Machine Learning
We developed a unique and valuable dataset specifically for advancing Brain-Computer Interface (BCI) systems by recording brain activity from a dedicated volunteer. The participant was asked to pronounce 100 carefully selected Malayalam words, along with their English translations, which were chosen for their relevance to astronauts during human space missions. The volunteer pronounced these words both vocally and subvocally, each word being repeated 50 times. Non-invasive Electroencephalography (EEG) sensors were employed to capture the brain activity associated with these tasks.
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635 Views
This study used a benchmark dataset, applying different embedding like LASER and FastText to capture contextual information, which was combined to create a new hybrid embedding. This hybrid embedding was fed to machine-learning (ML) and deep learning (DL) classifiers.
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281 Views
As the world increasingly becomes more interconnected, the demand for safety and security is ever-increasing, particularly for industrial networks. This has prompted numerous researchers to investigate different methodologies and techniques suitable for intrusion detection systems (IDS) requirements. Over the years, many studies have proposed various solutions in this regard, including signature-based and machine learning (ML)-based systems. More recently, researchers are considering deep learning (DL)-based anomaly detection approaches.
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224 Views
Smart grid, an application of Internet of Things (IoT) is modern power grid that encompasses power and communication network from generation to utilization. Home Area Network (HAN), Field or Neighborhood Area Network (FAN/NAN) and Wide Area network (NAN) using Wireless LAN and Wireless/Wired WAN protocols are employed from generation to utilization . Advanced Metering Infrastructure, a utilization side infrastructure facilitates communication between smart meters and the server where energy efficient protocols are mandate to support smart grid .
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351 Views
This dataset consists of 737 documents from the BBC Sport website, corresponding to sports news articles in five topical areas from 2004-2005. The class labels are divided into five categories: athletics, cricket, football, rugby, and tennis. The datasets have been pre-processed using the Porter stemming algorithm, stop-word removal, and filtering out terms with low frequency (count < 3).
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181 Views
The dataset contains two types of articles fake and real News. This dataset was collected from realworld sources; the truthful articles were obtained by crawling articles from Reuters.com (News website). As for the fake news articles, they were collected from different sources. The fake news articles were collected from unreliable websites that were flagged by Politifact (a fact-checking organization in the USA) and Wikipedia. The dataset contains different types of articles on different topics, however, the majority of articles focus on political and World news topics.
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1166 Views
These are tight pedestrian masks for the thermal images present in the KAIST Multispectral pedestrian dataset, available at https://soonminhwang.github.io/rgbt-ped-detection/
Both the thermal images themselves as well as the original annotations are a part of the parent dataset. Using the annotation files provided by the authors, we develop the binary segmentation masks for the pedestrians, using the Segment Anything Model from Meta.
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460 Views
The fifteen publicly available datasets from the UCI Machine Learning Library are selected for experiments. The selected datasets has no missing values, therefore, normalization is applied solely to the original datasets. For nominal data, it has been discretized and compressed to the range of 0 to 1. Similarly, for continuous data that does not fall within the range of 0 to 1, normalization has been applied.
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31 Views
Recently, combinatorial interaction strategies have a large spectrum as black box strategies for testing software and hardware. This paper discusses a novel adoption of a combinatorial interaction strategy to generate a sparse combinatorial data table (SCDT) for machine learning. Unlike test data generation strategies, in which the t-way tuples synthesize into a test case, the proposed SCDT requires analyzing instances against their corresponding tuples to generate a systematic learning dataset.
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126 Views
Efficient and realistic tools capable of modeling radio signal propagation are an indispensable component for the effective operation of wireless communication networks. The advent of artificial intelligence (AI) has propelled the evolution of a new generation of signal modeling tools, leveraging deep learning (DL) models that learn to infer signal characteristics.
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1209 Views