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A Comparative Analysis of Machine Learning Based Power Flow Study with Custom Made Open Source Python Codes
Full text linkPower flow analysis is a cornerstone of power system planning and operation, involving the solution of nonlinear equations to determine the steady-state operating conditions of the power grid. Traditionally, these equations are solved using iterative methods, which, despite their accuracy, are computationally intensive, may not converge to the solution and involve high time and space complexity. The challenges above can be overcome using Machine Learning (ML). Consequently, in this paper, a comprehensive comparative analysis of different ML algorithms developed for solving the power flow equations are presented. Experimental simulations for IEEE 3-bus and IEEE 118-bus networks have been conducted using custom-developed, open-source Python codes and technical insights are highlighted
'It’s like a shadow on my shoulder'. Exploring the experiences of eating disorders in later life women.
Full text linkReflexivity & Reflection (R&R) for Sociotechnical Safety:Creating a Space for Collective Learning
Full text linkResearchers in CSCW have long examined the sociotechnical aspects of digital security, privacy, and safety, building knowledge not only on the security challenges faced by (at-risk) communities, but also on the challenges of conducting responsible research. The burgeoning subfield of “sociotechnical safety" within computer security & privacy (S&P) has grown alongside this work, including topics like the S&P of at-risk users. These two research fields are distinct in epistemological and methodological approaches, but share a common goal: improving the digital safety of (at-risk) populations. During this critical time, we see an opportunity to gather as one community, to encourage honest conversation about the “hows" and “whys" of sociotechnical safety research. We invite researchers in both fields to discuss how CSCW’s methods, norms, and theories might bridge this emergent community, e.g., building meaningful collaborations with participants, researcher/participant safety. To cultivate reflexivity and reflection (R&R), we will host a closed-door panel of experienced researchers to share learnings from their work before collaboratively developing artifacts outlining actions that researchers can take to address these challenges. By fostering a collective learning environment at CSCW, we will assist researchers across disciplines to conduct responsible sociotechnical safety research by prioritising reflexivity
Coupled seismic-magmatic systems driven by fault-guided magma accumulation and ascent in the North Anatolian Fault Zone, Turkey
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Reflexivity & Reflection (R&R) for Sociotechnical Safety:Creating a Space for Collective Learning
Full text linkResearchers in CSCW have long examined the sociotechnical aspects of digital security, privacy, and safety, building knowledge not only on the security challenges faced by (at-risk) communities, but also on the challenges of conducting responsible research. The burgeoning subfield of “sociotechnical safety" within computer security & privacy (S&P) has grown alongside this work, including topics like the S&P of at-risk users. These two research fields are distinct in epistemological and methodological approaches, but share a common goal: improving the digital safety of (at-risk) populations. During this critical time, we see an opportunity to gather as one community, to encourage honest conversation about the “hows" and “whys" of sociotechnical safety research. We invite researchers in both fields to discuss how CSCW’s methods, norms, and theories might bridge this emergent community, e.g., building meaningful collaborations with participants, researcher/participant safety. To cultivate reflexivity and reflection (R&R), we will host a closed-door panel of experienced researchers to share learnings from their work before collaboratively developing artifacts outlining actions that researchers can take to address these challenges. By fostering a collective learning environment at CSCW, we will assist researchers across disciplines to conduct responsible sociotechnical safety research by prioritising reflexivity
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