IEEE 5G/6G Testbed

This dataset provides high-grade Received Signal Strength Indicator (RSSI) data collected from a set of experiments meant to estimate the number of drones present in a closed indoor space. The experiments are conducted varying the number of drones from one to seven, where all the variations in RSSI signal data are captured using a 5G transceiver setup established using Ettus E312 software-defined radio. There are seven files in the database, with a minimum of about 270 million samples.

<p>This dataset contains simulation results generated in OptiSystem for an 18‐tupling optical communication system. The parameters include optical source settings, modulator configurations, and a range of power and signal quality metrics. Key performance indicators—such as total power penalty (TPP), signal power penalty (SPP), and RMS jitter—are provided for each set of simulation inputs. The data are intended to facilitate reproducible research and to enable further analysis of high‐order frequency multiplication in optical networks.

This dataset contains heartbeat and electromyography (EMG) signals recorded from the brachioradialis muscle under different conditions: rest and induced fatigue. It is intended for research in biomechanics, fatigue detection, and physiological signal processing. The data provide insights into muscle activity and heart rate variations, making it valuable for applications in biomedical engineering and human performance analysis.

The dataset can be used to deal with the optimization design of feeder-bus network related to urban rail transit. The research on the optimization design of feeder-bus network related to urban rail transit is helpful to improve passengers' travel satisfaction and convenience, and solve the connection problem between rail transit station and bus stop. The dataset contains a 4 km by 5 km area, providing the coordinates of 80 bus stops and 4 rail transit stations.

In My study, we evaluate the performance of the proposed clustering method across a wide range of publicly available datasets that represent different data modalities. Specifically, Jaffe, ExtendYaleB, and ORL are employed as facial image datasets to assess the method's capability in handling variations in facial expressions and lighting conditions.

The shift towards cloud-native applications has been accelerating in recent years. Modern applications are increasingly distributed, taking advantage of cloud-native features such as scalability, flexibility, and high availability. However, this evolution also introduces various security challenges. From a networking perspective, the large number of interconnected components and their intricate communication patterns make detecting and mitigating traffic anomalies a complex task.

This dataset contains 609,934 real Modbus TCP packets collected from industrial control system (ICS) environments, capturing the full byte-level structure of Modbus communication, including MBAP headers and function-specific payloads. Designed to support research in industrial cybersecurity, this dataset addresses the scarcity of diverse and realistic Modbus traffic, which often hampers the development of intrusion detection systems (IDS) and protocol-compliant synthetic data generators.

All measurement campaigns are carried out in the standardized meeting room at 260-400 GHz. We categorize samples into two classes: near points Tx1-Tx7 and far points Tx8-Tx23.  The measurement setup maintains each static transmitter while positioning the receiver on a computer-controlled stepping rotator. Systematic spatial sampling is achieved through 128 discrete half-wavelength displacements of the receiver assembly, thereby synthesizing a virtual massive multi-antenna array.

This study is based on the analysis of the current state and main trends in the design, synthesis and application of various transparent electrodes, including transparent conductive semiconductor oxides, metal ultrathin films, partially filled structures and multilayer oxide/metal/oxide structures.

We introduce BS-Breath, the first open dataset for respiration sensing using a cell-free massive MIMO system. Collected from a 64-antenna MIMO testbed, this dataset provides uplink Channel State Information (CSI) at 3.51 GHz, captured from 10 subjects performing controlled breathing. Ground truth respiration data is synchronized using a Motion Capture (MoCap) system, enabling precise validation.