This paper proposes a parallel peak cancellation (PC) process for the computational complexity-efficient algorithm called PC with a channel-null constraint (PCCNC) in the adaptive peak-to-average power ratio (PAPR) reduction method using the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. By simultaneously adding multiple PC signals to the time-domain transmission signal vector, the required number of iterations of the iterative algorithm is effectively reduced along with the PAPR. We implement a constraint in which the PC signal is transmitted only to the null space in the MIMO channel by beamforming (BF). By doing so the data streams do not experience interference from the PC signal on the receiver side. Since the fast Fourier transform (FFT) and inverse FFT (IFFT) operations at each iteration are not required unlike the previous algorithm and thanks to the newly introduced parallel processing approach, the enhanced PCCNC algorithm reduces the required total computational complexity and number of iterations compared to the previous algorithms while achieving the same throughput-vs.-PAPR performance.

In this letter we analyze the economic worth of GPU on analytical processing of GPU-accelerated database management systems (DBMSes). To this end, we conducted rigorous experiments with TPC-H across three popular GPU DBMSes. Consequently, we show that co-processing with CPU and GPU in the GPU DBMSes was cost-effective despite exposed concerns.

The Topics over Time (TOT) model allows users to be aware of changes in certain topics over time. The proposed method inputs the divided dataset of security blog posts based on a fixed period using an overlap period to the TOT. The results suggest the extraction of topics that include malware and attack campaign names that are appropriate for the multi-labeling of cyber threat intelligence reports.

In this paper, the effective Long Range (LoRa) based wireless sensor network is designed and implemented to provide the remote data sensing functions for the planned smart agricultural recycling rapid processing factory. The proposed wireless sensor network transmits the sensing data from various sensors, which measure the values of moisture, viscosity, pH, and electrical conductivity of agricultural organic wastes for the production and circulation of organic fertilizers. In the proposed wireless sensor network design, the LoRa transceiver module is used to provide data transmission functions at the sensor node, and the embedded platform by Raspberry Pi module is applied to support the gateway function. To design the cloud data server, the MySQL methodology is applied for the database management system with Apache software. The proposed wireless sensor network for data communication between the sensor node and the gateway supports a simple one-way data transmission scheme and three half-duplex two-way data communication schemes. By experiments, for the one-way data transmission scheme under the condition of sending one packet data every five seconds, the packet data loss rate approaches 0% when 1000 packet data is transmitted. For the proposed two-way data communication schemes, under the condition of sending one packet data every thirty seconds, the average packet data loss rates without and with the data-received confirmation at the gateway side can be 3.7% and 0%, respectively.

In Internet applications, when users search for information, the search engines invariably return some invalid webpages that do not contain valid information. These invalid webpages interfere with the users' access to useful information, affect the efficiency of users' information query and occupy Internet resources. Accurate and fast filtering of invalid webpages can purify the Internet environment and provide convenience for netizens. This paper proposes an invalid webpage filtering model (HAIF) based on deep learning and hierarchical attention mechanism. HAIF improves the semantic and sequence information representation of webpage text by concatenating lexical-level embeddings and paragraph-level embeddings. HAIF introduces hierarchical attention mechanism to optimize the extraction of text sequence features and webpage tag features. Among them, the local-level attention layer optimizes the local information in the plain text. By concatenating the input embeddings and the feature matrix after local-level attention calculation, it enriches the representation of information. The tag-level attention layer introduces webpage structural feature information on the attention calculation of different HTML tags, so that HAIF is better applicable to the Internet resource field. In order to evaluate the effectiveness of HAIF in filtering invalid pages, we conducted various experiments. Experimental results demonstrate that, compared with other baseline models, HAIF has improved to various degrees on various evaluation criteria.

In recent years, checking sleep quality has become essential from a healthcare perspective. In this paper, we propose a respiratory rate (RR) monitoring system that can be used in the bedroom without wearing any sensor devices directly. To develop the system, passive radio-frequency identification (RFID) tags are introduced and attached to a blanket, instead of attaching them to the human body. The received signal strength indicator (RSSI) and phase values of the passive RFID tags are continuously obtained using an RFID reader through antennas located at the bedside. The RSSI and phase values change depending on the respiration of the person wearing the blanket. Thus, we can estimate the RR using these values. After providing an overview of the proposed system, the RR estimation flow is explained in detail. The processing flow includes noise elimination and irregular breathing period estimation methods. The evaluation demonstrates that the proposed system can estimate the RR and respiratory status without considering the user's body posture, body type, gender, or change in the RR.

