Smart and micro grid model for renewable energy based power system

The current energy crisis has fueled research in renewable energy. It is well known that renewable sources of energy would help in alleviating our dependence on perishable energy sources. A transmission and distribution network that could efficiently deliver the power generated from renewable energy to the load would further liberalize the world from fossil fuels. Full potential of renewable energy sources can be exploited by a smart grid, leading to a completely sustainable electricity supply system. The main objective of this paper is to emphasize the importance of smart gird and micro grid model for power systems connected with renewable energy resources

Fifty Years of College Choice: Social, Political and Institutional Influences on the Decision-Making Process

Explores how the process of choosing colleges has evolved for high school students during the second half of the twentieth century, the factors behind the changes, and the implications of recent developments for postsecondary equity, access, and success

Unified Explanations in Machine Learning Models: A Perturbation Approach

A high-velocity paradigm shift towards Explainable Artificial Intelligence (XAI) has emerged in recent years. Highly complex Machine Learning (ML) models have flourished in many tasks of intelligence, and the questions have started to shift away from traditional metrics of validity towards something deeper: What is this model telling me about my data, and how is it arriving at these conclusions? Previous work has uncovered predictive models generating explanations contrasting domain experts, or excessively exploiting bias in data that renders a model useless in highly-regulated settings. These inconsistencies between XAI and modeling techniques can have the undesirable effect of casting doubt upon the efficacy of these explainability approaches. To address these problems, we propose a systematic, perturbation-based analysis against a popular, model-agnostic method in XAI, SHapley Additive exPlanations (Shap). We devise algorithms to generate relative feature importance in settings of dynamic inference amongst a suite of popular machine learning and deep learning methods, and metrics that allow us to quantify how well explanations generated under the static case hold. We propose a taxonomy for feature importance methodology, measure alignment, and observe quantifiable similarity amongst explanation models across several datasets

Function2Gene: A gene selection tool to increase the power of genetic association studies by utilizing public databases and expert knowledge

<p>Abstract</p> <p>Background</p> <p>Many common disorders have multiple genetic components which convey increased susceptibility. SNPs have been used to identify genetic components which are associated with a disease. Unfortunately, many studies using these methods suffer from low reproducibility due to lack of power.</p> <p>Results</p> <p>We present a set of programs which implement a novel method for searching for disease-associated genes using prior information to select and order genes from publicly available databases by their prior likelihood of association with the disease. These programs were used in a published study of childhood-onset SLE which yielded novel associations with modest sample size.</p> <p>Conclusion</p> <p>Using prior information to decrease the size of the problem space to an amount commensurate with available samples and resources while maintaining appropriate power enables researchers to increase their likelihood of discovering reproducible associations.</p

What Matters in Student Loan Default: A Review of the Research Literature

Federal higher education policy has shifted over the past few decades from grants to lloans as the primary means for providing access to postsecondary education for low and moderate-income families. With this shift, policy makers have begun tracking student loan default rates as a key indicator of the efficacy of student loan programs. This effort requires a closer examination of how to define default and what default signifies: What is an acceptable rate of default? What factors contribute to default? Should default rates be used as indicators of institutional quality or loan program efficacy? These questions lead to further investigation of factors influencing default, such as whether default is a function of the characteristics of students or of the institutions they attend, and whether the types of loans borrowed influence the probabilities of default. To help answer these and related questions, this study reviewed the literature of research on student loan default conducted between 1978 and 2007, and identified 41 of the higher quality studies, the findings of which are summarized here

Mobile Working Students: A Delicate Balance of College, Family, and Work

Increasingly, education policymakers are turning attention to the access and persistence of the new college majority,-a group that may be described as mobile working students (Ewell, Schild, & Paulson, 2003). Traditionally, much research on college students has focused on students who graduate from high school and move on to attend a four-year college on a full-time basis, graduating in four to six years. However, as Adelman (2006) and others show, even among traditional-age college students this pattern of linear enrollment is less and less common. Thus, as Kasworm (chapter 2) also argues, metaphors such as the education pipeline no longer fit. Instead, students are more accurately represented as moving along pathways or even swirling toward postsecondary success. The experience of the mobile working student as conceived in this chapter encompasses multiple aspects of mobility and the varied, nonlinear, and evolving patterns of college going increasingly characteristic of students nationwide. One aspect of mobility in this complex and emerging picture centers on students\u27 experiences at commuter institutions, moving onto and off of campuses. In addition, students enroll in multiple institutions, moving between them. Finally, because they move into and out of institutions as well, the concomitant issues of attrition, stop-out, and degree attainment are also important to this project.https://ecommons.udayton.edu/books/1048/thumbnail.jp

Don Morrison Correspondence

Entries include a typed letter on personal stationery and correspondence from the Maine State Library

Institutional Merit-Based Aid and Student Departure: A Longitudinal Analysis

The use of merit criteria in awarding institutional aid has grown considerably and, some argue, is supplanting need as the central factor in awarding aid. Concurrently, the accountability movement in higher education has placed greater emphasis on retention and graduation as indicators of institutional success and quality. In this context, this study explores the relationship between institutional merit aid and student departure from a statewide system of higher education. We found that, once we account for self-selection to the extent possible, there was no significant relationship. By contrast, need-based aid was consistently related to decreased odds of departure

Review of Idealized Aircraft Wake Vortex Models

Properties of three aircraft wake vortex models, Lamb-Oseen, Burnham-Hallock, and Proctor are reviewed. These idealized models are often used to initialize the aircraft wake vortex pair in large eddy simulations and in wake encounter hazard models, as well as to define matched filters for processing lidar observations of aircraft wake vortices. Basic parameters for each vortex model, such as peak tangential velocity and circulation strength as a function of vortex core radius size, are examined. The models are also compared using different vortex characterizations, such as the vorticity magnitude. Results of Euler and large eddy simulations are presented. The application of vortex models in the postprocessing of lidar observations is discussed