Interdisciplinary Investigations in Support of Project DI-MOD

Various concepts from time series analysis are used as the basis for the development of algorithms to assist in the analysis and interpretation of remote sensed imagery. An approach to trend detection that is based upon the fractal analysis of power spectrum estimates is presented. Additionally, research was conducted toward the development of a software architecture to support processing tasks associated with databases housing a variety of data. An algorithmic approach which provides for the automation of the state monitoring process is presented

Effects of sequencing computer-based instruction and lecture in learning function concepts of C programming language

This study investigated the effectiveness of a computer-based lesson used before versus after formal lecture and examined students\u27 difficulties in learning the function concepts of the C programming language. The subjects were fifteen university students who were randomly assigned to two treatment groups that received different instructional sequences. The subjects completed questionnaires, a pretest, the computer-based lesson and a posttest. During the experiment, students\u27 learning processes were observed, their program errors were recorded by the computer system, and some students\u27 reactions were video-taped;Results showed that students\u27 posttest scores were not significantly affected by whether the computer-based lesson was presented before or after the formal lecture. The study reported students\u27 difficulties in syntax, semantics, design and debugging of C programs on the function topics. Recommendations for programming instruction, such as providing appropriate examples, teaching design and debugging strategies and developing a notional machine , were discussed. Use of a team approach, interviews of students, use of think-aloud and investigations of students\u27 preferences were also made for future research

Proceedings of Monterey Workshop 2001 Engineering Automation for Sofware Intensive System Integration

The 2001 Monterey Workshop on Engineering Automation for Software Intensive System Integration was sponsored by the Office of Naval Research, Air Force Office of Scientific Research, Army Research Office and the Defense Advance Research Projects Agency. It is our pleasure to thank the workshop advisory and sponsors for their vision of a principled engineering solution for software and for their many-year tireless effort in supporting a series of workshops to bring everyone together.This workshop is the 8 in a series of International workshops. The workshop was held in Monterey Beach Hotel, Monterey, California during June 18-22, 2001. The general theme of the workshop has been to present and discuss research works that aims at increasing the practical impact of formal methods for software and systems engineering. The particular focus of this workshop was "Engineering Automation for Software Intensive System Integration". Previous workshops have been focused on issues including, "Real-time & Concurrent Systems", "Software Merging and Slicing", "Software Evolution", "Software Architecture", "Requirements Targeting Software" and "Modeling Software System Structures in a fastly moving scenario".Office of Naval ResearchAir Force Office of Scientific Research Army Research OfficeDefense Advanced Research Projects AgencyApproved for public release, distribution unlimite

NASA Tech Briefs, March 2013

Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability

Algorithms in comparative genomics

The field of comparative genomics is abundant with problems of interest to computer scientists. In this thesis, the author presents solutions to three contemporary problems: obtaining better alignments for phylogeny reconstruction, identifying related RNA sequences in genomes, and ranking Single Nucleotide Polymorphisms (SNPs) in genome-wide association studies (GWAS). Sequence alignment is a basic and widely used task in bioinformatics. Its applications include identifying protein structure, RNAs and transcription factor binding sites in genomes, and phylogeny reconstruction. Phylogenetic descriptions depend not only on the employed reconstruction technique, but also on the underlying sequence alignment. The author has studied and established a simple prescription for obtaining a better phylogeny by improving the underlying alignments used in phylogeny reconstruction. This was achieved by improving upon Gotoh\u27s iterative heuristic by iterating with maximum parsimony guide-trees. This approach has shown an improvement in accuracy over standard alignment programs. A novel alignment algorithm named Probalign-RNAgenome that can identify non-coding RNAs in genomic sequences was also developed. Non-coding RNAs play a critical role in the cell such as gene regulation. It is thought that many such RNAs lie undiscovered in the genome. To date, alignment based approaches have shown to be more accurate than thermodynamic methods for identifying such non-coding RNAs. Probalign-RNAgenome employs a probabilistic consistency based approach for aligning a query RNA sequence to its homolog in a genomic sequence. Results show that this approach is more accurate on real data than the widely used BLAST and Smith- Waterman algorithms. Within the realm of comparative genomics are also a large number of recently conducted GWAS. GWAS aim to identify regions in the genome that are associated with a given disease. The support vector machine (SVM) provides a discriminative alternative to the widely used chi-square statistic in GWAS. A novel hybrid strategy that combines the chi-square statistic with the SVM was developed and implemented. Its performance was studied on simulated data and the Wellcome Trust Case Control Consortium (WTCCC) studies. Results presented in this thesis show that the hybrid strategy ranks causal SNPs in simulated data significantly higher than the chi-square test and SVM alone. The results also show that the hybrid strategy ranks previously replicated SNPs and associated regions (where applicable) of type 1 diabetes, rheumatoid arthritis, and Crohn\u27s disease higher than the chi-square, SVM, and SVM Recursive Feature Elimination (SVM-RFE)

