The paper studies controllability of an aggregate demand response system, i.e., the amount of the change of the total electric consumption in response to the change of the electric price, for real-time pricing (RTP). In order to quantify the controllability, this paper defines the controllability index as the lowest occurrence probability of the total electric consumption when the best possible the electric price is chosen. Then the paper formulates the problem which finds the consumer group maximizing the controllability index. The controllability problem becomes hard to solve as the number of consumers increases. To give a solution of the controllability problem, the article approximates the controllability index by the generalized central limit theorem. Using the approximated controllability index, the controllability problem can be reduced to a problem for solving nonlinear equations. Since the number of variables of the equations is independent of the number of consumers, an approximate solution of the controllability problem is obtained by numerically solving the equations.

Environment perception is an important task for intelligent vehicles applications. Typically, multiple sensors with different characteristics are employed to perceive the environment. To robustly perceive the environment, the information from the different sensors are often integrated or fused. In this article, we propose to perform the sensor fusion and registration of the LIDAR and stereo camera using the particle swarm optimization algorithm, without the aid of any external calibration objects. The proposed algorithm automatically calibrates the sensors and registers the LIDAR range image with the stereo depth image. The registered LIDAR range image functions as the disparity map for the stereo disparity estimation and results in an effective sensor fusion mechanism. Additionally, we perform the image denoising using the modified non-local means filter on the input image during the stereo disparity estimation to improve the robustness, especially at night time. To evaluate our proposed algorithm, the calibration and registration algorithm is compared with baseline algorithms on multiple datasets acquired with varying illuminations. Compared to the baseline algorithms, we show that our proposed algorithm demonstrates better accuracy. We also demonstrate that integrating the LIDAR range image within the stereo's disparity estimation results in an improved disparity map with significant reduction in the computational complexity.

Purchase behavior prediction is one of the most important issues to promote both e-commerce companies' sales and the consumers' satisfaction. The prediction usually uses features based on the statistics of items. This kind of features can lead to the loss of detailed information of items. While all items are included, a large number of features has the negative impact on the efficiency of learning the predictive model. In this study, we propose to use the most popular items for improving the prediction. Experiments on the real-world dataset have demonstrated the effectiveness and the efficiency of our proposed method. We also analyze the reason for the performance of the most popular items. In addition, our work also reveals if interactions among most popular items are taken into account, the further significant improvement can be achieved. One possible explanation is that online retailers usually use a variety of sales promotion methods and the interactions can help to predict the purchase behavior.

This letter presents a method for solving several linear equations in max-plus algebra. The essential part of these equations is reduced to constraint satisfaction problems compatible with mixed integer programming. This method is flexible, compared with optimization methods, and suitable for scheduling of certain discrete event systems.

Non-orthogonal multiple access (NOMA) makes multiple mobile users share the same frequency band. In a conventional NOMA scheme, a user pair that can be assigned to the same frequency resource is limited, which reduces the amount of capacity improvement possible. This is because a far user demodulates a signal without canceling an underlaid signal for a near user. In addition, semi-orthogonal multiple access (SOMA) modulation has been proposed. This modulation scheme helps to reduce scheduling complexity and demodulation complexity. In this paper, a joint detection scheme is applied to a far user as well as a near user in a NOMA downlink. The joint detection in the far user leads to a more number of user pairs that can be assigned to the same frequency resource through proportional fair scheduling. The total system throughput performance with the joint detection is evaluated with multi-cell system level simulation. Numerical results show that the joint detection in the original NOMA system increases the system throughput more effectively than that with SOMA modulation.

In text-independent online writer identification, the Gaussian Mixture Model(GMM) writer model trained with the GMM-Universal Background Model(GMM-UBM) framework has acquired excellent performance. However, the system assumes the items in the observation sequence are independent, which neglects the dynamic information between observations. This work shows that although in the text-independent application, the dynamic information between observations is still important for writer identification. In order to extend the GMM-UBM system to use the dynamic information, the hidden Markov model(HMM) with Gaussian observation model is used to model each writer's handwriting in this paper and a new training schematic is proposed. In particular, the observation model parameters of the writer specific HMM are set with the Gaussian component parameters of the GMM writer model trained with the GMM-UBM framework and the state transition matrix parameters are learned from the writer specific data. Experiments show that incorporating the dynamic information is capable of improving the performance of the GMM-based system and the proposed training method is effective for learning the HMM writer model.

