Artificial Intelligence
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.
that’s why country’s economy decrease, at first many company need to reduce their employee.
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46 Views
With the development of recommender systems (RSs), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS. Multi-criteria recommender systems (MCRSs) are designed to provide personalized recommendations by considering user preferences in multiple attributes or criteria simultaneously. Unlike traditional RSs that typically focus on a single rating, these systems help users make more informed decisions by considering their diverse preferences and needs across various dimensions.
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157 Views
Numerical simulations are used to assess the efficiency of floor heating, ceiling heating, and plane radiator heating in a selected family house room under winter conditions in the Central European climate zone. COMSOL Multiphysics software was used for computer simulations. The output data were subsequently processed and analyzed using MATLAB software. Results indicate that floor and ceiling heating systems achieve higher and more rapid temperature increases compared to plane radiators.
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137 Views
The data set includes attack implementations in an Internet of Things (IoT) context. The IoT nodes use Contiki-NG as their operating system and the data is collected from the Cooja simulation environment where a large number of network topologies are created. Blackhole and DIS-flooding attacks are implemented to attack the RPL routing protocol.
The datasets includes log file output from the Cooja simulator and a pre-processed feature set as input to an intrusion detection model.
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239 Views
A differential diagnostic (DDX) note generation dataset.
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111 Views
Offline-to-online is a key strategy for advancing reinforcement learning towards practical applications. This approach not only reduces the risks and costs associated with online exploration, but also accelerates the agent’s adaptation to real-world environments. It consists of two phases: offline-training and fine-tuning. However, offline-training and fine-tuning have different problems. In offline-training, the main difficulty is how to learn an excellent policy in a limited and incompletely distributed dataset.
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75 Views
Since the aircraft trajectory data in the field of air traffic management typically lacks labels, it limits the community's ability to explore classification models. Consequently, evaluations of clustering models often focus on the correctness of cluster assignment rather than merely the closeness within the cluster. To address this, we labeled the dataset for both classification and clustering tasks by referring to aeronautical publications. The process of obtaining the ATFM trajectory dataset consists of data sourcing, preprocessing, and annotation.
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140 Views
We used the broad group of 47,692 tweets from the Cyberbullying Classification dataset. This worldwide sourced dataset offers a broad range of examples of cyberbullying, guaranteeing a thorough viewpoint. Our thorough translation and modification procedure guaranteed the dataset's contextual and cultural relevance for the Tamil-speaking population, even though it is not solely from South Asia. These tweets were carefully divided into six classes, each of which represented a different facet of cyberbullying, as well as cases that weren't considered cyberbullying.
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376 Views
Text-to-image models, like Midjourney and DALL-E, have been shown to reinforce harmful biases, often perpetuating outdated and discriminatory stereotypes. In this study, we delve into a particularly insidious bias largely overlooked in generative image research: Brilliance Bias. By age six, many children begin to internalize the damaging notion that intellectual brilliance is a male trait—a belief that persists into adulthood. Our findings demonstrate that popular image AI models possess this bias, further entrenching the misguided notion that exceptional intelligence is inherently male.
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80 Views
Multimodal sensor fusion has been widely adopted in constructing scene understanding, perception, and planning for intelligent robotic systems. One of the critical tasks in this field is geospatial tracking, i.e., constantly detecting and locating objects moving across a scene. Successful development of multimodal sensor fusion tracking algorithms relies on large multimodal datasets where common modalities exist and are time-aligned, and such datasets are not readily available.
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664 Views