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At least 127 records · Page 7

First results from the spectral DCT trigger implemented in the Cyclone V Front-End Board used for a detection of very inclined showers in the Pierre Auger surface detector Engineering Array

The paper presents the first results from the trigger based on the Discrete Cosine Transform (DCT) operating in the new Front-End Boards with Cyclone V FPGA deployed in 8 test surface detectors in the Pierre Auger Engineering Array. The patterns of the ADC traces generated by very inclined showers were obtained from the Auger database and from the CORSIKA simulation package supported next by Offline reconstruction Auger platform which gives a predicted digitized signal profiles. Simulations for many variants of the initial angle of shower, initialization depth in the atmosphere, type of particle and its initial energy gave a boundary of the DCT coefficients used next for the on-line pattern recognition in the FPGA. Preliminary results have proven a right approach. We registered several showers triggered by the DCT for 120 MSps and 160 MSps. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Potential Collaborative Research topics with Korea’s Agency for Defense Development

This presentation provides a high level summary of current research activities at the Los Alamos National Laboratory (LANL)-University of California Jacobs School of Engineering (UCSD) Engineering Institute that will be presented at Korea's Agency for Defense Development (ADD). These research activities are at the basic engineering science level with different level of maturity ranging from initial concepts to field proof-of-concept demonstrations. We believe that all of these activities are appropriate for collaborative research activities with ADD subject to approval by each institution. All the activities summarized herein have the common theme that they are multi-disciplinary in nature and typically involved the integration of high-fidelity predictive modeling, advanced sensing technologies and new development in information technology. These activities include: Wireless Sensor Systems, Swarming Robot sensor systems, Advanced signal processing (compressed sensing) and pattern recognition, Model Verification and Validation, Optimal/robust sensor system design, Haptic systems for large-scale data processing, Cyber-physical security for robots, Multi-source energy harvesting, Reliability-based approaches to damage prognosis, SHMTools software development, and Cyber-physical systems advanced study institute.

42 ENGINEERING↗

Org.Lcsim: Event Reconstruction in Java

Maximizing the physics performance of detectors being designed for the International Linear Collider, while remaining sensitive to cost constraints, requires a powerful, efficient, and flexible simulation, reconstruction and analysis environment to study the capabilities of a large number of different detector designs. The preparation of Letters Of Intent for the International Linear Collider involved the detailed study of dozens of detector options, layouts and readout technologies; the final physics benchmarking studies required the reconstruction and analysis of hundreds of millions of events. We describe the Java-based software toolkit (org.lcsim) which was used for full event reconstruction and analysis. The components are fully modular and are available for tasks from digitization of tracking detector signals through to cluster finding, pattern recognition, track-fitting, calorimeter clustering, individual particle reconstruction, jet-finding, and analysis. The detector is defined by the same xml input files used for the detector response simulation, ensuring the simulation and reconstruction geometries are always commensurate by construction. We discuss the architecture as well as the performance.

43 PARTICLE ACCELERATORS↗

Monitoring and Control of Chemical Composition of InGaN Layers During MOCVD

This Department of Energy SBIR Phase II grant targets the inefficiency of the epitaxial processes used to deposit wide band-gap semiconductor thin films that are an essential part of the next generation high-brightness LEDs for solid state lighting. Non-uniformity of the layers over a single wafer and non-repeatability over the wafers in a single batch, separate batches and separate reactors are some of the primary source of reduced manufacturing yield. The team performed extensive research, development and validation of an in-situ spectroscopic optical monitoring and epitaxial process control system. The system monitors the LED thin films as they grow on the individual wafers inside the epitaxial reactor, records the signal in a broad spectral range and processes the information to retrieve essential film quality parameters and their variation over a single wafer, all the wafers in a batch and multiple batches. A novel software algorithm is implemented, which performs real-time spectral pattern recognition and displays any abnormalities or differences in the deposition, which is used by the engineer to optimize the epitaxial process. The project resulted in the optimization of the LED film growth and improvement of its uniformity and repeatability, reducing the cost of the final LED devices.

