracy, in this paper, we propose a new approach calls LNG (LDA and N-gram) model which takes advantages of the topic model LDA and word-based model N-gram. The LNG considers multiple factors, including textual information, semantic correlation, word order, contextual connections, and categorial information, that potentially affect the detection accuracy. Besides, the N-gram adopted in our LNG model is improved by modifying the similarity algorithm. The experiment is conducted under more than 230,000 real bug reports of the Eclipse project. In the evaluation, we propose a new evaluation metric, namely exact-accuracy (EA) rate, which can be used to enhance the understanding of the performance of duplicates detection. The evaluation results show that all the recall rate, precision rate, and EA rate of the proposed method are higher than treating them separately. Also, the recall rate is improved by 2.96%-10.53% compared to the state-of-art approach DBTM.

In lighting control systems, accurate data of artificial light (lighting coefficients) are essential for the illumination control accuracy and energy saving efficiency. This research proposes a novel Lambertian-Radial Basis Function Neural Network (L-RBFNN) to realize modeling of both lighting coefficients and the illumination environment for an office. By adding a Lambertian neuron to represent the rough theoretical illuminance distribution of the lamp and modifying RBF neurons to regulate the distribution shape, L-RBFNN successfully solves the instability problem of conventional RBFNN and achieves higher modeling accuracy. Simulations of both single-light modeling and multiple-light modeling are made and compared with other methods such as Lambertian function, cubic spline interpolation and conventional RBFNN. The results prove that: 1) L-RBFNN is a successful modeling method for artificial light with imperceptible modeling error; 2) Compared with other existing methods, L-RBFNN can provide better performance with lower modeling error; 3) The number of training sensors can be reduced to be the same with the number of lamps, thus making the modeling method easier to apply in real-world lighting systems.