Three main steps are involved in the proposed framework for classifying glioma brain tumors. The detailed proposed framework is presented in Fig. 1. At first, a preprocessing stage is employed to ensure consistency and quality of images….
Category: 7. Maths
-
Ensemble of deep learning and IoT technologies for improved safety in smart indoor activity monitoring for visually impaired individuals
This manuscript develops a novel EDLES-SIAM technique for visually impaired people. The method is primarily designed to enhance indoor activity monitoring, ensuring the safety of visually impaired people in IoT technologies. It comprises…
Continue Reading
-
Action unit based micro-expression recognition framework for driver emotional state detection
The research presented in this manuscript utilized established and annotated datasets that are publicly available for research purposes. The involvement of human subjects was limited to the recording of facial muscle movements corresponding to…
Continue Reading
-
A data-driven approach to prioritize MITRE ATT&CK techniques for active directory adversary emulation
This section provides a review of the academic and industry literature pertinent to the core components of this research: adversary emulation, Active Directory (AD) security, the role of threat intelligence, and the application of Multi-Criteria…
Continue Reading
-
A fully annotated pathology slide dataset for early gastric cancer and precancerous lesions
Data quality assessment
To comprehensively assess the quality of all slides in the dataset, we employed GrandQC39, a recently proposed state-of-the-art quality control tool for digital pathology. This tool enables high-precision artifact detection…
Continue Reading
-
ProWaste for proactive urban waste management using IoT and machine learning
Wire, B. Smart waste management systems global market report 2022: Growing volume of e-waste driving adoption worldwide—https://www.researchandmarkets.com/ (2022).
Silva, B. N., Khan, M. & Han, K. Towards sustainable smart cities: A review of…
Continue Reading
-
Predictive modeling of oil rate for wells under gas lift using machine learning
Ensemble learning
The proposed method employs an advanced ensemble learning framework, which merges the predictions of multiple, diverse machine learning algorithms to achieve improved predictive performance and model robustness. Ensemble learning…
Continue Reading
-
A text mining-based approach for comprehensive understanding of Chinese railway operational equipment failure reports
The overarching architecture of the model
In this study, the text sequences are preprocessed for NER using the BERT model. Rich features at the word level, encompassing syntax and semantics, are extracted from the sequences and subsequently…
Continue Reading
-
Salvador Urban Network Transportation (SUNT): A Landmark Spatiotemporal Dataset for Public Transportation
This section describes the steps taken to create the SUNT dataset. First, we present in detail the data collected from four distinct public transportation sources. We then explain the use of the Trip Chaining approach to integrate these data…
Continue Reading
-
A hybrid deep learning model for sentiment analysis of COVID-19 tweets with class balancing
The proposed methodology for sentiment analysis of COVID-19 tweets follows a structured pipeline encompassing preprocessing, data balancing, feature extraction, model training, and performance evaluation, as illustrated in Fig. 1. Initially, raw…
Continue Reading