We analyze the cost of networks consisting of optical cross-connect nodes with different architectures for realizing the next generation large bandwidth networks. The node architectures include wavelength granular and fiber granular optical routing cross-connects. The network cost, capital expenditure (CapEx), involves link cost and node cost, both of which are evaluated for different scale networks under various traffic volumes. Numerical experiments demonstrate that the subsystem modular architecture with wavelength granular routing yields the highest cost effectiveness over a wide range of parameter values.

This work reports a new technique to suppress the undesirable multiple-triggering effect in the typical diode triggered silicon controlled rectifier (DTSCR), which is frequently used as an ESD protection element in the advanced CMOS technologies. The technique is featured by inserting additional N-Well areas under the N+ region of intrinsic SCR, which helps to improve the substrate resistance. As a consequence, the delay of intrinsic SCR is reduced as the required triggering current is largely decreased and multiple-triggering related higher trigger voltage is removed. The novel DTSCR structures can alter the stacked diodes to achieve the precise trigger voltage to meet different ESD protection requirements. All explored DTSCR structures are fabricated in a 65-nm CMOS process. Transmission-line-pulsing (TLP) and Very-Fast-Transmission-line-pulsing (VF-TLP) test systems are adopted to confirm the validity of this technique and the test results accord well with our analysis.

The goal of cross-lingual entity alignment is to match entities from knowledge graph of different languages that represent the same object in the real world. Knowledge graphs of different languages can share the same ontology which we guess may be useful for entity alignment. To verify this idea, we propose a novel embedding model based on TransC. This model first adopts TransC and parameter sharing model to map all the entities and relations in knowledge graphs to a shared low-dimensional semantic space based on a set of aligned entities. Then, the model iteratively uses reinitialization and soft alignment strategy to perform entity alignment. The experimental results show that, compared with the benchmark algorithms, the proposed model can effectively fuse ontology information and achieve relatively better results.

Picross 3D is a popular single-player puzzle video game for the Nintendo DS. It presents a rectangular parallelepiped (i.e., rectangular box) made of unit cubes, some of which must be removed to construct an object in three dimensions. Each row or column has at most one integer on it, and the integer indicates how many cubes in the corresponding 1D slice remain when the object is complete. Kusano et al. showed that Picross 3D is NP-complete and Kimura et al. showed that the counting version, the another solution problem, and the fewest clues problem of Picross 3D are #P-complete, NP-complete, and Σ2P-complete, respectively, where those results are shown for the restricted input that the rectangular parallelepiped is of height four. On the other hand, Igarashi showed that Picross 3D is NP-complete even if the height of the input rectangular parallelepiped is one. Extending the result by Igarashi, we in this paper show that the counting version, the another solution problem, and the fewest clues problem of Picross 3D are #P-complete, NP-complete, and Σ2P-complete, respectively, even if the height of the input rectangular parallelepiped is one. Since the height of the rectangular parallelepiped of any instance of Picross 3D is at least one, our hardness results are best in terms of height.

In partially depleted SOI (PD-SOI) technology, the SCR-based protection device is desired due to its relatively high robustness, but be restricted to use because of its inherent low holding voltage (Vh) and high triggering voltage (Vt1). In this paper, the body-tie side triggering diode inserting silicon controlled rectifier (BSTDISCR) is proposed and verified in 180 nm PD-SOI technology. Compared to the other devices in the same process and other related works, the BSTDISCR presents as a robust and latchup-immune PD-SOI ESD protection device, with appropriate Vt1 of 6.3 V, high Vh of 4.2 V, high normalized second breakdown current (It2), which indicates the ESD protection robustness, of 13.3 mA/µm, low normalized parasitic capacitance of 0.74 fF/µm.

For the RF power amplifier, its exposed input and output are susceptible to damage from Electrostatic (ESD) damage. The bi-direction protection is required at the input in push-pull operating mode. In this paper, considering the process compatibility to the power amplifier, cascaded Grounded-gate NMOS (ggNMOS) and Polysilicon diodes (PDIO) are stacked together to form an ESD clamp with forward and reverse protection. Through Transmission line pulse (TLP) and CV measurements, the clamp is demonstrated as latch-up immune and low parasitic capacitance bi-direction ESD protection, with 18.67/17.34V holding voltage (Vhold), 4.6/3.2kV ESD protection voltage (VESD), 0.401/0.415pF parasitic capacitance (CESD) on forward and reverse direction, respectively.

