Performance evaluation and characterization of symmetric capacitors with carbon black, and asymmetric capacitors using a carbon foam supported nickel electrode

This thesis evaluates a novel asymmetric capacitor incorporating a carbon foam supported nickel hydroxide positive electrode and a carbon black negative electrode. A series of symmetric capacitors were prepared to characterize the carbon black (CB) negative electrode. The influence of the binder, PTFE, content on the cell properties was evaluated. X-ray diffraction characterization of the nickel electrode during cycling is also presented. The 3 wt% and 5 wt% PTFE/CB symmetric cells were examined using cyclic voltammetry (CV) and constant current charge/discharge measurements. As compared with symmetric cells containing more PTFE, the 3 wt% cell has the highest average specific capacitance, energy density and power density over 300 cycles, 121.8 F/g, 6.44 Wh/kg, and 604.1 W/kg, respectively. Over the 3 to 10 wt% PTFE/CB range, the 3 wt% sample exhibited the lowest effective resistance and the highest BET surface area. Three asymmetric cells (3 wt% PTFE/CB negative electrode and a nickel positive) were fabricated; cycle life was examined at 3 current densities. The highest average energy and power densities over 1000 cycles were 20 Wh/kg (21 mA/cm2) and 715 W/kg (31 mA/cm2), respectively. The longest cycle life was 11,505 cycles (at 8 mA/cm2), with an average efficiency of 79% and an average energy density of 14 Wh/kg. The XRD results demonstrate that the cathodically deposited nickel electrode is a typical α-Ni(OH)2 with the R3m structure (ABBCCA stacking); the charged electrodes are 3γ-NiOOH with the same stacking as the α-type; the discharged electrodes (including as-formed electrode) are aged to β’-Ni(OH)2 (a disordered β) with the P3m structure (ABAB stacking). A 3γ remnant was observed

Effects of laser fluence on silicon modification by four-beam laser interference

This paper discusses the effects of laser fluence on silicon modification by four-beam laser interference. In this work, four-beam laser interference was used to pattern single crystal silicon wafers for the fabrication of surface structures, and the number of laser pulses was applied to the process in air. By controlling the parameters of laser irradiation, different shapes of silicon structures were fabricated. The results were obtained with the single laser fluence of 354 mJ/cm, 495 mJ/cm, and 637 mJ/cm, the pulse repetition rate of 10 Hz, the laser exposure pulses of 30, 100, and 300, the laser wavelength of 1064 nm, and the pulse duration of 7-9 ns. The effects of the heat transfer and the radiation of laser interference plasma on silicon wafer surfaces were investigated. The equations of heat flow and radiation effects of laser plasma of interfering patterns in a four-beam laser interference distribution were proposed to describe their impacts on silicon wafer surfaces. The experimental results have shown that the laser fluence has to be properly selected for the fabrication of well-defined surface structures in a four-beam laser interference process. Laser interference patterns can directly fabricate different shape structures for their corresponding applications

Rethinking the Pipeline of Demosaicing, Denoising and Super-Resolution

Incomplete color sampling, noise degradation, and limited resolution are the three key problems that are unavoidable in modern camera systems. Demosaicing (DM), denoising (DN), and super-resolution (SR) are core components in a digital image processing pipeline to overcome the three problems above, respectively. Although each of these problems has been studied actively, the mixture problem of DM, DN, and SR, which is a higher practical value, lacks enough attention. Such a mixture problem is usually solved by a sequential solution (applying each method independently in a fixed order: DM $\to$ DN $\to$ SR), or is simply tackled by an end-to-end network without enough analysis into interactions among tasks, resulting in an undesired performance drop in the final image quality. In this paper, we rethink the mixture problem from a holistic perspective and propose a new image processing pipeline: DN $\to$ SR $\to$ DM. Extensive experiments show that simply modifying the usual sequential solution by leveraging our proposed pipeline could enhance the image quality by a large margin. We further adopt the proposed pipeline into an end-to-end network, and present Trinity Enhancement Network (TENet). Quantitative and qualitative experiments demonstrate the superiority of our TENet to the state-of-the-art. Besides, we notice the literature lacks a full color sampled dataset. To this end, we contribute a new high-quality full color sampled real-world dataset, namely PixelShift200. Our experiments show the benefit of the proposed PixelShift200 dataset for raw image processing.Comment: Code is available at: https://github.com/guochengqian/TENe

Optimizing High-Speed Railroad Timetable with Passenger and Station Service Demands: A Case Study in the Wuhan-Guangzhou Corridor

This paper aims to optimize high-speed railroad timetables for a corridor. We propose an integer programming model using a time-space network-based approach to consider passenger service demands, train scheduling, and station service demands simultaneously. A modified branch-and-price algorithm is used for the computation. This algorithm solves the linear relaxation of all nodes in a branch-and-bound tree using a column generation algorithm to derive a lower-bound value (LB) and derive an upper-bound value (UB) using a rapid branching strategy. The optimal solution is derived by iteratively updating the upper- and lower-bound values. Three acceleration strategies, namely, initial solution iteration, delayed constraints, and column removal, were designed to accelerate the computation. The effectiveness and efficiency of the proposed model and algorithm were tested using Wuhan-Guangzhou high-speed railroad data. The results show that the proposed model and algorithm can quickly reduce the defined cost function by 38.2% and improve the average travel speed by 10.7 km/h, which indicates that our proposed model and algorithm can effectively improve the quality of a constructed train timetable and the travel efficiency for passengers. Document type: Articl

Deep saliency detection-based pedestrian detection with multispectral multi-scale features fusion network

In recent years, there has been increased interest in multispectral pedestrian detection using visible and infrared image pairs. This is due to the complementary visual information provided by these modalities, which enhances the robustness and reliability of pedestrian detection systems. However, current research in multispectral pedestrian detection faces the challenge of effectively integrating different modalities to reduce miss rates in the system. This article presents an improved method for multispectral pedestrian detection. The method utilises a saliency detection technique to modify the infrared image and obtain an infrared-enhanced map with clear pedestrian features. Subsequently, a multiscale image features fusion network is designed to efficiently fuse visible and IR-enhanced maps. Finally, the fusion network is supervised by three loss functions for illumination perception, light intensity, and texture information in conjunction with the light perception sub-network. The experimental results demonstrate that the proposed method improves the logarithmic mean miss rate for the three main subgroups (all day, day and night) to 3.12%, 3.06%, and 4.13% respectively, at “reasonable” settings. This is an improvement over the traditional method, which achieved rates of 3.11%, 2.77%, and 2.56% respectively, thus demonstrating the effectiveness of the proposed method