The arrival of the era of the Internet of Things (IoT) has ensured the ubiquity of human-sensing technologies. Cameras have become inexpensive instruments for human sensing and have been increasingly used for this purpose. Because cameras produce large quantities of information, they are powerful tools for sensing; however, because camera images contain information allowing individuals to be personally identified, their use poses risks of personal privacy violations. In addition, because IoT-ready home appliances are connected to the Internet, camera-captured images of individual users may be unintentionally leaked. In developing our human-detection method [33], [34], we proposed techniques for detecting humans from unclear images in which individuals cannot be identified; however, a drawback of this method was its inability to detect moving humans. Thus, to enable tracking of humans even through the images are blurred to protect privacy, we introduce a particle-filter framework and propose a human-tracking method based on motion detection and heart-rate detection. We also show how the use of integral images [32] can accelerate the execution of our algorithms. In performance tests involving unclear images, the proposed method yields results superior to those obtained with the existing mean-shift method or with a face-detection method based on Haar-like features. We confirm the acceleration afforded by the use of integral images and show that the speed of our method is sufficient to enable real-time operation. Moreover, we demonstrate that the proposed method allows successful tracking even in cases where the posture of the individual changes, such as when the person lies down, a situation that arises in real-world usage environments. We discuss the reasons behind the superior behavior of our method in performance tests compared to those of other methods.

A 1-Transistor 4-Magnetic Tunnel Junction (1T-4MTJ) memory cell has been proposed for field type of Magnetic Random Access Memory (MRAM). Proposed 1T-4MTJ memory cell array is achieved 44% higher density than that of conventional 1T-1MTJ thanks to the common access transistor structure in a 4-bit memory cell. A self-reference sensing scheme which can read out with write-back in four clock cycles has been also proposed. Furthermore, we add to estimate with considering sense amplifier variation and show 1T-4MTJ cell configuration is the best solution in IoT applications. A 1-Mbit MRAM test chip is designed and fabricated successfully using 130-nm CMOS process. By applying 1T-4MTJ high density cell and partially embedded wordline driver peripheral into the cell array, the 1-Mbit macro size is 4.04 mm2 which is 35.7% smaller than the conventional one. Measured data shows that the read access is 55 ns at 1.5 V typical supply voltage and 25C. Combining with conventional high-speed 1T-1MTJ caches and proposed high-density 1T-4MTJ user memories is an effective on-chip hierarchical non-volatile memory solution, being implemented for low-power MCUs and SoCs of IoT applications.

Cooperative communication can reduce energy consumption effectively due to its superior diversity gain. To further prolong network lifetime and improve the energy efficiency, this paper studies energy-efficient packet transmission in wireless ad-hoc networks and proposes a novel cluster-based cooperative packet transmission (CCPT) protocol to mitigate the packet loss and balance the energy consumption of networks. The proposed CCPT protocol first constructs a highly energy-efficient initial routing path based on the required energy cost of non-cooperative transmission. Then an iterative cluster recruitment algorithm is proposed that selects cooperative nodes and organizing them into clusters, which can create transmit diversity in each hop of communication. Finally, a novel two-step cluster-to-cluster cooperative transmission scheme is designed, where all cluster members cooperatively forward the packet to the next-hop cluster. Simulation results show that the CCPT protocol effectively reduces the energy cost and prolongs the network lifetime compared with the previous CwR and noC schemes. The results also have shown that the proposed CCPT protocol outperforms the traditional CwR protocol in terms of transmit efficiency per energy, which indicates that CCPT protocol has achieved a better trade-off between energy and packet arrival ratio.

In this paper, new classes of binary generalized cyclotomic sequences of period 2pm+1qn+1 are constructed. These sequences are balanced. We calculate the linear complexity of the constructed sequences with a simple method. The results show that the linear complexity of such sequences attains the maximum.

