Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment

Security-constrained unit commitment (SCUC) is a computationally complex process utilized in power system day-ahead scheduling and market clearing. SCUC is run daily and requires state-of-the-art algorithms to speed up the process. The constraints and data associated with SCUC are both geographically and temporally correlated to ensure the reliability of the solution, which further increases the complexity. In this paper, an advanced machine learning (ML) model is used to study the patterns in power system historical data, which inherently considers both spatial and temporal (ST) correlations in constraints. The ST-correlated ML model is trained to understand spatial correlation by considering graph neural networks (GNN) whereas temporal sequences are studied using long short-term memory (LSTM) networks. The proposed approach is validated on several test systems namely, IEEE 24-Bus system, IEEE-73 Bus system, IEEE 118-Bus system, and synthetic South-Carolina (SC) 500-Bus system. Moreover, B-{\theta} and power transfer distribution factor (PTDF) based SCUC formulations were considered in this research. Simulation results demonstrate that the ST approach can effectively predict generator commitment schedule and classify critical and non-critical lines in the system which are utilized for model reduction of SCUC to obtain computational enhancement without loss in solution qualityComment: 8 Figures, 5 Tables, 1 Algorith

Acceptance Sampling Model for the Effects of Plasma Ghrelin using Fuzzy Exponential Distribution

In statistical quality control one of the most significant tools is the acceptance sampling plan. It plays an essential role in solving the problems involving the theory of probability distribution and fuzzy probability distribution. Ghrelin expression in the stomach and Ghrelin levels in plasma are increased after prolonged fasting and decreased in response to feeding. The results are reliable and we have shown that by means of acceptance sampling model using fuzzy exponential distribution, there is a considerable change of Ghrelin levels in plasma. Keywords: Acceptance Sampling, Fuzzy Exponential distribution, Ghrelin 2010 Mathematics Subject Classification: 62P10, 62DXX, 60A86

Machine Learning Assisted Approach for Security-Constrained Unit Commitment

Security-constrained unit commitment (SCUC) is solved for power system day-ahead generation scheduling, which is a large-scale mixed-integer linear programming problem and is very computationally intensive. Model reduction of SCUC may bring significant time savings. In this work, a novel approach is proposed to effectively utilize machine learning (ML) to reduce the problem size of SCUC. An ML model using logistic regression (LR) algorithm is proposed and trained with historical nodal demand profiles and the respective commitment schedules. The ML outputs are processed and analyzed to reduce variables and constraints in SCUC. The proposed approach is validated on several standard test systems including IEEE 24-bus system, IEEE 73-bus system, IEEE 118-bus system, synthetic South Carolina 500-bus system and Polish 2383-bus system. Simulation results demonstrate that the use of the prediction from the proposed LR model in SCUC model reduction can substantially reduce the computing time while maintaining solution quality.Comment: 6 Pages, 5 Figures, 3 tables, 1 algorith

Adoption of Collaboration Technologies: Integrating Technology Acceptance and Collaboration Technology Research

This paper integrates the technology acceptance model (TAM) with constructs from collaboration technology research to present a model of collaboration technology use. Specifically, constructs in four sets of characteristics—technology, individual and group, task, and situational—drawn from various media choice theories are presented as determinants of the TAM constructs of perceived usefulness, perceived ease of use, and attitude toward using collaboration technology. The model was tested among 349 short message service (SMS) users in Finland. The model was largely supported, with the most significant findings being the effects of the four technology characteristics—social presence, media richness, immediacy, and concurrency—on the TAM constructs. In addition to making an important contribution by integrating two of the more dominant streams of information systems research, the model presented here is focused on a specific class of technology—i.e., collaboration technology—and, therefore, answers recent calls for developing models that deepen our understanding about the technology artifact

OCT Findings in Myopic Traction Maculopathy

The prevalence of myopia is constantly on a rise. Patients with high myopia and pathological myopia can lose vision due to a number of degenerative changes occurring at the macula. With recent advances in imaging techniques such as spectral domain optical coherence tomography (OCT) and swept-source OCT, our understanding of macular pathology in myopia has improved significantly. New conditions such as myopic traction maculopathy have been identified and defined. Treatment approaches are now being planned on the basis of the pathoanatomy of myopic traction maculopathy on OCT. In this chapter, we discuss the role of OCT imaging in myopic traction maculopathy