IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains substantial noise in dialogue states and utterances, limiting state-tracking accuracy. We introduce IRWOZ 2.0, which addresses these limitations through large language model (LLM) enhanced generation (Mistral/Claude-3.5) and quality refinements. Our improved
Digital technology's pervasive impact is often limited by data silos within institutions. Enabling data sharing via Commonly Accessible Platforms (CAPs) across sectors like healthcare and education promises greater value. However, trust hinges on privacy, security, immutability, and cost-effectiveness. While Blockchain Technology (BCT) offers immutability, a research-practice gap exists due to operational challenges. This paper introduces Vedic Recordchain, a novel multi-hash platform offering an alternative to BCT for CAPs, addressing these challenges.
Data contains factors used to analyze the behavioral intentions of farmers. This dataset consists of ordinal survey responses collected across multiple features. Each feature appears to be evaluated on a 1–5 scale, where 1 indicates strong disagreement and 5 indicates strong agreement. The data is organized in a tabular format with a consistent structure across multiple pages. It is suitable for various statistical analyses, including factor analysis. This dataset is highly versatile.
Molecular Communications (MC), transferring information via chemical signals, holds promise for transformative healthcare applications within the Internet of Bio-Nano Things (IoBNT) framework. Despite promising advances toward practical MC systems, progress has been constrained by experimental testbeds that are costly, difficult to customize, and require labor-intensive fabrication.
Abstract
Hamstring Injuries (HSIs) are common among athletes and necessitate extended rehabilitation before Return to Sport (RTS). Post-injury, athletes undergo physical examinations, which often fall short in assessing injury severity or guiding rehabilitation. Therefore, imaging techniques such as Magnetic Resonance Imaging (MRI) are used to evaluate the injury more comprehensively, aiding in the assessment of optimal rehabilitation and RTS timelines. Given the significant impact of HSIs on athletic careers, early prediction is essential.
This dataset contains field test data of multi-USV collaborative area search and dynamic target trapping operations performed on a lake.
Synthetic EEG Dataset for CNN-LSTM Training: Clean and Artifact-Contaminated Signals
This dataset consists of synthetically generated EEG and EMG signals designed for training Convolutional Neural Networks (CNNs) in artifact detection and removal. The dataset includes both clean EEG signals and EEG signals contaminated with simulated EMG artifacts from various sources.
TRANSIT dataset is the default dataset of the simulation software Traffic Anomaly Simulation Tool (TRANSIT). You can get the code of TRANSIT in the page:
The composition of the natural gas components is as follows: $CH_{4}$ (97.07$\%$), $C_{2}H_{6}$ (0.17$\%$), $C_{3}H_{8}$ (0.02$\%$), $N_{2}$ (0.71$\%$), and $CO_{2}$ (2.03$\%$). The standard state conditions are a pressure of 101325 $Pa$ and a temperature of 20 $^\circ C$. The pipeline components have an inner diameter of 0.307 $m$, an outer diameter of 0.323 $m$, a total heat transfer coefficient of 0.5, and a roughness of 0.02286 $mm$. The initial temperature of both the pipeline and the surrounding medium is 15 $^\circ C$.
The composition of the natural gas components is as follows: $CH_{4}$ (97.07$\%$), $C_{2}H_{6}$ (0.17$\%$), $C_{3}H_{8}$ (0.02$\%$), $N_{2}$ (0.71$\%$), and $CO_{2}$ (2.03$\%$). The standard state conditions are a pressure of 101325 $Pa$ and a temperature of 20 $^\circ C$. The pipeline components have an inner diameter of 0.307 $m$, an outer diameter of 0.323 $m$, a total heat transfer coefficient of 0.5, and a roughness of 0.02286 $mm$. The initial temperature of both the pipeline and the surrounding medium is 15 $^\circ C$.
Transient simulation data set of natural gas pipeline under three working conditions,The composition of the natural gas components is as follows: $CH_{4}$ (97.07$\%$), $C_{2}H_{6}$ (0.17$\%$), $C_{3}H_{8}$ (0.02$\%$), $N_{2}$ (0.71$\%$), and $CO_{2}$ (2.03$\%$). The standard state conditions are a pressure of 101325 $Pa$ and a temperature of 20 $^\circ C$. The pipeline components have an inner diameter of 0.307 $m$, an outer diameter of 0.323 $m$, a total heat transfer coefficient of 0.5, and a roughness of 0.02286 $mm$.
