902 research outputs found
Growth, Condition, and Trophic Relations of Stocked Trout in Southern Appalachian Mountain Streams
Stream trout fisheries are among the most popular and valuable in the United States, but many are dependent on hatcheries to sustain fishing and harvest. Thus, understanding the ecology of hatchery‐reared trout stocked in natural environments is fundamental to management. We evaluated the growth, condition, and trophic relations of Brook Trout Salvelinus fontinalis, Brown Trout Salmo trutta, and Rainbow Trout Oncorhynchus mykiss that were stocked in southern Appalachian Mountain streams in western North Carolina. Stocked and wild (naturalized) trout were sampled over time (monthly; September 2012–June 2013) to compare condition and diet composition and to evaluate temporal dynamics of trophic position with stable isotope analysis. Relative weights (Wr) of stocked trout were inversely associated with their stream residence time but were consistently higher than those of wild trout. Weight loss of harvested stocked trout was similar among species and sizes, but fish stocked earlier lost more weight. Overall, 40% of 141 stomachs from stocked trout were empty compared to 15% of wild trout stomachs (N = 26). We identified a much higher rate of piscivory in wild trout (18 times that of stocked trout), and wild trout were 4.3 times more likely to consume gastropods relative to stocked trout. Hatchery‐reared trout were isotopically similar to co‐occurring wild fish for both δ13C and δ15N values but were less variable than wild trout. Differences in sulfur isotope ratios (δ34S) between wild and hatchery‐reared trout indicated that the diets of wild fish were enriched in δ34S relative to the diets of hatchery‐reared fish. Although hatcheryreared trout consumed prey items similar to those of wild fish, differences in consumption or behavior (e.g., reduced feeding) may have resulted in lower condition and negative growth. These findings provide critical insight on the trophic dynamics of stocked trout and may assist in developing and enhancing stream trout fisheries
A Formal Approach to Requirements-Based Programming
No significant general-purpose method is currently available to mechanically transform system requirements into a provably equivalent model. The widespread use of such a method represents a necessary step toward high-dependability system engineering for numerous application domains. Current tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The "gap" unfilled by such tools and methods is that the formal models cannot be proven to be equivalent to the requirements. We offer a method for mechanically transforming requirements into a provably equivalent formal model that can be used as the basis for code generation and other transformations. This method is unique in offering full mathematical tractability while using notations and techniques that are well known and well trusted. Finally, we describe further application areas we are investigating for use of the approach
System and method for deriving a process-based specification
A system and method for deriving a process-based specification for a system is disclosed. The process-based specification is mathematically inferred from a trace-based specification. The trace-based specification is derived from a non-empty set of traces or natural language scenarios. The process-based specification is mathematically equivalent to the trace-based specification. Code is generated, if applicable, from the process-based specification. A process, or phases of a process, using the features disclosed can be reversed and repeated to allow for an interactive development and modification of legacy systems. The process is applicable to any class of system, including, but not limited to, biological and physical systems, electrical and electro-mechanical systems in addition to software, hardware and hybrid hardware-software systems
Systems, methods and apparatus for pattern matching in procedure development and verification
Systems, methods and apparatus are provided through which, in some embodiments, a formal specification is pattern-matched from scenarios, the formal specification is analyzed, and flaws in the formal specification are corrected. The systems, methods and apparatus may include pattern-matching an equivalent formal model from an informal specification. Such a model can be analyzed for contradictions, conflicts, use of resources before the resources are available, competition for resources, and so forth. From such a formal model, an implementation can be automatically generated in a variety of notations. The approach can improve the resulting implementation, which, in some embodiments, is provably equivalent to the procedures described at the outset, which in turn can improve confidence that the system reflects the requirements, and in turn reduces system development time and reduces the amount of testing required of a new system. Moreover, in some embodiments, two or more implementations can be "reversed" to appropriate formal models, the models can be combined, and the resulting combination checked for conflicts. Then, the combined, error-free model can be used to generate a new (single) implementation that combines the functionality of the original separate implementations, and may be more likely to be correct
Automata learning algorithms and processes for providing more complete systems requirements specification by scenario generation, CSP-based syntax-oriented model construction, and R2D2C system requirements transformation
Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required
Formal Requirements-Based Programming for Complex Systems
Computer science as a field has not yet produced a general method to mechanically transform complex computer system requirements into a provably equivalent implementation. Such a method would be one major step towards dealing with complexity in computing, yet it remains the elusive holy grail of system development. Currently available tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The gap that such tools and methods leave unfilled is that the formal models cannot be proven to be equivalent to the system requirements as originated by the customer For the classes of complex systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations. While other techniques are available, this method is unique in offering full mathematical tractability while using notations and techniques that are well known and well trusted. We illustrate the application of the method to an example procedure from the Hubble Robotic Servicing Mission currently under study and preliminary formulation at NASA Goddard Space Flight Center
Systems, methods and apparatus for verification of knowledge-based systems
Systems, methods and apparatus are provided through which in some embodiments, domain knowledge is translated into a knowledge-based system. In some embodiments, a formal specification is derived from rules of a knowledge-based system, the formal specification is analyzed, and flaws in the formal specification are used to identify and correct errors in the domain knowledge, from which a knowledge-based system is translated
Experiences applying Formal Approaches in the Development of Swarm-Based Space Exploration Systems
NASA is researching advanced technologies for future exploration missions using intelligent swarms of robotic vehicles. One of these missions is the Autonomous Nan0 Technology Swarm (ANTS) mission that will explore the asteroid belt using 1,000 cooperative autonomous spacecraft. The emergent properties of intelligent swarms make it a potentially powerful concept, but at the same time more difficult to design and ensure that the proper behaviors will emerge. NASA is investigating formal methods and techniques for verification of such missions. The advantage of using formal methods is the ability to mathematically verify the behavior of a swarm, emergent or otherwise. Using the ANTS mission as a case study, we have evaluated multiple formal methods to determine their effectiveness in modeling and ensuring desired swarm behavior. This paper discusses the results of this evaluation and proposes an integrated formal method for ensuring correct behavior of future NASA intelligent swarms
Enabling Requirements-Based Programming for Highly-Dependable Complex Parallel and Distributed Systems
The manual application of formal methods in system specification has produced successes, but in the end, despite any claims and assertions by practitioners, there is no provable relationship between a manually derived system specification or formal model and the customer's original requirements. Complex parallel and distributed system present the worst case implications for today s dearth of viable approaches for achieving system dependability. No avenue other than formal methods constitutes a serious contender for resolving the problem, and so recognition of requirements-based programming has come at a critical juncture. We describe a new, NASA-developed automated requirement-based programming method that can be applied to certain classes of systems, including complex parallel and distributed systems, to achieve a high degree of dependability
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