Artificial Intelligence

This dataset presents the capacity fade data for eight Lithium Titanate Oxide (LTO) battery cells over progressive charge-discharge cycles. The measurements, recorded at intervals of 250 cycles up to 3500 cycles, track the aging effects on battery capacity over time. The aging procedure includes a rest period of 10 minutes between charging and discharging cycles. Each charging and discharging process was conducted with a constant current of 1 ampere (A). The maximum charge voltage was set to 2.75 volts (V), while the minimum discharge voltage was set at 1.30 V.

IWSLT2017-zh-en；WMT18-zh-en；CoQA

The IWSLT 2017 Multilingual Task addresses text translation, including zero-shot translation, with a single MT system across all directions including English, German, Dutch, Italian and Romanian. As unofficial task, conventional bilingual text translation is offered between English and Arabic, French, Japanese, Chinese, German and Korean.

CoQA is a large-scale dataset for building Conversational Question Answering systems.

Interference signals degrade and disrupt Global Navigation Satellite System (GNSS) receivers, impacting their localization accuracy. Therefore, they need to be detected, classified, and located to ensure GNSS operation. State-of-the-art techniques employ supervised deep learning to detect and classify potential interference signals. We fuse both modalities only from a single bandwidth-limited low-cost sensor, instead of a fine-grained high-resolution sensor and coarse-grained low-resolution low-cost sensor.

We began by selecting normally exposed images from several prominent endoscopic image repositories, including Kvasir, CVC-ColonDB, CVC-ClinicDB, ETIS-LaribPolypDB, and CVC-300. To simulate exposure anomalies reflective of real-world variations, we utilize the LECARM model, which allows us to apply a random exposure range of (-1,1). This generates a diverse spectrum of exposure anomalies that closely resemble those encountered in clinical settings.

This dataset comprises actual measurement data collected from a wind farm located in Xinjiang, China. It includes a range of parameters essential for understanding wind energy potential and environmental conditions. The data features wind speeds recorded at various heights—10 meters, 30 meters, 50 meters, and 70 meters—measured in meters per second (m/s). Additionally, the dataset includes wind direction at these same heights, recorded in degrees (°).

We present SMPL-IKS, an inverse kinematic solver to operate on the well-known Skinned Multi-Person Linear model (SMPL) to recover human mesh from 3D skeleton. The challenges of the task are threefold: (1) Shape Mismatching. (2) Error Accumulation. (3) Rotation Ambiguity. Instead of recovering human mesh from costly vertice up-sampling or iterative optimization as in previous methods, SMPL-IKS directly regresses the SMPL parameters (i.e., shape and pose parameters) in a clean and efficient way. Specifically, we propose to infer skeleton-to-mesh via two explicit mappings viz.

Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. Detecting anomalies in frequency snapshots is crucial to counteract these interferences effectively. The ability to adapt to diverse, unseen interference characteristics is essential for ensuring the reliability of GNSS in real-world applications. We recorded a dataset with our own sensor station at a German highway with eight interference classes and three non-interference classes.

TRAINING AND PLACEMENT CELL is a web based application developed in the windows platform for the training and placement department of the college in order to provide the details of its students in a database for the companies to their process of recruitment provided with a proper login. The TRAINING AND PLACEMENT CELL contains all the information about the students. The system stores all the personal information of the students, like their personal details, their aggregate marks, their skill set and their technical skills that are required in the CV to be sent to a company.

Tourism receipts worldwide are not expected to recover to 2019 levels until 2023. In 

the first half of this year, tourist arrivals fell globally by more than 65 percent, with a near halt 

since April—compared with 8 percent during the global financial crisis and 17 percent amid 

the SARS epidemic of 2003, according to ongoing IMF research on tourism in a post-pandemic 

world. Because of pandemic we faces the different struggles specially the business closed.