MUltiple SIgnal Classification (MUSIC) is a standard technique for direction of arrival (DOA) estimation with high resolution. However, MUSIC cannot estimate DOAs accurately in the case of underdetermined conditions, where the number of sources exceeds the number of microphones. To overcome this drawback, an extension of MUSIC using cumulants called 2q-MUSIC has been proposed, but this method greatly suffers from the variance of the statistics, given as the temporal mean of the observation process, and requires long observation. In this paper, we propose a new approach for extending MUSIC that exploits higher-order moments of the signal for the underdetermined DOA estimation with smaller variance. We propose an estimation algorithm that nonlinearly maps the observed signal onto a space with expanded dimensionality and conducts MUSIC-based correlation analysis in the expanded space. Since the dimensionality of the noise subspace is increased by the mapping, the proposed method enables the estimation of DOAs in the case of underdetermined conditions. Furthermore, we describe the class of mapping that allows us to analyze the higher-order moments of the observed signal in the original space. We compare 2q-MUSIC and the proposed method through an experiment assuming that the true number of sources is known as prior information to evaluate in terms of the bias-variance tradeoff of the statistics and computational complexity. The results clarify that the proposed method has advantages for both computational complexity and estimation accuracy in short-time analysis, i.e., the time duration of the analyzed data is short.

This paper presents a novel data compression method for testing integrated circuits within the selective dictionary coding framework. Due to the inverse value of dictionary indices made use of for the compatibility analysis with the heuristic algorithm utilized to solve the maximum clique problem, the method can obtain a higher compression ratio than existing ones.

Sentence similarity computation is an increasingly important task in applications of natural language processing such as information retrieval, machine translation, text summarization and so on. From the viewpoint of information theory, the essential attribute of natural language is that the carrier of information and the capacity of information can be measured by information content which is already successfully used for word similarity computation in simple ways. Existing sentence similarity methods don't emphasize the information contained by the sentence, and the complicated models they employ often need using empirical parameters or training parameters. This paper presents a fully unsupervised computational model of sentence semantic similarity. It is also a simply and straightforward model that neither needs any empirical parameter nor rely on other NLP tools. The method can obtain state-of-the-art experimental results which show that sentence similarity evaluated by the model is closer to human judgment than multiple competing baselines. The paper also tests the proposed model on the influence of external corpus, the performance of various sizes of the semantic net, and the relationship between efficiency and accuracy.

Increasing demand in data-traffic has been addressed over the last few years. It is expected that the data-traffic will present the significant part of the total backbone traffic. Accordingly, much more transmission systems will be required to support this growth. A free space optic (FSO) communication is the greatest promising technology supporting high-speed and high-capacity transport networks. It can support multi Gbit/s for few kilometers transmission distance. The benefits of an FSO system are widespread, low cost, flexibility, immunity to electromagnetic field, fast deployment, security, etc. However, it suffers from some drawbacks, which limit the deployment of FSO links. The main drawback in FSO is the degradation in the signal quality because of atmospheric channel impairments. In addition, it is high sensitive for illumination noise coming from external sources such as sun and lighting systems. It is more benefit that FSO and mmWave are operating as a complementary solution that is known as hybrid FSO/mmWave links. Whereas the mmWave is susceptible to heavy rain conditions and oxygen absorption, while fog has no particular effect. This paper will help to better understand the FSO and mmWave technologies and applications operating under various atmospheric conditions. Furthermore, in order to improve the system performance and availability, several modulation schemes will be discussed. In addition to, the hybrid FSO/mmWave with different diversity combining techniques are presented.

