Computational Intelligence

Gestational diabetes is a type of high blood sugar that develops during pregnancy. It can occur at any stage of pregnancy and cause problems for both the mother and the baby, during and after birth. The risks can be reduced if they are early detected and managed, especially in areas where only periodic tests of pregnant women are available. Intelligent systems designed by machine learning algorithms are remodelling all fields of our lives, including the healthcare system. This study proposes a combined prediction model to diagnose gestational diabetes.

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Software engineering metrics collected via SourceMeter for open-source Java repositories.

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5 Views

Ear biting is a welfare challenge in commercial pig farming. Pigs sustain injuries at the site of bite paving the way for bacterial infections. Early detection and management of this behaviour is important to enhance animal health and welfare, increase productivity whilst minimising inputs from medication. Pig management using physical observation is not practical due to the scale of modern pig production systems. The same applies to the manual analysis of captured videos from pig houses. Therefore, a method of automated detection is desirable.

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50 Views

In this study, we present advances on the development of proactive control for online individual user adaptation in a welfare robot guidance scenario, with the integration of three main modules: navigation control, visual human detection, and temporal error correlation-based neural learning. The proposed control approach can drive a mobile robot to autonomously navigate in relevant indoor environments. At the same time, it can predict human walking speed based on visual information without prior knowledge of personality and preferences (i.e., walking speed).

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92 Views

This Dataset is related to the data prices of the cryptocurrency "Ethereum" over four years, from 01/01/2018 to 11/22/2022. Also, the new dataset created by the predictions of the intelligent filtered LSTM model is included.

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132 Views

PROTEIN STRUCTURE AND SYNTHETIC MULTI-VIEW CLUSTERING DATASETS

Multi-View Clustering (MVC) datasets used in the following paper:

Evolutionary Multi-objective Clustering Over Multiple Conflicting Data Views. Authors: Mario Garza-Fabre, Julia Handl, and Adán José-García. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION. Accepted for publication, November 2022.

This entry contains all 420 datasets used in the paper, including:

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74 Views

A real-world radio frequency (RF) fingerprinting dataset for commercial off-the-shelf (COTS) Bluetooth and WiFi emitters under challenging testbed setups is presented in this dataset. The chipsets within the devices (2 laptops and 8 commercial chips) are WiFi-Bluetooth combo transceivers. The emissions are captured with a National Instruments Ettus USRP X300 radio outfitted with a UBX160 daughterboard and a VERT2450 antenna. The receiver is tuned to record a 66.67 MHz bandwidth of the spectrum centered at the 2.414 GHz frequency.

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316 Views

The data collection includes posts from social media networks popular among Russian-speaking people. The information was gathered using pre-defined keywords ("war," "special military operation," and so on) and is mainly relevant to Ukraine's continuing conflict with Russia. Following a thorough assessment and analysis of the data, propaganda and false news were detected. The information gathered has been anonymized. Feature engineering and text preparation can extract new insights and information from this data source.

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358 Views

To determine the effectiveness of any defense mechanism, there is a need for comprehensive real-time network data that solely references various attack scenarios based on older software versions or unprotected ports, and so on. This presented dataset has entire network data at the time of several cyber attacks to enable experimentation on challenges based on implementing defense mechanisms on a larger scale. For collecting the data, we captured the network traffic of configured virtual machines using Wireshark and tcpdump.

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571 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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537 Views

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