Dynamic models of exchange rate dependence using option prices and historical returns

Models for the conditional joint distribution of the U.S. Dollar/Japanese Yen and Euro/Japanese Yen exchange rates, from November 2001 until June 2007, are evaluated and compared. The conditional dependency is allowed to vary across time, as a function of either historical returns or a combination of past return data and option-implied dependence estimates. Using prices of currency options that are available in the public domain, risk-neutral dependency expectations are extracted through a copula repre- sentation of the bivariate risk-neutral density. For this purpose, we employ either the one-parameter \Normal" or a two-parameter \Gumbel Mixture" specification. The latter provides forward-looking information regarding the overall degree of covariation, as well as, the level and direction of asymmetric dependence. Specifications that include option-based measures in their information set are found to outperform, in-sample and out-of-sample, models that rely solely on historical returns.

Reliability of vegetation community information derived using decorana ordination and fuzzy c-means clustering

Descriptions of vegetation communities are often based on vague semantic terms describing species presence and dominance. For this reason, some researchers advocate the use of fuzzy sets in the statistical classification of plant species data into communities. In this study, spatially referenced vegetation abundance values collected from Greek phrygana were analysed by ordination (DECORANA), and classified on the resulting axes using fuzzy c-means to yield a point data-set representing local memberships in characteristic plant communities. The fuzzy clusters matched vegetation communities noted in the field, which tended to grade into one another, rather than occupying discrete patches. The fuzzy set representation of the community exploited the strengths of detrended correspondence analysis while retaining richer information than a TWINSPAN classification of the same data. Thus, in the absence of phytosociological benchmarks, meaningful and manageable habitat information could be derived from complex, multivariate species data. We also analysed the influence of the reliability of different surveyors' field observations by multiple sampling at a selected sample location. We show that the impact of surveyor error was more severe in the Boolean than the fuzzy classification. © 2007 Springer.

Using genetic programming and decision trees for generating structural descriptions of four bar mechanisms

Four bar mechanisms are basic components of many important mechanical devices. The kinematic synthesis of four bar mechanisms is a difficult design problem. A novel method that combines the genetic programming and decision tree learning methods is presented. We give a structural description for the class of mechanisms that produce desired coupler curves. Constructive induction is used to find and characterize feasible regions of the design space. Decision trees constitute the learning engine, and the new features are created by genetic programming.

Detection of urinary bladder cancer cells using redox ratio and double excitation wavelengths autofluorescence

The optical redox ratio as a measure of cellular metabolism is determined by an altered ratio between endogenous fluorophores NADH and flavin adenine dinucleotide (FAD). Although reported for other cancer sites, differences in optical redox ratio between cancerous and normal urothelial cells have not previously been reported. Here, we report a method for the detection of cellular metabolic states using flow cytometry based on autofluorescence, and a statistically significant increase in the redox ratio of bladder cancer cells compared to healthy controls. Urinary bladder cancer and normal healthy urothelial cell lines were cultured and redox overview was assessed using flow cytometry. Further localisation of fluorescence in the same cells was carried out using confocal microscopy. Multiple experiments show correlation between cell type and redox ratio, clearly differentiating between healthy cells and cancer cells. Based on our preliminary results, therefore, we believe that this data contributes to current understanding of bladder tissue fluorescence and can inform the design of endoscopic probes. This approach also has significant potential as a diagnostic tool for discrimination of cancer cells among shed urothelial cells in voided urine, and could lay the groundwork for an automated system for population screening for bladder cancer.

Wind power forecasts using Gaussian processes and numerical weather prediction

Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.

Robot Control Using Inductive, Deductive and Case Based Reasoning

The paper deals with a problem of intelligent system’s design for complex environments. There is discussed a possibility to integrate several technologies into one basic structure that could form a kernel of an autonomous intelligent robotic system. One alternative structure is proposed in order to form a basis of an intelligent system that would be able to operate in complex environments. The proposed structure is very flexible because of features that allow adapting via learning and adjustment of the used knowledge. Therefore, the proposed structure may be used in environments with stochastic features such as hardly predictable events or elements. The basic elements of the proposed structure have found their implementation in software system and experimental robotic system. The software system as well as the robotic system has been used for experimentation in order to validate the proposed structure - its functionality, flexibility and reliability. Both of them are presented in the paper. The basic features of each system are presented as well. The most important results of experiments are outlined and discussed at the end of the paper. Some possible directions of further research are also sketched at the end of the paper.