Periodic interference frequently affects the measurement of small signals and causes problems in clinical diagnostics. Adaptive filters can be used as potential tools for cancelling such interference. However, when the interference has a frequency fluctuation, the ideal adaptive-filter coefficients for cancelling the interference also fluctuate. When the adaptation property of the algorithm is slow compared with the frequency fluctuation, the interference-cancelling performance is degraded. However, if the adaptation is too quick, the performance is degraded owing to the target signal. To overcome this problem, we propose an adaptive filter that suppresses the fluctuation of the ideal coefficients by utilizing a $rac{pi}{2}$ phase-delay device. This method assumes a frequency response that characterizes the transmission path from the interference source to the main input signal to be sufficiently smooth. In the numerical examples, the proposed method exhibits good performance in the presence of a frequency fluctuation when the forgetting factor is large. Moreover, we show that the proposed method reduces the calculation cost.

With the popularization of Internet of things (IoT), the interaction between human and IoT has become a daily life. In this interaction, the objects of IoT usually require access to personal data, which are often sensitive. We propose a lightweight privacy-preserving model based on the trust evaluation that it can effectively protect privacy based on simple threshold detection. The key issue we address in this work is how to construct trust model so that non trusted objects were prevented from accessing private data. This work can be considered as a lightweight approach to access control for privacy-preservation. The main algorithm in the proposed model is a kind of dynamic self-adjusting trust evaluation mechanism that uses a combination of interaction information occurs between the human and the Internet of things, between the human and the human. According to the given threshold, the trust model can determine the data level of object access in the IoT. We have implemented a prototype of the proposed scheme, thereby demonstrating the feasibility of the proposed scheme on resource-constrained devices.

In this paper, we study the achievable degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) multi-way relay channel with asymmetric message set that models the scenario of the two-way communication between a base station and multiple users through a relay. Under the assumption of delayed channel state information at transmitters (CSIT), we propose an amplify-and-forward relaying scheme based on the scheme proposed by Maddah-Ali and Tse to support signal space alignment, so that the available dimensions of the signal spaces at the relay and the users can be efficiently utilized. The proposed scheme outperforms the traditional one-way scheme from the perspective of DoF, and is useful to relieve the communication bottleneck caused by the asymmetric traffic load inherent in cellular networks.

We have succeeded in developing three techniques, a precise lens-alignment technique, low-loss built-in Spatial Multiplexing optics and a well-matched electrical connection for high-frequency signals, which are indispensable for realizing compact high-performance TOSAs and ROSAs employing hybrid integration technology. The lens position was controlled to within ±0.3 µm by high-power laser irradiation. All components comprising the multiplexing optics are bonded to a prism, enabling the insertion loss to be held down to 0.8 dB due to the dimensional accuracy of the prism. The addition of an FPC layer reduced the impedance mismatch at the junction between the FPC and PCB. We demonstrated a compact integrated four-lane 25 Gb/s TOSA (15.1 mm × 6.5 mm × 5.6 mm) and ROSA (17.0 mm × 12.0 mm × 7.0 mm) using the built-in spatial Mux/Demux optics with good transmission performance for 100 Gb/s Ethernet. These are respectively suitable for the QSFP28 and CFP2 form factors.

The mixer is a crucial circuit block in a WiMax system receiver. The performance of a mixer depends on three specifications: conversion gain, linearity and noise figure. Many mixers have been recently proposed for UWB and wideband systems; however, they either cannot achieve the high conversion gain required for a WiMAX system or they are prone to high power consumption. In this paper, a folded mixer with a high conversion gain is designed for a 2-11GHz WiMAX system and it can achieve a 20MHz IF output signal. From the simulation results, the proposed folded mixer achieves a conversion gain of 18.9 to 21.5dB for the full bandwidth. With a 0.2 to 4.4dBm IIP3, the NF is 13.5 to 17.6dB. The folded mixer is designed using TSMC 0.18µm CMOS technology. The core power consumption of the mixer is 11.8mW.