36 MATERIALS SCIENCE↗

Computer-Assisted Diagnosis System for Breast Cancer in Computed Tomography Laser Mammography (CTLM)

Computed tomography laser mammography (Eid et al. Egyp J Radiol Nucl Med, 37(1): p. 633–643, 1) is a non-invasive imaging modality for breast cancer diagnosis, which is time-consuming and challenging for the radiologist to interpret the images. Some issues have increased the missed diagnosis of radiologists in visual manner assessment in CTLM images, such as technical reasons which are related to imaging quality and human error due to the structural complexity in appearance. The purpose of this study is to develop a computer-aided diagnosis framework to enhance the performance of radiologist in the interpretation of CTLM images. The proposed CAD system contains three main stages including segmentation of volume of interest (VOI), feature extraction and classification. A 3D Fuzzy segmentation technique has been implemented to extract the VOI. The shape and texture of angiogenesis in CTLM images are significant characteristics to differentiate malignancy or benign lesions. The 3D compactness features and 3D Grey Level Co-occurrence matrix (GLCM) have been extracted from VOIs. Multilayer perceptron neural network (MLPNN) pattern recognition has developed for classification of the normal and abnormal lesion in CTLM images. The performance of the proposed CAD system has been measured with different metrics including accuracy, sensitivity, and specificity and area under receiver operative characteristics (AROC), which are 95.2, 92.4, 98.1, and 0.98%, respectively.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deep modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.

60 APPLIED LIFE SCIENCES↗

Prospects for X(3872) Detection at P-barANDA

Monte-Carlo simulations for a resonance scan of the charmonium-like state X(3872) at P-barANDA are performed. Final state radiation hadronic background reactions are taken into account. The signal reconstruction uses a realistic pattern recognition (track finder and track fitter) and electron/pion discrimination.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Line broadening interference for high-resolution nuclear magnetic resonance spectra under inhomogeneous magnetic fields

Nuclear magnetic resonance spectroscopy serves as an important tool for analyzing chemicals and biological metabolites. However, its performance is subject to the magnetic-field homogeneity. Under inhomogeneous fields, peaks are broadened to overlap each other, introducing difficulties for assignments. Here, we propose a method termed as line broadening interference (LBI) to provide high-resolution information under inhomogeneous magnetic fields by employing certain gradients in the indirect dimension to interfere the magnetic-field inhomogeneity. The conventional spectral-line broadening is thus interfered to be non-diagonal, avoiding the overlapping among adjacent resonances. Furthermore, an inhomogeneity correction algorithm is developed based on pattern recognition to recover the high-resolution information from LBI spectra. Theoretical deductions are performed to offer systematic and detailed analyses on the proposed method. Moreover, experiments are conducted to prove the feasibility of the proposed method for yielding high-resolution spectra in inhomogeneous magnetic fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

99 GENERAL AND MISCELLANEOUS↗

A Planning Tool for Estimating Waste Generated by a Radiological Incident and Subsequent Decontamination Efforts - 13569

Management of debris and waste from a wide-area radiological incident would probably constitute a significant percentage of the total remediation cost and effort. The U.S. Environmental Protection Agency's (EPA's) Waste Estimation Support Tool (WEST) is a unique planning tool for estimating the potential volume and radioactivity levels of waste generated by a radiological incident and subsequent decontamination efforts. The WEST was developed to support planners and decision makers by generating a first-order estimate of the quantity and characteristics of waste resulting from a radiological incident. The tool then allows the user to evaluate the impact of various decontamination/demolition strategies on the waste types and volumes generated. WEST consists of a suite of standalone applications and Esri{sup R} ArcGIS{sup R} scripts for rapidly estimating waste inventories and levels of radioactivity generated from a radiological contamination incident as a function of user-defined decontamination and demolition approaches. WEST accepts Geographic Information System (GIS) shape-files defining contaminated areas and extent of contamination. Building stock information, including square footage, building counts, and building composition estimates are then generated using the Federal Emergency Management Agency's (FEMA's) Hazus{sup R}-MH software. WEST then identifies outdoor surfaces based on the application of pattern recognition to overhead aerial imagery. The results from the GIS calculations are then fed into a Microsoft Excel{sup R} 2007 spreadsheet with a custom graphical user interface where the user can examine the impact of various decontamination/demolition scenarios on the quantity, characteristics, and residual radioactivity of the resulting waste streams. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Damage Mechanism Evaluation of Large-Scale Concrete Structures Affected by Alkali-Silica Reaction Using Acoustic Emission

