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.

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.

Sieve algorithms are regarded as the best algorithms to solve the shortest vector problem (SVP) on account of its good asymptotical quality, which could make it outperform enumeration algorithms in solving SVP of high dimension. However, due to its large memory requirement, sieve algorithms are not practical as expected, especially on high dimension lattice. To overcome this bottleneck, TupleSieve algorithm was proposed to reduce memory consumption by a trade-off between time and memory. In this work, aiming to make TupleSieve algorithm more practical, we combine TupleSieve algorithm with SubSieve technique and obtain a sub-exponential gain in running time. For 2-tuple sieve, 3-tuple sieve and arbitrary k-tuple sieve, when selecting projection index d appropriately, the time complexity of our algorithm is O(20.415(n-d)), O(20.566(n-d)) and $O(2^{rac{kmathrm{log}_2p}{1-k}(n-d)})$ respectively. In practice, we propose a practical variant of our algorithm based on GaussSieve algorithm. Experimental results show that our algorithm implementation is about two order of magnitude faster than FPLLL's GuassSieve algorithm. Moreover, techniques such as XOR-POPCNT trick, progressive sieving and appropriate projection index selection can be exploited to obtain a further acceleration.

After a natural disaster it is critical to urgently find victims buried under collapsed buildings. Most people habitually carry smartphones with them. Smartphones have a feature that periodically transmits Wi-Fi signals called “Probe Requests” to connect with access points. Moreover, smartphones transmit “Clear to Send” when they receive a “Request to Send” alert. This motivated us to develop a hand-held smartphone finder system that integrates a novel method for accurately locating a smartphone using the Wi-Fi signals, to support rescue workers. The system has a unique graphical user interface that tracks target smartphones. Thus, rescue workers can easily reach victims who have their smartphones with them under collapsed buildings. In this paper, after introducing the localization method, the system architecture of the smartphone finder and its prototype system are described, along with some experimental results that demonstrate the effectiveness of the smartphone finder prototype.

A noise-robust and accuracy-enhanced microwave imaging algorithm is presented for microwave ablation monitoring of cancer treatment. The ablation impact of dielectric change can be assessed by microwave inverse scattering analysis, where the dimension and dielectric drop of the ablation zone enable safe ablation monitoring. We focus on the distorted Born iterative method (DBIM), which is applicable to highly heterogeneous and contrasted dielectric profiles. As the reconstruction accuracy and convergence speed of DBIM depend largely on the initial estimate of the dielectric profile or noise level, this study exploits a prior estimate of the DBIM for the pre-ablation state to accelerate the convergence speed and introduces the matched-filter-based noise reduction scheme in the DBIM framework. The two-dimensional finite-difference time-domain numerical test with realistic breast phantoms shows that our method significantly enhances the reconstruction accuracy with a lower computational cost.

An optical-layer adaptive restoration scheme is validated by a real-time experiment and numerical analyses. In this paper, it is assumed that this scheme can adaptively optimize the bitrate (up to 600Gb/s) and an optical reach with 100Gb/s granularity to maintain high-capacity optical signal transmission. The practicality of 600-Gb/s/carrier optical signal transmission over 101.6-km field-installed fiber is confirmed prior to the adaptive restoration experiment. After modifying the field setup, a real-time experiment on network recovery is demonstrated with bitrate adaptation for 600-Gb/s to 400-Gb/s signals. The results indicate that this scheme can restore failed connections with recovery times comparable to those of conventional restoration scheme; thus 99.9999% system availability can be easily attained even under double-link failures. Numerical analysis clarifies that adaptive restoration can recover >80% of double-link failures on several realistic topologies and improvement amount against conventional scheme is semi-statistically characterized by restoration path length.

