Petri net representation of decision models

Bibliography: p. 24-25."June 1984""N00014-83-K-0185" "AFOSR-80-0229"Daniel Tabak, Alexander H. Levis

Hardware Accelerator for MIMO Wireless Systems

Ever increasing demand for higher data rates and better Quality of Service (QoS) for a growing number of users requires new transceiver algorithms and architectures to better exploit the available spectrum and to efficiently counter the impairments of the radio channel. Multiple-Input Multiple-Output (MIMO) communication systems employ multiple antennas at both transmitter and at the receiver to meet the requirements of next-generation wireless systems. It is a promising technology to provide increased data rates while not involving an equivalent increase in the spectral requirements. However, practical implementation of MIMO detectors poses a significant challenge and has been consistently identified as the major bottleneck for realizing the full potential that multiple antenna systems promise. Furthermore, in order to make judicious use of the available bandwidth, the baseband units have to dynamically adapt to different modes (modulation schemes, code rates etc) of operations. Flexibility and high throughput requirements often place conflicting demands on the Very Large Scale Integration (VLSI) system designer. The major focus of this dissertation is to present efficient VLSI architectures for configurable MIMO detectors that can serve as accelerators to enable the realization of next generation wireless devices feasible. Both, hard output and soft output detector architectures are considered

Human-Centered Computing and Visual Analytics for Future of Work in Construction

Artificial intelligence (AI) is revolutionizing various systems within the Architecture, Engineering, Construction, and Facilities Management (AEC/FM) domains. The rapid advancements in computational methods, engineering knowledge, and sensor technologies is transforming the current construction practices that are heavily reliant on human intervention. Therefore, visionaries are foreseeing that future construction works will be collaborated by humans and machines which will lead to unprecedented socio-economic outcomes in the safety, health, and productivity of construction workers. This Dissertation aims to advance the fundamental knowledge for effectively implementing human-machine collaboration in the construction site. Particularly, the ultimate objective of this Dissertation is to design AI-based autonomous systems for continuously monitoring workplace safety and productivity. Toward this goal, firstly, a content retrieval scheme is designed to analyze a large volume of construction imagery at a rapid speed. Next, an object recognition framework is developed to detect construction-related objects from digital images or videos in real-time. By further extending this framework, an automated safety monitoring system is subsequently designed to verify workers’ compliance with the requirements related to personal protective equipment (PPE). Next, an AI-enabled image enhancement technique is developed to improve the quality of visual data to achieve better performance from the detection models in the preceding steps. Finally, an active vision system is proposed that enables an autonomous camera to intelligently navigates through a jobsite to monitor objects of interest for their safety and productivity

Understanding the College Completion Agenda on a Community College Campus: The Lived Experience of Faculty and Administrators

Former President Obama and business leaders placed community colleges at the center of a plan to avoid a shortage of skilled workers, relying heavily on the 2-year institutions to educate prospective employees and, thereby, uplift the nation's economy (Bailey, 2012) Several non-governmental organizations and charitable foundations responded by creating various national degree completion programs, known as the College Completion Agenda (CCA). In the push to increase degrees, student-learning outcomes may be overlooked and faculty roles ignored by external agencies and institutional administrators. There continues to be little empirical research focused on understanding practitioner knowledge and experiences regarding college degree attainment initiatives. The inclusion of both administrator and faculty experiences provided a rich empirical dataset relevant to an ongoing national conversation about reconciling emphasis on graduation statistics and learning outcomes in the evaluation of college completion initiatives.This case study explored the lived experiences of 5 administrators and 6 faculty members while implementing degree completion initiatives on an urban community college campus. Five themes and six sub-themes emerged from the data and revealed both the processes and possibilities for future reform initiatives. While collaborating with Achieving the Dream (AtD) coaches, participants spoke about developing a data-driven picture of the institution's strengths and weaknesses. Multiple course redesigns transpired in those programs where the greatest student attrition occurred, beginning with developmental math and English courses to college credit-bearing classes required for a degree. An outcome of these restructured courses was a "set curriculum" and assessment across all course sections. Quad-C administrators increased their dedication to increasing degrees through faculty professional development, partnering with Complete College America, and a new strategic plan. As a result, more students began to successfully complete their courses, and the institution experienced an increase in persistence and retention rates and college degrees. An open social system model was applied to the data in a post hoc fashion as a tool to examine first, the interaction between the environment and the institution and second, the interaction taking place internally between the multiple sub-systems of actors