Many autocorrelation-based frequency estimation algorithms have been proposed. However, some of them cannot construct a strict linear prediction (LP) property among the adjacent autocorrelation lags, which affects the estimators' performance. To improve the precision of frequency estimation, two novel autocorrelation based frequency estimation methods of the real sinusoid signal in additive white Gaussian noise (AWGN) are proposed in this paper. Firstly, a simple method is introduced to transform the real sinusoid signal into the noncircular signal. Secondly, the autocorrelation of the noncircular signal is analyzed and a strict LP property is constructed among the adjacent autocorrelation lags of the noncircular signal. Thirdly, the least squares (LS) and reformed Pisarenko harmonic decomposer (RPHD) frameworks are employed to improve estimation accuracy. The simulation results match well with the theoretical values. In addition, computer simulations demonstrate that the proposed algorithm provides high estimation accuracy and good noise suppression capability.

We present InP-based photodetectors monolithically integrated with a 90° hybrid toward over 400Gb/s coherent transmission systems. To attain a wide 3-dB bandwidth of more than 40GHz for 400Gb/s dual-polarization (DP)-16-ary quadrature amplitude modulation (16QAM) and 600Gb/s DP-64QAM through 64GBaud operation, A p-i-n photodiode structure consisting of a GaInAs thin absorption and low doping n-typed InP buffer layers was introduced to overcome the trade-off between short carrier transit time and low parasitic capacitance. Additionally, this InP buffer layer contributes to the reduction of propagation loss in the 90° hybrid waveguide, that is, this approach allows a high responsivity as well as wide 3-dB bandwidth operation. The coherent receiver module for the C-band (1530nm - 1570nm) operation indicated the wide 3-dB bandwidth of more than 40GHz and the high receiver responsivity of more than 0.070A/W (Chip responsivity within the C-band: 0.130A/W) thanks to photodetectors with this photodiode design. To expand the usable wavelengths in wavelength-division multiplexing toward large-capacity optical transmission, the photodetector integrated with the 90° hybrid optimized for the L-band (1565nm - 1612nm) operation was also fabricated, and exhibited the high responsivity of more than 0.120A/W over the L-band. Finally, the InP-based monolithically integrated photonic device consisting of eight-channel p-i-n photodiodes, two 90° hybrids and a beam splitter was realized for the miniaturization of modules and afforded the reduction of the total footprint by 70% in a module compared to photodetectors with the 90° hybrid and four-channel p-i-n photodiodes.

In this paper, a scramble phase assisting weighted-type fractional Fourier transform (SPA-WFRFT) based system is proposed to guarantee the communication's security. The original transmitting signal is divided into two parts. The first part is modulated by WFRFT and subsequently makes up the constellation beguiling. The other part is used to generate the scramble phase and also to assist in the encryption of the WFRFT modulated signal dynamically. The novel constellation optimal model is built and solved through the genetic algorithm (GA) for the constellation beguiling. And the double pseudo scheme is implemented for the scramble phase generation. Theoretical analyses show that excellent security performances and high spectral efficiency can be attained. Final simulations are carried out to evaluate the performances of the SPA-WFRFT based system, and demonstrate that the proposed system can effectively degrade the unauthorized receivers' bit error rate (BER) performance while maintaining its own communication quality.

A topological quantum circuit is a representation model for topological quantum computation, which attracts much attention recently as a promising fault-tolerant quantum computation model by using 3D cluster states. A topological quantum circuit can be considered as a set of “loops,” and we can transform the topology of loops without changing the functionality of the circuit if the transformation satisfies certain conditions. Thus, there have been proposed many researches to optimize topological quantum circuits by transforming the topology. There are two directions of research to optimize topological quantum circuits. The first group of research considers so-called a placement and wiring problem where we consider how to place “parts” in a 3D space which corresponds to already optimized sub-circuits. The second group of research focuses on how to optimize the structure and locations of loops in a relatively small circuit which is treated as one part in the above-mentioned first group of research. This paper proposes a new idea for the second group of research; our idea is to consider topological transformations as a placement and wiring problem for modules which we derive from the information how loops are crossed. By using such a formulation, we can use the techniques for placement and wiring problems, and successfully obtain an optimized solution. We confirm by our experiment that our method indeed can reduce the cost much more than the method by Paetznick and Fowler.

This paper concerned the research on a memristive chaotic system and the generated random sequence; by constructing a piecewise-linear memristor model, a kind of chaotic system is constructed, and corresponding numerical simulation and dynamical analysis are carried out to show the dynamics of the new memristive chaotic system. Finally the proposed memristive chaotic system is used to generate random sequence for the possible application in encryption field.

