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Keyword: ANOVAA prediction of Cutting Force, System Vibration, and Productivity in Five-Axis Milling Process of the Spiral Bevel Gear
In this study, Taguchi method and ANOVA that are applied to determine the influence of several input parametrs on cutting force amplitude (F), vibration acceleration amplitude (a), and machining productivity (P) in the five-axis finish milling process of the spiral bevel gear. Taguchi orthogonal L27 array is used to design the experimental matrix with 27…
Read MoreVariation Between DDC and SCAMSMA for Clustering of Wireless MultipathWaves in Indoor and Semi-Urban Channel Scenarios
The performance of Simultaneous Clustering and Model Selection Matrix Affinity (SCAMSMA) and Deep Divergence-Based Clustering (DDC) in clustering wireless mul- tipaths generated by COST 2100 channel model (C2CM) is compared. Enhancing the accuracy of clustering multipaths is an open area of research which the clustering ap- proaches try to improve. Jaccard index is used as…
Read MoreUser’s Demographic Characteristic on the Evaluation of Gamification Interactive Typing for Primary School Visually Impaired with System Usability Scale
This paper extends the gamification interactive typing for Primary School Visually Impaired in Indonesia with some development according to previous user’s feedback. This study focuses in to renew the application and evaluate the updated application for visually impaired children developed by utility Unity software. Besides, standards of good gamification are worthy of study and can…
Read MoreStudent’s Belief Detection and Segmentation for Real-Time: A Case Study of Indian University
This paper has explored the technology beliefs of university students considering four parameters. We have proposed an automatic belief identification system for academic institutions. For this, we used two different clustering algorithms to segment the student group with different beliefs about the technology. In the Hierarchical Clustering (HC), the Agglomerative approach was followed. The beliefs…
Read MoreThe Sound of Trust: Towards Modelling Computational Trust using Voice-only Cues at Zero-Acquaintance
Trust is essential in many interdependent human relationships. Trustworthiness is measured via the effectiveness of the relationships involving human perception. The decision to trust others is often made quickly (even at zero acquaintance). Previous research has shown the significance of voice in perceived trustworthiness. However, the listeners’ characteristics were not considered. A system has yet…
Read MoreDesigning Experiments: 3 Level Full Factorial Design and Variation of Processing Parameters Methods for Polymer Colors
In this work, we investigate the effects of variation of processing parameters on the quality of dispersion of polycarbonate compound. In order to achieve appropriate pigments dispersion, we performed compounding process parameters optimizations, by investigating three processing parameters, temperature, screw speed, and feed rate. We utilized experimental design for the optimization of process parameters based…
Read MorePredicting Smoking Status Using Machine Learning Algorithms and Statistical Analysis
Smoking has been proven to negatively affect health in a multitude of ways. As of 2009, smoking has been considered the leading cause of preventable morbidity and mortality in the United States, continuing to plague the country’s overall health. This study aims to investigate the viability and effectiveness of some machine learning algorithms for predicting…
Read MoreSelf-Organizing Map based Feature Learning in Bio-Signal Processing
Feature extraction is playing a significant role in bio-signal processing. Feature identification and selection has two approaches. The standard method is engineering handcraft which is based on user experience and application area. While the other approach is feature learning that based on making the system identify and select the best features suit the application. The…
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