Automatic tracking and classification are essential for studying the behaviors of wild animals. Owing to dynamic far-shooting photos, the occlusion problem, protective coloration, the background noise is irregular interference for designing a computerized algorithm for reducing human labeling resources. Moreover, wild dolphin images are hard-acquired by on-the-spot investigations, which takes a lot of waiting time and hardly sets the fixed camera to automatic monitoring dolphins on the ocean in several days. It is challenging tasks to detect well and classify a dolphin from polluted photos by a single famous deep learning method in a small dataset. Therefore, in this study, we propose a generic Cascade Small Object Detection (CSOD) algorithm for dolphin detection to handle small object problems and develop visualization to backbone based classification (V2BC) for removing noise, highlighting features of dolphin and classifying the name of dolphin. The architecture of CSOD consists of the P-net and the F-net. The P-net uses the crude Yolov3 detector to be a core network to predict all the regions of interest (ROIs) at lower resolution images. Then, the F-net, which is more robust, is applied to capture the ROIs from high-resolution photos to solve single detector problems. Moreover, a visualization to backbone based classification (V2BC) method focuses on extracting significant regions of occluded dolphin and design significant post-processing by referencing the backbone of dolphins to facilitate for classification. Compared to the state of the art methods, including faster-rcnn, yolov3 detection and Alexnet, the Vgg, and the Resnet classification. All experiments show that the proposed algorithm based on CSOD and V2BC has an excellent performance in dolphin detection and classification. Consequently, compared to the related works of classification, the accuracy of the proposed designation is over 14% higher. Moreover, our proposed CSOD detection system has 42% higher performance than that of the original Yolov3 architecture.

This work introduces a measurement model to estimate the naturalness of vibrato. We carried out a subjective evaluation using a mean opinion score (MOS). We then built a measurement model by using two-dimensional Gaussian functions. We found that three Gaussian functions can measure naturalness with an error of 4.0%.

A method for the calibration of S11 at the front surface of a material for a coaxial-feed type cut-off circular waveguide with three reference materials inserted and no short termination condition was proposed as a preliminary step for dielectric measurement in liquids. The equations for jig calibration of S11 with these reference materials were first defined, and the electrostatic capacitance for the analytical model unique to the jig was quantified by substituting the reflection constant (calculated at frequencies of 0.50, 1.5 and 3.0 GHz using the mode-matching (MM) technique) into the equivalent circuit, assuming the sample liquid in the jig. The accuracy of S11 measured using the proposed method was then verified. S11 for the front surface of the sample material was also measured with various liquids in the jig after calibration, and the dielectric constants of the liquids were estimated as an inverse problem based on comparison of S11 calculated from an analytical model using EM analysis via the MM technique with the measured S11 values described above. The effectiveness of the proposed S11 calibration method was verified by comparison with dielectric constants estimated after S11 SOM (short, open and reference material) calibration and similar, with results showing favorable agreement with each method.

We propose an iterative single-image haze-removal method that first divides images with haze into regions in which haze-removal processing is difficult and then estimates the ambient light. The existing method has a problem wherein it often overestimates the amount of haze in regions where there is a large distance between the location the photograph was taken and the subject of the photograph; this problem prevents the ambient light from being estimated accurately. In particular, it is often difficult to accurately estimate the ambient light of images containing white and sky regions. Processing those regions in the same way as other regions has detrimental results, such as darkness or unnecessary color change. The proposed method divides such regions in advance into multiple small regions, and then, the ambient light is estimated from the small regions in which haze removal is easy to process. We evaluated the proposed method through some simulations, and found that the method achieves better haze reduction accuracy even than the state-of-the art methods based on deep learning.