Wafers with smooth Au thin films (rms surface roughness: < 0.5nm, thickness: < 50nm) were successfully bonded in ambient air at room temperature after an Ar radio frequency plasma activation process. The room temperature bonded glass wafers without any heat treatment showed a sufficiently high die-shear strength of 47-70MPa. Transmission electron microscopy observations showed that direct bonding on the atomic scale was achieved. This surface-activated bonding method is expected to be a useful technique for future heterogeneous photonic integration.

Rapid process scaling and the introduction of the multilevel cell (MLC) concept have lowered costs of NAND Flash memories, but also degraded reliability. For this reason, the memories are depending on strong error correcting codes (ECCs), and this has enabled the memories to be used in wide range of storage applications, including solid-state drives (SSDs). Meanwhile, too strong error correcting capability requires excessive decoding complexity and check bits. In NAND Flash memories, cell errors to neighborhood voltage levels are more probable than those to distant levels. Several ECCs reflecting this characteristics, including limited-magnitude ECCs which correct only errors with a certain limited magnitude and low-density parity check (LDPC) codes, have been proposed. However, as most of these ECCs need the multiple bits in a cell for encoding, they cannot be used with multipage programing, a high speed programming method currently employed in the memories. Also, binary ECCs with Gray codes are no longer optimal when multilevel voltage shifts (MVSs) occur. In this paper, an error correction method reflecting the error characteristic is presented. This method detects errors by a binary ECC as a conventional manner, but a nonbinary value or whole the bits in a cell, are subjected to error correction, so as to be corrected into the most probable neighborhood value. The amount of bit error rate (BER) improvement is depending on the probability of the each error magnitude. In case of 2bit/cell, if only errors of magnitude 1 and 2 can occur and the latter occupies 5% of cell errors, acceptable BER is improved by 4%. This is corresponding to extending 2.4% of endurance. This method needs about 15% longer average latency, 19% longer maximum latency, and 15% lower throughput. However, with using the conventional method until the memories' lifetime number of program/erase cycling, and the proposed method after that, BER improvement can be utilized for extending endurance without latency and throughput degradation until the switch of the methods.

The layered cell configuration, in which a large number of small cells are set in a macro-cell coverage area, is attracting much attention recently as a promising approach to handle the rapidly increasing mobile data traffic. In this configuration, cells of various sizes, from macro to small, are placed in various locations, so that the variation in the number and the distribution of the users among cells becomes much wider than in conventional macro-cell homogeneous networks. Therefore, even in the layered cell configuration, the users in the cell with many users and low received signal quality may experience low throughput especially at cell edge. This is because such users experience both low spectral efficiency and few radio resources. In order to resolve this issue, a lot of techniques have been proposed such as load balancing and cooperative multi-point transmission. In this paper, we focus on scheduling priority control as a simple solution that can also be used in combination with load balancing and coordinated multi-point transmission. We propose an adaptive scheduling priority control scheme based on the congestion and user distribution of each cell and clarify the effect of the proposed method by computer simulations.

Similarity search is an important and fundamental problem, and thus widely used in various fields of computer science including multimedia, computer vision, database, information retrieval, etc. Recently, since loitering behavior often leads to abnormal situations, such as pickpocketing and terrorist attacks, its analysis attracts increasing attention from research communities. In this paper, we present AntiLoiter, a loitering discovery system adopting efficient similarity search on surveillance videos. As we know, most of existing systems for loitering analysis, mainly focus on how to detect or identify loiterers by behavior tracking techniques. However, the difficulties of tracking-based methods are known as that their analysis results are heavily influenced by occlusions, overlaps, and shadows. Moreover, tracking-based methods need to track the human appearance continuously. Therefore, existing methods are not readily applied to real-world surveillance cameras due to the appearance discontinuity of criminal loiterers. To solve this problem, we abandon the tracking method, instead, propose AntiLoiter to efficiently discover loiterers based on their frequent appearance patterns in longtime multiple surveillance videos. In AntiLoiter, we propose a novel data structure Luigi that indexes data using only similarity value returned by a corresponding function (e.g., face matching). Luigi is adopted to perform efficient similarity search to realize loitering discovery. We conducted extensive experiments on both synthetic and real surveillance videos to evaluate the efficiency and efficacy of our approach. The experimental results show that our system can find out loitering candidates correctly and outperforms existing method by 100 times in terms of runtime.

