Search

Showing total 10 results
Start Over Topic algorithms Publication Year Range Last 3 years Region xi'an shi (china) Database Complementary Index
10 results

1. Attraction Recommendation Based on Tourism Context Modeling and Multi‐neural Collaborative Filtering Algorithm.

Author

Zhang, Shuo, Wang, Lei, Fei, Rong, Xu, Xiangrong, and Li, Wei

Subjects
HERITAGE tourism, TOURISM, ALGORITHMS, NETWORK analysis (Planning)
Abstract

The key to generating tailored suggestions in the scenic location recommendation scene is how to model the diverse tourism environments in order to correctly acquire visitor preferences and scenic spot tourism features. However, most existing recommendation algorithms focus on the spatiotemporal background modeling of historical tourism trajectories. Only tourists' preferences are understood, and the rich heterogeneous tourism information such as tourists' personal tourism constraints and scenic spots' tourism attributes are ignored. In this paper, we proposed a multiple neural collaborative filtering attraction recommendation architecture (MNCF‐AR). To begin, we learn the tourism feature representation of tourists by modeling diverse tourism contexts, and then we create the tourism trajectory background of tourists using a large number of actual tourism logs to achieve the entire feature representation of tourists. Second, to learn the feature vector of scenic spots in the context, the tourism heterogeneous network map is used to build the scenic spot attribute background, the self‐attention network to learn the scenic spot sequence learning, and a neural network to project each scenic spot into a unified potential feature space. Finally, the multi‐neural collaborative filtering method is utilized to forecast the difference in scores between visitors and scenic sites so that tailored scenic spots may be recommended. Extensive experiments on mainstream datasets, such as MaFengwo, New York, Tokyo and Xi'an, show that the proposed method can effectively and accurately recommend attractions for users. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

2. Study Results from Shaanxi Normal University Provide New Insights into Engineering (An Effective Metaheuristic Technology of People Duality Psychological Tendency and Feedback Mechanism-based Inherited Optimization Algorithm for Solving...).

Subjects
OPTIMIZATION algorithms, METAHEURISTIC algorithms, ENGINEERING, EXPERT systems, CONSTRAINED optimization
Abstract

A new report from Shaanxi Normal University in Xi'an, China, presents research on an effective metaheuristic algorithm called the Inherited Optimization Algorithm (IOA). Inspired by the cognitive tendencies and adaptive feedback behavior of people, the IOA algorithm aims to solve complex optimization problems in engineering applications. The algorithm's performance was evaluated on various benchmarks and compared to other metaheuristics, demonstrating its computational efficiency and search efficiency. The research was funded by the National Natural Science Foundation of China and the Fundamental Research Funds for the Central Universities. [Extracted from the article]

Published
2024

3. Studies Conducted at Xi'an University of Science and Technology on Psychology and Psychiatry Recently Reported (Micro-expression Recognition Based On Multi-scale 3d Residual Convolutional Neural Network).

Subjects
CONVOLUTIONAL neural networks, FACIAL expression, PSYCHIATRY, TECHNOLOGICAL innovations
Abstract

A recent study conducted at Xi'an University of Science and Technology in Xi'an, People's Republic of China, focused on the accurate recognition of micro-expressions in demanding scenarios such as clinical psychotherapy and criminal interrogation. The study proposed a novel architecture based on a multi-scale 3D residual convolutional neural network, which effectively captured weak and fleeting facial features and improved recognition performance. The algorithm's performance was evaluated using public datasets, and it achieved recognition accuracies of 74.6%, 84.77%, and 91.35% on these datasets. The study concluded that the proposed algorithm could serve as an important reference for researchers working on high-precision micro-expression recognition. [Extracted from the article]

Published
2024

4. Estimating long‐term time‐resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs.

Author

Xia, Tongling, Qi, Yue, Dai, Xilei, Liu, Jinyu, Xiao, Can, You, Ruoyu, Lai, Dayi, Liu, Junjie, and Chen, Chun

Subjects
NATURAL ventilation, ALGORITHMS, SPATIAL variation, SEASONS
Abstract

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM2.5 in buildings. This study used an algorithm to automatically estimate the long‐term time‐resolved indoor PM2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time‐resolved indoor/outdoor PM2.5 concentrations and occupants' window actions, which were easily obtained from the low‐cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time‐resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long‐term outdoor PM2.5 monitoring using low‐cost light‐scattering sensors. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

6. Findings from Xi'an Polytechnic University Update Understanding of Occupational Diseases and Conditions (Small Target Detection Algorithm Based On Attention Mechanism and Data Augmentation).