Unrepeatered Nyquist PDM-16QAM transmission over 364 km using Raman amplification and multi-channel digital back-propagation

Transmission of a net 467-Gb/s PDM-16QAM Nyquist-spaced superchannel is reported with an intra-superchannel net spectral efficiency (SE) of 6.6 (b/s)/Hz, over 364-km SMF-28 ULL ultra-low loss optical fiber, enabled by bi-directional second-order Raman amplification and digital nonlinearity compensation. Multi-channel digital back-propagation (MC-DBP) was applied to compensate for nonlinear interference; an improvement of 2 dB in Q2 factor was achieved when 70-GHz DBP bandwidth was applied, allowing an increase in span length of 37 km.

A new regime for high rate growth of nanocrystalline diamond films using high power and CH4/H2/N2/O2 plasma

In this work, we report high growth rate of nanocrystalline diamond (NCD) films on silicon wafers of 2 inches in diameter using a new growth regime, which employs high power and CH4/H2/N2/O2 plasma using a 5 kW MPCVD system. This is distinct from the commonly used hydrogen-poor Ar/CH4 chemistries for NCD growth. Upon rising microwave power from 2000 W to 3200 W, the growth rate of the NCD films increases from 0.3 to 3.4 μm/h, namely one order of magnitude enhancement on the growth rate was achieved at high microwave power. The morphology, grain size, microstructure, orientation or texture, and crystalline quality of the NCD samples were characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction, and micro-Raman spectroscopy. The combined effect of nitrogen addition, microwave power, and temperature on NCD growth is discussed from the point view of gas phase chemistry and surface reactions. © 2011 Elsevier B.V. All rights reserved.

Dynamic strain sensor using a vcsel and a polymer fiber bragg grating in a multimode fiber

We have implemented a dynamic strain sensor using a Polymer Optical Fiber Bragg Grating (POFBG). In this paper, we have investigated an approach for making such systems cheaper through the use of easy to handle multimode fiber. A Vertical-Cavity Surface-Emitting Laser is used to decrease the cost of the interrogation system and a photodetector converts the reflected light into an electrical signal.

ASIC microcontroller design of a radiation monitoring system using VHDL modeling and FPGA implementation

Three new technologies have been brought together to develop a miniaturized radiation monitoring system. The research involved (1) Investigation a new HgI$\sb2$ detector. (2) VHDL modeling. (3) FPGA implementation. (4) In-circuit Verification. The packages used included an EG&G's crystal(HgI$\sb2$) manufactured at zero gravity, the Viewlogic's VHDL and Synthesis, Xilinx's technology library, its FPGA implementation tool, and a high density device (XC4003A). The results show: (1) Reduced cycle-time between Design and Hardware implementation; (2) Unlimited Re-design and implementation using the static RAM technology; (3) Customer based design, verification, and system construction; (4) Well suited for intelligent systems. These advantages excelled conventional chip design technologies and methods in easiness, short cycle time, and price in medium sized VLSI applications. It is also expected that the density of these devices will improve radically in the near future. ^

Effect of blood flow patterns on localized platelet adhesion under physiologic flow conditions using two-dimensional and three-dimensional stent models: An experimental and computational approach

This dissertation presents dynamic flow experiments with fluorescently labeled platelets to allow for spatial observation of wall attachment in inter-strut spacings, to investigate their relationship to flow patterns. Human blood with fluorescently labeled platelets was circulated through an in vitro system that produced physiologic pulsatile flow in (1) a parallel plate blow chamber that contained two-dimensional (2D) stents that feature completely recirculating flow, partially recirculating flow, and completely reattached flow, and (2) a three-dimensional (3D) cylindrical tube that contained stents of various geometric designs. ^ Flow detachment and reattachment points exhibited very low platelet deposition. Platelet deposition was very low in the recirculation regions in the 3D stents unlike the 2D stents. Deposition distal to a strut was always high in 2D and 3D stents. Spirally recirculating regions were found in 3D unlike in 2D stents, where the deposition was higher than at well-separated regions of recirculation. ^

Evaluating the external validity of comorbid disorders in youth using rating scales and behavior observations

