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State-space representation is a practical, efficient and reliable way to evaluate the high-frequency interaction of a transformer with the power network under different types of disturbances. Currently, this representation is available in commercial electromagnetic transient programs; however, this important tool is not yet implemented in the alternative transient program ATP. This paper describes the implementation methodology of the state-space model of the power transformer in ATP using the Norton type-94 component and foreign models.

Network Interface Cards (NICs) are one of the key enablers of the modern-day Internet. They serve as gateways for connecting computing devices to networks for the exchange of data with other devices. Recently, the pervasive nature of Internet-enabled devices coupled with the growing demands for faster network access have necessitated the enhancement of NICs to Smart NICs (SNICs), capable of processing enormous volumes of data at near real-time speed. These devices are fitted with Compute Elements that allow them to handle several tasks, thus relieve their host's CPUs of these workloads.

Abstract—This manuscript introduces the Chaos Fusion Mutation INFO algorithm (CFMINFO), which integrates multiple strategies and updates vector positions through three core processes. These processes incorporate Good Point Set initialization, Sine-Tent-Cosine (STC) chaotic parameterization, and Normal Cloud Mutation strategies. The algorithm is characterized by its simplicity, rapid convergence, and ability to avoid local optima. To validate its performance, CFMINFO is applied to the optimization of linear arrays.

This work presents a dataset based on multiple network and service metrics (KPIs and KQIs), the latest providing the E2E conditions of video on demand service. Particularly, the dataset also includes an attack situation where an attacker injects traffic into the network. In total, there are 3600 samples, with different configurations of Physical Resource Blocks and cell gain, from sessions of 60 seconds.

Following the setup of previous works [8, 16], we conducted experiments on various bit image restoration tasks.

We utilized a dataset of 2000 16-bit images, with training

data sourced from SINTEL [37] and FIVE-K [38]. SINTEL

is an animated short film dataset containing over 20,000 16-

bit lossless images with a resolution of 436 × 1024 pixels. In

FIVE-K, randomly select images from 5,000 16-bit natural

images for the experiment.The test set includes 8 images

randomly chosen from the SINTEL dataset (referred to as

To enhance the application of radiotherapy planning, we developed a novel head and neck imaging dataset, HND, comprising simulation X-ray computed tomography (CT) images from 486 patients with head and neck cancers who underwent intensity-modulated radiotherapy (IMRT) between February 2019 and June 2024 (Table 1).

This dataset contains 20,000 packets of wireless channel measurements collected between two simulated devices, Alice and Bob, using the Vienna 5G Link Level Simulator. The dataset captures channel state information (CSI), signal magnitude, and phase variations under four different wireless environments: Indoor Mobile (IME), Indoor Static (ISE), Outdoor Mobile (OME), and Outdoor Static (OSE), with corresponding correlation values of 0.65, 0.82, 0.66, and 0.63, respectively.

The ADS-B trajectory data is obtained from the public Internet and includes four aircraft targets, namely B737, C17-1, C17-2, and E35L. Each target contains 110 complete trajectories, totaling more than 100,000 trajectory points. The tracks used for training in the experiment are stored in the form of track points, encoded using UTF-8. Each line corresponds to one track point simultaneously, and the contents are time, longitude, latitude, altitude, speed, heading and climb respectively. All data is stored in txt format.

The National Institute of Standards and Technology (NIST) has recommended the use of stateful hash-based digital signatures for long-term applications that may require protection from future threats that use quantum computers.  XMSS and LMS, the two approved algorithms, have multiple parameter options that impact digital signature size, public key size, the number of signatures that can be produced over the life of a keypair, and the computational effort to validate signatures.  This collection of benchmark data is intended to support system designers in understanding the differen

The COVID-19 Vaccine Misinformation Aspects Dataset contains 3,822 English tweets discussing COVID-19 vaccine misinformation, collected from Twitter/X between December 31, 2020, and July 8, 2021. Each tweet is manually annotated and categorized into four distinct misinformation aspects: (1) Vaccine Constituent, (2) Adverse Effects, (3) Agenda-Driven Narratives, and (4) Efficacy and Clinical Trials.

The medical biometric dataset comprises 10,000 records collected across 23 patients spanning different demographics, biometric profiles, and temporal variations between 2022 and 2023. It is accumulated from various hospitals, digital health records, and biometric-enabled healthcare security systems. The dataset includes real-world biometric authentication and clinical profiling scenarios while ensuring compliance with standard medical and biometric data regulations.

