An efficient method based on machine learning for estimation of the wall parameters in through-the-wall imaging

The estimation of the wall parameters is important in through-the-wall radar imaging (TWRI). Ambiguities in the wall characteristics, including wall thickness, permittivity, and conductivity, will distort the imaging and shift the target position. To obtain a quick and accurate estimation of wall parameters, an efficient method based on machine learning is proposed. The estimation problem is converted to a regression problem. A map between wall parameters and the received signals is established and is regressed as a linear formulation after machine learning; in this manner, the wall parameters can be estimated in few seconds. The measurement results demonstrate that the estimated approach has the advantages of high precision and low computational time. The influence of the size, the location, the number of the targets and the length of the wall, the sampling interval, and noise on the estimation problems is discussed, and the image entropy is given to verify the effectiveness of the estimation values. The results based on support vector machines and least-square support vector machines (LS-SVMs), which are both machine-learning approaches, are compared. The comparison results reveal that the LS-SVM-based method can provide comparable performances in terms of accuracy and convenience but poor performances in terms of generalization and robustness.     

Algorithmic optimization method for effort estimation

This paper presents an improvement of an effort estimation method that can be used to predict the level of effort for software development projects. A new estimation approach based on a two-phase algorithm is used. In the first phase, we apply a calculation based on use case points (UCPs). In the second phase, we add correction values (a ₁, a ₂) obtained via least squares regression. This approach employs historical project data to refine the estimate. By applying the least squares regression approach, the algorithm filters out estimation errors caused by human factors and company practice.     

Energy Consumption Optimization for Mobile Robots Motion Using Predictive Control

Operation of mobile robots in off-road environment requires the attention to the torque saturation problem that occurs in the wheels DC motors while climbing hills. In the present work, off-road conditions are utilized to benefit while avoiding torque saturation. Energy optimization algorithm using predictive control is implemented on a two-DC motor-driven wheels mobile robot while crossing a ditch. The predictive control algorithm is simulated and compared with the PID control and the open-loop control. Predictive control showed more capability to avoid torque saturation and noticeable reduction in the energy consumption. Furthermore, using the wheels motors armature current instead of the supply voltage as control variable in the predictive control showed more efficient speed control. Simulation results showed that in case of known ditch dimensions ahead of time, the developed algorithm is feasible. Experimental examination of the developed energy optimization algorithm is presented. The experimental results showed a good agreement with the simulation results. The effects of the road slope and the prediction horizon length on the consumed energy are evaluated. The analytical study showed that the energy consumption is reduced by increasing the prediction horizon until it reaches a limit at which no more energy reduction is obtained. This limit is proportional to the width of the ditch in front of the mobile robot. Curve fitting is applied to the obtained results to address further the effect of the parameters on the energy consumption.     

Research on a large power thermal bubble micro-ejector with induction heating

The present study investigates a large power thermal bubble micro-ejector with induction heating device. The traditional thermal-bubble ejectors adopted resistors as the heating resources, it can only work with lower power and convey liquid with lower flow rate. Induction heating devices are adopted to replace the resistor for heating liquid in this paper. With this heating method, there is no physical contact between the heating core and the external power supply circuit. The liquid in the chamber of micro-ejector is heated by the induction heating device and changes from liquid phase to gas phase, generating vapor bubbles in the micro chamber of the micro ejector. The bubble expands rapidly and ejects droplets through the nozzle. The prototype of the micro-ejector is fabricated and experiments are carried out. Continuous droplets are ejected out from the nozzle as the applied AC current is 0.6–0.65 A with the power frequency of 100 kHz. The total volume of the continuous droplets is ranging from 18.84 to 49.87 nL, and the corresponding flow rate is about 0.52–1.36 μL/min. Furthermore, this new micro-ejector can be adopted in conveying of micro-scale liquid, the injection of trace drugs and the 3D printing.     

Single-crystal diamond micro-cupped resonators made by laser ablation

This paper presents a novel three-dimensional fabrication process of micro-scale shell resonator made of single-crystal diamond (SCD) called micro-cupped resonator (MCR). The key feature of the process is the application of laser ablation, which can contribute to the shaping process of SCD with higher accuracy, better structural symmetry, greater speed, and lower breakage rate. UV laser high precision processing machine has been employed for the ablation of SCD in the present investigation. This paper describes the principle of laser ablation of SCD and analyses the effects of beam parameters on ablation quality. Then MCR with better structural symmetry and less structural imperfection has been successfully fabricated based on optimum parameters by laser ablation. The MCR is promising for emerging applications such as micro rate-integrating gyroscope.     

Markov Models of Queueing–Inventory Systems with Variable Order Size

Markov models of queueing–inventory systems with variable order size are investigated. Two classes of models are considered: with instant service and with nonzero service time. The model with nonzero service time assumes that impatient customers can form a queue of either finite or infinite length. The exact and approximate methods are developed to calculate the characteristics of the systems under proposed restocking policy.     

A divide-and-conquer hole-filling method for handling disocclusion in single-view rendering

Large holes are unavoidably generated in depth image based rendering (DIBR) using a single color image and its associated depth map. Such holes are mainly caused by disocclusion, which occurs around the sharp depth discontinuities in the depth map. We propose a divide-and-conquer hole-filling method which refines the background depth pixels around the sharp depth discontinuities to address the disocclusion problem. Firstly, the disocclusion region is detected according to the degree of depth discontinuity, and the target area is marked as a binary mask. Then, the depth pixels located in the target area are modified by a linear interpolation process, whose pixel values decrease from the foreground depth value to the background depth value. Finally, in order to remove the isolated depth pixels, median filtering is adopted to refine the depth map. In these ways, disocclusion regions in the synthesized view are divided into several small holes after DIBR, and are easily filled by image inpainting. Experimental results demonstrate that the proposed method can effectively improve the quality of the synthesized view subjectively and objectively.     

A new approach for image databases design

This paper focuses on the methodologies to organize and structure image databases. Conventional relational database techniques are optimized to deal with textual and numeric data; however, they are not effective to handle image data. Some progresses have been made in developing new approaches to establish and use image databases, but the applications of these approaches are very labor-intensive, error-prone, and impractical to large-scale databases. In this paper, we propose a new approach to develop the structure of a large-scale image automatically. It is an integrated approach from existing technologies for the new application where the management of image data is focused. In addition, we present a solution to data indexing for the image database with different image types.