The IEEE 802.11p Enhanced Distributed Channel Access (EDCA) is a standardization for vehicle-to-vehicle and road-to-vehicle communications. The saturated throughputs of the IEEE 802.11p EDCA obtained from previous analytical expressions differ from those of simulations. The purpose of this paper is to explain the reason why the differences appear in the previous analytical model of the EDCA. It is clarified that there is a special state wherein the Backoff Timer (BT) is decremented in the first time slot of after a frame transmission, which cannot be expressed in the previous Markov model. In addition, this paper proposes modified Markov models, which allow the IEEE 802.11p EDCA to be correctly analyzed. The proposed models describe BT-decrement procedure in the first time slot accurately by adding new states to the previous model. As a result, the proposed models provide accurate transmission probabilities of network nodes. The validity of the proposed models is confirmed by the quantitative agreements between analytical predictions and simulation results.

In this letter, a flexible and compatible with fine resolution radar frequency measurement receiver is designed. The receiver is implemented on the platform of Virtex-5 Field Programmable Grid Array (FPGA) from Xilinx. The Digital Down Conversion (DDC) without mixer based on polyphase filter has been successfully introduced in this receiver to obtain lower speed data flow and better resolution. This receiver can adapt to more modulation types and higher density of pulse flow, up to 200000 pulses per second. The measurement results indicate that the receiver is capable of detecting radar pulse signal of 0.2us to 2.5ms width with a major frequency root mean square error (RMSE) within 0.44MHz. Moreover, the wider pulse width and the higher decimation rate of DDC result in better performance. This frequency measurement receiver has been successfully used in a spaceborne radar system.

Spectral graph theory, based on the adjacency matrix or the Laplacian matrix that represents the network topology and link weights, provides a useful approach for analyzing network structure. However, in large scale and complex social networks, since it is difficult to completely know the network topology and link weights, we cannot determine the components of these matrices directly. To solve this problem, we propose a method for indirectly determining the Laplacian matrix by estimating its eigenvalues and eigenvectors using the resonance of oscillation dynamics on networks.

All digital phased arrays generate multiple beams concurrently through the digital beam forming technique, which features digital processing with multiple identical receiving/transmitting channels in RF or microwave frequencies. However, the performance of this process strongly depends on accurately matching the amplitude and phase of the channels, as mismatching is likely to degrade radar performance. In this paper, we present a method to calibrate receiving array by using NCO phase increasing algorithm, which simplifies array system by removing the external far-field calibration signals often needed in array systems. Both analysis and simulation results suggest that the proposed method attains better calibration performance than existing approaches, even with a low SNR input signal. Experiments also varify that the proposed calibration method is effective and achieves a desired radiation pattern. We can further boost calibration accuracy and reduce calibration time by programming NCO phase width and NCO phase resolution.

Multi-attributed graphs, in which each node is characterized by multiple types of attributes, are ubiquitous in the real world. Detection and characterization of communities of nodes could have a significant impact on various applications. Although previous studies have attempted to tackle this task, it is still challenging due to difficulties in the integration of graph structures with multiple attributes and the presence of noises in the graphs. Therefore, in this study, we have focused on clusters of attribute values and strong correlations between communities and attribute-value clusters. The graph clustering methodology adopted in the proposed study involves Community detection, Attribute-value clustering, and deriving Relationships between communities and attribute-value clusters (CAR for short). Based on these concepts, the proposed multi-attributed graph clustering is modeled as CAR-clustering. To achieve CAR-clustering, a novel algorithm named CARNMF is developed based on non-negative matrix factorization (NMF) that can detect CAR in a cooperative manner. Results obtained from experiments using real-world datasets show that the CARNMF can detect communities and attribute-value clusters more accurately than existing comparable methods. Furthermore, clustering results obtained using the CARNMF indicate that CARNMF can successfully detect informative communities with meaningful semantic descriptions through correlations between communities and attribute-value clusters.

This study presents a joint dictionary learning approach for speech emotion recognition named locality preserved joint nonnegative matrix factorization (LP-JNMF). The learned representations are shared between the learned dictionaries and annotation matrix. Moreover, a locality penalty term is incorporated into the objective function. Thus, the system's discriminability is further improved.