A fully synthesizable all-digital phase-locked loop (AD-PLL) with a stochastic time-to-digital converter (STDC) is proposed in this paper. The whole AD-PLL circuit design is based on only standard cells from digital library, thus the layout of this AD-PLL can be automatically synthesized by a commercial place-and-route (P&R) tool with a foundry-provided standard-cell library. No manual layout and process modification is required in the whole AD-PLL design. In order to solve the delay mismatch issue in the delay-line-based time-to-digital converter (TDC), an STDC employing only standard D flip-flop (DFF) is presented to mitigate the sensitivity to layout mismatch resulted from automatic P&R. For the stochastic TDC, the key idea is to utilize the layout uncertainty due to automatic P&R which follows Gaussian distribution according to statistics theory. Moreover, the fully synthesized STDC can achieve a finer resolution compared to the conventional TDC. Implemented in a 28nm fully depleted silicon on insulator (FDSOI) technology, the fully synthesized PLL consumes only 480µW under 1.0V power supply while operating at 0.9GHz. It achieves a figure of merit (FoM) of -231.1dB with 4.0ps RMS jitter while occupying 0.0055mm2 chip area only.

WPA is the security protocol for IEEE 802.11 wireless networks standardized as a substitute for WEP in 2003, and uses RC4 stream cipher for encryption. It improved a 16-byte RC4 key generation procedure, which is known as TKIP, from that in WEP. One of the remarkable features in TKIP is that the first 3-byte RC4 key is derived from the public parameter IV, and an analysis using this feature has been reported by Sen Gupta et al. at FSE 2014. They focused on correlations between the keystream bytes and the known RC4 key bytes in WPA, which are called key correlations or linear correlations, and improved the existing plaintext recovery attack using their discovered correlations. No study, however, has focused on such correlations including the internal states in WPA. In this paper, we investigated new linear correlations including unknown internal state variables in both generic RC4 and WPA. From the result, we can successfully discover various new linear correlations, and prove some correlations theoretically.

A method based on score level fusion using logistic regression has been developed that uses packet header information to classify Internet applications. Applications are classified not on the basis of the individual flows for each type of application but on the basis of all the flows for each type of application, i.e., the “overall traffic flow.” The overall traffic flow is divided into equal time slots, and the applications are classified using statistical information obtained for each time slot. Evaluation using overall traffic flow generated by five types of applications showed that its true and false positive rates are better than those of methods using feature level fusion.

In the paradigm of network coding, when the network topology information cannot be utilized completely, random linear network coding (RLNC) is proposed as a feasible coding scheme. But since RLNC neither considers the global network topology nor coordinates codings between different nodes, it may not achieve the best possible performance of network coding. Hence, the performance analysis of RLNC is very important for both theoretical research and practical applications. Motivated by a fact that different network topology information can be available for different network communication problems, we study and obtain several upper and lower bounds on the failure probability at sink nodes depending on different network topology information in this paper, which is also the kernel to discuss some other types of network failure probabilities. In addition, we show that the obtained upper bounds are tight, the obtained lower bound is asymptotically tight, and we give the worst cases for different scenarios.

Connection Service Providers (CSP) are wishing to increase their Return on Investment (ROI) by utilizing the data assets generated by tracking subscriber behaviors. This results in the ability to apply personalized policies, monitor and control the service traffic to subscribers and gain more revenue through the usage of subscriber data with ad networks. In this paper, a system is proposed to monitor and analyze the Internet access of the subscribers of a regional SP in order to classify the subscribers into interest categories from the Interactive Advertising Bureau (IAB) categories. The study employs the categorization engine to build category vectors for all individuals using Internet services through the subscription. The proposal makes it easy to detect changes in the interests of individuals/subscribers over time.

We consider the problem of deciding whether a query can be rewritten by a nondeterministic view. It is known that rewriting is decidable if views are given by single-valued non-copying devices such as compositions of single-valued extended linear top-down tree transducers with regular look-ahead, and queries are given by deterministic MSO tree transducers. In this paper, we extend the result to the case that views are given by nondeterministic devices that are not always single-valued. We define two variants of rewriting: universal preservation and existential preservation, and discuss the decidability of them.

We have studied ultra-low-power superconductor circuits using adiabatic quantum flux parametron (AQFP) logic. Latches, which store logic data in logic circuits, are indispensable logic elements in the realization of AQFP computing systems. Among them, feedback latches, which hold data by using a feedback loop, have advantages in terms of their wide operation margins and high stability. Their drawbacks are their large junction counts and long latency. In this paper, we propose a majority gate-based feedback latch for AQFP logic with a reduced number of junctions. We designed and fabricated the proposed AQFP latches using a standard National Institute of Advanced Industrial Science and Technology (AIST) process. The measurement results showed that the feedback latches operate with wide operation margins that are comparable with circuit simulation results.

