Zero-shot learning refers to the object classification problem where no training samples are available for testing classes. For zero-shot learning, attribute transfer plays an important role in recognizing testing classes. One popular method is the indirect attribute prediction (IAP) model, which assumes that all attributes are independent and equally important for learning the zero-shot image classifier. However, a more practical assumption is that different attributes contribute unequally to the classifier learning. We therefore propose assigning different weights for the attributes based on the relevance probabilities between the attributes and the classes. We incorporate such weighed attributes to IAP and propose a relevance probability-based indirect attribute weighted prediction (RP-IAWP) model. Experiments on four popular attributed-based learning datasets show that, when compared with IAP and RFUA, the proposed RP-IAWP yields more accurate attribute prediction and zero-shot image classification.

We have proposed a quality of experience (QoE)-oriented wireless local area network (WLAN) to provide sufficient QoE to important application flows. Unlike ordinary IEEE 802.11 WLAN, the proposed QoE-oriented WLAN dynamically performs admission control with the aid of the prediction of a “loadable capacity” criterion. This paper proposes an algorithm for dynamic network reconfiguration by centralized control among multiple basic service sets (BSSs) of the QoE-oriented WLAN, in order to maximize the number of traffic flows whose QoE requirements can be satisfied. With the proposed dynamic reconfiguration mechanism, stations (STAs) can change access point (AP) to connect. The operating frequency channel of a BSS also can be changed. These controls are performed according to the current channel occupancy rate of each BSS and the required radio resources to satisfy the QoE requirement of the traffic flow that is not allowed to transmit its data by the admission control. The effectiveness of the proposed dynamic network reconfiguration is evaluated through indoor experiments with assuming two cases. One is a 14-node experiment with QoE-oriented WLAN only, and the other is a 50-node experiment where the ordinary IEEE 802.11 WLAN and the QoE-oriented WLAN coexist. The experiment confirms that the QoE-oriented WLAN can significantly increase the number of traffic flows that satisfy their QoE requirements, total utility of network, and QoE-satisfied throughput, which is the system throughput contributing to satisfy the QoE requirement of traffic flows. It is also revealed that the QoE-oriented WLAN can protect the traffic flows in the ordinary WLAN if the border of the loadable capacity is properly set even in the environment where the hidden terminal problem occurs.

In this paper, we propose an example-based single image super resolution (SR) method by l2 approximation with self-sampled image patches. Example-based super resolution methods can reconstruct high resolution image patches by a linear combination of atoms in an overcomplete dictionary. This reconstruction requires a pair of two dictionaries created by tremendous low and high resolution image pairs from the prepared image databases. In our method, we introduce the dictionary by random sampling patches from just an input image and eliminate its training process. This dictionary exploits the self-similarity of images and it will no more depend on external image sets, which consern the storage space or the accuracy of referred image sets. In addition, we modified the approximation of input image to an l2-norm minimization problem, instead of commonly used sparse approximation such as l1-norm regularization. The l2 approximation has an advantage of computational cost by only solving an inverse problem. Through some experiments, the proposed method drastically reduces the computational time for the SR, and it provides a comparable performance to the conventional example-based SR methods with an l1 approximation and dictionary training.

Event-triggered and self-triggered control methods are an important control strategy in networked control systems. Event-triggered control is a method that the measured signal is sent to the controller (i.e., the control input is recomputed) only when a certain condition is satisfied. Self-triggered control is a method that the control input and the (non-uniform) sampling interval are computed simultaneously. In this paper, we propose new methods of event-triggered control and self-triggered control from the viewpoint of online optimization (i.e., model predictive control). In self-triggered control, the control input and the sampling interval are obtained by solving a pair of a quadratic programming (QP) problem and a mixed integer linear programming (MILP) problem. In event-triggered control, whether the control input is updated or not is determined by solving two QP problems. The effectiveness of the proposed methods is presented by numerical examples.

