MULTICAST OPERATIONS, ADMINISTRATION, AND MANAGEMENT (OAM) TECHNIQUES UTILIZING PROTOCOL INDEPENDENT MULTICAST (PIM) FLOODING MECHANISMS

Multicast networks are often complex and to provide a visualization of traffic flows within a multicast network often involves the full knowledge of a distribution tree for the network. Further, isolating problems within a multicast network can involve tracing of multiple nodes across the distribution tree. Techniques presented provide efficient multicast tree discovery through Protocol Independent Multicast (PIM) flooding mechanisms, which can be further used to facilitate network visualizations and fault isolation within a network

Development of a dynamic traffic assignment system for short-term planning applications

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2002.Includes bibliographical references (p. 141-147).Evaluation of Intelligent Transportation Systems (ITS) at the planning level, as well as various short-term planning projects, require the use of appropriate tools that can capture the dynamic and stochastic interactions between demand and supply. The objective of this thesis is to develop a methodological framework for such applications and implement it in the context of an existing dynamic traffic assignment system, DynaMIT. The methodological framework captures the day-to-day evolution of traffic. Furthermore, it models traveler behavior and network performance, in response to special events and situations such as incidents, weather emergencies, sport events etc. The new planning tool DynaMIT-P, consists of a supply (network performance) simulator, a demand simulator and algorithms that capture their interactions. The supply simulator captures traffic dynamics in terms of evolution and dissipation of queues, spill-backs etc. The demand simulator estimates OD flows that best match current measurements of them in the network, and models travel behavior in terms of route choice, departure time choice and response to information. DynaMIT-P is particularly suited to evaluate Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS) at various levels of sophistication. The results of a case study, focusing on the evaluation of alternative designs of Variable Message Signs (VMS) using a network in Irvine, California, illustrate the functionality and potential of the system.by Srinivasan Sundaram.S.M

Development of an Integrated Generator Power Take-of Strategy using Model Predictive Control (MPC) for Ocean Wave Energy Conversion

Model Predictive Control (MPC) has previously been investigated on ocean waveenergy converters (WEC) to improve the amount of power captured, while respectingthe system constraints. Previous research done in the same area, focused onbuilding a control scheme by using the knowledge of the past & current statesof the system and predicting the future states of the system based on which thecontrol action was taken for the power-take-o (PTO) to maximize power capture.This was done by maximizing the product of force and velocity and at the sametime, staying under the permissible limits of both force and velocity (constraints).Our research attempts investigate if an integrated approach for power maximizationis possible by trying to modify the way power maximization is done. Thisis made possible by integrating a state-space generator model with a state-spaceWEC model. This combined generator-WEC model is then used with an MPCcontroller. So rather than having PTO-force as the input for the wave energy converter,dq reference frame voltages are used as inputs and the product of voltagesand currents for the d and q axes (i.e. the electrical power) is maximized.Keywords: model predictive control, pto, wec, mpc, wave energy, control

Over-reaction to the CALPERS focus list?

The California Public Employees Retirement System (CalPERS) has over $ 200 billion in assets. Over the years it has gained an activist reputation. The size of investment provides it with a strong voice and the incentive to incur monitoring costs. CalPERS nudges the management and the board to act in the best interest of the shareholders. CalPERS regularly examines its portfolio and seeks change in firms that can potentially perform better. Some firms heed to this attention while those that ignore the attention end up on the focus list. This study examines the reaction of the market to the publishing of the CalPERS focus list. On one hand, an investor could interpret this news positively: A large shareholder is actively pushing management and the board, to improve operations. In the remaining sections, the literature is reviewed, we present our results and the paper ends with a discussion