The phaseless antenna measurement technique is advantageous for high-frequency near-field measurements in which the uncertainty of the measured phase is a problem. In the phaseless measurement, which is expected to be used in the frequency band with a short wavelength, a slight positional deviation error of the probe greatly deteriorates the measurement result. This paper proposes a phase retrieval method that can compensate the measurement errors caused by misalignment of a probe and its jig. And this paper proposes a far-field estimation method by phase resurrection that incorporated the compensation techniques. We find that the positioning errors are due to the random errors occurring at each measurement point because of minute vibrations of the probe; in addition, we determine that the stationary depth errors occurring at each measurement surface as errors caused by improper setting of the probe jig. The random positioning error is eliminated by adding a low-pass filter in wavenumber space, and the depth positioning error is iteratively compensated on the basis of the relative residual obtained in each plane. The validity of the proposed method is demonstrated by estimating the far-field patterns using the results from numerical simulations, and is also demonstrated using measurement data with probe-positioning error. The proposed method can reduce the probe-positioning error and improve the far-field estimation accuracy by more over than 10 dB.

The residue number system (RNS) is a method for representing an integer x as an n-tuple of its residues with respect to a given set of moduli. In RNS, addition, subtraction, and multiplication can be carried out by independent operations with respect to each modulus. Therefore, an n-fold speedup can be achieved by parallel processing. The main disadvantage of RNS is that we cannot efficiently compare the magnitude of two integers or determine the sign of an integer. Two general methods of comparison are to transform a number in RNS to a mixed-radix system or to a radix representation using the Chinese remainder theorem (CRT). We used the CRT to derive an equation approximating a value of x relative to M, the product of moduli. Then, we propose two algorithms that efficiently evaluate the equation and output a sign bit. The expected number of steps of these algorithms is of order n. The algorithms use a lookup table that is (n+3) times as large as M, which is reasonably small for most applications including cryptography.

Smart business management has been built to efficiently carry out enterprise business activities and improve its business outcomes in a global business circumstance. Firms have applied their smart business to their business activities in order to enhance the smart business results. The outcome of an enterprise's smart business fulfillment has to be managed and measured to effectively establish and control the smart business environment based on its business plan and business departments. In this circumstance, we need the measurement framework that can reasonably gauge a firm's smart business output in order to control and advance its smart business ability. This research presents a measurement instrument for an enterprise smart business performance in terms of a general smart business outcome. The developed measurement scale is verified on its validity and reliability through factor analysis and reliability analysis based on previous literature. This study presents an 11-item measurement tool that can reasonably gauge a firm smart business performance in both of finance and non-finance perspective.

Motion deblurring for noisy and blurry images is an arduous and fundamental problem in image processing community. The problem is ill-posed as many different pairs of latent image and blur kernel can render the same blurred image, and thus, the optimization of this problem is still unsolved. To tackle it, we present an effective motion deblurring method for noisy and blurry images based on prominent structure and a data-driven heavy-tailed prior of enhanced gradient. Specifically, first, we employ denoising as a preprocess to remove the input image noise, and then restore strong edges for accurate kernel estimation. The image extreme channels-based priors (dark channel prior and bright channel prior) as sparse complementary knowledge are exploited to extract prominent structure. High closeness of the extracted structure to the clear image structure can be obtained via tuning the parameters of extraction function. Next, the integration term of enhanced interim image gradient and clear image heavy-tailed prior is proposed and then embedded into the image restoration model, which favors sharp images over blurry ones. A large number of experiments on both synthetic and real-life images verify the superiority of the proposed method over state-of-the-art algorithms, both qualitatively and quantitatively.

Authors had proposed a hybrid electromagnetic field analysis method suitable for an airport surface so far. In this paper, the hybrid method is validated by measurements by using a 1/50 scale-model of an airport considering several layouts of the buildings and sloping ground. The measured power distributions agreed with the analyzed ones within 5 dB errors excepting null points and the null positions of the distribution is also estimated within one wavelength errors.

Mode-by-mode impulse responses, or spectral transfer matrix (STM) of birefringent fibers are measured by using linear optical sampling, with assist of polarization multiplexed probe pulse. By using the eigenvalue analysis of the STM, the differential mode delay and PMD vector of polarization-maintaining fiber are analyzed as a function of optical frequency over 1THz. We show that the amplitude averaging of the complex impulse responses is effective for enhancing the signal-to-noise ratio of the measurement, resulting in improving the accuracy and expanding the bandwidth of the measurement.

