Image Classification of High Variant Objects in Fast Industrial Applications

Recent advances in machine learning and image processing have expanded the applications of computer vision in many industries. In industrial applications, image classification is a crucial task since high variant objects present difficult problems because of their variety and constant change in attributes. Computer vision algorithms can function effectively in complex environments, working alongside human operators to enhance efficiency and data accuracy. However, there are still many industries facing difficulties with automation that have not yet been properly solved and put into practice. They have the need for more accurate, convenient, and faster methods. These solutions drove my interest in combining multiple learning strategies as well as sensors and image formats to enable the use of computer vision for these applications. The motivation for this work is to answer a number of research questions that aim to mitigate current problems in hinder their practical application. This work therefore aims to present solutions that contribute to enabling these solutions. I demonstrate why standard methods cannot simply be applied to an existing problem. Each method must be customized to the specific application scenario in order to obtain a working solution. One example is face recognition where the classification performance is crucial for the system’s ability to correctly identify individuals. Additional features would allow higher accuracy, robustness, safety, and make presentation attacks more difficult. The detection of attempted attacks is critical for the acceptance of such systems and significantly impacts the applicability of biometrics. Another application is tailgating detection at automated entrance gates. Especially in high security environments it is important to prevent that authorized persons can take an unauthorized person into the secured area. There is a plethora of technology that seem potentially suitable but there are several practical factors to consider that increase or decrease applicability depending which method is used. The third application covered in this thesis is the classification of textiles when they are not spread out. Finding certain properties on them is complex, as these properties might be inside a fold, or differ in appearance because of shadows and position. The first part of this work provides in-depth analysis of the three individual applications, including background information that is needed to understand the research topic and its proposed solutions. It includes the state of the art in the area for all researched applications. In the second part of this work, methods are presented to facilitate or enable the industrial applicability of the presented applications. New image databases are initially presented for all three application areas. In the case of biometrics, three methods that identify and improve specific performance parameters are shown. It will be shown how melanin face pigmentation (MFP) features can be extracted and used for classification in face recognition and PAD applications. In the entrance control application, the focus is on the sensor information with six methods being presented in detail. This includes the use of thermal images to detect humans based on their body heat, depth images in form of RGB-D images and 2D image series, as well as data of a floor mounted sensor-grid. For textile defect detection several methods and a novel classification procedure, in free-fall is presented. In summary, this work examines computer vision applications for their practical industrial applicability and presents solutions to mitigate the identified problems. In contrast to previous work, the proposed approaches are (a) effective in improving classification performance (b) fast in execution and (c) easily integrated into existing processes and equipment

Passive Electric Field Sensing for Ubiquitous and Environmental Perception

Electric Field Sensing plays an important role in the research branches of Environmental Perception as well as in Ubiquitous Computing. Environmental Perception aims to collect data of the surroundings, while Ubiquitous Computing has the objective of making computing available at any time. This includes the integration of sensors to perceive environmental influences in an unobtrusive way. Electric Field Sensing, also referenced as Capacitive Sensing, is an often used sensing modality in these research fields, for example, to detect the presence of persons or to locate touches and interactions on user interfaces. Electric Field Sensing has a number of advantages over other technologies, such as the fact that Capacitive Sensing does not require direct line-of-sight contact with the object being sensed and that the sensing system can be compact in design. These advantages facilitate high integrability and allow the collection of data as required in Environmental Perception, as well as the invisible incorporation into a user's environment, needed in Ubiquitous Computing. However, disadvantages are often attributed to Capacitive Sensing principles, such as a low sensing range of only a few centimeters and the generation of electric fields, which wastes energy and has several more problems concerning the implementation. As shown in this thesis, this only affects a subset of this sensing technology, namely the subcategory of active capacitive measurements. Therefore, this thesis focuses on the mainly open area of Passive Electric Field Sensing in the context of Ubiquitous Computing and Environmental Perception, as active Capacitive Sensing is an open research field which already gains a lot of attention. The thesis is divided into three main research questions. First, I address the question of whether and how Passive Electric Field Sensing can be made available in a cost-effective and simple manner. To this end, I present various techniques for reducing installation costs and simplifying the handling of these sensor systems. After the question of low-cost applicability, I examine for which applications passive electric field sensor technology is suitable at all. Therefore I present several fields of application where Passive Electric Field Sensing data can be collected. Taking into account the possible fields of application, this work is finally dedicated to the optimization of Passive Electric Field Sensing in these cases of application. For this purpose, different, already known signal processing methods are investigated for their application for Passive Electric Field sensor data. Furthermore, besides these software optimizations, hardware optimizations for the improved use of the technology are presented

Nuclear power plant security assessment technical manual.