To evaluate the theoretical underpinnings of current categorical approaches to classify childhood psychopathological conditions, this dissertation examined whether children with a single diagnosis of an anxiety disorder (ANX only) and children with an anxiety diagnosis comorbid with other diagnoses (i.e., anxiety + anxiety disorder [ANX + ANX], anxiety + depressive disorder [ANX + DEP], and anxiety + disruptive disorder [ANX + EXT]) could be differentiated using external validation criteria of clinical phenomenology (i.e., levels of anxiety, depression, and internalizing, externalizing and total behavior problems). This study further examined whether the four groups could be differentiated in terms of their interaction patterns with their parents and peers, respectively. The sample consisted of 129 youth and their parents who presented to the Child Anxiety and Phobia Program (CAPP) housed within the Child and Family Psychosocial Research Center at Florida International University, Miami. Youth were between the ages of 8 and 14 years old. A battery of questionnaires was used to assess participants' clinical presentation in terms of levels of anxiety, depression, and internalizing and externalizing symptoms. Family and peer interaction were evaluated through rating scales and through behavior observation tasks. Statistics based on the parameter estimates of the structured equation models indicated that all the comorbid groups were significantly different from the pure anxiety disorder group when it came to depression indices of clinical phenomenology. Further, significant differences appeared mainly in terms of the ANX + DEP comorbid group relative to the other comorbid groups. In terms of Parent-child interaction the ANX + EXT and the ANX + DEP comorbid groups were differentiated from the pure anxiety disorder and ANX + ANX comorbid group when it came to the appraisal of the parent/child relationship by the parent, and the acceptance subscale according to the mother report. In terms of peer-child interaction the ANX + EXT and the ANX + DEP comorbid groups were statistically significantly different from the pure anxiety disorder only when it came to the positive interactions and the social skills as rated by mother. Limitations and future research recommendations are discussed.

Customization of the design of antenna using genetic algorithm and finite-difference time-domain technique

Antenna design is an iterative process in which structures are analyzed and changed to comply with certain performance parameters required. The classic approach starts with analyzing a "known" structure, obtaining the value of its performance parameter and changing this structure until the "target" value is achieved. This process relies on having an initial structure, which follows some known or "intuitive" patterns already familiar to the designer. The purpose of this research was to develop a method of designing UWB antennas. What is new in this proposal is that the design process is reversed: the designer will start with the target performance parameter and obtain a structure as the result of the design process. This method provided a new way to replicate and optimize existing performance parameters. The base of the method was the use of a Genetic Algorithm (GA) adapted to the format of the chromosome that will be evaluated by the Electromagnetic (EM) solver. For the electromagnetic study we used XFDTD™ program, based in the Finite-Difference Time-Domain technique. The programming portion of the method was created under the MatLab environment, which serves as the interface for converting chromosomes, file formats and transferring of data between the XFDTD™ and GA. A high level of customization had to be written into the code to work with the specific files generated by the XFDTD™ program. Two types of cost functions were evaluated; the first one seeking broadband performance within the UWB band, and the second one searching for curve replication of a reference geometry. The performance of the method was evaluated considering the speed provided by the computer resources used. Balance between accuracy, data file size and speed of execution was achieved by defining parameters in the GA code as well as changing the internal parameters of the XFDTD™ projects. The results showed that the GA produced geometries that were analyzed by the XFDTD™ program and changed following the search criteria until reaching the target value of the cost function. Results also showed how the parameters can change the search criteria and influence the running of the code to provide a variety of geometries.

In vivo characterization of myocardial tissue post myocardial infarction using combined fluorescence and diffuse reflectance spectroscopy

Accurately assessing the extent of myocardial tissue injury induced by Myocardial infarction (MI) is critical to the planning and optimization of MI patient management. With this in mind, this study investigated the feasibility of using combined fluorescence and diffuse reflectance spectroscopy to characterize a myocardial infarct at the different stages of its development. An animal study was conducted using twenty male Sprague-Dawley rats with MI. In vivo fluorescence spectra at 337 nm excitation and diffuse reflectance between 400 nm and 900 nm were measured from the heart using a portable fiber-optic spectroscopic system. Spectral acquisition was performed on (1) the normal heart region; (2) the region immediately surrounding the infarct; and (3) the infarcted region—one, two, three and four weeks into MI development. The spectral data were divided into six subgroups according to the histopathological features associated with various degrees/severities of myocardial tissue injury as well as various stages of myocardial tissue remodeling, post infarction. Various data processing and analysis techniques were employed to recognize the representative spectral features corresponding to various histopathological features associated with myocardial infarction. The identified spectral features were utilized in discriminant analysis to further evaluate their effectiveness in classifying tissue injuries induced by MI. In this study, it was observed that MI induced significant alterations (p < 0.05) in the diffuse reflectance spectra, especially between 450 nm and 600 nm, from myocardial tissue within the infarcted and surrounding regions. In addition, MI induced a significant elevation in fluorescence intensities at 400 and 460 nm from the myocardial tissue from the same regions. The extent of these spectral alterations was related to the duration of the infarction. Using the spectral features identified, an effective tissue injury classification algorithm was developed which produced a satisfactory overall classification result (87.8%). The findings of this research support the concept that optical spectroscopy represents a useful tool to non-invasively determine the in vivo pathophysiological features of a myocardial infarct and its surrounding tissue, thereby providing valuable real-time feedback to surgeons during various surgical interventions for MI.