In this paper, we present a hardware implementation of a colorectal cancer diagnosis support system using a colorectal endoscopic video image on customizable embedded DSP. In an endoscopic video image, color shift, blurring or reflection of light occurs in a lesion area, which affects the discrimination result by a computer. Therefore, in order to identify lesions with high robustness and stable classification to these images specific to video frame, we implement a computer-aided diagnosis (CAD) system for colorectal endoscopic images with Narrow Band Imaging (NBI) magnification with the Convolutional Neural Network (CNN) feature and Support Vector Machine (SVM) classification. Since CNN and SVM need to perform many multiplication and accumulation (MAC) operations, we implement the proposed hardware system on a customizable embedded DSP, which can realize at high speed MAC operations and parallel processing with Very Long Instruction Word (VLIW). Before implementing to the customizable embedded DSP, we profile and analyze processing cycles of the CAD system and optimize the bottlenecks. We show the effectiveness of the real-time diagnosis support system on the embedded system for endoscopic video images. The prototyped system demonstrated real-time processing on video frame rate (over 30fps @ 200MHz) and more than 90% accuracy.

We studied an acoustic anomaly detection system for equipments, where the outlier detection method based on recorded sounds is used. In a real environment, the SNR of the target sound against background noise is low, and there is the problem that it is necessary to catch slight changes in sound buried in noise. In this paper, we propose a system in which a sound source extraction process is provided at the preliminary stage of the outlier detection process. In the proposed system, nonnegative matrix factorization based on generalized Gaussian distribution (GGD-NMF) is used as a sound source extraction process. We evaluated the improvement of the anomaly detection performance in a low-SNR environment. In this experiment, SNR capable of detecting an anomaly was greatly improved by providing GGD-NMF for preprocessing.

In our previous work, we developed a quadrotor with a tilting frame using the parallel link mechanism. It can tilt its frame in the pitch direction by driving only one servo motor. However, it has a singularity such that the input torque in the pitch direction equals 0 at ±π/2 tilted state. In this letter, we analyze the Hopf bifurcation of the controlled quadrotor around the singularity and show the stable limit cycle occurs in the pitch direction by simulation and experiments.

Orthogonal frequency division multiplexing (OFDM) technique has been widely used in communication systems in pursuit of the most efficient utilization of spectrum. However, the increase of the number of orthogonal subcarriers will lead to the rise of the peak-to-average power ratio (PAPR) of the waveform, thus reducing the efficiency of the power amplifiers. In this letter we propose a phase-changed PAPR reduction technique based on windowing function architecture for OFDM systems. This technique is based on the idea of phase change, which makes the spectrum of output signal almost free of regrowth caused by peak clipping. It can reduce more than 28dBc adjacent channel power ratio (ACPR) compared with the traditional peak windowing clipping methods in situation that peak is maximally suppressed. This technique also has low algorithm complexity so it can be easily laid out on hardware. The proposed algorithm has been laid out on a low-cost field-programmable gate array (FPGA) to verify its effectiveness and feasibility. A 64-QAM modulated 20M LTE-A waveform is used for measurement, which has a sampling rate of 245.67M.

Recently, new optimization machines based on non-silicon physical systems, such as quantum annealing machines, have been developed, and their commercialization has been started. These machines solve the problems by searching the state of the Ising spins, which minimizes the Ising Hamiltonian. Such a property of minimization of the Ising Hamiltonian can be applied to various combinatorial optimization problems. In this paper, we introduce the coherent Ising machine (CIM), which can solve the problems in a milli-second order, and has higher performance than the quantum annealing machines especially on the problems with dense mutual connections in the corresponding Ising model. We explain how a target problem can be implemented on the CIM, based on the optimization scheme using the mutually connected neural networks. We apply the CIM to traveling salesman problems as an example benchmark, and show experimental results of the real machine of the CIM. We also apply the CIM to several combinatorial optimization problems in wireless communication systems, such as channel assignment problems. The CIM's ultra-fast optimization may enable a real-time optimization of various communication systems even in a dynamic communication environment.