Research and Technology Report: 1997

This volume highlights the most significant results from research and development projects sponsored through NASA's Office of Equal Opportunity Programs, Minority University Research and Education Division, in collaboration with Headquarters Program Offices, during Academic Year 1996-97 and Summer 1996. It includes the work of major multidisciplinary research groups, such as those sponsored under NASA's University Research Centers at Minority Institutions and Institutional Research Awards programs, as well as that of individual principal investigators sponsored under the Faculty Awards for Research or other MUREP programs. It encompasses contributions from 863 students and 388 faculty-level researchers at institutions eligible to compete for MUREP funding, including: Historically Black Colleges and Universities (HBCU), Hispanic-Serving Institutions (HSI), Tribal Colleges and Universities (TCU), and accredited minority colleges or universities with a 50 percent or greater underrepresented minority student enrollment. It stands as a testimony to NASA's response to Executive Orders 12876, 12900, and 13021, which mandate increased Federal support to these classes of institutions. We firmly believe that maintaining America's leadership in aerospace and related areas depends on fully utilizing the talents available at the Nation's minority universities

Characterization of Fluorescent Molecular Switches for MINFLUX Nanoscopy

After circumventing the diffraction limit with super-resolution techniques like STED and PALM/STORM, MINFLUX nanoscopy combines the advantages of these techniques, pushing the optical resolution down to the label size. Thus, more than ever, fluorescence microscopy focuses on single fluorophores, exploiting different fluorescent and non-fluores-cent states. However, the behavior of the photoswitching between these states has not been investigated with respect to the MINFLUX performance. These fluorophore-specific properties heavily influence the image quality, particularly the localization efficiency in terms of success and speed. In this thesis, two dye classes with different excitation-decoupled switching mechanisms (reversible and irreversible) were evaluated for their potential for MINFLUX imaging. To this end, a versatile microscope setup was designed, enabling characterizations on single molecule level in confocal and wide-field illumination mode as well as PALM/STORM microscopy to identify the best dye candidates for MINFLUX imaging. Spontaneously blinking fluorophores (reversible switching) allowed for an up to 30-fold increase of localization speed as compared to previously reported blinking dyes. With photoactivatable dyes (irreversible switching), the localization success of MINFLUX nanoscopy was quantitatively benchmarked for the first time against PALM microscopy. Moreover, intra-marker distances were visualized, provoking a new perspective on labeling strategies for biostructural imaging

Parallel and Distributed Execution of Model Management Programs

The engineering process of complex systems involves many stakeholders and development artefacts. Model-Driven Engineering (MDE) is an approach to development which aims to help curtail and better manage this complexity by raising the level of abstraction. In MDE, models are first-class artefacts in the development process. Such models can be used to describe artefacts of arbitrary complexity at various levels of abstraction according to the requirements of their prospective stakeholders. These models come in various sizes and formats and can be thought of more broadly as structured data. Since models are the primary artefacts in MDE, and the goal is to enhance the efficiency of the development process, powerful tools are required to work with such models at an appropriate level of abstraction. Model management tasks – such as querying, validation, comparison, transformation and text generation – are often performed using dedicated languages, with declarative constructs used to improve expressiveness. Despite their semantically constrained nature, the execution engines of these languages rarely capitalize on the optimization opportunities afforded to them. Therefore, working with very large models often leads to poor performance when using MDE tools compared to general-purpose programming languages, which has a detrimental effect on productivity. Given the stagnant single-threaded performance of modern CPUs along with the ubiquity of distributed computing, parallelization of these model management program is a necessity to address some of the scalability concerns surrounding MDE. This thesis demonstrates efficient parallel and distributed execution algorithms for model validation, querying and text generation and evaluates their effectiveness. By fully utilizing the CPUs on 26 hexa-core systems, we were able to improve performance of a complex model validation language by 122x compared to its existing sequential implementation. Up to 11x speedup was achieved with 16 cores for model query and model-to-text transformation tasks