Titlebook: Computational Intelligence in Data Science; 6th IFIP TC 12 Inter Sarath Chandran K R,Sujaudeen N,Shahul Hamead H Conference proceedings 202

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Case Study Production Network Optimization,ing models whereas neglecting their interpretability. So, Clinicians find it difficult to interpret these complex models. In this study, to assist medical specialists with supporting diagnostic tools, we investigate how well a machine learning algorithm performs in developing an accurate FTD subtype

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,Analysis of?Cost-Sensitive Algorithms for?Degree of?Imbalancing,odel to penalize the misclassification errors according to the skewness of the data to reduce the learning bias of the model towards the majority class. we present empirical evaluations of the reference model over four popular datasets and analyse its behaviour using MAE and Kappa values.

隱士

FinTech: Deep Learning-Based Sentiment Classification of User Reviews from Various Bangladeshi Mobilected from the Google Play Store and classified as negative, neutral, or positive. The data model has been evaluated using CNN, LSTM, and BiLSTM algorithms. Compared to CNN and LSTM, the BiLSTM algorithm produced the best model with an accuracy of 97.07%.

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Cloud Based Remote File Access from PC to Mobile Using File Directory,ir device. Security is provided in this file access method by a key issued by the NodeJS application, which uses the JSON Web Token (JWT) technique for confirmation of the user. Result of the developed work is compared with file sharing services provided by Google drive, Gmail and others, and the pr

Resection

Stock Trade Recommendations Using Knowledge Graph,ch, we conduct experiments on a real-time stock market dataset. We compare the performance of our approach to a baseline system that uses only traditional machine learning techniques. Our results show that our KG approach outperforms the baseline system in terms of accuracy, and profitability. We fo

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Understanding the Determinants of Adoption of Healthcare Information Technology,tween the respondents’ Perceived Expectation (PE), Effort Expectation (EE), Technology Trust (TR), and Technology Awareness (TA) and the rate at which Online Pharmacy was adopted in Oman.We also discovered a moderating effect of BI on the decision to use an online pharmacy (OPA). Health literacy, co

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,Frontotemporal Dementia Detection Model Based on?Explainable Machine Learning Approach,ing models whereas neglecting their interpretability. So, Clinicians find it difficult to interpret these complex models. In this study, to assist medical specialists with supporting diagnostic tools, we investigate how well a machine learning algorithm performs in developing an accurate FTD subtype

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Smart Driving Alert System Using MT CNN,l Landmark algorithm is used here to get the facial feature points. Here we are obtaining feature points like left and right eyes, left and right ear, mouth. The alert sound and hardware kit alerts the drowsy driver according to the behavioural state of the driver which was analyzed from the captured video.