This paper investigates the wireless information surveillance in a suspicious millimeter wave (mmWave) wireless communication system via the spoofing relay based proactive eavesdropping approach. Specifically, the legitimate monitor in the system acts as a relay to simultaneously eavesdrop and send spoofing signals to vary the source transmission rate. To maximize the effective eavesdropping rate, an optimization problem for both hybrid precoding design and power distribution is formulated. Since the problem is fractional and non-convex, we resort to the Dinkelbach method to equivalently reduce the original problem into a series of non-fractional problems, which is still coupling. Afterwards, based on the BCD-type method, the non-fractional problem is reduced to three subproblems with two introduced parameters. Then the GS-PDD-based algorithm is proposed to obtain the optimal solution by alternately optimizing the three subproblems and simultaneously updating the introduced parameters. Numerical results verify the effectiveness and superiority of our proposed scheme.

The methods proposed in this paper enable resynchronization when a synchronization deviation occurs in a sensor node without a beacon or an ack in a wireless sensor network under ultra-limited but stable resources such as the energy generated from tiny solar cell batteries. The method for a single-hop network is straightforward; when a receiver does not receive data, it is simply placed in recovery mode, in which the receiver sets its cycle length TB to (b±γ)T, where b is non-negative integer, 0 < γ < 1, and T is its cycle length in normal mode, and in which the receiver sets its active interval WB to a value that satisfies WB ≥ W + γT, where W is its active interval in normal mode. In contrast, a sender stays in normal mode. Resynchronization methods for linear multi-hop and tree-based multi-hop sensor networks are constructed using the method for a single-hop network. All the methods proposed here are complete because they are always able to resynchronize networks. The results of simulations based on the resynchronization methods are given and those of an experiment using actual sensor nodes with wireless modules are also presented, which show that the methods are feasible.

A novel algorithm is proposed for estimating the direction of arrival (DOA) of linear frequency modulated (LFM) signals for the uniform circular array (UCA). Firstly, the UCA is transformed into an equivalent virtual uniform linear array (ULA) using the mode-space algorithm. Then, the short time Fourier transform (STFT) of each element's output is worked out. We can obtain the spatial time-frequency distribution matrix of the virtual ULA by selecting the single-source time-frequency (t-f) points in the t-f plane and then get the signal subspace of the array. The characteristics nature of the Bessel function allow us to obtain the multiple invariance (MI) of the virtual ULA. So the multiple rotational invariant equation of the array can be obtained and its closed-form solution can be worked out using the multi-least-squares (MLS) criterion. Finally, the two dimensional (2-D) DOA estimation of LFM signals for UCA can be obtained. Numerical simulation results illustrate that the UCA-STFT-MI-ESPRIT algorithm proposed in this paper can improve the estimation precision greatly compared with the traditional ESPRIT-like algorithms and has much lower computational complexity than the MUSIC-like algorithms.

Approximate computing is a promising paradigm to realize fast, small, and low power characteristics, which are essential for modern applications, such as Internet of Things (IoT) devices. This paper proposes the Carry-Predicting Adder (CPredA), an approximate adder that is scalable relative to accuracy and power consumption. The proposed CPredA improves the accuracy of a previously studied adder by performing carry prediction. Detailed simulations reveal that, compared to the existing approximate adder, accuracy is improved by approximately 50% with comparable energy efficiency. Two application-level evaluations demonstrate that the proposed approximate adder is sufficiently accurate for practical use.

In this paper, we first evaluate Breadcrumbs in wireless multi-hop networks and reveal that they brings throughput improvement of not only popular content but also less popular content. Breadcrumbs can distribute popular content traffic towards edges of a wireless network, which enables low-popularity content to be downloaded from the gateway node. We also propose a new caching decision, called receiver caching. In receiver caching, only the receiver node caches the transmitted content. Our simulation results show that receiver caching prevents frequent replacement of cached content, which reduces invalid Breadcrumbs trails to be remained. And they also show that receiver caching significantly improves the total throughput performance of Breadcrumbs.

