Machine Learning
Mental health greatly affects the quality of life. The ability to detect and classify multiple levels of stress is therefore imperative. The aim of this work is to develop machine learning models for detection and multiple level classification of stress through ECG and EEG signals for both unspecified and specified genders. The models for the detection of stress from ECG are developed for real-world use, while the models based on ECG and EEG for the detection and multiple level classification of stress are devised towards clinical use.
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2502 Views
We manually analyze 730 concurrency bug reports from four open source projects and summarize 97 linguistic patterns. These linguistic patterns describe the common properties of concurrency bug reports. We then design a tool, called CTagger, which can be configured to integrate the linguistic patterns in different ways to classify concurrency bug reports. We evaluate CTagger on 7,280 bug reports from Github and Jira.
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107 Views
The cold start problem is a significant challenge in recommendation systems. Traditional methods are ineffective when the amount of interaction data is small. Further, as meta-learning has achieved increasingly remarkablesuccess in few-shot classification, some studies in recent years has abstracted cold-start recommendations into few-shot problems and applied meta-learning-based approaches, but mostly, simple transplants of generic approaches have been adopted.
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62 Views
Chinese electric power audit text dataset
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45 Views
The evolution of the Industrial Internet of Things (IIoT) introduces several benefits, such as real-time monitoring, pervasive control and self-healing. However, despite the valuable services, security and privacy issues still remain given the presence of legacy and insecure communication protocols like IEC 60870-5-104. IEC 60870-5-104 is an industrial protocol widely applied in critical infrastructures, such as the smart electrical grid and industrial healthcare systems.
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7806 Views
Nowadays, more and more machine learning models have emerged in the field of sleep staging. However, they have not been widely used in practical situations, which may be due to the non-comprehensiveness of these models' clinical and subject background and the lack of persuasiveness and guarantee of generalization performance outside the given datasets. Meanwhile, polysomnogram (PSG), as the gold standard of sleep staging, is rather intrusive and expensive. In this paper, we propose a novel automatic sleep staging architecture calle
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192 Views
Due to the smaller size, low cost, and easy operational features, small unmanned aerial vehicles (SUAVs) have become more popular for various defense as well as civil applications. They can also give threat to national security if intentionally operated by any hostile actor(s). Since all the SUAV targets have a high degree of resemblances in their micro-Doppler (m-D) space, their accurate detection/classification can be highly guaranteed by the appropriate deep convolutional neural network (DCNN) architecture.
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6465 Views
In the view of national security, radar micro-Doppler (m-D) signatures-based recognition of suspicious human activities becomes significant. In connection to this, early detection and warning of terrorist activities at the country borders, protected/secured/guarded places and civilian violent protests is mandatory.
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6419 Views
This dataset containg EMG data recorded with a sample rate of 1kHz. Data was collected from the brachioradialis, flexor carpi ulnaris and common extensor digitorum muscles.
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538 Views
The biographies_EN dataset contains 1000 biographies of literature writers retrieved from the english version of Wikipedia.
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102 Views