This report (Nuclear Power Plant Security Assessment Technical Manual) is a revision to NUREG/CR-1345 (Nuclear Power Plant Design Concepts for Sabotage Protection) that was published in January 1981. It provides conceptual and specific technical guidance for U.S. Nuclear Regulatory Commission nuclear power plant design certification and combined operating license applicants as they: (1) develop the layout of a facility (i.e., how buildings are arranged on the site property and how they are arranged internally) to enhance protection against sabotage and facilitate the use of physical security features; (2) design the physical protection system to be used at the facility; and (3) analyze the effectiveness of the PPS against the design basis threat. It should be used as a technical manual in conjunction with the 'Nuclear Power Plant Security Assessment Format and Content Guide'. The opportunity to optimize physical protection in the design of a nuclear power plant is obtained when an applicant utilizes both documents when performing a security assessment. This document provides a set of best practices that incorporates knowledge gained from more than 30 years of physical protection system design and evaluation activities at Sandia National Laboratories and insights derived from U.S. Nuclear Regulatory Commission technical staff into a manual that describes a development and analysis process of physical protection systems suitable for future nuclear power plants. In addition, selected security system technologies that may be used in a physical protection system are discussed. The scope of this document is limited to the identification of a set of best practices associated with the design and evaluation of physical security at future nuclear power plants in general. As such, it does not provide specific recommendations for the design and evaluation of physical security for any specific reactor design. These best practices should be applicable to the design and evaluation of physical security for all future plants. Note that the original NUREG/CR-1345 remains valid for many light water reactor designs. While the focus of this document is on new plants, existing nuclear power plants and nuclear material facilities may be able to apply these best practices and security system technologies when upgrading or modifying their physical protection systems

A Learning-based Approach to Exploiting Sensing Diversity in Performance Critical Sensor Networks

Wireless sensor networks for human health monitoring, military surveillance, and disaster warning all have stringent accuracy requirements for detecting and classifying events while maximizing system lifetime. to meet high accuracy requirements and maximize system lifetime, we must address sensing diversity: sensing capability differences among both heterogeneous and homogeneous sensors in a specific deployment. Existing approaches either ignore sensing diversity entirely and assume all sensors have similar capabilities or attempt to overcome sensing diversity through calibration. Instead, we use machine learning to take advantage of sensing differences among heterogeneous sensors to provide high accuracy and energy savings for performance critical applications.;In this dissertation, we provide five major contributions that exploit the nuances of specific sensor deployments to increase application performance. First, we demonstrate that by using machine learning for event detection, we can explore the sensing capability of a specific deployment and use only the most capable sensors to meet user accuracy requirements. Second, we expand our diversity exploiting approach to detect multiple events using a distributed manner. Third, we address sensing diversity in body sensor networks, providing a practical, user friendly solution for activity recognition. Fourth, we further increase accuracy and energy savings in body sensor networks by sharing sensing resources among neighboring body sensor networks. Lastly, we provide a learning-based approach for forwarding event detection decisions to data sinks in an environment with mobile sensor nodes