Quantum learning algorithms imply circuit lower bounds

We establish the first general connection between the design of quantum algorithms and circuit lower bounds. Specifically, let $\mathfrak{C}$ be a class of polynomial-size concepts, and suppose that $\mathfrak{C}$ can be PAC-learned with membership queries under the uniform distribution with error $1/2 - \gamma$ by a time $T$ quantum algorithm. We prove that if $\gamma^2 \cdot T \ll 2^n/n$, then $\mathsf{BQE} \nsubseteq \mathfrak{C}$, where $\mathsf{BQE} = \mathsf{BQTIME}[2^{O(n)}]$ is an exponential-time analogue of $\mathsf{BQP}$. This result is optimal in both $\gamma$ and $T$, since it is not hard to learn any class $\mathfrak{C}$ of functions in (classical) time $T = 2^n$ (with no error), or in quantum time $T = \mathsf{poly}(n)$ with error at most $1/2 - \Omega(2^{-n/2})$ via Fourier sampling. In other words, even a marginal improvement on these generic learning algorithms would lead to major consequences in complexity theory. Our proof builds on several works in learning theory, pseudorandomness, and computational complexity, and crucially, on a connection between non-trivial classical learning algorithms and circuit lower bounds established by Oliveira and Santhanam (CCC 2017). Extending their approach to quantum learning algorithms turns out to create significant challenges. To achieve that, we show among other results how pseudorandom generators imply learning-to-lower-bound connections in a generic fashion, construct the first conditional pseudorandom generator secure against uniform quantum computations, and extend the local list-decoding algorithm of Impagliazzo, Jaiswal, Kabanets and Wigderson (SICOMP 2010) to quantum circuits via a delicate analysis. We believe that these contributions are of independent interest and might find other applications

A NEW ENHANCED GOAT ALGORITHM FOR FINDING OPTIMUM SWITCHING ANGLE AND HARMONIC REDUCTION

Abstract:-Multi level inverters are used now a days at large,because they have lesser harmonics  than single level inverter. Several methodologies  have been worked out  in order  to reduce the harmonics.It has been proved that  the soft computing algorithms based switching angle calculation are more efficient than the conventional methods.In this paper  a 7 level inverter has been used  for DC to AC conversion.A new nature inspired Goat algorithm has been proposed  in this paper.This algorithm has been applied  for  a single phase  seven level inverter first. This algorithm has been tested by writing proper code  in MATLAB-Mfile and it has been found that it consumes  less computational time than the other  algorithms since several goats explore solution space at a time. The results show  that the  harmonics obtained from inverter using the switching angles calculated from the algorithm are very much reduced and THD  is almost around 12%.Key Words-7 level inverter, Goat algorithm, Switching angle ,Total harmonic distortio

Performance Analysis of Thermal Image Processing-Based Photovoltaic Fault Detection and PV Array Reconfiguration—A Detailed Experimentation

Due to the flexibility, sustainability, affordability, and ease of installation of solar photovoltaic systems, their use has significantly increased over the past two decades. The performance of a solar PV system can be constrained by a variety of external conditions, including hotspots, partial shade, and other minor faults. This causes the PV system to permanently fail and power losses. The power output in a partially shaded solar system is improved in this work by the introduction of a fault classifier based on thermal image analysis with a reconfiguration algorithm. For that purpose, the entire PV array is divided into two parts, with one of these being the male part and the other being the female part. MOSFET switches are used to build the switching matrix circuit that connects these parts. The Flir T420bx thermal camera captures thermal pictures, and MATLAB/Simulink® is used to extract the image properties. The pairing reconfiguration pattern is found using an algorithm based on image processing and the image attributes. The switching signals to the switching circuit are triggered by an Arduino controller. The image attributes of the thermal images may also be used to categorize PV system defects. This reconfiguration technique is easy, simple to use, and it can also be used to check the health of each PV module. The performance of the proposed work was validated using a 5 kW PV system with a 4 × 5 TCT array configuration at Sethu Institute of Technology’s renewable energy lab in India. The proposed method was simulated using the MATLAB-Simulink software program, and the outcomes were verified on different hardware setups.publishedVersio

Multidimensional Poverty and Child Survival in India

Background: Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results: The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the nonpoor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion: Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge t