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FCA-based θ-iceberg core decomposition in graphs

Journal of Ambient Intelligence and Humanized Computing 2024年第2期15卷 1423-1428页

作者： Hao, Fei Xinchang, Khamphaphone Park, Doo-Soon Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an China School of Computer Science Shaanxi Normal University Xi’an710119 China Department of Computer Science and Engineering Soonchunhyang University Asan31538 Korea Republic of Department of Computer Software Engineering Soonchunhyang University Asan31538 Korea Republic of

Complex networking analysis is a powerful technique for understanding both complex networks and big graphs in ubiquitous computing. Particularly, there are several novel metrics, such as k-clique and k-core are proposed in order to study the relative importance of nodes in complex networks. Among of those metrics, k-core analysis is an effective approach for simplifying graphical structure. However, the relation between k and the scale of networks is not explored in most existing literature. Toward this end, this paper formulate a new research problem, θ-Iceberg Core decomposition in graphs, which is able to incorporate a parameter θ (0 © Springer-Verlag GmbH Germany, part of Springer Nature 2017.

关键词： Formal concept analysis

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Congestion Control Method for Campus Opportunity Network Based on Ant Colony Algorithm

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Chinese Journal of Electronics 2025年第2期34卷 576-585页

作者： Li Peng Cao Yumei Jia Huan Wang Xiaoming Wu Xiaojun School of Computer Science Shaanxi Normal University Xi’an 710119 China Key Laboratory of Intelligent Computing and Service Technology for Folk Song Ministry of Culture and Tourism Xi’an 710119 China Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an 710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi’an 710119 China Xi’an Key Laboratory of Cultural Tourism Resources Development and Utilization Xi’an 710062 China

Due to the limited storage resources of portable devices, congestion control has become a hot direction in opportunity networks. To address the issue of heavy loads on certain nodes, which can impact routing efficiency and overall network performance, this paper proposes a load-balancing opportunity routing algorithm based on ant colony optimization (LBOR) in a campus environment. The congestion status is represented by the ratio of message drop receptions within a certain period and the occupancy of the cache. Path selection is based on the concentration of pheromones and the pheromones on the path are updated when a data transmission is completed. In the event of congestion, the algorithm prevents a large amount of data from entering the node and unloads the data to other nodes, even if they are not the optimal relay nodes. Experimental results demonstrate that the proposed algorithm effectively improves data transmission success rates, reduces network loads, and decreases the number of packet losses, especially under low latency conditions.

关键词： Opportunity network Routing protocol Congestion control Cache management

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Radiative cooling for passive thermal management towards sustainable carbon neutrality

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National science Review 2023年第1期10卷 87-97页

作者： Jun Liang Jiawei Wu Jun Guo Huagen Li Xianjun Zhou Sheng Liang Cheng-Wei Qiu Guangming Tao Wuhan National Laboratory for Optoelectronics and Optics Valley Laboratory Huazhong University of Science and Technology Department of Electrical and Computer Engineering National University of Singapore MOE Key Laboratory of Thermo-Fluid Science and Engineering School of Energy and Power Engineering Xi'an Jiaotong University Key Laboratory of Education Ministry on Luminescence and Optical Information Technology National Physical Experiment Teaching Demonstration CenterDepartment of PhysicsSchool of Physical Science and Engineering Beijing Jiaotong University State Key Laboratory of Material Processing and Die &Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology

Photonic structures at the wavelength scale offer innovative energy solutions for a wide range of applications,from high-efficiency photovoltaics to passive cooling,thus reshaping the global energy *** cooling based on structural and material design presents new opportunities for sustainable carbon neutrality as a zero-energy,ecologically friendly cooling *** this review,in addition to introducing the fundamentals of the basic theory of radiative cooling technology,typical radiative cooling materials alongside their cooling effects over recent years are summarized and the current research status of radiative cooling materials is outlined and ***,technical challenges and potential advancements for radiative cooling are forecast with an outline of future application scenarios and development *** the future,radiative cooling is expected to make a significant contribution to global energy saving and emission reduction.

关键词： photonic structures radiative cooling energy saving and emission reduction carbon neutrality

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Image analysis and machine learning-based malaria assessment system

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Digital Communications and Networks 2022年第2期8卷 132-142页

作者： Kyle Manning Xiaojun Zhai Wangyang Yu School of Computer Science and Electronic Engineering University of EssexColchesterCO43SQUK Key Laboratory of Modern Teaching Technology Ministry of EducationSchool of Computer Science Shaanxi Normal UniversityXi'anChina

Malaria is an important and worldwide fatal disease that has been widely reported by the World Health Organization(WHO),and it has about 219 million cases worldwide,with 435,000 of those *** common malaria diagnosis approach is heavily reliant on highly trained experts,who use a microscope to examine the ***,there is a need to create an automated solution for the diagnosis of *** of the main objectives of this work is to create a design tool that could be used to diagnose malaria from the image of a blood *** this paper,we firstly developed a graphical user interface that could be used to help segment red blood cells and infected cells and allow the users to analyze the blood ***,a Feed-forward Neural Network(FNN)is designed to classify the cells into two *** achieved results show that the proposed techniques can be used to detect malaria,as it has achieved 92%accuracy with a database that contains 27,560 benchmark images.

