A^2Net: Adjacent Aggregation Networks for Image Raindrop Removal

Existing methods for single images raindrop removal either have poor robustness or suffer from parameter burdens. In this paper, we propose a new Adjacent Aggregation Network (A^2Net) with lightweight architectures to remove raindrops from single images. Instead of directly cascading convolutional layers, we design an adjacent aggregation architecture to better fuse features for rich representations generation, which can lead to high quality images reconstruction. To further simplify the learning process, we utilize a problem-specific knowledge to force the network focus on the luminance channel in the YUV color space instead of all RGB channels. By combining adjacent aggregating operation with color space transformation, the proposed A^2Net can achieve state-of-the-art performances on raindrop removal with significant parameters reduction

Influence of Rain on Vision-Based Algorithms in the Automotive Domain

The Automotive domain is a highly regulated domain with stringent requirements that characterize automotive systems’ performance and safety. Automotive applications are required to operate under all driving conditions and meet high levels of safety standards. Vision-based systems in the automotive domain are accordingly required to operate at all weather conditions, favorable or adverse. Rain is one of the most common types of adverse weather conditions that reduce quality images used in vision-based algorithms. Rain can be observed in an image in two forms, falling rain streaks or adherent raindrops. Both forms corrupt the input images and degrade the performance of vision-based algorithms. This dissertation describes the work we did to study the effect of rain on the quality images and the target vision systems that use them as the main input. To study falling rain, we developed a framework for simulating failing rain streaks. We also developed a de-raining algorithm that detects and removes rain streaks from the images. We studied the relation between image degradation due to adherent raindrops and the performance of the target vision algorithm and provided quantitive metrics to describe such a relation. We developed an adherent raindrop simulator that generates synthetic rained images, by adding generated raindrops to rain-free images. We used this simulator to generate rained image datasets, which we used to train some vision algorithms and evaluate the feasibility of using transfer-learning to improve DNN-based vision algorithms to improve performance under rainy conditions.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/170924/1/Yazan Hamzeh final dissertation.pdfDescription of Yazan Hamzeh final dissertation.pdf : Dissertatio

Conference on Charge-Coupled Device Technology and Applications

Papers were presented from the conference on charge coupled device technology and applications. The following topics were investigated: data processing; infrared; devices and testing; electron-in, x-ray, radiation; and applications. The emphasis was on the advances of mutual relevance and potential significance both to industry and NASA's current and future requirements in all fields of imaging, signal processing and memory