Alkali-silica reaction has caused damage to concrete structures, endangering structural serviceability and integrity. This is of concern in sensitive structures such as nuclear power plants. In this study, acoustic emission (AE) was employed as a structural health monitoring strategy in large-scale, reinforced concrete specimens affected by alkali-silica reaction with differing boundary conditions resembling the common conditions found in nuclear containments. An agglomerative hierarchical algorithm was utilized to classify the AE data based on energy-frequency based features. The AE signals were transferred into the frequency domain and the energies in several frequency bands were calculated and normalized to the total energy of signals. Principle component analysis was used to reduce feature redundancy. Then the selected principal components were considered as features in an input of the pattern recognition algorithm. The sensor located in the center of the confined specimen registered the largest portion of AE energy release, while in the unconfined specimen the energy is distributed more uniformly. This confirms the results of the volumetric strain, which shows that the expansion in the confined specimen is oriented along the thickness of the specimen.

36 MATERIALS SCIENCE↗

Upper bounds on Shannon and Renyi entropies for central potentials

The Renyi and Shannon entropies are information-theoretic measures, which have enabled to formulate the position-momentum uncertainty principle in a much more adequate and stringent way than the (variance-based) Heisenberg-like relation. Moreover, they are closely related to various energetic density functionals of quantum systems. Here we derive upper bounds on these quantities in terms of the second-order moment <r{sup 2}> for general central potentials. This improves previous results of this type. The proof uses the Renyi maximization procedure with a covariance constraint due to Costa et al. [in Proceedings of the Fourth International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), edited by A.Rangarajan, M.A. T.Figueiredo, and J.Zerubia (Springer-Verlag, Lisbon, 2003), [Lect. Notes Comput. Sci. 52, 211 (2003).]] The contributions to these bounds coming from the radial and angular parts of the physical wave functions are taken into account. Finally, the application to the d-dimensional (d{>=} 3) hydrogenic and oscillator-like systems is provided.

97 MATHEMATICS AND COMPUTING↗

Global proteomic analysis of two tick-borne emerging zoonotic agents: Anaplasma phagocytophilum and Ehrlichia chaffeensis

Anaplasma phagocytophilum and Ehrlichia chaffeensis are obligatory intracellular {alpha}-proteobacteria that infect human leukocytes and cause potentially fatal emerging zoonoses. In the present study, we determined global protein expression profiles of these bacteria cultured in the human promyelocytic leukemia cell line, HL-60. Mass spectrometric (MS) analyses identified a total of 1,212 A. phagocytophilum and 1,021 E. chaffeensis proteins, representing 89.3 and 92.3% of the predicted bacterial proteomes, respectively. Nearly all bacterial proteins ({approx}99%) with known functions were expressed, whereas only approximately 80% of hypothetical proteins were detected in infected human cells. Quantitative MS/MS analyses indicated that highly expressed proteins in both bacteria included chaperones, enzymes involved in biosynthesis and metabolism, and outer membrane proteins, such as A. phagocytophilum P44 and E. chaffeensis P28/OMP-1. Among 113 A. phagocytophilum p44 paralogous genes, 110 of them were expressed and 88 of them were encoded by pseudogenes. In addition, bacterial infection of HL-60 cells up-regulated the expression of human proteins involved mostly in cytoskeleton components, vesicular trafficking, cell signaling, and energy metabolism, but down regulated some pattern recognition receptors involved in innate immunity. Our proteomics data represent a comprehensive analysis of A. phagocytophilum and E. chaffeensis proteomes, and provide a quantitative view of human host protein expression profiles regulated by bacterial infection. The availability of these proteomic data will provide new insights into biology and pathogenesis of these obligatory intracellular pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