关键词： Malaria assessment system Image analysis Image segmentation Artificial intelligence

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Adaptive Compression-Encryption Scheme for Medical Image Based on Improved Compressive Sensing and Deoxyribonucleic Acid Coding-Compression

Adaptive Compression-Encryption Scheme for Medical Image Bas...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Xue, Xianglian Jin, Haiyan Zhou, Changjun Xi'an University of Technology School of Computer Science and Engineering Xi'an China Shaanxi University of Chinese Medicine Section of Computer Teaching and Research Xianyang China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Zhejiang Normal University School of Computer Science and Technology Jinhua China

ISBN: (纸本)9798350386226

Medical images often occupy large storage space and contain patient privacy or sensitive information, which makes them difficult and unsafe to be transmitted through the network. This paper proposed an adaptive compression-encryption scheme based on improved compressive sensing (CS) and deoxyribonucleic acid (DNA) coding-compression, which helps to solve the above problem. In the proposed scheme, first the original medical image was compressed to a floating point CS matrix using the discrete wavelet transform and the partial Hadamard matrix. The CS matrix was then normalized and rounded for matrix quantification. The result of quantification was fed to DNA fixed encoding and DNA run length coding for encryption and secondary compression. Finally the compressed-encrypted image was obtained after DNA dynamic encoding-decoding and regroups operation. The proposed scheme was tested against 9 images and proved to be effective in reducing the quantization errors and enhancing the compression performance. For instance, when the benchmark compression ratio (CR) is 0.5, the CR can be reduced by 5%(CR = 0.4453) ∼ 23%(CR = 0.2636), with the corresponding peak signal-to-noise ratio values consistently surpassing the benchmark. Furthermore, the execution of DNA compression and DNA dynamic encoding-decoding provided double guarantee for the algorithm's security. © 2024 IEEE.

关键词： Encoding (symbols)

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Semantic Aware Just Noticeable Differences for VVC Compressed Text Screen Content Images 24

Semantic Aware Just Noticeable Differences for VVC Compresse...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Yang, Kaifang Zhao, Xinrong Gong, Yanchao School of Computer Science Shaanxi Normal University Xi'an China School of Communication and Information Engineering Xi'an University of Posts and Telecommunications Xi'an China Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University China

ISBN: (纸本)9798400706868

With the rapid development of multimedia applications such as online education, remote conferences, and telemedicine, an emerging type of image known as the text screen content image (TSCI) has gained widespread utilization. Distinguishing from natural images captured by cameras, TSCI is generally generated or rendered by computers and exhibits significant differences in content characteristics. Notably, TSCI primarily comprises text, which is a symbol system uniquely defined by humans with specific semantics. As an important carrier for transmitting semantic information, the quality of text in TSCI significantly affects the subjective perception experience of multimedia system users. Just noticeable difference (JND) is a widely studied image quality measure that is theoretically closest to human perception. However, the traditional JND (T-JND) experiments fail to distinguish text from other image contents, ignoring the significant impact of text semantic readability on image quality. This paper, for the first time, focuses on the impact of text semantics on the quality of TSCI, and JND experiments for TSCIs compressed by the state-of-the-art versatile video coding (VVC) standard are explored and discussed. Specifically, a matching TSCI dataset is first established. Using the dataset, image subjective observation experiments are further designed and carried out to construct the traditional JND (T-JND) experiment as well as the semantic aware JND (S-JND) experiment. By comparing the experimental results, crucial conclusions are reached, including the fact that the S-JND experiment provides a more precise description of the TSCI quality compared to the T-JND experiment. These conclusions have important guiding significance for the subsequent development of efficient JND models suitable for TSCIs compressed by VVC. © 2024 ACM.

关键词： Multimedia systems

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Multi-factor Balanced Feedback and Reliability Analysis of Adaptive Cruise Control System Based on Petri Nets

Multi-factor Balanced Feedback and Reliability Analysis of A...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Guo, Qi Yu, Wangyang Qi, Liang Shaanxi Normal University Key Laboratory of Modern Teaching Technology Ministry of Education School of Computer Science Xi'an China Shandong University of Science and Technology College of Computer Science and Engineering Qingdao China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

The intelligent transportation system has developed rapidly in recent years, and its reliability and safety have also attracted a lot of attention. The Adaptive Cruise control (ACC) system is a significant achievement of traffic intelligence. The principle of the ACC system is the process of balance feedback between the relative speed and distance of the front and current vehicles. In this paper, the running principle of ACC system is abstracted, and the Balanced Feedback Net (BFN) is proposed to model and analyze it based on Petri nets. The reachable marking graph and the incidence matrix of Petri nets are used to analyze the BFN model. The analysis results show a certain risk of rear-end collision in the balance feedback process of the ACC system. In this regard, we give a relevant risk identification algorithm to reduce the risk of rear-end collision and improve the reliability of the ACC system. © 2022 IEEE.

