Warner Robins and the Buy Purchase Request Process

Throughout the United States Air Force, Warner Robins Air Logistics Center (ALC) has a reputation of being ahead of the game when it comes to lean implementation. Efforts on the shop floor have contributed vastly to that reputation. In addition, administrative accomplishments need to be recognized as a significant contribution to the lean effort at Warner Robins. At the Warner Robins Air Logistics Center (ALC), the ultimate goal of every employee is to serve the warfighter effectively and efficiently through the maintenance and repair of aircraft. The ALC’s main work is in Program Depot Maintenance (PDM) which supports aircraft sustainment operations for seven Product Directorates. Within Product Directorates are the System Program Offices (SPOs), such as C-5 or C-130, of Air Force weapon systems. Sustainment is a dauntingly complex process for the Air Force involving the Depot and PDM efforts, movement and storage of parts, and the base repair process. In 2002, Warner Robins embarked upon a lean journey to improve the reliability, timeliness and costs associated with its repair operations. Within the context of that improvement attempt, this case study examines the efforts to maximize purchase request efficiency, (i.e., shorten the time needed to acquire parts)

Learning-Based Synthesis of Safety Controllers

We propose a machine learning framework to synthesize reactive controllers for systems whose interactions with their adversarial environment are modeled by infinite-duration, two-player games over (potentially) infinite graphs. Our framework targets safety games with infinitely many vertices, but it is also applicable to safety games over finite graphs whose size is too prohibitive for conventional synthesis techniques. The learning takes place in a feedback loop between a teacher component, which can reason symbolically about the safety game, and a learning algorithm, which successively learns an overapproximation of the winning region from various kinds of examples provided by the teacher. We develop a novel decision tree learning algorithm for this setting and show that our algorithm is guaranteed to converge to a reactive safety controller if a suitable overapproximation of the winning region can be expressed as a decision tree. Finally, we empirically compare the performance of a prototype implementation to existing approaches, which are based on constraint solving and automata learning, respectively

Using Platelet-Rich Plasma to Reverse the Effects of Tendinopathy and Prevent Tendon Re-rupture after Surgery in Athletes: The Search for a Standardized Protocol

30-50% of all lesions amateur and professional sports players will experience during activity are related to the tendon. Moreover, the incidence of tendinopathy, a precursor to tendon rupture, is much higher in both of these groups due to excessive loading of tendons during physical activity, insufficient rest afterwards and certain antibiotic use. The tendon anatomically has both a low blood supply and a low cell turnover rate, which contribute to the relative ease by which an athlete can develop tendinopathy. Chronic tendinopathy has very few high-success treatments but in recent years, platelet-rich plasma (PRP), a treatment in which platelets are isolated from the patient’s blood and injected back into the diseased tendon, has seen promising results. Prior research has focused on assessing the viability of PRP as a treatment but failed to come up with a standard and procedure protocol for its administration. In this study, PRP is evaluated in terms of success rate, concentration of cells other than platelets, concentration of growth factors, life of growth factors, and size and cross section of the tendon to develop a formulation standard, injection plan, and procedure protocol for different tendinopathies. Furthermore, a rehabilitation program that takes into account both the treatment and natural healing process of the tendon to shorten the time the athlete spends off the field is outlined

Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn

Spartan Daily, October 10, 1980

Volume 75, Issue 29https://scholarworks.sjsu.edu/spartandaily/6665/thumbnail.jp

Extending the Life-Cycle of Optical Media

This paper examines the products that two companies provide to protect optical media and to eliminate scratches, gauges, and other marks that deface the playing surface