Displacement current is the last piece of the puzzle of electromagnetic theory. Its existence implies that electromagnetic disturbance can propagate at the speed of light and finally it led to the discovery of Hertzian waves. On the other hand, since magnetic fields can be calculated only with conduction currents using Biot-Savart's law, a popular belief that displacement current does not produce magnetic fields has started to circulate. But some people think if this is correct, what is the displacement current introduced for. The controversy over the meaning of displacement currents has been going on for more than hundred years. Such confusion is caused by forgetting the fact that in the case of non-stationary currents, neither magnetic fields created by conduction currents nor those created by displacement currents can be defined. It is also forgotten that the effect of displacement current is automatically incorporated in the magnetic field calculated by Biot-Savart's law. In this paper, mainly with the help of Helmholtz decomposition, we would like to clarify the confusion surrounding displacement currents and provide an opportunity to end the long standing controversy.

A novel displacement sensor was proposed based on a frequency delta-sigma modulator (FDSM) employing a microwave oscillator. To demonstrate basic operation, we fabricated a stylus surface profiler using a cylindrical cavity resonator, where one end of the cavity is replaced by a thin metal diaphragm with a stylus probe tip. Good surface profile was successfully obtained with this device. A 10 nm depth trench was clearly observed together with a 10 µm trench in a single scan without gain control. This result clearly demonstrates an extremely wide dynamic range of the FDSM displacement sensors.

Triboelectric generators have been attracting much attention as electrical power sources in scientific communities and industries. Based on dielectric physics, two microscopic routes are available as current sources: One is charge displacement and the other is dipolar rotation. We have been investigating these routes as power sources for triboelectric generation. In other words, dipolar energy transfer process during a course of depolarization has the potentiality to be utilized as triboelectric generator. In this paper, we show that polyimide polymer film with permanent dipoles, i.e., PMDA-ODA polyimide, can provide current source capacity enhanced at elevated temperature, which is in good agreement with our idea based on dipolar energy mode of triboelectric generator. That is, permanent dipoles rotate quickly at elevated temperature, and act as an enhanced current source in the dipolar energy source model of triboelectric generator.

When BJTs are irradiated by gamma rays, interface trapped charges and positive oxide trapped charges are formed by ionization at the Si-SiO2 interface and SiO2 regions, respectively. These trapped charges affect the movement of carriers depending on the type of BJT. This paper presents experimental results regarding operating characteristics of gamma irradiated pnp Si BJTs.

Triboelectric generator is attracting much attention as a power source of electronics application. Electromotive force induced by rubbing is a key for triboelectric generator. From dielectric physics point of view, there are two microscopic origins for electromotive force, i.e., electronic charge displacement and dipolar rotation. A new way for evaluating these two origins is an urgent task. We have been developing an optical second-harmonic generation (SHG) technique as a tool for probing charge displacement and dipolar alignment, selectively, by utilizing wavelength dependent response of SHG to the two origins. In this paper, an experimental way that identifies polarity of electronic charge displacement, i.e., positive charge and negative charge, is proposed. Results showed that the use of local oscillator makes it possible to identify the polarity of charges by means of SHG. As an example, positive and negative charge distribution created by rubbing polyimide surface is illustrated.

On surfaces of tris-(8-hydroxyquinolate) aluminum (Alq) and tris(7-propyl-8-hydroxyquinolinato) aluminum (Al7p) thin-films, positive and negative polarization charges appear, respectively, owing to spontaneous orientation of these polar molecules. Alq is a typical electron transport material where electrons are injected from cathode. Because the polarization charge exists at the Alq/cathode interface, it is likely that it affects the electron injection process because of Coulomb interaction. In order to evaluate an impact of polarization charge on electron injection from cathode, electron only devices (EODs) composed of Alq or Al7p were prepared and evaluated by displacement current measurement. We found that Alq-EOD has lower resistance than Al7p-EOD, indicating that the positive polarization charge at Alq/cathode interface enhances the electron injection due to Coulomb attraction, while the electron injection is suppressed by the negative polarization charge at the Al7p/Al interface. These results clearly suggest that it is necessary to design organic semiconductor devices by taking polarization charge into account.

Image sensor communication (ISC), derived from visible light communication (VLC) is an attractive solution for outdoor mobile environments, particularly for intelligent transport systems (ITS). In ITS-ISC, tracking a transmitter in the image plane is critical issue since vehicle vibrations make it difficult to selsct the correct pixels for data reception. Our goal in this study is to develop a precise tracking method. To accomplish this, vehicle vibration modeling and its parameters estimation, i.e., represetative frequencies and their amplitudes for inherent vehicle vibration, and the variance of the Gaussian random process represnting road surface irregularity, are required. In this paper, we measured actual vehicle vibration in a driving situation and determined parameters based on the frequency characteristics. Then, we demonstrate that vehicle vibration that induces transmitter displacement in an image plane can be modeled by only Gaussian random processes that represent road surface irregularity when a high frame rate (e.g., 1000fps) image sensor is used as an ISC receiver. The simplified vehicle vibration model and its parameters are evaluated by numerical analysis and experimental measurement and obtained result shows that the proposed model can reproduce the characteristics of the transmitter displacement sufficiently.