Development of the Integrated Biomass Supply Analysis and Logistics Model (IBSAL)

The Integrated Biomass Supply & Logistics (IBSAL) model is a dynamic (time dependent) model of operations that involve collection, harvest, storage, preprocessing, and transportation of feedstock for use at a biorefinery. The model uses mathematical equations to represent individual unit operations. These unit operations can be assembled by the user to represent the working rate of equipment and queues to represent storage at facilities. The model calculates itemized costs, energy input, and carbon emissions. It estimates resource requirements and operational characteristics of the entire supply infrastructure. Weather plays an important role in biomass management and thus in IBSAL, dictating the moisture content of biomass and whether or not it can be harvested on a given day. The model calculates net biomass yield based on a soil conservation allowance (for crop residue) and dry matter losses during harvest and storage. This publication outlines the development of the model and provides examples of corn stover harvest and logistics

Space station integrated wall design and penetration damage control

A methodology was developed to allow a designer to optimize the pressure wall, insulation, and meteoroid/debris shield system of a manned spacecraft for a given spacecraft configuration and threat environment. The threat environment consists of meteoroids and orbital debris, as specified for an arbitrary orbit and expected lifetime. An overall probability of no penetration is calculated, as well as contours of equal threat that take into account spacecraft geometry and orientation. Techniques, tools, and procedures for repairing an impacted and penetrated pressure wall were developed and tested. These techniques are applied from the spacecraft interior and account for the possibility of performing the repair in a vacuum. Hypervelocity impact testing was conducted to: (1) develop and refine appropriate penetration functions, and (2) determine the internal effects of a penetration on personnel and equipment

Feasibility study of an Integrated Program for Aerospace-vehicle Design (IPAD) system. Volume 6: Implementation schedule, development costs, operational costs, benefit assessment, impact on company organization, spin-off assessment, phase 1, tasks 3 to 8

A baseline implementation plan, including alternative implementation approaches for critical software elements and variants to the plan, was developed. The basic philosophy was aimed at: (1) a progressive release of capability for three major computing systems, (2) an end product that was a working tool, (3) giving participation to industry, government agencies, and universities, and (4) emphasizing the development of critical elements of the IPAD framework software. The results of these tasks indicate an IPAD first release capability 45 months after go-ahead, a five year total implementation schedule, and a total developmental cost of 2027 man-months and 1074 computer hours. Several areas of operational cost increases were identified mainly due to the impact of additional equipment needed and additional computer overhead. The benefits of an IPAD system were related mainly to potential savings in engineering man-hours, reduction of design-cycle calendar time, and indirect upgrading of product quality and performance

Towards reliable logging in the internet of things networks

The internet of things is one of the most rapidly developing technologies, and its low cost and usability make it applicable to various critical disciplines. Being a component of such critical infrastructure needs, these networks have to be dependable and offer the best outcome. Keeping track of network events is one method for enhancing network reliability, as network event logging supports essential processes such as debugging, checkpointing, auditing, root-cause analysis, and forensics. However, logging in the IoT networks is not a simple task. IoT devices are positioned in remote places with unstable connectivity and inadequate security protocols, making them vulnerable to environmental flaws and security breaches. This thesis investigates the problem of reliable logging in IoT networks. We concentrate on the problem in the presence of Byzantine behaviour and the integration of logging middleware into the network stack. To overcome these concerns, we propose a technique for distributed logging by distributing loggers around the network. We define the logger selection problem and the collection problem, and show that only the probabilistic weak variant can solve the problem. We examine the performance of the Collector algorithm in several MAC setups. We then explore the auditability notion in IoT; we show how safety specification can be enforced through the analogies of fair exchange. Next, we review our findings and their place in the existing body of knowledge. We also explore the limits we faced when investigating this problem, and we finish this thesis by providing opportunities for future work