The article Aims to compare the application effect of different machine learning algorithms in the recognition of badminton stroke types, so as to better meet the needs of quantitative analysis of badminton skills and tactics, and provide a more reasonable basis for the layout of game strategies.
This dataset is associated with the paper entitled "User-Centric Caching in Personal Vehicles: MyCar-MyCache". It tracks 3,463 app sessions from 5 users over 14 days in a residential wireless local area network. Seven distinct apps appear with App_A being most popular (678 sessions). Usage peaks midday (12pm: 210 sessions) and is lowest late evening (11pm: 89 sessions). Average session duration is 30 minutes with 50.2 MB data consumption per session. Daily activity remains consistent (234-266 sessions) with no significant day-of-week patterns.
The dataset is constructed using SUMO. It contains two road network datasets of different scales: a small-scale network (SR) and a larger regional network in Shenyang (SY). The dataset was constructed using the SUMO simulation platform, containing two road network datasets at different scales: a small-scale test network (SR) and a regional-level Shenyang network (SY). The SR network comprises 110 road segments, while the SY network contains 514 segments.
As global energy shortages intensify and the drive for Sustainable Development Goals (SDGs) grows, enhancing energy efficiency in agriculture has become a pivotal factor in fostering green development. Energy Performance Contracting (EPC) presents a key opportunity for achieving energy conservation and emission reduction, but these projects are often beset by significant risks due to their complexity.
Black Swan failures in aviation cybersecurity represent significant and unpredictable disruptions that stem from intricate interactions among behavioral drift, flaws in system design, and organizational inertia, thereby eluding conventional, pattern-based threat detection methodologies. This study presents the Black Swan Cyber Resilience Framework (BSCRF), which integrates principles of antifragility and supraresilience into the realm of cybersecurity, emphasizing adaptive learning over static defensive measures.
This dataset comprises high-resolution 3-axis accelerometer recordings collected from human participants performing distinct hand gestures, intended for training gesture-based assistive interfaces. Each participant’s raw motion signals are individually organized, enabling both user-specific and generalizable model development. The dataset includes time-series accelerometer data, along with a feature-augmented version containing extracted statistical and temporal descriptors such as RMS, Jerk, Entropy, and SMA.
This dataset comprises the time cost of ten cryptographic operations on our testing platform, as well as the required number of operations and corresponding time consumption at each phase of the authentication schemes from six selected literature sources. The data is utilized for comparative analysis and evaluation of the operational efficiency among various identity authentication schemes.
This data provides a comprehensive collection of air quality and meteorological data from several large cities in India. With 1,410 records, it includes key characteristics like the Air Quality Index (AQI) according to both U.S. and China standards, temperature, atmospheric pressure, humidity, wind speed, wind direction, and timestamps.
Two images from Sentinel - 2 and Gaofen - 2, with resolutions of 10 m and 0.8 m respectively, underwent orthorectification and geometric correction. Then, using the Sentinel - 2 image as the reference, the Gaofen - 2 image was coregistered.Two images from Sentinel - 2 and Gaofen - 2, with resolutions of 10 m and 0.8 m respectively, underwent orthorectification and geometric correction.
Two images from Sentinel - 2 and Gaofen - 2, with resolutions of 10 m and 0.8 m respectively, underwent orthorectification and geometric correction. Then, using the Sentinel - 2 image as the reference, the Gaofen - 2 image was coregistered.
Two images from Sentinel - 2 and Gaofen - 2, with resolutions of 10 m and 0.8 m respectively, underwent orthorectification and geometric correction. Then, using the Sentinel - 2 image as the reference, the Gaofen - 2 image was coregistered.
Two images from Sentinel - 2 and Gaofen - 2, with resolutions of 10 m and 0.8 m respectively, underwent orthorectification and geometric correction. Then, using the Sentinel - 2 image as the reference, the Gaofen - 2 image was coregistered.
Two images from Sentinel - 2 and Gaofen - 2, with resolutions of 10 m and 0.8 m respectively, underwent orthorectification and geometric correction. Then, using the Sentinel - 2 image as the reference, the Gaofen - 2 image was coregistered.
The proliferation of IoT devices which can be more easily compromised than desktop computers has led to an increase in the occurrence of IoT-based botnet attacks. In order to mitigate this new threat there is a need to develop new methods for detecting attacks launched from compromised IoT devices and differentiate between hour and millisecond long IoT-based attacks.