Several applications for 3-D visualization require dense detection of correspondence for displacement estimation among heterogeneous multi-view images. Due to differences in resolution or sampling density and field of view in the images, estimation of dense displacement is not straight forward. Therefore, we propose a scale invariant polynomial expansion method that can estimate dense displacement between two heterogeneous views. Evaluation on heterogeneous images verifies accuracy of our approach.

This paper presents a novel method for unsupervised segmentation of objects with large displacements in high speed video sequences. Our general framework introduces a new foreground object predicting method that finds object hypotheses by encoding both spatial and temporal features via a semantic motion signature scheme. More specifically, temporal cues of object hypotheses are captured by the motion signature proposed in this paper, which is derived from sparse saliency representation imposed on magnitude of optical flow field. We integrate semantic scores derived from deep networks with location priors that allows us to directly estimate appearance potentials of foreground hypotheses. A unified MRF energy functional is proposed to simultaneously incorporate the information from the motion signature and semantic prediction features. The functional enforces both spatial and temporal consistency and impose appearance constancy and spatio-temporal smoothness constraints directly on the object hypotheses. It inherently handles the challenges of segmenting ambiguous objects with large displacements in high speed videos. Our experiments on video object segmentation benchmarks demonstrate the effectiveness of the proposed method for segmenting high speed objects despite the complicated scene dynamics and large displacements.

Displacement mapping has been widely used for adding geometric surface details to 3D mesh models. However, it requires sufficient tessellation of the mesh if fine details are to be represented. In this paper, we propose a method for applying the displacement mapping even on coarse models by using an augmented patch mesh. The patch mesh is a regularly tessellated flat square mesh, which is mapped onto the target area. Our method applies displacement mapping to the patch mesh for fitting it to the original mesh as well as for adding surface details. We generate a patch map, which stores three-dimensional displacements from the patch mesh to the original mesh. A displacement map is also provided for defining the new surface feature. The target area in the original mesh is then replaced with the patch mesh, and the patch mesh reconstructs the original shape using the patch map and the new surface detail is added using the displacement map. Our results show that our method conveniently adds surface features to various models. The proposed method is particularly useful if the surface features change dynamically since the original mesh is preserved and the separate patch mesh overwrites the target area at runtime.

This paper proposes a new method that reduces the computational cost of the phase-only correlation (POC)-based methods for displacement estimation in old film sequences. Conventional POC-based methods calculate all the points of the POC and only use the highest peak of the POC and its neighboring points to estimate the displacement with subpixel accuracy. Our proposed method reduces the computational cost by calculating the POC in a small region, instead of all the points of the POC. The proposed method combines a displacement pre-estimation with a modified inverse discrete Fourier transform (IDFT). The displacement pre-estimation uses the 1-D POCs of frame projections to pre-estimate the displacement with pixel accuracy and chooses a small region in the POC including the desired points for displacement estimation. The modified IDFT is then used to calculate the points in this small region for displacement estimation. Experimental results show that use of the proposed method can effectively reduce the computational cost of the POC-based methods without compromising the accuracy.

We analyze the carrier dynamics in MOSFETs under low-voltage operation. For this purpose the displacement (charging/discharging) current, induced during switching operations is studied experimentally and theoretically for a 90 nm CMOS technology. It is found that the experimental transient characteristics can only be well reproduced in the circuit simulation of low voltage applications by considering the carrier-transit delay in the compact MOSFET model. Long carrier transit delay under the low voltage switching-on operation results in long duration of the displacement current flow. On the other hand, the switching-off characteristics are independent of the bias condition.

Interpretations by physicians of capsule endoscopy image sequences captured over periods of 7-8 hours usually require 45 to 120 minutes of extreme concentration. This paper describes a novel method to reduce diagnostic time by automatically controlling the display frame rate. Unlike existing techniques, this method displays original images with no skipping of frames. The sequence can be played at a high frame rate in stable regions to save time. Then, in regions with rough changes, the speed is decreased to more conveniently ascertain suspicious findings. To realize such a system, cue information about the disparity of consecutive frames, including color similarity and motion displacements is extracted. A decision tree utilizes these features to classify the states of the image acquisitions. For each classified state, the delay time between frames is calculated by parametric functions. A scheme selecting the optimal parameters set determined from assessments by physicians is deployed. Experiments involved clinical evaluations to investigate the effectiveness of this method compared to a standard-view using an existing system. Results from logged action based analysis show that compared with an existing system the proposed method reduced diagnostic time to around 32.5 7 minutes per full sequence while the number of abnormalities found was similar. As well, physicians needed less effort because of the systems efficient operability. The results of the evaluations should convince physicians that they can safely use this method and obtain reduced diagnostic times.

This letter proposes a motion information inferring scheme for multi-view video coding motivated by the idea that the aspect of motion vector between the corresponding positions in the neighboring view pair is quite similar. The proposed method infers the motion information from the corresponding macroblock in the neighboring view after RD optimization with the existing prediction modes. This letter presents evaluation showing that the method significantly enhances the efficiency especially at high bit rates.