This dataset provides the full list of security controls proposed in the article "Enhancing Cybersecurity in the Judiciary: Integrating Additional Controls into the CIS Framework". The dataset includes a detailed classification of security controls derived from the CIS Controls framework and additional measures specifically tailored to address cybersecurity challenges in the Judiciary. These controls enhance operational risk management, digital asset protection, and organizational resilience.

Binary classification is the most suitable task considering the common use cases in MCUs. Numerous datasets for image classification have been proposed. The Visual Wake Words (VWW) dataset, which is derived from the COCO dataset, distinguishes between ‘w/ person’ and ‘w/o person’ and is designed for object detection on MCUs. Therefore, datasets for binary classification and object detection exist. However, the dataset for binary classification has not been proposed for the semantic segmentation task.

This dataset is designed for research on 2D Multi-frequency Electrical Impedance Tomography (mfEIT). It includes:

With the gradual maturity of UAV technology, it can provide extremely powerful support for smart agriculture and precise monitoring. Currently, there is no dataset related to green walnuts in the field of agricultural computer vision. Therefore, in order to promote the algorithm design in the field of agricultural computer vision, we used UAV to collect remote sensing data from 8 walnut sample plots.

These two datasets are significantly different from each other in terms of the image color, cell shape, background, etc., which can better evaluate the robustness of WBC segmentation approach. The ground truth segmentation results are manually sketched by domain experts, where the nuclei, cytoplasms and background including red blood cells are marked in white, gray and black respectively. We also submitted the segmentation results by our approach, where the whole WBC region are marked in white and the others are marked in black.

This dataset is a large-scale video benchmark constructed for RGB-Thermal (RGB-T) object tracking tasks, featuring the following key characteristics:

1. **Scale & Diversity**  

- Contains 234,000 total frames, with sequences up to 8,000 frames  

- Covers diverse scenarios and complex environmental conditions  

- Currently the largest publicly available RGB-T dataset in the field  

2. **Precise Multimodal Alignment**  

We consider the automation of polishing process for manufactured components, which is typically an iterative, multi-stage process that depends heavily on the practitioner’s expertise and visual inspection to guide decisions on polishing pad changes and fine-tuning of control parameters. We use a model-free, on-policy actor-critic reinforcement learning (RL) algorithm to determine the choice of pad, downforce, rotational speed, polishing duration for each stage, and the total number of polishing / inspection stages.

We consider the automation of polishing process for manufactured components, which is typically an iterative, multi-stage process that depends heavily on the practitioner’s expertise and visual inspection to guide decisions on polishing pad changes and fine-tuning of control parameters. We use a model-free, on-policy actor-critic reinforcement learning (RL) algorithm to determine the choice of pad, downforce, rotational speed, polishing duration for each stage, and the total number of polishing / inspection stages.

Spread spectrum time domain reflectometry (SSTDR) is proposed to replace the VNA or UWB pulsed systems and switches in a microwave imaging system. These tests evaluate an SSTDR system (Keysight N7081A) from 2-4 GHz. 16 ultrawideband (UWB) antennas were placed in contact with the breast phantom. The McGill breast phantom is a hemispherical carbon-based phantom with the electrical properties of fat. A cylindrical hole allows for the insertion of a plug with fat properties or fat+tumor properties. These were both measured and provided in the attached data set.

This dataset accompanies the IEEE IoT Journal paper titled "A Dual System IoT Strategy for Hyperlocal Spatial-Temporal Microclimate Monitoring in Urban Environments Using LoRa." It is intended for validating bespoke sensors against commercial sensors. The data were collected using two different types of sensors deployed at eight locations in East London, starting on August 1, 2023, and covering a period of one year.

Data was acquired using data aquisiton interface in a laboratory on a flow control unit. The data has been transformed into two excel spreadsheets which was later used in Matlab. This dataset also consists of three Matlab codes. First one is the code for the experiment in which the ANN models were developed. Second Matlab code is the code for data importing from the excel spreadsheets and the third Matlab code is the data preparation code for the Simulink purposes in order to test the models.

Twelve (12) realistic datasets encapsulating residents’ preferences, with each dataset representing the appliance-usage preferences expressed for a variant set of households by their respective residents for a specific season and day. The preferences were extracted from the REFIT dataset, a public 500MB dataset which contains real kW readings of the power output for the most energy-intensive shiftable/real-time appliances in 20 households in the UK, between September 2013 and July 2015.

The measurements in this study were carried out at Xidian University's north campus in China. The building density and height in this area are typical of urban environments, and there are fewer uncertainties that could affect the experimental results. Figure shows an aerial view of the measurement environment, including the chosen Tx and Rx locations. Centered at each receiver, a square with a side length 15 times the wavelength of the transmitted signal was constructed. The receiving antenna was moved inside each square following the path shown in the figure.