Cross-component linear model (CCLM) chromaticity prediction is a new technique introduced in Versatile Video Coding (VVC), which utilizes the reconstructed luminance component to predict the chromaticity parts, and can improve the coding performance. However, it increases the coding complexity. In this paper, how to accelerate the chroma intra-prediction process is studied based on texture characteristics. Firstly, two observations have been found through experimental statistics for the process. One is that the choice of the chroma intra-prediction candidate modes is closely related to the texture complexity of the coding unit (CU), and the other is that whether the direct mode (DM) is selected is closely related to the texture similarity between current chromaticity CU and the corresponding luminance CU. Secondly, a fast chroma intra-prediction mode decision algorithm is proposed based on these observations. A modified metric named sum modulus difference (SMD) is introduced to measure the texture complexity of CU and guide the filtering of the irrelevant candidate modes. Meanwhile, the structural similarity index measurement (SSIM) is adopted to help judging the selection of the DM mode. The experimental results show that compared with the reference model VTM8.0, the proposed algorithm can reduce the coding time by 12.92% on average, and increases the BD-rate of Y, U, and V components by only 0.05%, 0.32%, and 0.29% respectively.

Recently, researchers paid more attention on designing optical routers, since they are essential building blocks of all photonic interconnection architectures. Thus, improving them could lead to a spontaneous improvement in the overall performance of the network. Optical routers suffer from the dilemma of increased insertion loss and crosstalk, which upraises the power consumed as the network scales. In this paper, we propose a new 7×7 non-blocking optical router based on the Dimension Order Routing (DOR) algorithm. Moreover, we develop a method that can ensure the least number of MicroRing Resonators (MRRs) in an optical router. Therefore, by reducing these optical devices, the optical router proposed can decrease the crosstalk and insertion loss of the network. This optical router is evaluated and compared to Ye's router and the optimized crossbar for 3D Mesh network that uses XYZ routing algorithm. Unlike many other proposed routers, this paper evaluates optical routers not only from router level prospective yet also consider the overall network level condition. The appraisals show that our optical router can reduce the worst-case network insertion loss by almost 8.7%, 46.39%, 39.3%, and 41.4% compared to Ye's router, optimized crossbar, optimized universal OR, and Optimized VOTEX, respectively. Moreover, it decreases the Optical Signal-to-Noise Ratio (OSNR) worst-case by almost 27.92%, 88%, 77%, and 69.6% compared to Ye's router, optimized crossbar, optimized universal OR, and Optimized VOTEX, respectively. It also reduces the power consumption by 3.22%, 23.99%, 19.12%, and 20.18% compared to Ye's router, optimized crossbar, optimized universal OR, and Optimized VOTEX, respectively.

During the recent several years, deep learning has achieved excellent results in image recognition, voice processing, and other research areas, which has set off a new upsurge of research and application. Internal defects and external malicious attacks may threaten the safe and reliable operation of a deep learning system and even cause unbearable consequences. The technology of testing deep learning systems is still in its infancy. Traditional software testing technology is not applicable to test deep learning systems. In addition, the characteristics of deep learning such as complex application scenarios, the high dimensionality of input data, and poor interpretability of operation logic bring new challenges to the testing work. This paper focuses on the problem of test case generation and points out that adversarial examples can be used as test cases. Then the paper proposes MTGAN which is a framework to generate test cases for deep learning image classifiers based on Generative Adversarial Network. Finally, this paper evaluates the effectiveness of MTGAN.

The use of locating arrays is motivated by the use of generating software test suites to locate interaction faults in component-based systems. In this paper, we introduce a new combinatorial configuration, with which a general combinatorial description of $(ar{1},t)$-locating arrays is presented. Based on this characterization, a number of locating arrays by means of SSOA and difference covering arrays with prescribed properties are constructed effectively. As a consequence, upper bounds on the size of locating arrays with small number of factors are then obtained.

This letter proposes a downlink multiple-input multiple-output (MIMO) non-orthogonal multiple access technique that mitigates multi-cell interference (MCI) at cell-edge users, regardless of the number of interfering cells, thereby improving the spectral efficiency. This technique employs specific receive beamforming vectors at the cell-edge users in clusters to minimize the MCI. Based on the receive beamforming vectors adopted by the cell-edge users, the transmit beamforming vectors for a base station (BS) and the receive beamforming vectors for cell-center users are designed to eliminate the inter-cluster interference and maximize the spectral efficiency. As each user can directly obtain its own receive beamforming vector, this technique does not require channel feedback from the users to a BS to design the receive beamforming vectors, thereby reducing the system overhead. We also derive the upper bound of the average sum rate achievable using the proposed technique. Finally, we demonstrate through simulations that the proposed technique achieves a better sum rate performance than the existing schemes and that the derived upper bound is valid.

We have proposed a waveguide to microstrip line transition, which perpendicularly connects one waveguide into two microstrip lines. It consists of only a waveguide and a dielectric substrate with copper foils. A backshort waveguide for typical transitions is not needed. Additionally, the transition does not require via holes on the substrate. These innovations simplify the structure and the manufacturing process. We assume that our transition and antennas are co-located on the substrate. We reduced the undesirable radiation from the transition so as not to contaminate the desirable radiation pattern. In this paper, we address output phase of our transition. Since the transition has two MSL output ports connecting to different radiation elements, the phase error between two dividing signals leads to beam shift in the radiation pattern. Unfortunately, misalignment of etching pattern between copper layers of the substrate is unavoidable. The structural asymmetry causes the phase error. In order to tolerate the misalignment, we propose to add a pair of open stubs to the transition. We show that the structure drastically stabilizes the output phase. Though the stubs create some extra radiation, we confirm that the impact is not significant. Moreover, we fabricate and measure a prototype antenna that uses the transition. In the case of with stubs, the radiation pattern is unchanged even if the misalignment is severe.

In this study, we propose a secure data-providing system by using a verifiable attribute-based keyword search (VABKS), which also has the functions of privacy preservation and feedback to providers with IP anonymous server. We give both theoretic and experimental result, which show that our proposed system is a secure system with real-time property. One potential application of the system is to Integrated Broadcast-Broadband (IBB) services, which acquire information related to broadcast programs via broadband networks. One such service is a recommendation service that delivers recommendations matching user preferences (such as to TV programs) determined from the user's viewing history. We have developed a real-time system outsourcing data to the cloud and performing keyword searches on it by dividing the search process into two stages and performing heavy processing on the cloud side.

An n-variate Farlie-Gumbel-Morgenstern (FGM) copula consists of 2n - n - 1 parameters that express multivariate dependence among random variables. Motivated by the dependence structure of the n-variate FGM copula, we derive the exact range of the n-variate FGM copula's parameter. The exact range of the parameter is given by a closed-form expression under the condition that all parameters take the same value. Moreover, under the same condition, we reveal that the n-variate FGM copula becomes the independence copula for n → ∞. This result contributes to the dependence modeling such as reliability analysis considering dependent failure occurrence.

An efficient approximate computing circuit is developed for polynomial functions through the hybrid of analog and stochastic domains. Different from the ordinary time-based stochastic computing (TBSC), the proposed circuit exploits not only the duty cycle of pulses but also the pulse strength of the analog current to carry information for multiplications. The accumulation of many multiplications is performed by merely collecting the stochastic-current. As the calculation depth increases, the growth of latency (while summations), signal power weakening, and disparity of output signals (while multiplications) are substantially avoidable in contrast to that in the conventional TBSC. Furthermore, the calculation range spreads to bipolar infinite without scaling, theoretically. The proposed multi-domain stochastic computing (MDSC) is designed and simulated in a 0.18 µm CMOS technology by employing a set of current mirrors and an improved scheme of the TBSC circuit based on the Neuron-MOS mechanism. For proof-of-concept, the multiply and accumulate calculations (MACs) are implemented, achieving an average accuracy of 95.3%. More importantly, the transistor counting, power consumption, and latency decrease to 6.1%, 55.4%, and 4.2% of the state-of-art TBSC circuit, respectively. The robustness against temperature and process variations is also investigated and presented in detail.