Wireless networked control systems (WNCSs) are control systems whose components are connected through wireless networks. In WNCSs, a controlled object (CO) could become unstable due to bursty packet losses in addition to random packet losses and round-trip delays on wireless networks. In this paper, to reduce these network-induced effects, we propose a new design for multihop TDMA-based WNCSs with two-disjoint-path switching, where two disjoint paths are established between a controller and a CO, and they are switched if bursty packet losses are detected. In this system, we face the following two difficulties: (i) link scheduling in TDMA should be done in such a way that two paths can be switched without rescheduling, taking into account of the constraint of control systems. (ii) the conventional cross-layer design method of control systems is not directly applicable because round-trip delays may vary according to the path being used. Therefore, to overcome the difficulties raised by the two-path approach, we reformulate link scheduling in multihop TDMA and cross-layer design for control systems. Simulation results confirm that the proposed WNCS achieves better performance in terms of the 2-norm of CO's states.

Here, we present a novel spectroscopic imaging method based on the boundary-extraction scheme for wide-beam terahertz (THz) three-dimensional imaging. Optical-lens-focusing systems for THz subsurface imaging generally require the depth of the object from the surface to be input beforehand to achieve the desired azimuth resolution. This limitation can be alleviated by incorporating a wide-beam THz transmitter into the synthetic aperture to automatically change the focusing depth in the post-signal processing. The range point migration (RPM) method has been demonstrated to have significant advantages in terms of imaging accuracy over the synthetic-aperture method. Moreover, in the RPM scheme, spectroscopic information can be easily associated with each scattering center. Thus, we propose an RPM-based terahertz spectroscopic imaging method. The finite-difference time-domain-based numerical analysis shows that the proposed algorithm provides accurate target boundary imaging associated with each frequency-dependent characteristic.

In this letter, we propose a novel deep domain-adaptive convolutional neural network (DDACNN) model to handle the challenging cross-corpus speech emotion recognition (SER) problem. The framework of the DDACNN model consists of two components: a feature extraction model based on a deep convolutional neural network (DCNN) and a domain-adaptive (DA) layer added in the DCNN utilizing the maximum mean discrepancy (MMD) criterion. We use labeled spectrograms from source speech corpus combined with unlabeled spectrograms from target speech corpus as the input of two classic DCNNs to extract the emotional features of speech, and train the model with a special mixed loss combined with a cross-entrophy loss and an MMD loss. Compared to other classic cross-corpus SER methods, the major advantage of the DDACNN model is that it can extract robust speech features which are time-frequency related by spectrograms and narrow the discrepancies between feature distribution of source corpus and target corpus to get better cross-corpus performance. Through several cross-corpus SER experiments, our DDACNN achieved the state-of-the-art performance on three public emotion speech corpora and is proved to handle the cross-corpus SER problem efficiently.

The arms race between offense and defense in the cloud impels the innovation of techniques for monitoring attacks and unauthorized activities. The promising technique of virtual machine introspection (VMI) becomes prevalent for its tamper-resistant capability. However, some elaborate exploitations are capable of invalidating VMI-based tools by breaking the assumption of a trusted guest kernel. To achieve a more reliable and robust introspection, we introduce a practical approach to monitor and detect attacks that attempt to subvert VMI in this paper. Our approach combines supervised machine learning and hardware architectural events to identify those malicious behaviors which are targeted at VMI techniques. To demonstrate the feasibility, we implement a prototype named HyperMon on the Xen hypervisor. The results of our evaluation show the effectiveness of HyperMon in detecting malicious behaviors with an average accuracy of 90.51% (AUC).

Hand-dorsa vein recognition is solved based on the convolutional activations of the pre-trained deep convolutional neural network (DCNN). In specific, a novel task-specific cross-convolutional-layer pooling is proposed to obtain the more representative and discriminative feature representation. Rigorous experiments on the self-established database achieves the state-of-the-art recognition result, which demonstrates the effectiveness of the proposed model.

For cross-corpus speech emotion recognition (SER), how to obtain effective feature representation for the discrepancy elimination of feature distributions between source and target domains is a crucial issue. In this paper, we propose a Target-adapted Subspace Learning (TaSL) method for cross-corpus SER. The TaSL method trys to find a projection subspace, where the feature regress the label more accurately and the gap of feature distributions in target and source domains is bridged effectively. Then, in order to obtain more optimal projection matrix, ℓ1 norm and ℓ2,1 norm penalty terms are added to different regularization terms, respectively. Finally, we conduct extensive experiments on three public corpuses, EmoDB, eNTERFACE and AFEW 4.0. The experimental results show that our proposed method can achieve better performance compared with the state-of-the-art methods in the cross-corpus SER tasks.

This paper proposes a novel interaction technique to transfer data across various types of digital devices in uniform a manner and to allow specifying what kind of data should be sent. In our framework, when users tap multiple devices rhythmically, data corresponding to the rhythm (transfer type) are transferred from a device tapped in the first tap (source device) to the other (target device). It is easy to operate, applicable to a wide range of devices, and extensible in a sense that we can adopt new transfer types by adding new rhythms. Through a subjective evaluation and a simulation, we had a prospect that our approach would be feasible. We also discuss suggestions and limitation to implement the technique.