Crystalline GaN films can be grown even on amorphous substrates with the use of graphene buffer layers by pulsed sputtering deposition (PSD). The graphene buffer layers allowed us to grow highly c-axis-oriented GaN films at low substrate temperatures. Full-color GaN-based LEDs can be fabricated on the GaN/graphene structures and they are operated successfully. This indicates that the present technique is promising for future large-area light-emitting displays on amorphous substrates.

We prepared a bR thin film by the wire-bar coating technique, and investigated the transient photo-current characteristics of the bR photocell. The transient photo-current signal of bR photocells prepared by the wire-bar coating technique and the dip coating technique was compared. An almost identical transient photo-current signal intensity was obtained both for the wire-bar coating technique and dip coating technique, while the thickness of bR thin film prepared by the wire-bar coating technique is slightly thinner than that prepared by the dip-coating technique. Transparent conductive oxide dependence of the transient photo-current signal is almost the same dependence for the bR photocells with a bR thin film prepared by both techniques. Application of the wire-bar coating technique is significant from the viewpoints of the bR's sample consumption as well as simplicity of sample preparation.

Compact and room-temperature operable terahertz emitting devices have been proposed using a semiconductor coupled multilayer cavity that consists of two functional cavity layers and three distributed Bragg reflector (DBR) multilayers. Two cavity modes with an optical frequency difference in the terahertz region are realized since two cavities are coupled by the intermediate DBR multilayer. In the proposed device, one cavity is used as the active layer for two-color lasing in the near-infrared region by current injection and the other is used as the second-order nonlinear optical medium for difference-frequency generation of the two-color fundamental laser light. The control of the nonlinear polarization by face-to-face bonding of two epitaxial wafers with different orientations is quite effective to achieve bright terahertz emission from the coupled cavity. In this study, two-color emission by optical excitation was measured for the wafer-bonded GaAs/AlGaAs coupled multilayer cavity containing self-assembled InAs quantum dots (QDs). We found that optical loss at the bonding interface strongly affects the two-color emission characteristics when the bonding was performed in the middle of the intermediate DBR multilayer. The effect was almost eliminated when the bonding position was carefully chosen by considering electric field distributions of the two modes. We also fabricated the current-injection type devices using the wafer-bonded coupled multilayer cavities. An assemble of self-assembled QDs is considered to be desirable as the optical gain medium because of the discrete nature of the electronic states and the relatively wide gain spectrum due to the inhomogeneous size distribution. The gain was, however, insufficient for two-color lasing even when the nine QD layers were used. Substituting two types of InGaAs multiple quantum wells (MQWs) for the QDs, we were able to demonstrate two-color lasing of the device when the gain peaks of MQWs were tuned to the cavity modes by lowering the operating temperature.

An adaptive time-step control method is proposed for the damped pseudo-transient analysis (DPTA) method. The new method is based on the idea of switched evolution/relaxation (SER), which can automatically adapt the step size for different circuit states. Considering the number of iterations needed for the convergence of Newton-Raphson (NR) method and the states in previous steps, the proposed method can automatically optimize the time-step size. Using numerical examples, the new method is proven to improve robustness, simulation efficiency, and the convergence of DPTA for solving nonlinear DC circuit equations.

The maintenance of a system on a ship has limitations when the ship is engaged in a voyage because of limited maintenance resources. When a system fails, it is either repaired instantly on ship with probability p or remains unrepaired during the voyage with probability 1-p owing to the lack of maintenance resources. In the latter case, the system is repaired after the voyage. We propose two management policies for the overhaul interval of an IFR system: one manages the overhaul interval by number of voyages and the other manages it by the total voyage time. Our goal is to determine the optimal policy that ensures the required availability of the system and minimizes the expected cost rate.