39 research outputs found
Pseudo-Boolean Programming for Bivalent Optimization
Get PDFTitle: Pseudo-Boolean Programming for Bivalent Optimization, Author: M. Natesan, Location: ThodeThis thesis introduces an effective computational algorithm making
use of Boolean algebra for solving bivalent optimization problems with
linear and nonlinear constraints. This method is a combination of the
algorithm suggested by Hammer and the branch and bound method. The whole
system of constraints is replaced by a single Boolean resolvent function
and the solutions of this resolvent are found by branch and bound method
which are found to be the feasible solutions of the system of constraints.
Some practical applications are also discussed.ThesisMaster of Engineering (ME
A finite element superconvergence approximations for singularly perturbed system of convection-diffusion problems
No full text
Advanced Robotic System with Keypoint Extraction and YOLOv5 Object Detection Algorithm for Precise Livestock Monitoring
No full textMolting is an essential operation in the life of every lobster, and observing this process will help us to assist lobsters in their recovery. However, traditional observation consumes a significant amount of time and labor. This study aims to develop an autonomous AI-based robot monitoring system to detect molt. In this study, we used an optimized Yolov5s algorithm and DeepLabCut tool to analyze and detect all six molting phases such as S1 (normal), S2 (stress), S3–S5 (molt), and S6 (exoskeleton). We constructed the proposed optimized Yolov5s algorithm to analyze the frequency of posture change between S1 (normal) and S2 (stress). During this stage, if the lobster stays stressed for 80% of the past 6 h, the system will assign the keypoint from the DeepLabCut tool to the lobster hip. The process primarily concentrates on the S3–S5 stage to identify the variation in the hatching spot. At the end of this process, the system will re-import the optimized Yolov5s to detect the presence of an independent shell, S6, inside the tank. The optimized Yolov5s embedded a Convolutional Block Attention Module into the backbone network to improve the feature extraction capability of the model, which has been evaluated by evaluation metrics, comparison studies, and IoU comparisons between Yolo’s to understand the network’s performance. Additionally, we conducted experiments to measure the accuracy of the DeepLabCut Tool’s detections
Relation between composition, microstructure and oxidation in iron aluminides
Get PDFThe relation between chemical composition, microstructure and oxidation properties has been investigated on various FeAl based alloys, the aim being to induce changes in the microstructure of the compound by selective oxidation of aluminium. Oxidation kinetics that was evaluated on bulk specimens showed that, due to fast diffusion in the alloys, no composition gradient is formed during the aluminium selective oxidation. Accordingly, significant aluminium depletion in the compound could be observed in the thinnest part of oxidised wedge-shape specimens. Another way to obtain samples of variable aluminium content was to prepare diffusion couples with one aluminide and pure iron as end members. These latter specimens have been characterised using electron microscopy and first results of oxidation experiments are presented
Erring Modernization : The Dilemma Of Developing Societies.
Get PDFThe old and the vanquished does not immediately descend into the grave. The resistance and' longevity of that which is at the point of vanishing are based on the instinct of 'self-preservation inherent to all that exists
Design and Analysis of a Radial Active Magnetic Bearing for Vibration Control
No full textAbstractVibration caused by rotor unbalance is one of the most pertinent problems facing the rotating machines, including electrical motors and turbo machinery among others. Thus vibration attenuation has become very essential in improving the overall performance of such machines. In this paper, a 12-pole radial Active Magnetic Bearing (AMB), using AC excitation has been proposed to counteract the unbalance. Here a switching variation of AMB teeth excitation currents is implemented to generate a rotating force, synchronous with the rotor unbalance but in opposite direction
Accurate models vs. accurate estimates: A simulation study of Bayesian single-case experimental designs
Get PDFOpen practices statement: Software codes used to generate the data and evaluate the models are available, and preregistration is not applicable.Copyright © The Author(s) 2021. Although statistical practices to evaluate intervention effects in single-case experimental design (SCEDs) have gained prominence in recent times, models are yet to incorporate and investigate all their analytic complexities. Most of these statistical models incorporate slopes and autocorrelations, both of which contribute to trend in the data. The question that arises is whether in SCED data that show trend, there is indeterminacy between estimating slope and autocorrelation, because both contribute to trend, and the data have a limited number of observations. Using Monte Carlo simulation, we compared the performance of four Bayesian change-point models: (a) intercepts only (IO), (b) slopes but no autocorrelations (SI), (c) autocorrelations but no slopes (NS), and (d) both autocorrelations and slopes (SA). Weakly informative priors were used to remain agnostic about the parameters. Coverage rates showed that for the SA model, either the slope effect size or the autocorrelation credible interval almost always erroneously contained 0, and the type II errors were prohibitively large. Considering the 0-coverage and coverage rates of slope effect size, intercept effect size, mean relative bias, and second-phase intercept relative bias, the SI model outperformed all other models. Therefore, it is recommended that researchers favor the SI model over the other three models. Research studies that develop slope effect sizes for SCEDs should consider the performance of the statistic by taking into account coverage and 0-coverage rates. These helped uncover patterns that were not realized in other simulation studies. We underline the need for investigating the use of informative priors in SCEDs
Explainable Cross-Topic Stance Detection for Search Results
Get PDFOne way to help users navigate debated topics online is to apply stance detection in web search. Automatically identifying whether search results are against, neutral, or in favor could facilitate diversification efforts and support interventions that aim to mitigate cognitive biases. To be truly useful in this context, however, stance detection models not only need to make accurate (cross-topic) predictions but also be sufficiently explainable to users when applied to search results - an issue that is currently unclear. This paper presents a study into the feasibility of using current stance detection approaches to assist users in their web search on debated topics. We train and evaluate 10 stance detection models using a stance-annotated data set of 1204 search results. In a preregistered user study (N = 291), we then investigate the quality of stance detection explanations created using different explainability methods and explanation visualization techniques. The models we implement predict stances of search results across topics with satisfying quality (i.e., similar to the state-of-the-art for other data types). However, our results reveal stark differences in explanation quality (i.e., as measured by users' ability to simulate model predictions and their attitudes towards the explanations) between different models and explainability methods. A qualitative analysis of textual user feedback further reveals potential application areas, user concerns, and improvement suggestions for such explanations. Our findings have important implications for the development of user-centered solutions surrounding web search on debated topics. Web Information System
Visualizing Bibliometric Networks on Green Advertising Literature: What we know and what we do not know
No full textThis article aims to perform a bibliometric analysis of the extant research in the area of green advertising to identify the dominant themes and research gaps in the said area. For the purpose of the study, 220 articles were sourced from the Scopus database after running a search query using designated keywords. This study examines the literature on green advertising over the last few years and reviews the published documents using VOSviewer software. While shortlisting the research articles, open-access articles, conference papers, and papers written in other languages were discarded. The study shows the key research trends in the area of green advertising, in terms of parameters like co-author analysis, keyword analysis, country analysis, and organizational analysis. Journal of Advertising, International Journal of Advertising and Sustainability are the leading journals publishing papers in the area of green advertising. China, the United States, and Korea play a major role in research on this topic, with the highest number of corresponding authors coming from these three countries. The findings provide useful insights to academicians in terms of directions for further research that needs to be done