Research on the System Safety Management in Urban Railway

Nowadays, rail transport has become one of the most widely utilised forms of transport thanks to its high safety level, large capacity, and cost-effectiveness. With the railway network's continuous development, including urban rail transit, one of the major areas of increasing attention and demand is ensuring safety or risk management in operation long-term remains for the whole life cycle by scientific tools, management of railway operation (Martani 2017), specifically in developed and developing countries like Vietnam. The situation in Vietnam demonstrates that the national mainline railway network has been built and operated entirely in a single narrow gauge (1000mm) since the previous century, with very few updates of manual operating technology. This significantly highlights that up to now, the conventional technique for managing the safety operation in general, and collision in particular, of the current Vietnamese railway system, including its subsystems, is only accident statistics which is not a scientific-based tool as the others like risk identify and analyse methods, risk mitigation…, that are already available in many countries. Accident management of Vietnam Railways is limited and responsible for accident statistics analysis to avoid and minimise the harm caused by phenomena that occur only after an accident. Statistical analysis of train accident case studies in Vietnam railway demonstrates that, because hazards and failures that could result in serious system occurrences (accidents and incidents) have not been identified, recorded, and evaluated to conduct safety-driven risk analysis using a well-suited assessment methodology, risk prevention and control cannot be achieved. Not only is it hard to forecast and avoid events, but it may also raise the chance and amount of danger, as well as the severity of the later effects. As a result, Vietnam's railway system has a high number of accidents and failure rates. For example, Vietnam Rail-ways' mainline network accounted for approximately 200 railway accidents in 2018, a 3% increase over the previous year, including 163 collisions between trains and road vehicles/persons, resulting in more than 100 fatalities and more than 150 casualties; 16 accidents, including almost derailments, the signal passed at danger… without fatality or casual-ty, but significant damage to rolling stock and track infrastructure (VR 2021). Focusing and developing a new standardised framework for safety management and availability of railway operation in Vietnam is required in view of the rapid development of rail urban transport in the country in recent years (VmoT 2016; VmoT 2018). UMRT Line HN2A in southwest Hanoi is the country's first elevated light rail transit line, which was completed and officially put into revenue service in November 2021. This greatly highlights that up to the current date, the UMRT Line HN2A is the first and only railway line in Vietnam with operational safety assessment launched for the first time and long-term remains for the whole life cycle. The fact that the UMRT Hanoi has a large capacity, more complicated rolling stock and infrastructure equipment, as well as a modern communica-tion-based train control (CBTC) signalling system and automatic train driving without the need for operator intervention (Lindqvist 2006), are all advantages. Developing a compatible and integrated safety management system (SMS) for adaption to the safety operating requirements of this UMRT is an important major point of concern, and this should be proven. In actuality, the system acceptance and safety certification phase for Metro Line HN2A prolonged up to 2.5 years owing to the identification of difficulties with noncompliance to safety requirements resulting from inadequate SMS documents and risk assessment. These faults and hazards have developed during the manufacturing and execution of the project; it is impossible to go back in time to correct them, and it is also impossible to ignore the project without assuming responsibility for its management. At the time of completion, the HN2A metro line will have required an expenditure of up to $868 million, thus it is vital to create measures to prevent system failure and assure passenger safety. This dissertation has reviewed the methods to solve the aforementioned challenges and presented a solution blueprint to attain the European standard level of system safety in three-phase as in the following: • Phase 1: applicable for lines that are currently in operation, such as Metro Line HN2A. Focused on operational and maintenance procedures, as well as a training plan for railway personnel, in order to enhance human performance. Complete and update the risk assessment framework for Metro Line HN2A. The dissertation's findings are described in these applications. • Phase 2: applicable for lines that are currently in construction and manufacturing, such as Metro Line HN3, Line HN2, HCMC Line 1 and Line 2. Continue refining and enhancing engineering management methods introduced during Phase 1. On the basis of the risk assessment by manufacturers (Line HN3, HCMC Line 2 with European manufacturers) and the risk assessment framework described in Chapter 4, a risk management plan for each line will be developed. Building Accident database for risk assessment research and development. • Phase 3: applicable for lines that are currently in planning. Enhance safety requirements and life-cycle management. Building a proactive Safety Culture step by step for the railway industry. This material is implemented gradually throughout all three phases, beginning with the creation of the concept and concluding with an improvement in the attitude of railway personnel on the HN2A line. In addition to this overview, Chapters 4 through Chapter 9 of the dissertation include particular solutions for Risk assessment, Vehicle and Infrastructure Maintenance methods, Inci-dent Management procedures, and Safety Culture installation. This document focuses on constructing a system safety concept for railway personnel, providing stringent and scientific management practises to assure proper engineering conditions, to manage effectively the metro line system, and ensuring passenger safety in Hanoi's metro operatio

Smart Water Utilities

Today there is increasing pressure on the water infrastructure and although unsustainable water extraction and wastewater handling can continue for a while, at some point water needs to be managed in a way that is sustainable in the long-term. We need to handle water utilities “smarter”. New and effective tools and technologies are becoming available at an affordable cost and these technologies are steadily changing water infrastructure options. The quality and robustness of sensors are increasing rapidly and their reliability makes the automatic handling of critical processes viable. Online and real-time control means safer and more effective operation. The combination of better sensors and new water treatment technologies is a strong enabler for decentralised and diversified water treatment. Plants can be run with a minimum of personnel attendance. In the future, thousands of sensors in the water utility cycle will handle all the complexity in an effective way. Smart Water Utilities: Complexity Made Simple provides a framework for Smart Water Utilities based on an M-A-D (Measurement-Analysis-Decision). This enables the organisation and implementation of “Smart” in a water utility by providing an overview of supporting technologies and methods. The book presents an introduction to methods and tools, providing a perspective of what can and could be achieved. It provides a toolbox for all water challenges and is essential reading for the Water Utility Manager, Engineer and Director and for Consultants, Designers and Researchers