Analysis of security governed by dynamics of power systems, which we refer to as dynamic security analysis, is a primary but challenging task because of its hybrid nature, that is, nonlinear continuous-time dynamics integrated with discrete switchings. In this paper, we formulate this analysis problem as checking the reachability of a mathematical model representing dynamic performances of a target power system. We then propose a computational approach to the analysis based on the so-called RRT (Rapidly-exploring Random Tree) algorithm. This algorithm searches for a feasible trajectory connecting an initial state possibly at a lower security level and a target set with a desirable higher security level. One advantage of the proposed approach is that it derives a concrete control strategy to guarantee the desirable security level if the feasible trajectory is found. The performance and effectiveness of the proposed approach are demonstrated by applying it to two running examples on power system studies: single machine-infinite system and two-area system for frequency control problem.

Many actual systems, e.g. computer programs, can be modeled as a subclass of Petri nets, called bridge-less workflow nets. For bridge-less workflow nets, we revealed the following properties: (i) any acyclic bridge-less workflow net is free choice; (ii) an acyclic bridge-less workflow net is sound iff it is well-structured; and (iii) any sound bridge-less workflow net is well-structured. We also proposed a necessary and sufficient condition to decide whether a given workflow net is bridge-less, and then constructed a polynomial-time procedure for it.

Patch clamp measurement technique is one of the most important techniques in the field of electrophysiology. The elucidation of the channels, nerve cells, and brain activities as well as contribution of the treatment of neurological disorders is expected from the measurement of ion current. A current-to-voltage converter, which is the front end circuit of the patch clamp measurement system is fabricated using 0.18µm CMOS technology. The current-to-voltage converter requires a resistance as high as 50MΩ as a feedback resistor in order to ensure a high signal-to-noise ratio for very small signals. However, the circuit becomes unstable due to the large parasitic capacitance between the poly layer and the substrate of the on-chip feedback resistor and the instability causes the peaking at lower frequency. The instability of a current-to-voltage converter with a high-resistance as a feedback resistor is analyzed theoretically. A compensation circuit to stabilize the amplifier by driving the N-well under poly resistor to suppress the effect of parasitic capacitance using buffer circuits is proposed. The performance of the proposed circuit is confirmed by both simulation and measurement of fabricated chip. The peaking in frequency characteristic is suppressed properly by the proposed method. Furthermore, the bandwidth of the amplifier is expanded up to 11.3kHz, which is desirable for a patch clamp measurement. In addition, the input referred rms noise with the range of 10Hz ∼ 10kHz is 2.09 Arms and is sufficiently reach the requirement for measure of both whole-cell and a part of single-channel recordings.

Noise and area consumption has been a trade-off in circuit design. Especially for switched-capacitor filters (SCF), kT/C noise gives a limitation to the minimum value of unit capacitance. In case of SCFs with a large capacitance spread, this limitation will result in a large area consumption due to large capacitors. This paper introduces a technique to reduce capacitance spread using charge scaling. It will be shown that this technique can reduce total capacitance of SCFs without deteriorating their noise performances. A design method to reduce the output noise of SC low-pass filters (LPF) based on the combination of cut-set scaling, charge scaling and adaptive configuration is proposed. The proposed technique can reduce the output noise voltage by 30% for small input signals.

A multisignature (MS) scheme enables a group of signers to produce a compact signature on a common message. In analyzing security of MS schemes, a key registration protocol with proof-of-possession (POP) is considered to prevent rogue key attacks. In this paper, we refine the POP-based security model by formalizing a new strengthened POP model and showing relations between the previous POP models and the new one. We next suggest a MS scheme that achieves: (1) non-interactive signing process, (2) O(1) pairing computations in verification, (3) tight security reduction under the co-CDH assumption, and (4) security under the new strengthened POP model. Compared to the tightly-secure BNN-MS scheme, the verification in ours can be at least 7 times faster at the 80-bit security level and 10 times faster at the 128-bit security level. To achieve our goal, we introduce a novel and simple POP generation method that can be viewed as a one-time signature without random oracles. Our POP technique can also be applied to the LOSSW-MS scheme (without random oracles), giving the security in the strengthened POP model.