If a shared IP network is to deliver large-volume streaming media content, such as real-time videos, we need a technique for explicitly setting and dynamically changing the transmission paths used to respond to the congestion situation of the network, including multi-path transmission of a single-flow, to maximize network bandwidth utilization and stabilize transmission quality. However, current technologies cannot realize flexible multi-path transmission because they require complicated algorithms for route searching and the control load for route changing is excessive. This paper proposes a scheme that realizes routing control for multi-path transmission by combining multiple virtual networks on the same physical network. The proposed scheme lowers the control load incurred in creating a detour route because routing control is performed by combining existing routing planes. In addition, our scheme simplifies route searching procedure because congestion avoidance control of multi-path transmission can be realized by the control of a single path. An experiment on the JGN-X network virtualization platform finds that while the time taken to build an inter-slice link must be improved, the time required to inspect whether each slice has virtual nodes that can be connected to the original slice and be used as a detour destination can be as short as 40 microseconds per slice even with large slices having more than 100 virtual nodes.

Language models are a key technology in various tasks, such as, speech recognition and machine translation. They are usually used on texts covering various domains and as a result domain adaptation has been a long ongoing challenge in language model research. With the rising popularity of neural network based language models, many methods have been proposed in recent years. These methods can be separated into two categories: model based and feature based adaptation methods. Feature based domain adaptation has compared to model based domain adaptation the advantage that it does not require domain labels in the corpus. Most existing feature based adaptation methods are based on bias adaptation. We propose a novel feature based domain adaptation technique using hidden layer factorisation. This method is fundamentally different from existing methods because we use the domain features to calculate a linear combination of linear layers. These linear layers can capture domain specific information and information common to different domains. In the experiments, we compare our proposed method with existing adaptation methods. The compared adaptation techniques are based on two different ideas, that is, bias based adaptation and gating of hidden units. All language models in our comparison use state-of-the-art long short-term memory based recurrent neural networks. We demonstrate the effectiveness of the proposed method with perplexity results for the well-known Penn Treebank and speech recognition results for a corpus of TED talks.

Superconducting nanowire single-photon detector(SNSPD) has been one of the important ingredients for photonic quantum information processing (QIP). In order to see the potential of SNSPDs, I briefly review recent progresses of the photonic QIP with SNSPDs implemented for various purposes and present a possible direction for the development of SNSPDs.

Pre-weighting based Contention Resolution Diversity Slotted ALOHA-like (PW-CRDSA-like) schemes with joint multi-user multi-slot detection (JMMD) algorithm are proposed to improve the throughput of random access (RA) in geostationary earth orbit (GEO) satellite networks. The packet and its replicas are weighted by different pre-weighting factors at each user terminal, and are sent in randomly selected slots within a frame. The correlation of channels between user terminals and satellite node in different slots are removed by using pre-weighting factors. At the gateway station, after the decoding processing of CRDSA, the combinations of remained signals in slots that can construct virtual multiple-input multiple-output (MIMO) signal models are found and decoded by the JMMD algorithm. Deadlock problems that can be equivalent to virtual MIMO signal models in the conventional CRDSA-like schemes can be effectively resolved, which improves the throughput of these CRDSA-like schemes. Simulation results show that the PW-CRDSA-like schemes with the JMMD significantly outperform the conventional CRDSA-like schemes in terms of the throughput under equal packet loss ratio (PLR) conditions (e.g. PLR =10-2), and as the number of the transmitted replicas increases, the throughput of the PW-CRDSA-like schemes also increases, and the normalized maximum throughput of the PW-CRDSA-5 (i.e., PW-CRDSA with 5 replicas) scheme can reach 0.95.

The recent rapid increase in the scale of superconducting quantum computing systems greatly increases the demand for qubit control by digital circuits operating at qubit temperatures. In this paper, superconducting digital circuits, such as single-flux quantum and adiabatic quantum flux parametron circuits are described, that are promising candidates for this purpose. After estimating their energy consumption and speed, a conceptual overview of the superconducting electronics for controlling a multiple-qubit system is provided, as well as some of its component circuits.