This work presents a DNN accelerator architecture specifically designed for performing efficient inference on compressed and sparse DNN models. Leveraging the data sparsity, a runtime processing scheme is proposed to deal with the encoded weights and activations directly in the compressed domain without decompressing. Furthermore, a new data flow is proposed to facilitate the reusage of input activations across the fully-connected (FC) layers. The proposed design is implemented and verified using the Xilinx Virtex-7 FPGA. Experimental results show it achieves 1.99×, 1.95× faster and 20.38×, 3.04× more energy efficient than CPU and mGPU platforms, respectively, running AlexNet.

An olfactory display is a device to present smells. Temporal characteristics of three types of olfactory displays such as one based upon high-speed switching of solenoid valves, desktop-type one based on SAW atomizer and wearable-type one based on SAW atomizer were evaluated using three odorants with different volatilities. The sensory test revealed that the olfactory displays based on SAW atomizer had the presentation speeds faster than that of solenoid valves switching. Especially, the wearable one had an excellent temporal characteristic. These results largely depend on the difference in the odor delivery method. The data obtained in this study provides basic knowledge when we make olfactory contents.

Source localization in a wireless sensor network (WSN) is sensitive to the sensors' positions. In practice, due to mobility, the receivers' positions may be known inaccurately, leading to non-negligible degradation in source localization estimation performance. The goal of this paper is to develop a semidefinite programming (SDP) method using time-difference-of arrival (TDOA) and frequency-difference-of-arrival (FDOA) by taking the sensor position uncertainties into account. Specifically, we transform the commonly used maximum likelihood estimator (MLE) problem into a convex optimization problem to obtain an initial estimation. To reduce the coupling between position and velocity estimator, we also propose an iterative method to obtain the velocity and position, by using weighted least squares (WLS) method and SDP method, respectively. Simulations show that the method can approach the Cramér-Rao lower bound (CRLB) under both mild and high noise levels.

Surveillance through aerial systems is in place for years. Such systems are expensive, and a large fleet is in operation around the world without upgrades. These systems have low resolution and multiple analog cameras on-board, with Digital Video Recorders (DVRs) at the control station. Generated digital videos have multi-scenes from multi-feeds embedded in a single video stream and lack video stabilization. Replacing on-board analog cameras with the latest digital counterparts requires huge investment. These videos require stabilization and other automated video analysis prepossessing steps before passing it to the mosaicing algorithm. Available mosaicing software are not tailored to segregate feeds from different cameras and scenes, automate image enhancements, and stabilize before mosaicing (image stitching). We present "AirMatch", a new automated system that first separates camera feeds and scenes, then stabilize and enhance the video feed of each camera; generates a mosaic of each scene of every feed and produce a super quality mosaic by stitching mosaics of all feeds. In our proposed solution, state-of-the-art video analytics techniques are tailored to work on videos from vintage cameras in aerial applications. Our new framework is independent of specialized hardware requirements and generates effective mosaics. Affine motion transform with smoothing Gaussian filter is selected for the stabilization of videos. A histogram-based method is performed for scene change detection and image contrast enhancement. Oriented FAST and rotated BRIEF (ORB) is selected for feature detection and descriptors in video stitching. Several experiments on a number of video streams are performed and the analysis shows that our system can efficiently generate mosaics of videos with high distortion and artifacts, compared with other commercially available mosaicing software.

Connected services have been under development in the automotive industry. Meanwhile, the volume of predictive notifications that utilize travel-related data is increasing, and there are concerns that drivers cannot process such an amount of information or do not accept and follow such predictive instructions straightforwardly because the information provided is predicted. In this work, an interactive voice system using two agents is proposed to realize notifications that can easily be accepted by drivers and enhance the reliability of the system by adding contextual information. An experiment was performed using a driving simulator to compare the following three forms of notifications: (1) notification with no contextual information, (2) notification with contextual information using one agent, and (3) notification with contextual information using two agents. The notification content was limited to probable near-miss incidents. The results of the experiment indicate that the driver may decelerate more with the one- and two-agent notification methods than with the conventional notification method. The degree of deceleration depended the number of times the notification was provided and whether there were cars parked on the streets.