In this study, the transient characteristics on the super-steep subthreshold slope (SS) of a PN-body tied (PNBT) silicon-on-insulator field-effect transistor (SOI-FET) were investigated using technology computer-aided design and pulse measurements. Carrier charging effects were observed on the super-steep SS PNBT SOI-FET. It was found that the turn-on delay time decreased to nearly zero when the gate overdrive-voltage was set to 0.1-0.15 V. Additionally, optimizing the gate width improved the turn-on delay. This has positive implications for the low speed problems of this device. However, long-term leakage current flows on turn-off. The carrier lifetime affects the leakage current, and the device parameters must be optimized to realize both a high on/off ratio and high-speed operation.

This paper proposes an active vibration-suppression control method for the systems with multiple disturbances using only the relative displacements and velocities. The controller can suppress the vibration of the main body in the world coordinate, where a velocity disturbance and a force disturbance affect the system simultaneously. The added device plays a similar role as an accelerometer, but we avoid the algebraic loop. The main idea of the feedback law is to convert a nonlinear system into an aseismatic desired system by using the energy shaping technique. A parameter selection procedure is derived by combining the constraints of nonlinear IDA-PBC and the evaluation of the control performance of the linearly approximated system. The effectiveness of the proposed method is confirmed by simulations for an example.

Plane wave scattering from a circular conducting cylinder and a circular conducting strip has been formulated by equivalent surface currents which are postulated from the scattering geometrical optics (GO) field. Thus derived radiation far fields are found to be the same as those formulated by a conventional physical optics (PO) approximation for both E and H polarizations.

Simultaneous multithreading technology (SMT) can effectively improve the overall throughput and fairness through improving the resources usage efficiency of processors. Traditional works have proposed some metrics for evaluation in real systems, each of which strikes a trade-off between fairness and throughput. How to choose an appropriate metric to meet the demand is still controversial. Therefore, we put forward suggestions on how to select the appropriate metrics through analyzing and comparing the characteristics of each metric. In addition, for the new application scenario of cloud computing, the data centers have high demand for the quality of service for killer applications, which bring new challenges to SMT in terms of performance guarantees. Therefore, we propose a new metric P-slowdown to evaluate the quality of performance guarantees. Based on experimental data, we show the feasibility of P-slowdown on performance evaluation. We also demonstrate the benefit of P-slowdown through two use cases, in which we not only improve the performance guarantee level of SMT processors through the cooperation of P-slowdown and resources allocation strategy, but also use P-slowdown to predict the occurrence of abnormal behavior against security attacks.

This paper describes a method of measuring the unsymmetric voltage of conducted noise using a floating measurement system. Here, floating means that there is no physical connection to the reference ground. The method works by correcting the measured voltage to the desired unsymmetric voltage using the capacitance between the measurement instrument and the reference ground plane acting as the return path of the conducted electromagnetic noise. The existing capacitance measurement instrument needs a probe in contact with the ground, so it is difficult to use for on-site measurement of stray capacitance to ground at troubleshooting sites where the ground plane is not exposed or no ground connection point is available. The authors have developed a method of measuring stray capacitance to ground that does not require physical connection of the probe to the ground plane. The developed method can be used to estimate the capacitance between the measurement instrument and ground plane even if the distance and relative permittivity of the space are unknown. And a method is proposed for correcting the voltage measured with the floating measurement system to obtain the unsymmetric voltage of the noise by using the measured capacitance to ground. In the experiment, the unsymmetric voltage of a sinusoidal wave transmitting on a co-axial cable was measured with a floating oscilloscope in a shield room and the measured voltage was corrected to within 2dB of expected voltage by using the capacitance measured with the developed method. In addition, the voltage of a rectangular wave measured with the floating oscilloscope, which displays sag caused by the stray capacitance to ground, was corrected to a rectangular wave without sag. This means that the phase of the unsymmetric voltage can also be corrected by the measured stray capacitance. From these results, the effectiveness of the proposed methods is shown.