The research on displacement vector detection has gained increasing attention in recent years. However, no relationship between displacement vectors and the outlines of objects in motion has been established. We describe a new method of detecting displacement vectors through edge segment detection by emphasizing the correlation between displacement vectors and their outlines. Specifically, after detecting an edge segment, the direction of motion of the edge segment can be inferred through the variation in the values of the Laplacian-Gaussian filter at the position near the edge segment before and after the motion. Then, by observing the degrees of displacement before and after the motion, the displacement vector can be calculated. The accuracy compared to other methods of displacement vector detection demonstrates the feasibility of this method.

Displaced subdivision surface representation [13] is a new form of representing a polygonal surface model, where a detailed surface model is defined as a scaler-valued displacement map over a smooth domain surface; it puts forth a number of attractive features for editing, geometry compression, animation, scalability, and adaptive rendering of polygonal models. The construction of the smooth domain surface is a challenging task in the conversion process of a detailed polygonal surface model into this representation. In this paper, we propose a new efficient method for defining the smooth domain surface based on -subdivision scheme. The proposed algorithm not only performs better in terms of the quality of the generated surfaces but is computationally more efficient and occupies less memory as compared to the original algorithm [13] and generates surfaces with more levels of detail due to the specific nature of -subdivision when the prescribed target complexity of the generated mesh must not be exceeded. To corroborate the efficiency and the quality of the new technique, the conversion results for several public domain models have been presented.

The author's recent research topics of organic monolayer films have been reviewed. The importance of the study of organic monolayers is discussed from the viewpoints of future electronics and dielectric physics, keeping in mind the difference between monolayers and bulk materials.

In order to estimate elasticity distribution of living soft tissue by ultrasonic pulse-echo method, we developed an algorithm by which we estimate 2-D displacement vector field from two successive rf echo data frames. The algorithm estimates a displacement vector iteratively by matching the phase characteristics of the local regions of two data frames. The estimation process is composed of coarse one and the fine one. In the coarse estimation process, the displacement is estimated by detecting the peak of the 2-D cross-correlation function. In the fine process, the displacement is estimated iteratively by shifting the 2nd frame data so that the phase characteristics matches with that of the 1st frame data. In each iterative step of both processes, the estimated displacement vector field is spatially smoothed. This proposed algorithm exhibits excellent performance in obtaining accurate and smooth distribution of displacement vector which is required to obtain strain distribution and finally shear modulus distribution. We conducted an experiment on an agar phantom which has inhomogeneous shear modulus distribution. Using the proposed method, we obtained 2-D displacement field with reasonable accuracy. We reconstructed a relative shear modulus map using axial strain assuming 1-D stress condition. The reconstructed map using the calculated axial strain through 2-D displacement estimation algorithm was satisfactory, and was clearly superior to the one through 1-D displacement estimation algorithm. The proposed 2-D displacement field estimation algorithm seems to be a versatile and powerful tool to measure strain distribution for the purpose of tissue elasticity estimation under various deformation conditions.

This paper uses both network analysis and experiments to confirm that the neural network learning algorithm that minimizes output variation (BPV) provides much more robustness than back-propagation (BP) or BP with noise-modified training samples (BPN). Network analysis clarifies the relationship between sample displacement and what and how the network learns. Sample displacement generates variation in the output of the output units in the output layer. The output variation model introduces two types of deformation error, both of which modify the mean square error. We propose a new error which combines the two types of deformation error. The network analysis using this new error considers that BPV learns two types of training samples where the modification is either towards or away from the category mean, which is defined as the center of sample distribution. The magnitude of modification depends on the position of the training sample in the sample distribution and the degree of leaning completion. The conclusions is that BPV learns samples modified towards to the category mean more stronger than those modified away from the category mean, namely it achieves nonuniform learning. Another conclusion is that BPN learns from uniformly modified samples. The conjecture that BPV is much more robust than the other two algorithms is made. Experiments that evaluate robustness are performed from two kinds of viewpoints: overall robustness and specific robustness. Benchmark studies using distorted handprinted Kanji character patterns examine overall robustness and two specifically modified samples (noise-modified samples and directionally-modified samples) examine specific robustness. Both sets of studies confirm the superiority of BPV and the accuracy of the conjecture.

A method to measure the displacement from the phase rotation of the Doppler signal including the displacement information of the moving body is proposed, where the displacement resolution can be improved 4 times by making the phase rotation faster. Furthermore, this test system is applied in clinical use. The test system is built up by using a two-phase microwave Doppler sensor covering a 10GHz band, where the Doppler frequency is multiplied 4 times by signal processing. Thus, the resolution is improved from a conventional 12.6mm (in case of 11.9GHz) to 3.15mm, and practical utilization has been attained. The microwave Doppler radar system described in this paper is adequate for the displacement measurement for a relatively fast moving body. As a medical sensor for clinical use, measurement examples of head movement in a vestibule examination (vestibule oculomotor reflexive inspection) and finger movement in a cerebellum function test are given. Furthermore by using two sets of this Doppler radar system, a 2-dimensional measurement of head movement is possible.