Controlling the peak-to-mean envelope power ratio (PMEPR) of orthogonal frequency-division multiplexed (OFDM) transmissions is a significant obstacle in many low-cost applications of OFDM. An coding approach proposed by H.R. Sadjadpour presents non-square M-QAM symbols as a combination of QPSK and BPSK signals when M=22n+1, and then uses QPSK and BPSK Golay (or Golay-like) sequences with a constant PMEPR to generate M-QAM sequences. This paper proposes a new scheme in which M-QAM sequences are generated by QPSK and BPSK sequences with variable PMEPRs. In other words, this new scheme is a general case of the existing approach. As a result, the code rate of the new sequence is significantly improved, while the upper bound of its PMEPR remains at a comparative level.

It is known that, using just a deck of cards, an arbitrary number of parties with private inputs can securely compute the output of any function of their inputs. In 2009, Mizuki and Sone constructed a six-card COPY protocol, a four-card XOR protocol, and a six-card AND protocol, based on a commonly used encoding scheme in which each input bit is encoded using two cards. However, up until now, there are no known results to construct a set of COPY, XOR, and AND protocols based on a two-card-per-bit encoding scheme, which all can be implemented using only four cards. In this paper, we show that it is possible to construct four-card COPY, XOR, and AND protocols using polarizing plates as cards and a corresponding two-card-per-bit encoding scheme. Our protocols use a minimum number of cards in the setting of two-card-per-bit encoding schemes since four cards are always required to encode the inputs. Moreover, we show that it is possible to construct two-card COPY, two-card XOR, and three-card AND protocols based on a one-card-per-bit encoding scheme using a common reference polarizer which is a polarizing material accessible to all parties.

This paper proposes two linearity enhancement techniques for open-loop amplifiers. One technique is nonlinearity cancellation. An amplifier with reversed nonlinearity is proposed to cascade with a conventional common source amplifier. The product of these two nonlinear gains demonstrates much higher linearity. It achieves a SFDR of 71 dB when differential output range is 600 mV. Compared with the conventional common source amplifier, about 24 dB improvement is achieved. Another proposed technique is gain adapting. An input amplitude detector utilizing second order nonlinearity is combined with a source-degenerated amplifier. It can adjust the gain automatically according to the input amplitude, and compensate the gain compression when the input amplitude becomes larger. A SFDR of 69 dB is realized when the differential output range is 600 mV. An improvement of 23 dB is achieved after gain is adapted. Furthermore, mismatch calibration for the two proposed linearity enhancement techniques is investigated. Finally, comparison between two proposed amplifiers is introduced. The amplifier with nonlinearity cancellation has advantage in large signal range while the amplifier utilizing gain adapting is more competitive on accurate calibration, fast response and low noise.

This paper considers an optimal stabilization problem of quantitative discrete event systems (DESs) under the influence of disturbances. We model a DES by a deterministic weighted automaton. The control cost is concerned with the sum of the weights along the generated trajectories reaching the target state. The region of weak attraction is the set of states of the system such that all trajectories starting from them can be controlled to reach a specified set of target states and stay there indefinitely. An optimal stabilizing controller is a controller that drives the states in this region to the set of target states with minimum control cost and keeps them there. We consider two control objectives: to minimize the worst-case control cost (1) subject to all enabled trajectories and (2) subject to the enabled trajectories starting by controllable events. Moreover, we consider the disturbances which are uncontrollable events that rarely occur in the real system but may degrade the control performance when they occur. We propose a linearithmic time algorithm for the synthesis of an optimal stabilizing controller which is robust to disturbances.