关键词： Adaptive cruise control

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Research on Generating Xi'an Drum Music Based on Generative Adversarial Network

Research on Generating Xi'an Drum Music Based on Generative ...

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2023 IEEE International Conference on Sensors, Electronics and computer engineering, ICSECE 2023

作者： Liang, Tianmian Li, Peng Cao, Yumei Wu, Xiaojun Zhao, Huifang Qi, Chenye School of Computer Science Shaanxi Normal University Xi'an710119 China Shaanxi Normal University School of Computer Science Xi'an710119 China Ministry of Education Key Laboratory of Modern Teaching Technology Xi'an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi'an710119 China Xi'An Key Laboratory of Cultural Tourism Resources Development and Utilization Xi'an710062 China Shaanxi Normal University School of Music Xi'an710119 China

ISBN: (纸本)9798350313734

Currently most AI music generator platforms mainly focus on creating modern music, without focusing on the creation of folk music. And most music generation neural network models use recursive neural networks and their variants, resulting in excessively repetitive music information, greatly reducing the fun of music. When using only generative adversarial networks (GANs) to generate music, it is easy to experience unstable training, vanishing gradients, and mode collapse. Failure to consider time dependence can reduce the authenticity of generated music. In order to solve the problem that most of the conventional deep learning GAN music generation network models do not consider music theory rules in music generation and Xi'an drum music faces the scarcity of tracks and difficulties in composition, we proposed a GAN network music generative model based on music theory rules and characteristics of Chinese Folk Songs. When generating music, the generator CNN and the regulator CNN train together, and generate music melodies under the constraints of the voice column CNN module. The generated results are sent to the discriminator CNN, which submits feedback to the generator CNN for competition, to compensate for the shortcomings of previous technology and ultimately generate better melodies, thereby improving the authenticity, sweetness, and rhythm of the generated music. © 2023 IEEE.

关键词： Music

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A Novel Hybrid Makeup Transfer Method Based on Latent Vector Manipulation 2

A Novel Hybrid Makeup Transfer Method Based on Latent Vector...

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2nd International Conference on Artificial Intelligence and computer Information Technology, AICIT 2023

作者： Li, Yumiao Li, Peng Shen, Ziqi Li, Wenhui Key Laboratory of Intelligent Computing and Service Technology for Folk Song Ministry of Culture and Tourism Xi'an710119 China School of Computer Science Shaanxi Normal University Xi'an710119 China Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi'an710119 China Xi'an Key Laboratory of Cultural Tourism Resources Development and Utilization Xi'an710062 China

ISBN: (纸本)9798350302950

With the development of image processing technology and the improvement of people's living standards, there is a wide demand for makeup services in society. In this paper, we focus on style transfer and its application in automatic makeup generation, and propose a facial feature fusion recovery technique that utilizes an adaptive spatial feature fusion attention mechanism to solve the problem of inconsistent clarity between the reference image and the source image. By using the moving least squares method to calculate similarity on each sample image, the reference image set achieving the optimal makeup transfer effect can be efficiently selected. At the same time, the latent vector can be manipulated to achieve on-demand hybrid makeup generation and de-makeup image generation. By assigning different weights, the proportion of makeup in specific reference image in the final makeup effect can be controlled, and a new mixed makeup style can be obtained. The experiment shows that the proposed model can achieve state-of-the-art makeup transfer effect, and can also generate suitable makeup effects for low resolution input images. © 2023 IEEE.

关键词： Image enhancement

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A Sentiment Classification Model Based on Attention TIG-CNN-BiGRU

A Sentiment Classification Model Based on Attention TIG-CNN-...

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2023 International Conference on Culture-Oriented science and Technology, CoST 2023

作者： Li, Peng Liang, Tianmian An, Ning Zhang, Lichen Wu, Xiaojun Wang, Xiaoming Lu, Junling Key Laboratory of Intelligent Computing and Service Technology for Folk Song Ministry of Culture and Tourism Xi'an710119 China School of Computer Science Shaanxi Normal University Xi'an710119 China Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi'an710119 China Xi'An Key Laboratory of Cultural Tourism Resources Development and Utilization Xi'an710062 China

ISBN: (纸本)9798350357998

The uniqueness of folk song expression forms and complex semantic relationships, and the existing models are not good at recognizing the emotion category of folk song lyrics, so an attention TIG-CNN-BiGRU based emotion classification model is proposed. That is, we first propose a text vector representation based on TF-IDF feature weighted pretrained Glove word embedding to extract important features by assigning different weights, and then combine CNN, BiGRU and attention mechanism to extract local features using multi-scale convolutional kernel CNN, BiGRU to capture semantic dependencies of long sequences and attention mechanism to assign high weights to key features to make the model have better lyrics recognition ability. Experiments comparing the model with various baseline methods on the lyrics dataset show that the model outperforms other lyrics sentiment classification models in terms of sentiment classification accuracy and various other metrics. © 2023 IEEE.

关键词： Deep neural networks

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