Statistical and Electrical Features Evaluation for Electrical Appliances Energy Disaggregation

In this paper we evaluate several well-known and widely used machine learning algorithms for regression in the energy disaggregation task. Specifically, the Non-Intrusive Load Monitoring approach was considered and the K-Nearest-Neighbours, Support Vector Machines, Deep Neural Networks and Random Forest algorithms were evaluated across five datasets using seven different sets of statistical and electrical features. The experimental results demonstrated the importance of selecting both appropriate features and regression algorithms. Analysis on device level showed that linear devices can be disaggregated using statistical features, while for non-linear devices the use of electrical features significantly improves the disaggregation accuracy, as non-linear appliances have non-sinusoidal current draw and thus cannot be well parametrized only by their active power consumption. The best performance in terms of energy disaggregation accuracy was achieved by the Random Forest regression algorithm.Peer reviewedFinal Published versio

Disability and American Education

Disability and American Education is a 2 credit, in-person, undergraduate course offered at a public liberal arts university. It is designed to introduce students to issues related to disability in the context of American schools, both P-12 and post-secondary. In addition to introducing students to classroom practice, the course focuses on important theory in Disability Studies and the social and political history that has led to our systems of special education

The Value of Conflict and Disagreement in Democratic Teacher Education

Deliberative democracy surfaces disagreements so that people holding conflicting stances understand each other’s reasons for the purpose of decision-making. Democratic education approaches should provide students with the opportunity to learn and practice how to address conflict in the collective decision-making process. In this paper, I examine the Foxfire Course for Teachers, a professional development retreat in which teachers learn to practice democratic teaching by themselves experiencing democratic decision-making. In particular, a series of disagreements among course participants is analyzed in detail to understand the learning that resulted and the conditions that supported that learning. As a result of this experiential learning opportunity, teachers came to realize the importance of allowing students to experience and reason through disagreement although it may cause discomfort. Teachers also came to view democratic participation as a developmental process that requires practice

Report on the Djibouti Refugee Situation

In 1982-83 as a result of a tripartite agreement between the governments of Djibouti and Ethiopiaand the UNHCR, the implementation of a repatriation programme was begun

Understanding the Electoral Participation Gap: A Study of Racialized Minorities in Canada

Racialized minorities constitute an increasingly substantial segment of modern electorates in Western democracies, in part driven by immigration. Analyzing data from the 2021 Canadian Election Study (N = 9,496) and yearly Democracy Checkup surveys between 2020 and 2023 (N = 26,908), we explore the significance of racial identity as a determinant of voter turnout. Our findings reveal stark disparities in electoral participation between the most racialized minority groups in Canada and the White majority. Except for Latino identifiers, Indigenous, Asian, Black, and Arab-identifying respondents all exhibit lower voting rates, with Black voters facing the most significant gap, nearly 16 percentage points below their White counterparts. The gap is particularly prominent among second-generation racialized Canadians, suggesting that newcomers to Canada exhibit relatively high levels of engagement compared to their children. Next, we explore three key individual factors that may contribute to the gap: differences in socioeconomics, psychological engagement, and mobilization and community embeddedness. We employ a linear decomposition technique to assess the contributions of these factors to the majority–minority participation gap. Our analysis underscores the potency of socio-economic and psychological models in explaining minority under-participation in the Canadian context. The mobilization and community embeddedness model, however, exhibits weak explanatory power. Despite these insights, a substantial portion of the participation differentials remains unexplained, suggesting the necessity for novel perspectives to understand gaps in the electoral participation of racialized electors