Electrical connectors are the basic components of the electric system in automobiles, aircrafts and ships to realize the current and electrical signal transmission. In the aviation electrical system, the electrical connectors are indispensable supporting devices accessories, which play important roles in connecting electrical system, monitoring and controlling equipment, and provide a guarantee for the reliable transmission of electrical signals between the aviation equipment and system. Whether aviation electrical connectors work reliably directly affects the safety and reliability of the entire aircraft aviation system. The random vibration of aircraft caused by turbulence during flight is one of the main factors affecting the contact performance of the electrical connectors. In this paper, the contacts of the circular four-slot three-pin electrical connectors were chosen as the research specimens. The theoretical model of the contact force for contacts of electrical connectors was established. The test method for contact force measurement was determined. According to the test scheme, the detecting device for the contact force and contact resistance of the electrical connectors was designed, and the turbulence test of the electrical connectors was carried out. Through the analysis of the test data, the influence rule of the turbulence degree, flight speed and flight height on the contact force and contact resistance of the aviation electrical connectors was obtained.

We propose a compact magnetic tunnel junction (MTJ) model for circuit simulation by de-facto standard SPICE in this paper. It is implemented by Verilog-A language which makes it easy to simulate MTJs with other standard devices. Based on the switching probability, we smoothly connect the adiabatic precessional model and the thermal activation model by using an interpolation technique based on the cubic spline method. We can predict the switching time after a current is applied. Meanwhile, we use appropriate physical models to describe other MTJ characteristics. Simulation results validate that the model is consistent with experimental data and effective for MTJ/CMOS hybrid circuit simulation.

A temperature-variation-tolerant intermittent startup circuit (ISC) that suppresses quiescent current to 300nA at 0.48V was developed. The ISC is a key circuit for a batteryless wireless sensor that can detect a 1μA generation current of energy harvesting sources from the intervals of wireless signals. The ISC consists of an ultralow-voltage detector composed of a depletion-type MOSFET and low-Vth MOSFETs, a Dickson-type gate-boosted charge pump circuit, and a power-switch control circuit. The detector consists of a voltage reference comparator and a feedback-controlled latch circuit for a hysteresis function. The voltage reference comparator, which has a common source stage with a folded constant-current-source load composed of a depletion-type nMOSFET, makes it possible to reduce the temperature dependency of the detection voltage, while suppressing the quiescent current to 300nA at 0.48V. The ISC fabricated with fully-depleted silicon-on-insulator (FD-SOI) CMOS technology also suppresses the variation of the quiescent current. To verify the effectiveness of the circuit, the ISC was fabricated in a 0.8-μm triple-Vth FD-SOI CMOS process. An experiment on the fabricated system, the ISC boosts the input voltage of 0.48V to 2.4V while suppressing the quiescent current to less than 300nA at 0.48V. The measured temperature coefficient of the detection voltage was ±50ppm/°C. The fluctuation of the quiescent current was 250nA ± 90nA in the temperature range from 0°C to 40°C. An intermittent energy harvesting sensor with the ISC was also fabricated. The sensor could detect a generation current of 1μA at EH sources within an accuracy of ±15% in the temperature range from 0°C to 40°C. It was also successfully applied to a self-powered wireless plant-monitoring sensor system.

Shape matching with local descriptors is an underlying scheme in shape analysis. We can visually confirm the matching results and also assess them for shape classification. Generally, shape matching is implemented by determining the correspondence between shapes that are represented by their respective sets of sampled points. Some matching methods have already been proposed; the main difference between them lies in their choice of matching cost function. This function measures the dissimilarity between the local distribution of sampled points around a focusing point of one shape and the local distribution of sampled points around a referring point of another shape. A local descriptor is used to describe the distribution of sampled points around the point of the shape. In this paper, we propose an extended scheme for shape matching that can compensate for errors in existing local descriptors. It is convenient for local descriptors to adopt our scheme because it does not require the local descriptors to be modified. The main idea of our scheme is to consider the correspondence of neighboring sampled points to a focusing point when determining the correspondence of the focusing point. This is useful because it increases the chance of finding a suitable correspondence. However, considering the correspondence of neighboring points causes a problem regarding computational feasibility, because there is a substantial increase in the number of possible correspondences that need to be considered in shape matching. We solve this problem using a branch-and-bound algorithm, for efficient approximation. Using several shape datasets, we demonstrate that our scheme yields a more suitable matching than the conventional scheme that does not consider the correspondence of neighboring sampled points, even though our scheme requires only a small increase in execution time.