This paper presents an efficient wideband two-dimensional direction-of-arrival (DOA) estimation for an L-shaped microphone array. We propose a way to construct a wideband sample cross-correlation matrix without any process of DOA preliminary estimation, such as beamforming technique, by exploiting sample cross-correlation matrices of two different frequencies for all frequency bins. Subsequently, wideband DOAs can be estimated by using this wideband matrix along with a scheme of estimating DOA in a narrowband subspace method. Therefore, a contribution of our study is providing an alternative framework for recent narrowband subspace methods to estimating the DOA of wideband sources directly. It means that this framework enables cutting-edge techniques in the existing narrowband subspace methods to implement the wideband direction estimation for reducing the computational complexity and facilitating the estimation algorithm. Theoretical analysis and effectiveness of the proposed method are substantiated through numerical simulations and experiments, which are performed in reverberating environments. The results show that performance of the proposed method performs better than others over a range of signal-to-noise ratio with just a few microphones. All these advantages make the proposed method a powerful tool for navigation systems based on acoustic signal processing.

Network function virtualization (NFV) achieves the flexibility of network service provisioning by using virtualization technology. However, NFV is exposed to a serious security threat known as cross-VM cache timing attacks. In this letter, we look into real security impacts on network virtualization. Specifically, we present two kinds of practical cache timing attacks on virtualized firewalls and routers. We also propose some countermeasures to mitigate such attacks on virtualized network functions.

Recent research on graph drawing focuses on Right-Angle-Crossing (RAC) drawings of 1-plane graphs, where each edge is drawn as a straight line and two crossing edges only intersect at right angles. We give a transformation from a restricted case of the RAC drawing problem to a problem of finding a straight-line drawing of a maximal plane graph where some angles are required to be acute. For a restricted version of the latter problem, we show necessary and sufficient conditions for such a drawing to exist, and design an O(n2)-time algorithm that given an n-vertex plane graph produces a desired drawing of the graph or reports that none exists.

A fast cross-validation algorithm for model selection in kernel ridge regression problems is proposed, which is aiming to further reduce the computational cost of the algorithm proposed by An et al. by eigenvalue decomposition of a Gram matrix.

Wavelength-division multiplexing multicore fibers can transmit a large amount of information over one fiber, and high-density core allocations enable a large number of fiber lines to be deployed in limited spaces. However, inter-core crosstalk degrades the signal in these systems. This paper describes the design of a frequency interleaving scheme for a 7-core hexagonal multicore fiber. Interleaving schemes shift signal spectra between neighboring cores to reduce the signal degradation caused by inter-core crosstalk. The channel frequency allocation that most efficiently lowers the bit error rate is numerically determined in this study. The results indicate that the optimum frequency interleaving improves the allowable crosstalk ratio by 6.3 dB for QPSK signals, demonstrating its potential for improving wavelength-division multiplexing multicore fiber transmission systems.

A novel adaptive cross-layer optimal power allocation (OPA) scheme over physical layer and data-link layer for two-way relaying system with amplify-and-forward policy (TWR-AF) is proposed in this paper. Our goal is to find the optimal power allocation factors under each channel state information (CSI) to maximize the sum throughput of two sources under total transmit power constraint in the physical layer while guaranteeing the statistical delay quality-of-service (QoS) requirement in the data-link layer. By integrating information theory with the concept of effective capacity, the OPA problem is formulated into an optimization problem to maximize the sum effective capacity. It is solved through Lagrange multiplier approach, and the optimal power allocation factors are presented. Simulations are developed and the results show that the proposed cross-layer OPA scheme can achieve the best sum effective capacity with relatively low complexity when compared with other schemes. In addition, the proposed cross-layer OPA scheme achieves the maximal sum effective capacity when the relay is located in (or near) the middle of the two source nodes, and the sum effective capacity becomes smaller when the difference between two QoS exponents becomes larger.

This paper presents a theoretical analysis of a tunable resonator using a coupled line and switches for the first time. The tunable resonator has the capability to tune its resonant frequency and bandwidth. The resonator has two suitable features on its tunable capability. The first feature is that the resonator retains its resonant frequency during bandwidth tuning. The second feature is that the on-state switch for tuning the bandwidth does not affect the insertion loss at the resonant frequency. These features are theoretically confirmed by its mathematically derived input impedance. The results from electromagnetic simulation and measurement of the fabricated tunable resonator also confirm these features. The fabricated tunable resonator changes the resonant frequency from 2.6 GHz to 6.4 GHz and bandwidth between 9% and 55%.