Yellow Perch population assessment in Southwestern Lake Michigan, including evaluation of sampling techniques and identification of the factors that determine Yellow Perch year-class strength April 1, 2004 - March 31, 2005

ID: 8528; Annual Report to Division of Fisheries, Illinois Department of Natural Resources; F-123-R-11

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of factors that Determine Yellow Perch Year-Class Strength April 1, 2005 - March 31, 2006

Annual Report, Federal Aid Project F-123-R-12, April 1, 2005 - March 31, 2006

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and the Identification Factors that Determine Yellow Perch Year-Class Strength April 1,1997 - March 31, 1998

ID: 8827; issued June 1, 1998

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and the identification Factors that Determine Yellow Perch Year-Class Strength April 1, 1998 - March 31, 1999

ID: 8863; issued June 1, 1999

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of the Factors that Determine Yellow Perch Year-Class Strength April 1, 2007 – March 31, 2008

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: F-123 R-14

Yellow perch population assessment in southwestern Lake Michigan, including evaluation of sampling techniques and identification of the factors that determine yellow perch year-class strength April 1, 2006 – March 31, 2007

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: F-123 R-13

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of the Factors that Determine Yellow Perch Year-Class Strength April 1, 2008 – June 30, 2009

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: Federal Aid Project F-123 R-15

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Simplified Chinese lacquer techniques and Nanban style decoration on Luso-Asian objects from the late sixteenth or early seventeenth centuries

The meeting of multiple cultures and their mutual influence during the Portuguese expansion in Asia led to the emergence of different types of fusion styles in objects commissioned by the settlers, merchants, and religious orders present in Portuguese India. The east-Asian lacquer coatings of modestly sized wooden objects of various types dating from the sixteenth and early seventeenth centuries have been analyzed as part of the research for a doctoral thesis that aims to establish their cultural and geographical attribution within the context of the Getty Conservation Institute’s lacquer research project. Among the objects were three seventeenthcentury lacquered trays from Portuguese museums and private collections that had previously been classified as Japanese Nanban, Chinese or Ryukyuan lacquers or even as Indo-Portuguese artifacts. The materials and techniques that were identified show close similarities with Chinese techniques mentioned in historic accounts — the only existing Ming Chinese Treatise on lacquering Xiushi lu and the eighteenth-century memoirs of the Jesuit priest d’Incarville. These nearly 400-year-old artifacts are among the first lacquered objects commissioned by Europeans and probably the first of Chinese origin. Their detailed technical study contributes to international lacquer research and complements existing knowledge and perceptions of the lacquering processes that were applied in response to an early European demand for exotic items.

ANALYSE THE VULNERABILITY IN THE MARANHÃO ILHA, BRAZIL, USING GIS TECHNIQUES AND GEOSPATIAL INFERENCE

Vulnerability and sustainability studies of an area help to assess both its level of exposure and capacity to support possible environmental impacts, and it is of primordial importance for proposals of the Legislation on Zoning, Allotment, Land Use/land cover, aiming to stimulate those areas indicated for urban growth, to discourage growth of overcrowded areas, to detect sections with restrictive use, as well as districts for permanent protection. This paper aims to analyze the vulnerability in the Maranhão Ilha, using GIS techniques, geospatial inference intersected with relevant social-environmental indicators.Estudos de vulnerabilidade e de sustentabilidade de uma área ajudam a avaliar o seu grau de exposição e sua capacidade de suporte a possíveis impactos ambientais, sendo fundamental para propostas de Lei de Zoneamento, Parcelamento, Uso e Ocupação do Solo, tendo por finalidade orientar as áreas onde deverá haver estímulo para o crescimento urbano; contenção da malha urbana; detecção de locais com possibilidade de uso restritivo, bem como locais de proteção permanente. Este trabalho propõe analisar o índice de vulnerabilidade a perda de solo da Ilha do Maranhão com base na metodologia proposta por (CREPANI, et al. 2001) e em técnicas de inferência espacial com apoio na AHP (Análise Hierárquica de Processo).

Calibration of the maximum carboxylation velocity (Vcmax) using data mining techniques and ecophysiological data from the Brazilian Semiarid region, for use in Dynamic Global Vegetation Models.

The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga

A short training program improves the accuracy of portion-size estimates in future dietitians

[EN] The objective of this study was to determine whether a short training program, using real foods, would decreased their portion-size estimation errors after training. 90 student volunteers (20.18±0.44 y old) of the University of the Basque Country (Spain) were trained in observational techniques and tested in food-weight estimation during and after a 3-hour training period. The program included 57 commonly consumed foods that represent a variety of forms (125 different shapes). Estimates of food weight were compared with actual weights. Effectiveness of training was determined by examining change in the absolute percentage error for all observers and over all foods over time. Data were analyzed using SPSS vs. 13.0. The portion-size errors decreased after training for most of the foods. Additionally, the accuracy of their estimates clearly varies by food group and forms. Amorphous was the food type estimated least accurately both before and after training. Our findings suggest that future dietitians can be trained to estimate quantities by direct observation across a wide range of foods. However this training may have been too brief for participants to fully assimilate the application.

Improving the Accessibility of Lightweight Formal Verification Systems

In research areas involving mathematical rigor, there are numerous benefits to adopting a formal representation of models and arguments: reusability, automatic evaluation of examples, and verification of consistency and correctness. However, broad accessibility has not been a priority in the design of formal verification tools that can provide these benefits. We propose a few design criteria to address these issues: a simple, familiar, and conventional concrete syntax that is independent of any environment, application, or verification strategy, and the possibility of reducing workload and entry costs by employing features selectively. We demonstrate the feasibility of satisfying such criteria by presenting our own formal representation and verification system. Our system’s concrete syntax overlaps with English, LATEX and MediaWiki markup wherever possible, and its verifier relies on heuristic search techniques that make the formal authoring process more manageable and consistent with prevailing practices. We employ techniques and algorithms that ensure a simple, uniform, and flexible definition and design for the system, so that it easy to augment, extend, and improve.

Implementation of a network flow lookup circuit for next-generation packet classifiers

This paper presents a lookup circuit with advanced memory techniques and algorithms that examines network packet headers at high throughput rates. Hardware solutions and test scenarios are introduced to evaluate the proposed approach. The experimental results show that the proposed lookup circuit is able to achieve at least 39 million packet header lookups per second, which facilitates the application of next-generation stateful packet classifications at beyond 20Gbps internet traffic throughput rates.

Localization Algorithm Performance in Ultra Low Power Active RFID Based Patient Tracking

Indoor personnel localization research has generated a range of potential techniques and algorithms. However, these typically do not account for the influence of the user's body upon the radio channel. In this paper an active RFID based patient tracking system is demonstrated and three localization algorithms are used to estimate the location of a user within a modern office building. It is shown that disregarding body effects reduces the accuracy of the algorithms' location estimates and that body shadowing effects create a systematic position error that estimates the user's location as closer to the RFID reader that the active tag has line of sight to.