This paper studies the problem of recovering an arbitrarily distributed sparse matrix from its one-bit (1-bit) compressive measurements. We propose a matrix sketching based binary method iterative hard thresholding (MSBIHT) algorithm by combining the two dimensional version of BIHT (2DBIHT) and the matrix sketching method, to solve the sparse matrix recovery problem in matrix form. In contrast to traditional one-dimensional BIHT (BIHT), the proposed algorithm can reduce computational complexity. Besides, the MSBIHT can also improve the recovery performance comparing to the 2DBIHT method. A brief theoretical analysis and numerical experiments show the proposed algorithm outperforms traditional ones.

In this paper, we propose a novel architecture for a deep learning system, named k-degree layer-wise network, to realize efficient geo-distributed computing between Cloud and Internet of Things (IoT). The geo-distributed computing extends Cloud to the geographical verge of the network in the neighbor of IoT. The basic ideas of the proposal include a k-degree constraint and a layer-wise constraint. The k-degree constraint is defined such that the degree of each vertex on the h-th layer is exactly k(h) to extend the existing deep belief networks and control the communication cost. The layer-wise constraint is defined such that the layer-wise degrees are monotonically decreasing in positive direction to gradually reduce the dimension of data. We prove the k-degree layer-wise network is sparse, while a typical deep neural network is dense. In an evaluation on the M-distributed MNIST database, the proposal is superior to a state-of-the-art model in terms of communication cost and learning time with scalability.

Small loop gain and low crossover frequency result in poor dynamic performance of a single-loop output voltage controlled boost converter in continuous conduction mode. Multi-loop current control can improve the dynamic performance, however, the cost, size and weight of the circuit will also be increased. Sensorless multi-loop control solves the problems, however, the difficulty of the closed-loop characteristics evaluation will be severely aggravated, because there are more parameters in the loops, meanwhile, different from the single-loop, the relationships between the loop gains and closed-loop characteristics including audio susceptibility and output impedance are generally indirect for the multi-loop. Therefore, in this paper, a novel robust H∞ synthesis approach in the time-domain is proposed to design a sensorless controller for boost converters, which need not solve any algebraic Riccati equation or linear matrix inequalities, and most importantly, provides an approach to parameterizing the controller by an adjustable parameter. The adjustable parameter behaves like a ‘knob’ on the dynamic performance, consequently, which makes the closed-loop characteristics evaluation straightforward. A boost converter is used to verify the proposed synthesis approach. Simulations show the great convenience of the closed-loop characteristics evaluation. Practical experiments confirm the simulations.

Past disasters, e.g., mega-quakes, tsunamis, have taught us that it is difficult to fully repair heavily damaged network systems in a short time. The only method for quickly restoring core communications is to start by fully utilizing the surviving network resources from different networks. However, as these networks might be built using different vendors' products (which are often incompatible with each other), the interconnection and utilization of these surviving resources are not straightforward. In this paper, we consider an all-optical multi-vendor interconnection method as an efficient reactive approach during disaster recovery. First, we introduce a disaster recovery scenario in which we use the multi-vendor interconnection approach. Second, we present two sub-problems and propose solutions: (1) network planning problem for multi-vendor interconnection-based emergency optical network construction and (2) interconnection problem for multi-vendor optical networks including both the data-plane and the control-and-management-plane. To enable the operation of multi-vendor systems, command translation middleware is developed for individual vendor-specific network control-and-management systems. Simulations are conducted to evaluate our proposal for sub-problem (1). The results reveal that multi-vendor interconnection can lead to minimum-cost network recovery. Additionally, an emergency optical network prototype is implemented on a two-vendor optical network test-bed to address sub-problem (2). Demonstrations of both the data-plane and the control-and-management-plane validate the feasibility of the multi-vendor interconnection approach in disaster recovery.

Wi-Fi P2P has been deployed extensively in mobile devices. However, Wi-Fi P2P is not efficient because it requires an IP layer connection for transmitting even short messages to nearby devices, especially in high density or highly mobile environments owing to the fact that a user on the move has difficulty selecting service-available devices, and a user device has to frequently connect to and be released from nearby devices. This paper proposes a new messaging framework that enables application-level messages to be exchanged between nearby devices with no IP layer connectivity over Wi-Fi P2P. The pre-association messaging framework (PAMF) supports both broadcast and unicast transmission to maximize the delivery success rate, considering the number of peers and messages. Evaluations of PAMF conducted under real scenarios show that application-level messages can be exchanged within a few seconds, with high success rate. PAMF provides high portability and extensibility because it does not breach the Wi-Fi P2P standard. Moreover, the demonstrations show that PAMF is practical for new proximity services such as local marketing and urgent messaging.

