*.csv

For the data acquisition we used JINS MEME smart glasses -- a device furnished with three-point EOG and six-axis inertial measurement unit (IMU) with an accelerometer and a gyroscope. The sampling frequency of the acquired signals is 100 Hz. The data are transmitted to a computer via Bluetooth or USB and can be exported to CSV file.

Data were acquired under real road conditions from 30 healthy subjects, including twenty experienced drivers and ten students attending a driving school. 16 males and 14 females with average age = 38 +-17 participated in the study.

The birth weight of a child is totally dependent on multiple factors related to mother. The factors may be clinical as well as socioeconomic. Healthcare centers keep records of so many parameters of mother right from conceive to five years age of baby. We create this dataset considering 17 important clinical features of mother like- Age(years), Height(cm), Bgroup, Parity, ANC, Iwt(kg), Fwt(kg), IBP_sys, IBP_dias, FBP_sys, FBP_dias, IHb(gm%), Fhb(gm%), BS(RBS), Term/Preterm, Sex, Bwt(kg) and 1 socioeconomic feature called SEC.

The dataset shows the decisions of the participants in a dictator game split into two rounds. The participants faced an android as their opponent. Round 1 represents their decision in the game after they met the android and listened to its introductory speech. Round 2 is their decision in the game after having an interactive conversation with the android.

The software engineering community is working to develop reliable metrics to improve software quality. It is estimated that understanding the source code accounts for 60% of the software maintenance effort. Cognitive informatics is important in quantifying the degree of difficulty or the efforts made by developers to understand the source code. Several empirical studies were conducted in 2003 to assign cognitive weights to each possible basic control structure of software, and these cognitive weights are used by several researchers to evaluate the cognitive complexity of software systems.

Industrial drying processes are an energy extensive and often one of the most time consuming processes in a manufacturing line. Optimizing the drying process can therefore lead to a reducing in energy consumption and an increase in manufacturing throughput.

In the last few years, several organizations have manifested their concern over the increase in use of Hateful Speech or Hate Speech for short, this concept refers to forms of expression or audio-visual content that encourage discrimination or violence against individuals or groups solely based on their gender, sexual orientation, ethnicity, religion or nationality.

The ReMouse dataset is collected in a guided environment, and it contains repeat sessions generated by the same human user(s). ReMouse dataset contains the mouse dynamics information of 100 users of mixed nationality, residing in diverse geographical regions and using different devices (hardware and software components).

This research has produced datasets that can be used openly for other researchers. The dataset is compiled from images of woven fabrics originating from the East Nusa Tenggara Province of Indonesia. A total of 68 fabrics from six districts have been grouped and gone through the image embedding process to become RAW numerical data for further processing. By using Logistic Regression, the classifier accuracy rate for this dataset is only 79.4%. For that other researchers can contribute to improve this accuracy.

This letter presents a random forest regression (RFR)-based adaptive power allocation (APA) scheme to predict an optimized power factor for user's fair access to data rate in a downlink mmWave non-orthogonal multiple access systems. Notably, the proposed APA scheme learns from the sum rates dataset associated with both distance and inverse pathloss (power factor optimization) models to predict optimized power factors with respect to average value approach.

The dataset contains two industrial cases with measurement devices installed at the medium voltage bus entrance and at the target load to be identified. It can be used for the research of non-invasive load monitoring algorithms. The types of data measured include three-phase voltage, current, active power, reactive power, as well as the amplitude and phase angle of each harmonic.