Background: The applying of third-party libraries is an integral part of many applications. But the libraries choosing is time-consuming even for experienced developers. The automated recommendation system for libraries recommendation is widely researched to help developers to choose libraries. Aim: from software engineering aspect, our research aims to give developers a reliable recommended list of third-party libraries at the early phase of software development lifecycle to help them build their development environment faster; and from technical aspect, our research aims to build a generalizable recommendation system framework which combines collaborative filtering and topic modeling techniques, in order to improve the performance of libraries recommendation significantly. Our works on this research: 1) we design a hybrid methodology to combine collaborative filtering and LDA text mining technology; 2) we build a recommendation system framework successfully based on the above hybrid methodology; 3) we make a well-designed experiment to validate the methodology and framework which use the data of 1,013 mobile application projects; 4) we do the evaluation for the result of the experiment. Conclusions: 1) hybrid methodology with collaborative filtering and LDA can improve the performance of libraries recommendation significantly; 2) based on the hybrid methodology, the framework works very well on the libraries recommendation for helping developers' libraries choosing. Further research is necessary to improve the performance of the libraries recommendation including: 1) use more accurate NLP technologies improve the correlation analysis; 2) try other similarity calculation methodology for collaborative filtering to rise the accuracy; 3) on this research, we just bring the time-series approach to the framework and make an experiment as comparative trial, the result shows that the performance improves continuously, so in further research we plan to use time-series data-mining as the basic methodology to update the framework.

We propose a recursive algorithm to reduce the computational complexity of the r-order nonlinearity of n-variable Boolean functions. Applying the algorithm and using the sufficient and necessary condition put forward by [1] to cut the vast majority of useless search branches, we show that the covering radius of the Reed-Muller Code R(3, 7) in R(5, 7) is 20.

As IT systems, including network systems using SDN/NFV technologies, become large-scaled and complicated, the cost of system management also increases rapidly. Network operators have to maintain their workflow in constructing and consistently updating such complex systems, and thus these management tasks in generating system update plan are desired to be automated. Declarative system update with state space search is a promising approach to enable this automation, however, the current methods is not enough scalable to practical systems. In this paper, we propose a novel heuristic approach to greatly reduce computation time to solve system update procedure for practical systems. Our heuristics accounts for structural bottleneck of the system update and advance search to resolve bottlenecks of current system states. This paper includes the following contributions: (1) formal definition of a novel heuristic function specialized to system update for A* search algorithm, (2) proofs that our heuristic function is consistent, i.e., A* algorithm with our heuristics returns a correct optimal solution and can omit repeatedly expansion of nodes in search spaces, and (3) results of performance evaluation of our heuristics. We evaluate the proposed algorithm in two cases; upgrading running hypervisor and rolling update of running VMs. The results show that computation time to solve system update plan for a system with 100 VMs does not exceed several minutes, whereas the conventional algorithm is only applicable for a very small system.

As an emerging and promising technique, device-free localization (DFL) has drawn considerable attention in recent years. By exploiting the inherent spatial sparsity of target localization, the compressive sensing (CS) theory has been applied in DFL to reduce the number of measurements. In practical scenarios, a prior knowledge about target locations is usually available, which can be obtained by coarse localization or tracking techniques. Among existing CS-based DFL approaches, however, few works consider the utilization of prior knowledge. To make use of the prior knowledge that is partly or erroneous, this paper proposes a novel faulty prior knowledge aided multi-target device-free localization (FPK-DFL) method. It first incorporates the faulty prior knowledge into a three-layer hierarchical prior model. Then, it estimates location vector and learns model parameters under a variational Bayesian inference (VBI) framework. Simulation results show that the proposed method can improve the localization accuracy by taking advantage of the faulty prior knowledge.