The new generation video standard, i.e., High-efficiency Video Coding (HEVC), shows a significantly improved efficiency relative to the last standard, i.e., H.264. However, the quad tree structured coding units (CUs), which are adopted in HEVC to improve compression efficiency, cause high computational complexity. In this study, a novel fast algorithm is proposed for CU partition in intra coding to reduce the computational complexity. A rough minimum depth prediction of the largest CU method and an early termination method for CU partition based on the total coding bits of the current CU are employed. Many approaches have been proposed to reduce the encoding complexity of HEVC, but these methods do not use the total coding bits of the current CU as the main basis for judgment to judge the CU complexity. Compared with the reference software HM16.6, the proposed algorithm reduces encoding time by 45% on average and achieves an approximately 1.1% increase in Bjntegaard delta bit rate and a negligible peak signal-to-noise ratio loss.

We numerically demonstrated the improvement of single-electron (SE) digital logic gates by utilizing SE input discretizers (IDs). The parameters of the IDs were adjusted to achieve SE tunneling at the threshold voltage designed for switching. An SE four-junction inverter (FJI) with an ID (ID-FJI) had steep switching characteristics between the high and low output voltage levels. The limiting temperature and the critical parameter margins were evaluated. An SE NAND gate with IDs also achieved abrupt switching characteristics between output logic levels.

On-chip neural interface devices based on CMOS image sensor technology are proposed and demonstrated. The devices were designed with target applications to optogenetics in bioscience. Multifunctional CMOS image sensors equipped with an addressable on-chip electrode array were integrated with a functional interface chip that contained embedded GaInN light emitting diodes (LEDs) and electrodes to create a neural interface. Detailed design information regarding the CMOS sensor chip and the functional interface chip including the packaging structure and fabrication processes are presented in this paper. The on-chip optical stimulation functionality was demonstrated in an in vitro experiment using neuron-like cells cultured on the proposed device.

Nonlinear precoding improves the downlink bit error rate (BER) performance of multi-user multiple-input multiple-output (MU-MIMO). Broadband single-carrier (SC) block transmission can improve the capability that nonlinear precoding reduces BER, as it provides frequency diversity gain. This paper considers Tomlinson-Harashima precoding (THP) as a nonlinear precoding scheme for SC-MU-MIMO downlink. In the SC-MU-MIMO downlink with frequency-domain THP proposed by Degen and Rrühl (called SC-FDTHP), the inter-symbol interference (ISI) is suppressed by transmit frequency-domain equalization (FDE) after suppressing the inter-user interference (IUI) by frequency-domain THP. Transmit FDE increases the signal variance, hence transmission performance improvement is limited. In this paper, we propose a new SC-MU-MIMO downlink with time-domain THP which can pre-remove both ISI and IUI (called SC-TDTHP) if perfect channel state information (CSI) is available. Modulo operation in THP suppresses the signal variance increase caused by ISI and IUI pre-removal, and hence the transmission quality improves. For further performance improvement, vector perturbation is introduced to SC-TDTHP (called SC-TDTHP w/VP). Computer simulation shows that SC-TDTHP achieves better BER performance than SC-FDTHP and that SC-TDTHP w/VP offers further improvement in BER performance over SC-MU-MIMO with VP (called SC-VP). Computational complexity is also compared and it is showed that SC-TDTHP and SC-TDTHP w/VP incur higher computational complexity than SC-FDTHP but lower than SC-VP.

In this paper, an analytical threshold voltage model of the strained gate-all-around MOSFET fabricated on the Si1-xGex virtual substrate is presented by solving the two-dimensional Poisson equation. The impact of key parameters such as the strain, channel length, gate oxide thickness and radius of the silicon cylinder on the threshold voltage has been investigated. It has been demonstrated that the threshold voltage decreases as the strain in the channel increases. The threshold voltage roll-off becomes severe when increasing the Ge content in the Si1-xGex virtual substrate. The model is found to tally well with the device simulator.