890 resultados para real option analysis


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This paper describes in detail the design of a custom CMOS Fast Fourier Transform (FFT) processor for computing 256-point complex FFT. The FFT is well suited for real-time spectrum analysis in instrumentation and measurement applications. The FFT butterfly processor consists of one parallel-parallel multiplier and two adders. It is capable of computing one butterfly computation every 100 ns thus it can compute 256-complex point FFT in 25.6 μs excluding data input and output processes.

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The IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks including sensor networks. It presents the advantage to fit different requirements of potential applications by adequately setting its parameters. When enabling its beacon mode, the protocol makes possible real-time guarantees by using its Guaranteed Time Slot (GTS) mechanism. This paper analyzes the performance of the GTS allocation mechanism in IEEE 802.15.4. The analysis gives a full understanding of the behavior of the GTS mechanism with regards to delay and throughput metrics. First, we propose two accurate models of service curves for a GTS allocation as a function of the IEEE 802.15.4 parameters. We then evaluate the delay bounds guaranteed by an allocation of a GTS using Network Calculus formalism. Finally, based on the analytic results, we analyze the impact of the IEEE 802.15.4 parameters on the throughput and delay bound guaranteed by a GTS allocation. The results of this work pave the way for an efficient dimensioning of an IEEE 802.15.4 cluster.

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Fault injection is frequently used for the verification and validation of dependable systems. When targeting real time microprocessor based systems the process becomes significantly more complex. This paper proposes two complementary solutions to improve real time fault injection campaign execution, both in terms of performance and capabilities. The methodology is based on the use of the on-chip debug mechanisms present in modern electronic devices. The main objective is the injection of faults in microprocessor memory elements with minimum delay and intrusiveness. Different configurations were implemented and compared in terms of performance gain and logic overhead.

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Wireless Body Area Network (WBAN) is the most convenient, cost-effective, accurate, and non-invasive technology for e-health monitoring. The performance of WBAN may be disturbed when coexisting with other wireless networks. Accordingly, this paper provides a comprehensive study and in-depth analysis of coexistence issues and interference mitigation solutions in WBAN technologies. A thorough survey of state-of-the art research in WBAN coexistence issues is conducted. The survey classified, discussed, and compared the studies according to the parameters used to analyze the coexistence problem. Solutions suggested by the studies are then classified according to the followed techniques and concomitant shortcomings are identified. Moreover, the coexistence problem in WBAN technologies is mathematically analyzed and formulas are derived for the probability of successful channel access for different wireless technologies with the coexistence of an interfering network. Finally, extensive simulations are conducted using OPNET with several real-life scenarios to evaluate the impact of coexistence interference on different WBAN technologies. In particular, three main WBAN wireless technologies are considered: IEEE 802.15.6, IEEE 802.15.4, and low-power WiFi. The mathematical analysis and the simulation results are discussed and the impact of interfering network on the different wireless technologies is compared and analyzed. The results show that an interfering network (e.g., standard WiFi) has an impact on the performance of WBAN and may disrupt its operation. In addition, using low-power WiFi for WBANs is investigated and proved to be a feasible option compared to other wireless technologies.

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This thesis provides a complete analysis of the Standard Capital Requirements given by Solvency II for a real insurance portfolio. We analyze the investment portfolio of BPI Vida e Pensões, an insurance company affiliated with a Portuguese bank BPI, both at security, sub-portfolio and asset class levels. By using the Standard Formula from EIOPA, Total SCR amounts to 239M€. This value is mostly explained by Market and Default Risk whereas the former is driven by Spread and Concentration Risks. Following the methodology of Leblanc (2011), we examine the Marginal Contribution of an asset to the SCR which allows for the evaluation of the risks of each security given its characteristics and interactions in the portfolio. The top contributors to the SCR are Corporate Bonds and Term Deposits. By exploring further the composition of the portfolio, our results show that slight changes in allocation of Term and Cash Deposits have severe impacts on the total Concentration and Default Risks, respectively. Also, diversification effects are very relevant by representing savings of 122M€. Finally, Solvency II represents an opportunity for the portfolio optimization. By constructing efficient frontiers, we find that as the target expected return increases, a shift from Term Deposits/ Commercial Papers to Eurozone/Peripheral and finally Equities occurs.

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The current study investigated the effects that barriers (both real and perceived) had on participation and completion of speech and language programs for preschool children with communication delays. I compared 36 families of preschool children with an identified communication delay that have completed services (completers) to 13 families that have not completed services (non-completers) prescribed by Speech and Language professionals. Data findings reported were drawn from an interview with the mother, a speech and language assessment of the child, and an extensive package of measures completed by the mother. Children ranged in age from 32 to 71 mos. These data were collected as part of a project funded by the Canadian Language and Literacy Research Networks of Centres of Excellence. Findings suggest that completers and non-completers shared commonalities in a number of parenting characteristics but differed significantly in two areas. Mothers in the noncompleting group were more permissive and had lower maternal education than mothers in the completing families. From a systemic standpoint, families also differed in the number of perceived barriers to treatment experienced during their time with Speech Services Niagara. Mothers in the non-completing group experienced more perceived barriers to treatment than completing mothers. Specifically, these mothers perceived more stressors and obstacles that competed with treatment, perceived more treatment demands and they perceived the relevance of treatment as less important than the completing group. Despite this, the findings suggest that non-completing families were 100% satisfied with services. Contrary to predictions, there were no significant differences in child characterisfics and economic characteristics between completers and non-completers. The findings in this study are considered exploratory and tentative due to the small sample size.

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Ten pieces originally published in the Columbian Centinel. A later edition with imprint New York, Printed for E. Sargeant, 1809, contains two additional pieces.

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Department of Computer Applications, Cochin University of Science and Technology

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This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.

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Lecture notes for a real analysis course

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Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).