In parallel computing systems, the interconnection network forms the critical infrastructure which enables robust and scalable communication between hundreds of thousands of nodes. The traditional packet-switched network tends to suffer from long communication time when network congestion occurs. In this context, we explore the use of circuit switching (CS) to replace packet switches with custom hardware that supports circuit-based switching efficiently with low latency. In our target CS network, a certain amount of bandwidth is guaranteed for each communication pair so that the network latency can be predictable when a limited number of node pairs exchange messages. The number of allocated time slots in every switch is a direct factor to affect the end-to-end latency, we thereby improve the slot utilization and develop a network topology generator to minimize the number of time slots optimized to target applications whose communication patterns are predictable. By a quantitative discrete-event simulation, we illustrate that the minimum necessary number of slots can be reduced to a small number in a generated topology by our design methodology while maintaining network cost 50% less than that in standard tori topologies.

A PCB-integratable metal cap slot antenna is developed for the 60-GHz band. The antenna is composed of two slots and a T-junction and is fed by a post-wall waveguide on a substrate. The dimensions of the designed antenna are 8.0×4.5×2.5mm3. The designed antenna is insensitive with a metal block behind the antenna. The designed antenna is fabricated by machining a brass block and evaluated by measurement. The measurement shows reflection less than -10.0dB, gain larger than 7.8dBi and beamwidth between 54°-65° over the 60-GHz band with endfire radiation. The antenna showed high gain together with short length of half wavelength in the radiation direction. This antenna also can be integrated with printed circuit board (PCB) and is suitable for mobile terminals such as smart phones and tablets.

In this paper, we propose a method for enhancing the visibility of omnidirectional spherical images by enlarging the foreground and compressing the background without provoking a sense of visual incompatibility by using a simplified spring model.

This paper investigates energy-efficient resource allocation problem for the wireless power transfer (WPT) enabled multi-user massive multiple-input multiple-output (MIMO) systems. In the considered systems, the sensor nodes (SNs) are firstly powered by WPT from the power beacon (PB) with a large scale of antennas. Then, the SNs use the harvested energy to transmit the data to the base station (BS) with multiple antennas. The problem of optimizing the energy efficiency objective is formulated with the consideration of maximum transmission power of the PB and the quality of service (QoS) of the SNs. By adopting fractional programming, the energy-efficient optimization problem is firstly converted into a subtractive form. Then, a joint power and time allocation algorithm based on the block coordinate descent and Dinkelbach method is proposed to maximize energy efficiency. Finally, simulation results show the proposed algorithm achieves a good compromise between the spectrum efficiency and total power consumption.

Spectral graph theory gives an algebraic approach to the analysis of the dynamics of a network by using the matrix that represents the network structure. However, it is not easy for social networks to apply the spectral graph theory because the matrix elements cannot be given exactly to represent the structure of a social network. The matrix element should be set on the basis of the relationship between persons, but the relationship cannot be quantified accurately from obtainable data (e.g., call history and chat history). To get around this problem, we utilize the universality of random matrices with the feature of social networks. As such a random matrix, we use the normalized Laplacian matrix for a network where link weights are randomly given. In this paper, we first clarify that the universality (i.e., the Wigner semicircle law) of the normalized Laplacian matrix appears in the eigenvalue frequency distribution regardless of the link weight distribution. Then, we analyze the information propagation speed by using the spectral graph theory and the universality of the normalized Laplacian matrix. As a result, we show that the worst-case speed of the information propagation changes up to twice if the structure (i.e., relationship among people) of a social network changes.

In this paper, a printed inverted-F antenna for radiating circularly polarized wave around its resonant frequency is proposed. To get good axial ratio at the frequency band with 10dB-return loss, a rectangular element is loaded at the feeding line perpendicularly. The axial ratio and the frequency giving the minimum axial ratio can be adjusted by the ratio of the length to the width of the whole antenna and by the dimension of the loaded rectangular element. The operational principle for circular polarization is explained using the electric current distributions. Moreover, the approach of the enhancement for the bandwidth is discussed. The simulated and measured bandwidths of the 10dB-return loss with a 3dB-axial ratio are 2.375GHz-2.591GHz (216MHz) and 2.350-2.534GHz (184MHz), respectively. The proposed antenna's dimension is 0.067λ2c (λc is the wavelength at the center frequency). The proposed antenna is compact and planar, and is therefore useful for circular polarization in the ISM band.