Artificial Intelligence

Automatic Identification System (AIS) data are critical for maritime domain awareness, enabling tasks such as vessel classification, trajectory prediction, and anomaly detection. However, AIS datasets frequently suffer from domain shifts, data sparsity, and class imbalance, which limit the generalization of predictive models. To address these challenges, this paper presents AISCycleGen, a novel data augmentation framework that leverages Cycle-Consistent Generative Adversarial Networks to synthesize realistic AIS sequences through unpaired domain translation.

We developed IIST BCI Dataset-9, a novel EEG-based Brain-Computer Interface (BCI)
dataset to improve wheelchair control systems using Malayalam dialect variations. BCI
systems help people with motor disabilities by allowing them to control devices using brain
signals. The limited number of BCI datasets in Indian languages makes it harder for native
speakers to use these systems. To address this, we created a dataset with 15 Malayalam
words related to basic wheelchair commands like Forward, Backward, Go, Stop, Reverse,

ITDAV-25 (Indian Thermal Dataset for Autonomous Vehicles), a thermal image dataset specifically curated to advance research in Advanced Driver Assistance Systems (ADAS), particularly for environments characterized by low visibility, night-time conditions, and inclement weather. The dataset comprises of 13,688 raw thermal images, collected without any synthetic augmentation techniques.

Feature extraction on the camelyon 17 dataset (https://camelyon17.grand-challenge.org/Data/) using the tile-level encoder of the Prov-GigaPath model (10.1038/s41586-024-07441-w) and the trident project (https://github.com/mahmoodlab/trident/). 

This dataset was curated mainly to cater to mitigation strategies for the Human-Peafowl Conflict that exists in these regions. The absence of natural predators has contributed to a significant increase in the peafowl population, exacerbating challenges for farmers. Peafowls are sometimes considered agricultural pests due to their tendency to feed on and damage crops. The vocalizations are from the Indian Peafowl (Pavo cristatus), a species native to the Indian subcontinent and especially abundant in India and Sri Lanka.

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

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.