Software copyright claims an exclusive right for the software copyright owner to determine whether and under what conditions others can modify, reuse, or redistribute this software. For Free and Open Source Software (FOSS), it is very important to identify the copyright owner who can control those activities with license compliance. Copyright notice is a few sentences mostly placed in the header part of a source file as a comment or in a license document in a FOSS project, and it is an important clue to establish the ownership of a FOSS project. Repositories of FOSS projects contain rich and varied information on the development including the source code contributors who are also an important clue to establish the ownership. In this paper, as a first step of understanding copyright owner, we will explore the situation of the software copyright in the Linux kernel, a typical example of FOSS, by analyzing and comparing two kinds of datasets, copyright notices in source files and source code contributors in the software repositories. The discrepancy between two kinds of analysis results is defined as copyright inconsistency. The analysis result has indicated that copyright inconsistencies are prevalent in the Linux kernel. We have also found that code reuse, affiliation change, refactoring, support function, and others' contributions potentially have impacts on the occurrence of the copyright inconsistencies in the Linux kernel. This study exposes the difficulty in managing software copyright in FOSS, highlighting the usefulness of future work to address software copyright problems.

A differential on chip oscillator (OCO) is proposed in this paper for low supply voltage, high frequency accuracy and fast startup. The differential architecture helps the OCO achieve a good power supply rejection ratio (PSRR) without using a regulator so as to make the OCO suitable for a low power supply voltage of 1.38V. A reference voltage generator is also developed to generate two output voltages lower than Vbe for low supply voltage operation. The output frequency is locked to 48MHz by a frequency-locked loop (FLL) and a 3.3-ppm/°C temperature coefficient of frequency is realized by the differential voltage ratio adjusting (differential VRA) technique. The startup time is only 1.47μs because the differential OCO is not necessary to charge a big capacitor for ripple reduction.

In this paper, we propose a robust output feedback control method for nonlinear systems with uncertain time-varying parameters associated with diagonal terms and there are additional external disturbances. First, we provide a new practical guidance of obtaining a compact set which contains the allowed time-varying parameters by utilizing a Lyapunov equation and matrix inequalities. Then, we show that all system states and observer errors of the controlled system remain bounded by the proposed controller. Moreover, we show that the ultimate bounds of some system states and observer errors can be made (arbitrarily) small by adjusting a gain-scaling factor depending on the system nonlinearity. With an application example, we illustrate the effectiveness of our control scheme over the existing one.

Due to the legal reform on the protection of personal information in US/Japan and the enforcement of the General Data Protection Regulation (GDPR) in Europe, service providers are obliged to more securely manage the sensitive data stored in their server. In order to protect this kind of data, they generally employ a cryptographic encryption scheme and secure key management schemes such as a Hardware Security Module (HSM) and Trusted Platform Module (TPM). In this paper, we take a different approach based on the space-hard cipher. The space-hard cipher has an interesting property called the space hardness. Space hardness guarantees sufficient security against the adversary who gains a part of key data, e.g., 1/4 of key data. Combined with a simple network monitoring technique, we develop a practical leakage resilient scheme Virtual Vault, which is secure against the snapshot adversary who has full access to the memory in the server for a short period. Importantly, Virtual Vault is deployable by only a low-price device for network monitoring, e.g. L2 switch, and software of space-hard ciphers and packet analyzer, while typical solutions require a dedicated hardware for secure key managements such as HSM and TPM. Thus, Virtual Vault is easily added on the existing servers which do not have such dedicated hardware.

In this paper, a compact microwave push-push oscillator based on a resonant tunneling diode (RTD) has been fabricated and demonstrated. A symmetrical spiral inductor structure has been used in order to reduce a chip area. The designed symmetric inductor is integrated into the InP-based RTD monolithic microwave integrated circuit (MMIC) technology. The circuit occupies a compact active area of 0.088 mm2 by employing symmetric inductor. The fabricated RTD oscillator shows an extremely low DC power consumption of 87 µW at an applied voltage of 0.47 V with good figure-of-merit (FOM) of -191 dBc/Hz at an oscillation frequency of 27 GHz. This is the first implementation as the RTD push-push oscillator with the symmetrical spiral inductor.