We propose an object detector using a sliding window method for an event-driven camera which outputs a subtracted frame (usually a binary value) when changes are detected in captured images. Since sliding window skips unchanged portions of the output, the number of target object area candidates decreases dramatically, which means that our system operates faster and with lower power consumption than a system using a straightforward sliding window approach. Since the event-driven camera output consists of binary precision frames, an all binarized convolutional neural network (ABCNN) can be available, which means that it allows all convolutional layers to share the same binarized convolutional circuit, thereby reducing the area requirement. We implemented our proposed method on the Xilinx Inc. Zedboard and then evaluated it using the PETS 2009 dataset. The results showed that our system outperformed BCNN system from the viewpoint of detection performance, hardware requirement, and computation time. Also, we showed that FPGA is an ideal method for our system than mobile GPU. From these results, our proposed system is more suitable for the embedded systems based on stationary cameras (such as security cameras).

Saliency quality assessment aims at estimating the objective quality of a saliency map without access to the ground-truth. Existing works typically evaluate saliency quality by utilizing information from saliency maps to assess its compactness and closedness while ignoring the information from image content which can be used to assess the consistence and completeness of foreground. In this letter, we propose a novel multi-information fusion network to capture the information from both the saliency map and image content. The key idea is to introduce a siamese module to collect information from foreground and background, aiming to assess the consistence and completeness of foreground and the difference between foreground and background. Experiments demonstrate that by incorporating image content information, the performance of the proposed method is significantly boosted. Furthermore, we validate our method on two applications: saliency detection and segmentation. Our method is utilized to choose optimal saliency map from a set of candidate saliency maps, and the selected saliency map is feeded into an segmentation algorithm to generate a segmentation map. Experimental results verify the effectiveness of our method.

Real-time monitoring of heart rate (HR) and body temperature (BT) is crucial for the prognosis and the diagnosis of cardiovascular disease and healthcare. Since current monitoring systems are too rigid and bulky, it is not easy to attach them to the human body. Also, their large current consumption limits the working time. In this paper, we develop a wireless sensor patch for HR and BT by integrating sensor chip, wireless communication chip, and electrodes on the flexible boards that is covered with non-toxic, but skin-friendly adhesive patch. Our experimental results reveal that the flexible wireless sensor patch can efficiently detect early diseases by monitoring the HR and BT in real time.

A new fuzzy level set method (FLSM) based on the global search capability of quantum particle swarm optimization (QPSO) is proposed to improve the stability and precision of image segmentation, and reduce the sensitivity of initialization. The new combination of QPSO-FLSM algorithm iteratively optimizes initial contours using the QPSO method and fuzzy c-means clustering, and then utilizes level set method (LSM) to segment images. The new algorithm exploits the global search capability of QPSO to obtain a stable cluster center and a pre-segmentation contour closer to the region of interest during the iteration. In the implementation of the new method in segmenting liver tumors, brain tissues, and lightning images, the fitness function of the objective function of QPSO-FLSM algorithm is optimized by 10% in comparison to the original FLSM algorithm. The achieved initial contours from the QPSO-FLSM algorithm are also more stable than that from the FLSM. The QPSO-FLSM resulted in improved final image segmentation.

In order to solve the problem in Automatic Identification System (AIS) that the signal in the target slot cannot be correctly received due to partial overlap of signals in adjacent time slots, the paper introduces a new criterion: maximum expected signal power (MESP) and proposes a novel beamforming algorithm based on generalized singular value decomposition (GSVD) and orthogonal projection. The algorithm employs GSVD to estimate the signal subspace, and adopts orthogonal projection to project the received signal onto the orthogonal subspace of the non-target signal. Then, beamforming technique is used to maximize the output power of the target signal on the basis of MESP. Theoretical analysis and simulation results show the effectiveness of the proposed algorithm.

This paper proposes a novel low complexity lattice reduction-aided iterative receiver for overloaded MIMO. Novel noise cancellation is proposed that increases an equivalent channel gain with a scalar gain introduced in this paper, which results in the improvement of the signal to noise power ratio (SNR). We theoretically analyze the performance of the proposed receiver that the lattice reduction raises the SNR of the detector output signals as the scalar gain increases, when the Lenstra-Lenstra-Lova's (LLL) algorithm is applied to implement the lattice reduction. Because the SNR improvement causes the scalar gain to increase, the performance is improved by iterating the reception process. Computer simulations confirm the performance. The proposed receiver attains a gain of about 5dB at the BER of 10-4 in a 6×2 overloaded MIMO channel. Computational complexity of the proposed receiver is about 1/50 as much as that of the maximum likelihood detection (MLD).

This paper presents a numerical study of the wireless channel characteristics of liver implants in a frequency range of 4.5-6.5GHz, considering different digital human phantoms by employing two inhomogeneous male and female models. Path loss data for in-body to on-body and in-body to off-body communication scenarios are provided. The influence of respiration-induced organ movement on signal attenuation is demonstrated. A narrower range of attenuation deviation is observed in the female model as compared to the male model. The path loss data in the female body is between 40-80dB which is around 5-10dB lower than the male model. Path loss data for the in-body to off-body scenario in both models suggest that in-body propagation is the main component of total path loss in the channel. The results demonstrate that channel characteristics are subject dependent, and thus indicate the need to take subject dependencies into consideration when investigating in-body communication channels.

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.

Soft error jeopardizes the reliability of semiconductor devices, especially those working at low voltage. In recent years, silicon-on-thin-box (SOTB), which is a FD-SOI device, is drawing attention since it is suitable for ultra-low-voltage operation. This work evaluates the contributions of SRAM, FF and combinational circuit to chip-level soft error rate (SER) based on irradiation test results. For this evaluation, this work performed neutron irradiation test for characterizing single event transient (SET) rate of SOTB and bulk circuits at 0.5 V. Using the SBU and MCU data in SRAMs from previous work, we calculated the MBU rate with/without error correcting code (ECC) and with 1/2/4-col MUX interleaving. Combining FF error rates reported in literature, we estimated chip-level SER and each contribution to chip-level SER for embedded and high-performance processors. For both the processors, without ECC, 95% errors occur at SRAM in both SOTB and bulk chips at 0.5 V and 1.0 V, and the overall chip-level SERs of the assumed SOTB chip at 0.5 V is at least 10 x lower than that of bulk chip. On the other hand, when ECC is applied to SRAM in the SOTB chip, SEUs occurring at FFs are dominant in the high-performance processor while MBUs at SRAMs are not negligible in the bulk embedded chips.

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.

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.

Malware-infected hosts have typically been detected using network-based Intrusion Detection Systems on the basis of characteristic patterns of HTTP requests collected with dynamic malware analysis. Since attackers continuously modify malicious HTTP requests to evade detection, novel HTTP requests sent from new malware samples need to be exhaustively collected in order to maintain a high detection rate. However, analyzing all new malware samples for a long period is infeasible in a limited amount of time. Therefore, we propose a system for efficiently collecting HTTP requests with dynamic malware analysis. Specifically, our system analyzes a malware sample for a short period and then determines whether the analysis should be continued or suspended. Our system identifies malware samples whose analyses should be continued on the basis of the network behavior in their short-period analyses. To make an accurate determination, we focus on the fact that malware communications resemble natural language from the viewpoint of data structure. We apply the recursive neural network, which has recently exhibited high classification performance in the field of natural language processing, to our proposed system. In the evaluation with 42,856 malware samples, our proposed system collected 94% of novel HTTP requests and reduced analysis time by 82% in comparison with the system that continues all analyses.

To solve the low accuracy problem of the recommender system for long term users, in this paper, we propose a top-N-balanced sequential recommendation based on recurrent neural network. We postulated and verified that the interactions between users and items is time-dependent in the long term, but in the short term, it is time-independent. We balance the top-N recommendation and sequential recommendation to generate a better recommender list by improving the loss function and generation method. The experimental results demonstrate the effectiveness of our method. Compared with a state-of-the-art recommender algorithm, our method clearly improves the performance of the recommendation on hit rate. Besides the improvement of the basic performance, our method can also handle the cold start problem and supply new users with the same quality of service as the old users.

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.

We report our recent progress in silicon photonics integrated device technology targeting on-chip-level large-capacity optical interconnect applications. To realize high-capacity data transmission, we successfully developed on-package-type silicon photonics integrated transceivers and demonstrated simultaneous 400 Gbps operation. 56 Gbps pulse-amplitude-modulation (PAM) 4 and wavelength-division-multiplexing technologies were also introduced to enhance the transmission capacity.

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.