An "artificial retina" processor for track reconstruction at the full LHC crossing rate

Here, we present the latest results of an R&D; study for a specialized processor capable of reconstructing, in a silicon pixel detector, high-quality tracks from high-energy collision events at 40 MHz. The processor applies a highly parallel pattern-recognition algorithm inspired to quick detection of edges in mammals visual cortex. After a detailed study of a real-detector application, demonstrating that online reconstruction of offline-quality tracks is feasible at 40 MHz with sub-microsecond latency, we are implementing a prototype using common high-bandwidth FPGA devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Prognostics and Life Beyond 60 Years for Nuclear Power Plants

Safe, secure, reliable and sustainable energy supply is vital for advanced and industrialized life styles. To meet growing energy demand there is interest in longer term operation (LTO) for the existing nuclear power plant fleet and enhancing capabilities in new build. There is increasing use of condition based maintenance (CBM) for active components and growing interest in deploying on-line monitoring instead of periodic in service inspection (ISI) for passive systems. Opportunities exist to move beyond monitoring and diagnosis based on pattern recognition and anomaly detection to prognostics with the ability to provide an estimate of remaining useful life (RUL). The adoption of digital I&C systems provides a framework within which added functionality including on-line monitoring can be deployed, and used to maintain and even potentially enhance safety, while at the same time improving planning and reducing both operations and maintenance costs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

The fundamental role of symmetry in nuclear models

The purpose of these lectures is to illustrate how symmetry and pattern recognition play essential roles in the progression from experimental observation to an understanding of nuclear phenomena in terms of interacting neutrons and protons. We do not discuss weak interactions nor relativistic and sub-nucleon degrees of freedom. The explicit use of symmetry and the power of algebraic methods, in combination with analytical and geometrical methods are illustrated by their use in deriving a shell-model description of nuclear rotational dynamics and the structure of deformed nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A new APDS approach - alarm processing based on alarm prioritization - 201

We take for granted that the advances in technology bring improvements to the conditions in which humans perform activities associated to them. Is that the case for digital alarm systems in nuclear power plants? The answer is not that simple. A review of the related literature, shows that still, the single most significant problem with alarm systems, is the large number of alarm messages presented to the operator at once. This is an issue that affects analog I and C control rooms with conventional annunciators and gets aggravated in digital I and C based control rooms. Digital alarm systems present the alarms in the form of lists in computer screens. This kind of presentation forces the operator to scroll or navigate pages to review the active alarms. Also, the alarm lists do not allow the operator to apply the pattern recognition practices acquired during training when using with fixed position alarm systems. An Alarm Processing and Diagnostic System (APDS) facilitates the alarm monitoring task by applying alarm reduction techniques based on alarm priorities. It allows the operators to focus on the most important alarms during plant upsets. A new generation of APDS should be based in an improved alarm analysis methodology. To develop such methodology, Tecnatom reviewed applicable standards and our own alarm analysis experiences. This paper documents the process and conclusions of the methodology development. (authors)

42 ENGINEERING↗

Welding Defect Classification from Simulated Ultrasonic Signals

Nondestructive testing is widely used to detect and to size up discontinuities embedded in a material. Among the several ultrasonic techniques, time of flight diffraction (TOFD) combines high speed inspection, high sizing reliability and low rate of incorrect results. However, the classification of defects through ultrasound signals acquired by the TOFD technique depends heavily on the knowledge and experience of the operator and thus, this classification is still frequently questioned. Besides, this task requires long processing time due to the large amount of data to be analyzed. Nevertheless, computational tools for pattern recognition can be employed to analyze a high amount of data with large efficiency. In the present work, simulation of ultrasound propagation in two-dimensional media containing, each one, different kinds of modeled discontinuities which mimic defects in welded joints were performed. Clustering (k-means) and classification (principal component analysis and k-nearest neighbors) algorithms were employed to associate each simulated ultrasound signal with its corresponding modeled defects. The results for each method were analyzed, discussed and compared. The results are very promising.

42 ENGINEERING↗