In IoT (Internet-of-Things) era, the number and variety of hardware devices becomes continuously increasing. Several IoT devices are utilized at infrastructure equipments. How to maintain such IoT devices is a serious concern. Capacitance measurement is one of the powerful ways to detect anomalous states in the structure of the hardware devices. Particularly, measuring capacitance while the hardware device is running is a major challenge but no such researches proposed so far. This paper proposes a capacitance measuring device which measures device capacitance in operation. We firstly combine the AC (alternating current) voltage signal with the DC (direct current) supply voltage signal and generates the fluctuating signal. We supply the fluctuating signal to the target device instead of supplying the DC supply voltage. By effectively filtering the observed current in the target device, the filtered current can be proportional to the capacitance value and thus we can measure the target device capacitance even when it is running. We have implemented the proposed capacitance measuring device on the printed wiring board with the size of 95mm × 70mm and evaluated power consumption and accuracy of the capacitance measurement. The experimental results demonstrate that power consumption of the proposed capacitance measuring device is reduced by 65% in low-power mode from measuring mode and proposed device successfully measured capacitance in 0.002μF resolution.

A low frequency electric field probe that integrates data acquisition and storage is developed in this paper. An electric small monopole antenna printed on the circuit board is used as the receiving antenna; the rear end of the monopole antenna is connected to the integral circuit to achieve the flat frequency response; the logarithmic detection method is applied to obtain a high measurement dynamic range. In addition, a Microprogrammed Control Unit is set inside to realize data acquisition and storage. The size of the probe developed is not exceeding 20 mm × 20 mm × 30 mm. The field strength 0.2 V/m ~ 261 V/m can be measured in the frequency range of 500 Hz ~ 10 MHz, achieving a dynamic range over 62 dB. It is suitable for low frequency electric field strength measurement and shielding effectiveness test of small shield.

In this paper, an analysis method for calculating balanced and unbalanced modes of a small antenna is summarized. Modal condactances which relate dissipated power of the antenna are directly obtained from standard S-parameters that we can measure by a 2-port network analyzer. We demonstrate the validity and effectiveness of the proposed method by simulation and measurement for a dipole antenna with unbalaned feed. The ratio of unbalanced-mode power to the total power (unbalanced-mode power ratio) calculated by the proposed method agrees precisely with that yielded by the conventional method using measured radiation patterns. Furthermore, we analyze a small loop antenna with unbalanced feed by the proposed method and show that the self-balancing characteristic appears when the loop is set in resonant state by loading capacitances or the whole length of the loop is less than 1/20th the wavelength.

Internationalized domain names (IDNs) are abused to create domain names that are visually similar to those of legitimate/popular brands. In this work, we systematize such domain names, which we call deceptive IDNs, and analyze the risks associated with them. In particular, we propose a new system called DomainScouter to detect various deceptive IDNs and calculate a deceptive IDN score, a new metric indicating the number of users that are likely to be misled by a deceptive IDN. We perform a comprehensive measurement study on the identified deceptive IDNs using over 4.4 million registered IDNs under 570 top-level domains (TLDs). The measurement results demonstrate that there are many previously unexplored deceptive IDNs targeting non-English brands or combining other domain squatting methods. Furthermore, we conduct online surveys to examine and highlight vulnerabilities in user perceptions when encountering such IDNs. Finally, we discuss the practical countermeasures that stakeholders can take against deceptive IDNs.

With our ever increasing dependence on computers, many governments around the world have started to investigate strengthening the regulations on vulnerabilities and their lifecycle management. Although many previous works have studied this problem space for mainstream software packages and web applications, relatively few have studied this for consumer IoT devices. As our first step towards filling this void, this paper presents a pilot study on the vulnerability disclosures and patch releases of three prominent consumer IoT vendors in Japan and three in the United States. Our goals include (i) characterizing the trends and risks in the vulnerability lifecycle management of consumer IoT devices using accurate long-term data, and (ii) identifying problems, challenges, and potential approaches for future studies of this problem space. To this end, we collected all published vulnerabilities and patches related to the consumer IoT products by the included vendors between 2006 and 2017; then, we analyzed our dataset from multiple perspectives, such as the severity of the included vulnerabilities and the timing of the included patch releases with respect to the corresponding disclosures and exploits. Our work has uncovered several important findings that may inform future studies. These findings include (i) a stark contrast between how the vulnerabilities in our dataset were disclosed in the two markets, (ii) three alarming practices by the included vendors that may significantly increase the risk of 1-day exploits for customers, and (iii) challenges in data collection including crawling automation and long-term data availability. For each finding, we also provide discussions on its consequences and/or potential migrations or suggestions.