The linguistic Multi-Criteria Group Decision-Making (MCGDM) problem involves various types of uncertainties. To deal with this problem, a new linguistic MCGDM method combining cloud model and evidence theory is thus proposed. Cloud model is firstly used to handle the fuzziness and randomness of the linguistic concept, by taking both the average level and fluctuation degree of the linguistic concept into consideration. Hence, a method is presented to transform linguistic variables into clouds, and then an asymmetrical weighted synthetic cloud is proposed to aggregate the clouds of decision makers on each criterion. Moreover, evidence theory is used to handle the imprecision and incompleteness of the group assessment, with the belief degree and the ignorance degree. Hence, the conversion from the cloud to the belief degree is investigated, and then the evidential reasoning algorithm is adopted to aggregate the criteria values. Finally, the average utility is applied to rank the alternatives. A numerical example, which is given to confirm the validity and feasibility, also shows that the proposed method can take advantage of cloud model and evidence theory to efficiently deal with the uncertainties caused by both the linguistic concept and group assessment.

In this paper, we propose a periodic reactance time function for 2-element electronically steerable passive array radiator (ESPAR) antennas applicable to the receivers of both single-input multiple-output (SIMO) and multiple-input multiple-output (MIMO) systems with 2 outputs. Based on the proposed function, we evaluate the power patterns of the antenna for various distances between two antenna elements. Moreover, for the distances, we discuss the correlation properties and the strength of the two outputs to find the appropriate distance for the receiver. From the discussions, we can conclude that distances from 0.1 to 0.35 times the wavelength are effective in terms of receive diversity.

This paper focuses on on-demand wireless sensor networks (WSNs) where a wake-up receiver is installed into each node. In on-demand WSNs, each node sends a wake-up signal including a wake-up ID assigned to a specific destination node in order to remotely activate its main radio interface. This wake-up control helps each node to reduce energy consumed during idle periods, however, the wake-up signal transmitted before every data transmission results in overhead, which degrades communication quality and increases energy consumption at each sender node. In order to reduce the overhead for wake-up control, in this paper, we propose three schemes. First, we propose a scheme called Double Modulation (DM), where each node embeds the sensing data to be transmitted into the payload field of a wake-up signal. The destination interprets the wake-up message differently depending on its wake-up state: if it is in a sleep state, it treats the message as a wake-up signal, otherwise it extracts the sensing data from the detected message. Second, we propose a scheme called Overhearing (OH), where each node observes the frames transmitted by a destination node and suppresses the transmission of wake-up signal when detecting the active state of their destination. Finally, we propose a hybrid scheme that combines OH and DM schemes. Our simulation results show that the proposed schemes can effectively reduce the negative impact of wake-up overhead, and significantly improve data collection rate and energy-efficiency in comparison to on-demand WSN without the proposed schemes.

To recognize transportation modes without any additional sensor devices, we demonstrate that the transportation modes can be recognized from communication quality factors. In the demonstration, instead of using global positioning system (GPS) and accelerometer sensors, we collect mobile TCP throughputs, received-signal strength indicators (RSSIs), and cellular base-station IDs (Cell IDs) through in-line network measurement when the user enjoys mobile services, such as video streaming. In accuracy evaluations, we conduct two different field experiments to collect the data in six typical transportation modes (static, walking, riding a bicycle, riding a bus, riding a train and riding a subway), and then construct the classifiers by applying a support-vector machine (SVM), k-nearest neighbor (k-NN), random forest (RF), and convolutional neural network (CNN). Our results show that these transportation modes can be recognized with high accuracy by using communication quality factors as well as the use of accelerometer sensors.

Recent works on enhancing the comfort and convenience of vehicles have revealed the advantage of various wireless sensor nodes for information collection. For the highly required reliability in vehicles, Reliable Wireless Communication based on Substitute Forwarding (RWCSF) has been proposed. It ensures that 99.999% of communications can finish within 20ms, which is the quality of communication equivalent to wired links. However, the performance was evaluated in very limited situations, where two or more communications never occurred simultaneously and no noise was present. In this paper, we enhance RWCSF to achieve the target communication quality even if two or more communications occur simultaneously. In addition, we evaluate the enhanced method in various types of vehicles that create internal noise.