Machine Learning
This dataset extracts the entropy of each of the PE sections of benign and ransomware reports to be used for detecting ransomware. Several machine learning classifiers were trained on this dataset such as Decision Tree, Random Forest, KNN, XGBoost and Naive Bayes. From the results, PE entropy can accurately detect ransomware with a decision tree classifier yielding the overall best result with a 98.8% accuracy and an AUC of 0.969. The latency with the prediction of the decision tree classifier was extremely quick with a result of 1.509 milliseconds.
- Categories:
279 Views
With the rapid development of high-speed trains (HSTs), safety and reliability in HSTs operation have attracted plenty of attention. The wheel, as one of the most crucial components, requires absolutely high reliability. The non-roundness wear is a typical failure mode of the HST wheel, which can have a detrimental influence on track and train components, leading to increased risks of rail breaks, sleeper cracking, high-cycle fatigue of wheels and axles, and bearing damage.
- Categories:
44 Views
Sensor arrays are ubiquitous. They capture images in digital cameras, record the swipes of our fingers on the screens of our phones and tablets, or map pressure distribution over an area. Soft capacitive sensor arrays have been proposed to make electronic pressure-sensing skins capable of identifying the location and intensity of touch. However, large arrays of those sensors remain challenging to produce, as they require high-resolution patterning of electrodes and routing of long and thin electrical connections.
- Categories:
161 Views
A non-speech dataset built by a nine-classification discrete emotion model can be used for emotion recognition. The nine emotion dimensions are happy, angry, fearful, sad, brave, favorite, neutral, and calm. Recognition is performed by extracting their 384-dimensional feature vectors, which contain F0 envelopes, short-time excess zero rates, twelve-dimensional Meier cepstral coefficients, etc., as well as their first-order low-pass data. A total of 2,337 data samples were available.
- Categories:
19 Views
This dataset contains the measurement in an ultrawide band (UWB) system in the 6.5 GHz band, considering the presence of the human body as the only obstacle. There are measurements in line-of-sight condition to compare the results of the analysis performed. The measurements are part of our research on the adverse effects of the body shadowing in pedestrian localization systems.
The UWB system has four fixed terminals and one mobile terminal. The mobile terminal is worn on the chest of the person.
- Categories:
190 Views
We introduce a high-performance computer vision based Intraveneous (IV) infusion speed measurement system as a camera application on an iPhone or Android phone. Our system uses You Only Look Once version 5 (YOLOv5) as it was designed for real-time object detection, making it substantially faster than two-stage algorithms such as R-CNN. In addition, YOLOv5 offers greater precision than its predecessors, making it more competitive with other object detection methods.
- Categories:
19 Views
Problems related to ventral hernia are very common, and evaluating them using computational methods can assist in selecting the most appropriate treatment. This study collected data from over 3500 patients from different European countries observed during last 11 years (2012-2022), which were collected by specialists in hernia surgery. The majority of patients underwent standard surgical procedures, with a growing trend towards robotic surgery. This paper focuses on statistically evaluating the treatment methods in relation to patient age, body mass index (BMI), and the type of repair.
- Categories:
232 Views
Indian Rice Disease dataset (IRDD) contains rice leaf images of two classes namely BrownSpot and Healthy. The images are taken under various lightning conditions. Some images contain dew drops on the leaves. The rice leaf images are gatherd from fields in West Bengal, India. These images have been taken using smartphone camera by the project team members of IIIT Kalyani and IIT Kharagpur. The images are annotated and verified by the domain experts. This datset is a part of the project entitled "AI for Agriculture and Food Sustainability" funded by MeitY, Govt of India.
- Categories:
333 Views
IMUs have gained popularity for tracking joint kinematics due to their portability and versatility. However, challenges such as limited accuracy, lack of real-time data analysis, and complex sensor-to-segment calibration procedures have hindered their widespread use. To address these limitations, we developed a portable system that integrates four IMUs to collect treadmill walking data, with ground truth values obtained from a Motion Capture System.
- Categories:
67 Views
This study presents a benchmark for evaluating action-constrained reinforcement learning (RL) algorithms. In action-constrained RL, each action taken by the learning system must comply with certain constraints. These constraints are crucial for ensuring the feasibility and safety of actions in real-world systems. We evaluate existing algorithms and their novel variants across multiple robotics control environments, encompassing multiple action constraint types.
- Categories:
90 Views