Subjects
OCCUPATIONAL diseases, DATA augmentation, ALGORITHMS, VIDEO processing, OCCUPATIONAL medicine
Abstract

Researchers from Xi'an Polytechnic University in China have developed a small target detection algorithm for mask-wearing detection. The algorithm, based on an improved version of YOLOv5s, addresses challenges such as small target size, a large number of targets, and mutual occlusion. The researchers embedded an ultralightweight attention mechanism module in the algorithm to improve accuracy, explored different loss functions, and adopted data augmentation methods to enhance model performance. The proposed algorithm achieved a mean average precision of 92.1% on the verification set, outperforming the original algorithm by 4.4%. This research has been peer-reviewed and published in Signal Image and Video Processing. [Extracted from the article]

Published
2024

7. Researchers from Xi'an University Discuss Findings in Obesity, Fitness and Wellness (Improving Plunger Motion Law Based On Multi-objective Optimization Algorithm).

Subjects
OPTIMIZATION algorithms, LEGAL motions, RESEARCH personnel, OBESITY, CONSTRAINT algorithms
Abstract

Researchers from Xi'an University in China have conducted a study on improving the plunger motion law in pumping machines to increase pump filling degree and optimize efficiency. The researchers used a multi-objective optimization genetic algorithm to optimize the plunger movement law without changing the stroke and stroke times. The results showed a 5% increase in pump filling degree and a 75.36% decrease in average acceleration of plunger movement. This research provides a reference for optimizing the plunger motion law in pumping machines. [Extracted from the article]

Published
2024

8. New Brain Diseases and Conditions Study Findings Have Been Reported by Researchers at Northwest University (An Eeg Abnormality Detection Algorithm Based On Graphic Attention Network).

Subjects
CENTRAL nervous system diseases, ELECTROENCEPHALOGRAPHY
Abstract

Keywords: Xi'an; People's Republic of China; Asia; Algorithms; Brain Diseases; Brain Diseases and Conditions; Central Nervous System Diseases and Conditions EN Xi'an People's Republic of China Asia Algorithms Brain Diseases Brain Diseases and Conditions Central Nervous System Diseases and Conditions 605 605 1 09/04/23 20230908 NES 230908 2023 SEP 4 (NewsRx) -- By a News Reporter-Staff News Editor at Pain & Central Nervous System Week -- A new study on Central Nervous System Diseases and Conditions - Brain Diseases and Conditions is now available. Xi'an, People's Republic of China, Asia, Algorithms, Brain Diseases, Brain Diseases and Conditions, Central Nervous System Diseases and Conditions. [Extracted from the article]

Published
2023

10. New Findings from Xidian University Describe Advances in Brain Cancer (Fast Brain Tumor Detection Using Adaptive Stochastic Gradient Descent On Shared-memory Parallel Environment).

Subjects
BRAIN tumors, BRAIN cancer, OPTIMIZATION algorithms, DISCRETE wavelet transforms
Abstract

Keywords: Xi'an; People's Republic of China; Asia; Algorithms; Brain Cancer; Cancer; Health and Medicine; Oncology EN Xi'an People's Republic of China Asia Algorithms Brain Cancer Cancer Health and Medicine Oncology 701 701 1 04/03/23 20230403 NES 230403 2023 APR 3 (NewsRx) -- By a News Reporter-Staff News Editor at Clinical Oncology Week -- A new study on Oncology - Brain Cancer is now available. Xi'an, People's Republic of China, Asia, Algorithms, Brain Cancer, Cancer, Health and Medicine, Oncology. [Extracted from the article]

Published
2023