GAP43: una nueva proteína interactora del receptor CB1 cannabinoide

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Biológicas, leída el 20-05-2021The hemp plant (Cannabis sativa L.) has been used in medicine for at least fifty centuries. However, the chemical structure of its specific active components, the cannabinoids (9-tetrahydrocannabinol - THC and cannabidiol - CBD), was not elucidated until the early 1960s. Afterwards, two speci c G protein-coupled cannabinoid receptors were identi ed: CB1R, which is especially abundant in areasof the central nervous system (CNS) involved in the control of motor behaviour, learning and memory, or emotions; and CB2R, which is preferentially expressed in the immune system. These receptors are activated by endogenous ligands, the endocannabinoids (eCBs). By engaging CB1R in particular, both endogenous and exogenous cannabinoids exert pleiotropic, neuromodulatory effects on our brain. Particularly high levels of CB1R occur in the hippocampal formation, which shows a highly organized intrinsic circuit with the main purpose of memory consolidation...La planta del cáñamo (Cannabis sativa L.) se ha utilizado en medicina desde hace al menos cincuenta siglos. Sin embargo, la estructura química de sus componentes activos, los cannabinoides (9-tetrahydrocannabinol - THC and cannabidiol - CBD)no fue dilucidada hasta la decada de 1960. Tres decadas despues, dos receptores de cannabinoides acoplados a protenas G fueron caracterizados: el de tipo 1 (CB1R),que es especialmente abundante en las areas del sistema nervioso central implicadas en el control de la actividad motora, aprendizaje y memoria o emociones; y el de tipo2 (CB2R), que se expresa preferentemente en el sistema inmune. Estos receptores son activados por ligandos endogenos, los endocannabinoides (eCBs). Concretamente a traves de la activacion de CB1R, los cannabinoides, tanto endogenos como exogenos, ejercen importantes efectos neuromoduladores en nuestro cerebro. Niveles de expresion de CB1R particularmente altos se pueden encontrar en la formacion hipocampal, que alberga circuitos altamente interconectados implicados en la consolidacion de la memoria...Fac. de Ciencias BiológicasTRUEunpu

Campus Communications Systems: Converging Technologies

This book is a rewrite of Campus Telecommunications Systems: Managing Change, a book that was written by ACUTA in 1995. In the past decade, our industry has experienced a thousand-fold increase in data rates as we migrated from 10 megabit links (10 million bits per second) to 10 gigabit links (10 billion bits per second), we have seen the National Telecommunications Policy completely revamped; we have seen the combination of voice, data, and video onto one network; and we have seen many of our service providers merge into larger corporations able to offer more diverse services. When this book was last written, A CUT A meant telecommunications, convergence was a mathematical term, triple play was a baseball term, and terms such as iPod, DoS, and QoS did not exist. This book is designed to be a communications primer to be used by new entrants into the field of communications in higher education and by veteran communications professionals who want additional information in areas other than their field of expertise. There are reference books and text books available on every topic discussed in this book if a more in-depth explanation is desired. Individual chapters were authored by communications professionals from various member campuses. This allowed the authors to share their years of experience (more years than many of us would care to admit to) with the community at large. Foreword Walt Magnussen, Ph.D. Preface Ron Kovac, Ph.D. 1 The Technology Landscape: Historical Overview . Walt Magnussen, Ph.D. 2 Emerging Trends and Technologies . Joanne Kossuth 3 Network Security . Beth Chancellor 4 Security and Disaster Planning and Management Marjorie Windelberg, Ph.D. 5 Student Services in a University Setting . Walt Magnussen, Ph.D. 6 Administrative Services David E. O\u27Neill 7 The Business Side of Information Technology George Denbow 8 The Role of Consultants . David C. Metz Glossary Michelle Narcavag

Columbia Chronicle (03/10/2014)

Student newspaper from March 10, 2014 entitled The Columbia Chronicle. This issue is 44 pages and is listed as Volume 49, Number 22. Cover story: A new kind of \u27Speed\u27 Editor-in-Chief: Lindsey Woodshttps://digitalcommons.colum.edu/cadc_chronicle/1902/thumbnail.jp

Analysis of operations and cyber security policies for a system of cooperating Flexible Alternating Current Transmission System (FACTS) devices.

Flexible Alternating Current Transmission Systems (FACTS) devices are installed on electric power transmission lines to stabilize and regulate power flow. Power lines protected by FACTS devices can increase power flow and better respond to contingencies. The University of Missouri Rolla (UMR) is currently working on a multi-year project to examine the potential use of multiple FACTS devices distributed over a large power system region in a cooperative arrangement in which the FACTS devices work together to optimize and stabilize the regional power system. The report describes operational and security challenges that need to be addressed to employ FACTS devices in this way and recommends references, processes, technologies, and policies to address these challenges