As technology nodes continue to shrink, the impact of radiation-induced soft error on processor reliability increases. Estimation of processor reliability and identification of vulnerable flip-flops requires accurate soft error rate (SER) analysis techniques. This paper presents a proposal for a soft error propagation analysis technique. We specifically examine single event upset (SEU) occurring at a flip-flop in sequential circuits. When SEUs propagate in sequential circuits, the faults can be masked temporally and logically. Conventional soft error propagation analysis techniques do not consider error convergent timing on re-convergent paths. The proposed technique can analyze soft error propagation while considering error-convergent timing on a re-convergent path by combinational analysis of temporal and logical effects. The proposed technique also considers the case in which the temporal masking is disabled with an enable signal of the erroneous flip-flop negated. Experimental results show that the proposed technique improves inaccuracy by 70.5%, on average, compared with conventional techniques using ITC 99 and ISCAS 89 benchmark circuits when the enable probability is 1/3, while the runtime overhead is only 1.7% on average.

To study the similarity between queries and retrieved masses, we design an interactive CBIR (Content-based Image Retrieval) CADx (Computer-aided Diagnosis) system using relevance feedback for the characterization of breast masses in ultrasound (US) images based on radiologists' visual similarity assessment. The CADx system retrieves masses that are similar to query masses from a reference library based on six computer-extracted features that describe the texture, width-to-height, and posterior shadowing of the mass. The k-NN retrieval with Euclidean distance similarity measure and the Rocchio relevance feedback algorithm (RRF) are used. To train the RRF parameters, the similarities of 1891 image pairs from 62 (31 malignant and 31 benign) masses are rated by 3 MQSA (Mammography Quality Standards Act) radiologists using a 9-point scale (9=most similar). The best RRF parameters are chosen based on 3 observer experiments. For testing, 100 independent query masses (49 malignant and 51 benign) and 121 reference masses on 230 (79 malignant and 151 benign) images were collected. Three radiologists rated the similarity between the query masses and the computer-retrieved masses. Average similarity ratings without and with RRF were 5.39 and 5.64 for the training set and 5.78 and 6.02 for the test set, respectively. Average AUC values without and with RRF were, respectively, 0.86±0.03 and 0.87±0.03 for the training set and 0.91±0.03 and 0.90±0.03 for the test set. On average, masses retrieved using the CBIR system were moderately similar to the query masses based on radiologists' similarity assessments. RRF improved the similarity of the retrieved masses.

For detecting the image copies of a given original image generated by arbitrary rotation, the existing image copy detection methods can not simultaneously achieve desirable performances in the aspects of both accuracy and efficiency. To address this challenge, a novel effective and efficient image copy detection method is proposed based on two global features extracted from rotation invariant partitions. Firstly, candidate images are preprocessed by an averaging operation to suppress noise. Secondly, the rotation invariant partitions of the preprocessed images are constructed based on pixel intensity orders. Thirdly, two global features are extracted from these partitions by utilizing image gradient magnitudes and orientations, respectively. Finally, the extracted features of images are compared to implement copy detection. Promising experimental results demonstrate our proposed method can effectively and efficiently resist rotations with arbitrary degrees. Furthermore, the performances of the proposed method are also desirable for resisting other typical copy attacks, such as flipping, rescaling, illumination and contrast change, as well as Gaussian noising.

In this paper, the system identification problem from the high-dimensional input and output is considered. If the relationship between the features extracted from the data is represented as a linear time-invariant dynamical system, the input-output manifold learning method has shown to be a powerful tool for solving such a system identification problem. However, in the previous study, the system is assumed to be initially relaxed because the transfer function model is used for system representation. This assumption may not hold in several tasks. To handle the initially non-relaxed system, we propose the alternative approach of the input-output manifold learning with state space model for the system representation. The effectiveness of our proposed method is confirmed by experiments with synthetic data and motion capture data of human-human conversation.

Network virtualization (NV) provides a promising solution to overcome the resistance of the current Internet in aspects of architecture change, and virtual network embedding (VNE) has been recognized as a core component in NV. In this paper, the current advances in exploring model, methods and technologies for embedding the virtual network into the substrate network, are summarized. Furthermore, the future research trends are drawn. The main distinctive aspects of this survey with early ones include that it is mainly contributed to simplify the VNE problem on large networks, and that more recent publications in this field are introduced. In addition, the suggestions to the future investigation will concern some new terms of the VNE optimization.