Characterizations of realized metal-insulator-silicon-insulator-metal waveguides and nanochannel fabrication via insulator removal

We investigate experimentally metal-insulator-silicon-insulator-metal (MISIM) waveguides that are fabricated by using fully standard CMOS technology. They are hybrid plasmonic waveguides, and they have a feature that their insulator is replaceable with functional material. We explain a fabrication process for them and discuss fabrication results based on 8-inch silicon-on-insulator wafers. We measured the propagation characteristics of the MISIM waveguides that were actually fabricated to be connected to Si photonic waveguides through symmetric and asymmetric couplers. When incident light from an optical source has transverse electric (TE) polarization and its wavelength is 1318 or 1554 nm, their propagation losses are between 0.2 and 0.3 dB/mu m. Excess losses due to the symmetric couplers are around 0.5 dB, which are smaller than those due to the asymmetric couplers. Additional measurement results indicate that the MISIM waveguide supports a TE-polarized hybrid plasmonic mode. Finally, we explain a process of removing the insulator without affecting the remaining MISIM structure to fabricate similar to 30-nm-wide nanochannels which may be filled with functional material.open8

Impact angle control guidance synthesis for evasive maneuver against intercept missile

This paper proposes a synthesis of new guidance law to generate an evasive maneuver against enemy’s missile interception while considering its impact angle, acceleration, and field-of-view constraints. The first component of the synthesis is a new function of repulsive Artificial Potential Field to generate the evasive maneuver as a real-time dynamic obstacle avoidance. The terminal impact angle and terminal acceleration constraints compliance are based on Time-to-Go Polynomial Guidance as the second component. The last component is the Logarithmic Barrier Function to satisfy the field-of-view limitation constraint by compensating the excessive total acceleration command. These three components are synthesized into a new guidance law, which involves three design parameter gains. Parameter study and numerical simulations are delivered to demonstrate the performance of the proposed repulsive function and guidance law. Finally, the guidance law simulations effectively achieve the zero terminal miss distance, while satisfying an evasive maneuver against intercept missile, considering impact angle, acceleration, and field-of-view limitation constraints simultaneously

Understandings of classical and incremental backstepping controllers with model uncertainties

This paper suggests closed-loop analysis results for both classical and incremental backstepping controllers considering model uncertainties. First, transfer functions with each control algorithm under the model uncertainties, are compared with the ones for the nominal case. The effects of the model uncertainties on the closed-loop systems are critically assessed via investigations on stability conditions and performance metrics. Second, closed-loop characteristics with classical and incremental backstepping controllers under the model uncertainties are directly compared using derived common metrics from their transfer functions. This comparative study clarifies how the effects of the model uncertainties to the closed-loop system become different depending on the applied control algorithm. It also enables understandings about the effects of additional measurements in the incremental algorithm. Third, case studies are conducted assuming that the uncertainty exists only in one aerodynamic derivative estimate while the other estimates have true values. This facilitates systematic interpretations on the impacts of the uncertainty on the specific aerodynamic derivative estimate to the closed-loop system

Closed-loop analysis with incremental backstepping controller considering measurement bias

In this paper, closed loop system characteristics with an incremental backstepping controller are investigated through theoretical analysis when both measurement biases and model uncertainties exist. Incremental backstepping algorithm is proposed in previous studies to reduce model dependency of classical backstepping algorithm with additional measurements about state derivatives and control surface deflection angles. This research enables to have following critical understandings especially about the effects of biases on these additional measurements to system characteristics with incremental backstepping method. First, these biases do not affect a characteristic equation, so they do not have any influence about a condition for absolute stability. Second, these biases cause a steady state error, and model uncertainty in control effectiveness information starts to have an impact to it when these biases are additionally considered

Hypertensive brainstem encephalopathy involving deep supratentorial regions: does only blood pressure matter?

We report on a 42-year-old female patient who presented with high arterial blood pressure of 245/150 mmHg and hypertensive brainstem encephalopathy that involved the brainstem and extensive supratentorial deep gray and white matter. The lesions were nearly completely resolved several days after stabilization of the arterial blood pressure. Normal diffusion-weighted imaging findings and high apparent diffusion coefficient values suggested that the main pathomechanism was vasogenic edema owing to severe hypertension. On the basis of a literature review, the absolute value of blood pressure or whether the patient can control his/her blood pressure seems not to be associated with the degree of the lesions evident on magnetic resonance imaging. It remains to be determined if the acceleration rate and the duration of elevated arterial blood pressure might play a key role in the development of the hypertensive encephalopathy pattern

A Design Approach for Real-Time Embedded Systems with Energy and Code Size Constraints

Real-time embedded systems often have multiple resource constraints such as energy and code size constraints. Traditionally, techniques for reducing energy consumption for real-time embedded systems have been developed without considering code size constraints, whereas code size reduction techniques have been developed without considering energy constraints. There, however, is a tradeoff relationship between reducing dynamic energy consumption and reducing code size for real-time embedded systems. Therefore, reducing code size may result in increasing energy consumption. In this paper, we present a triple-tradeoff relationship among code size, execution time, and energy consumption and then address the code size minimization problem while considering simultaneously the energy constraints and the real-time requirements of embedded systems. We formulate such an optimization problem and prove this optimization problem is NP-hard. Given the difficulty of finding the optimal solution to the problem, we then propose four heuristic algorithms to find sub-optimal solutions and evaluate their performance through simulations

Soil moisture retrieval model design with multispectral and infrared images from unmanned aerial vehicles using convolutional neural network

This paper deals with a soil moisture retrieval model design with airborne measurements for remote monitoring of soil moisture level in large crop fields. A small quadrotor unmanned aerial vehicle (UAV) is considered as a remote sensing platform for high spatial resolutions of airborne images and easy operations. A combination of multispectral and infrared (IR) sensors is applied to overcome the effects of canopies convering the field on the sensor measurements. Convolutional neural network (CNN) is utilized to take the measurement images directly as inputs for the soil moisture retrieval model without loss of information. The procedures to obtain an input image corresponding to a certain soil moisture level measurement point are addressed, and the overall structure of the proposed CNN-based model is suggested with descriptions. Training and testing of the proposed soil moisture retrieval model are conducted to verify and validate its performance and address the effects of input image sizes and errors on input images. The soil moisture level estimation performance decreases when the input image size increases as the ratio of the pixel corresponding to the point to estimate soil moisture level to the total number of pixels in the input image, whereas the input image size should be large enough to include this pixel under the errors in input images. The comparative study shows that the proposed CNN-based algorithm is advantageous on estimation performance by maintaining spatial information of pixels on the input images