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The quartz crystal microbalance (QCM) sensor with asymmetric ring electrodes has received widespread attention for its uniform sensitivity distribution. At the same time, its 5-overtone mass sensitivity also greatly improves the fundamental frequency mass sensitivity. The 5-overtone quality (Q) factor is a technical indicator to measure the stable operation of the quartz crystal resonator with asymmetric ring electrodes in the fifth overtone mode. However, there are few papers to report the 5-overtone quality factor (Q5) of QCM sensor with asymmetric ring electrodes.

This dataset is related to the paper [3D CT Slice Image-Based Algorithm for Non-Wet Defect Inspection in Solder Joints]. 

Please refer to the following link: here

This dataset supports the numerical experiments conducted in the paper "Optimization of Energy-Constrained Computing Task Assignment and Resource Allocation Problem." It provides simulation data for the optimization of energy-constrained computing task assignment and resource allocation in end-edge-cloud collaborative systems.

Abstract—This study evaluates the long-term tectonic influence on landform development as well as the present-day tectonic activity in the Nanga Parbat-Haramosh Syntaxis (NPHS), a geologically complex region in the northwestern Himalayas. Using geomorphic indices and remote sensing techniques, including Interferometric Synthetic Aperture Radar (InSAR) and existing Global Positioning System (GPS) data, this research identifies significant neotectonic deformation, with active faults contributing to slope hazards and seismic risks.

Multimodal MR image synthesis aims to generate missing modality images by effectively fusing and mapping from a subset of available MRI modalities. Most existing methods adopt an image-to-image translation paradigm, treating multiple modalities as input channels. However, these approaches often yield sub-optimal results due to the inherent difficulty in achieving precise feature- or semantic-level alignment across modalities.

The STAV360 dataset is a subjective 360° video dataset.

In today’s digital ecosystem, verifying the authenticity of identity documents is essential for secure access control and digital trust. Sectors such as finance, education, government, and employment frequently rely on scanned or digital versions of documents like Aadhaar cards, PAN cards, Voter IDs, Driving Licenses, and Passports. However, this convenience introduces risks related to document forgery and fraudulent activity.

Dataset used in an IOP publication under review in the journal Physics in Medicine & Biology.

Automated inspection of textile surfaces is challenged by the scarcity and geometric intricacy of real defect samples, especially the elongated, sub-millimetre scratches critical for quality grading. Existing generative approaches often prioritize image realism, thereby neglecting the geometric continuity and contextual fidelity essential for robust detection by mo

This data set includes student responses and expert ratings from the test administrations for the Turkish History course. For each question, the correct answer is assigned a new label, while incorrect answers are labeled as “0”. For 15 questions, there are true-false scores and for 4 questions there are true-partially true-false scores.

The dataset consists of airport specific ground crew and allocation data for four major airports - Kempegowda International Airport (BLR), Rajiv Gandhi International Airport (HYD), Indira Gandhi International Airport (DEL), and Chhatrapati Shivaji Maharaj International Airport (BOM). The tasks, floors and gates,  i.e, the tasks and their locations are factual data where as the allocation data is approximately close to realistic demand. The crew demand is synthetically generated.

The datasets include historical daily market information in the Chinese A-share stock markets, such as closing prices, opening prices, highest prices, lowest prices, trading volumes in terms of value, and trading volumes in terms of quantity, from 2015 to 2021.

The Cross-Domain Deception Dataset (CD3) contains frame-level features extracted from video data using OpenFace and OpenPose to support research in deception detection through facial expressions, facial action units, body and hand gestures, and gaze coordinates. Using a commercial off-the-shelf laptop and Microsoft Teams, we collected video data of 45 participants completing mock interviews where they answered questions related to biographical information, academic success, and well-being across two sessions.

The dataset used in this study consists of Airborne LiDAR Bathymetry (ALB) waveform data collected by the Norwegian Mapping Authority via Field Geospatial AS. It covers the Fjøløy Island area in Stavanger, Norway, a region characterized by fjords and diverse submerged environments. The dataset is proprietary and was provided to the authors under a research collaboration agreement.

Two subsets were extracted from the full dataset:

• Dataset 1: 6,379 waveform files
• Dataset 2: 4,428 waveform files

Each waveform file contains:

6 typical suppression-type interference signals are generated by MATLAB 2021b: Sine amplitude modulation(SAM), Sine frequency modulation(SFM), Noise frequency modulation(NFM), Noise amplitude modulation(NAM), Linear frequency modulation sweep(LFM), Logarithmic frequency modulation sweep (LogFM).

This dataset consists of four datasets. LWNN train and LWNN test data sets consist of synthetically generated 64-OFDM carrier-wise QAM signals. Each signal consists of 1000 I-Q samples. RNN-BC-train and RNN-BC-test datasets consist of modulation (QAM64, QAM32, QAM16, QAM8, QAM4) in each carrier allocated by a bit loading algorithm based on a synthetically generated multipath channel response.

Timeseries data of impedance measurement, created by dSPACE ControlDesk, stored in MATLAB format

The data set used here is a part of the Bialystok PLUS cohort study, where residents of Białystok were randomly selected from the Municipal Office database and invited to participate in the study. In this part of  study they were between 30 and 70 years old and constituted a representative sample of the local population. Data contains proteomics and atherosclerosis risk factors.

This dataset contains IoT-based soil data collected from various districts of Bangladesh, aimed at assessing soil quality for crop recommendation purposes. The data includes key soil parameters, such as nitrogen, phosphorus, potassium levels, soil conductivity, pH, humidity, and temperature, measured over multiple time intervals. The dataset includes a Soil Quality Index (SQI) and fuzzy classification categories, allowing for an in-depth soil fertility analysis.

We designed multijunction solar modules for installation on building walls, in which all the submodules are composed of organic-inorganic hybrid perovskite solar cells, adopting the monolithically series-interconnected structures.

This study aims to create a robust hand grasp recognition system using surface electromyography (sEMG) data collected from four electrodes. The grasps to be utilized in this study include cylindrical grasp, spherical grasp, tripod grasp, lateral grasp, hook grasp, and pinch grasp. The proposed system seeks to address common challenges, such as electrode shift, inter-day difference, and individual difference, which have historically hindered the practicality and accuracy of sEMG-based systems.

In low-altitude unmanned aerial vehicle (UAV) detection scenarios, the initial segment of radar linear frequency modulation (LFM) signals is often corrupted due to building occlusions and noise interference, making accurate range estimation difficult. To address this issue, we propose a deep learning-based framework named Deep Time-Frequency Inverse Reconstruction Network (DTFIRNet) for radar echo signal restoration and precise ranging.

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This dataset is for the paper “FMOBA: Frequency-Domain Multi-Objective Black-Box Adversarial Attacks for SAR Image”