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Recent Advances in computer science and Information engineering 1

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丛书名： Lecture Notes in Electrical engineering

1000年

作者： Zhihong Qian Lei Cao Weilian Su Tingkai Wang Huamin Yang

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Research on Tibetan Tourism Viewpoints Information Generation System Based on LLM

Research on Tibetan Tourism Viewpoints Information Generatio...

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Intelligent Computing and Wireless Optical Communications (ICWOC), International Conference on

作者： Jinhu Qi Shuai Yan Wentao Zhang Yibo Zhang Zirui Liu Ke Wang Department of Artificial Intelligence Chengdu Jincheng College Chengdu China Department of Software Engineering Chengdu Jincheng College Chengdu China Department of Computer Science Chengdu Jincheng College Chengdu China

ISBN: (数字)9798350374377

ISBN: (纸本)9798350374384

Tibet, ensconced within China’s territorial expanse, is distinguished by its labyrinthine and heterogeneous topography, a testament to its profound historical heritage, and the cradle of a unique religious ethos. The very essence of these attributes, however, has impeded the advancement of Tibet’s tourism service infrastructure, rendering existing smart tourism services inadequate for the region’s visitors. This study delves into the ramifications of informational disparities at tourist sites on Tibetan tourism and addresses the challenge of establishing the Large Language Model (LLM) evaluation criteria. It introduces an innovative approach, the DualGen Bridge AI system, employing supervised fine-tuning techniques to bolster model functionality and enhance optimization processes. Furthermore, it pioneers a multi-structured generative results assessment framework. Empirical validation confirms the efficacy of this framework. The study also explores the application of the supervised fine-tuning method within the proprietary DualGen Bridge AI, aimed at refining the generation of tourist site information. The study’s findings offer valuable insights for optimizing system performance and provide support and inspiration for the application of LLM technology in Tibet’s tourism services and beyond, potentially revolutionizing the smart tourism industry with advanced, tailored information generation capabilities.

关键词： Bridges Adaptation models Accuracy Computational modeling Diversity reception LoRa computer architecture

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Developing Common Bacteria Blight Disease Detection Model for Common Bean Using Deep Learning Approach

Research Square

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Research Square 2023年

作者： Senbato, Assefa Ayalew, Tsion Department of Computer Science Informatics College Bule Hora University Bule Hora Ethiopia Department of Software Engineering College of Informatics Bule Hora University Bule Hora Ethiopia

In many farm locations in Ethiopia, common bacterial blight (CBB), one of the common bean's known diseases, impacts the crop, lowers yield by up to 45 percent of the production, and also has an impact on seed quality. Recently, many researchers have tried to overcome this disease by conducting field surveys, crop management activities, crop rotation, chemical treatment, proper cultural practices, and integrated disease management. However, this method is a very tedious, time-consuming, and costly technique that requires more experts. To overcome these issues, a modern deep learning approach is proposed for the early detection of common bean disease. The three main phases are followed for the proposed approach. Firstly, the collection of healthy and diseased common bean images with the help of domain experts from different agricultural research centers is done. Then the design of a modern convolutional neural network that can detect and classify the input image as diseased or healthy is done. Lastly, the designed model is trained and evaluated. During the classification, the designed model is assessed against the performance of two pre-trained models (VGG16 and InceptionV3) to accurately detect the common bean disease. The performance of the proposed model is evaluated using a dataset that contains total images of 3,135 with two classes of healthy and common bacterial blight disease. We have used data augmentation techniques to generate more images to fit the proposed model. Based on our experimental results, the best performance is achieved using a proposed model with a classification accuracy of 98.2% for early detection of common bacterial blight disease on a common bean leaf. The result of this study can help farmers and domain experts by detecting CBB disease at an early stage for the necessary treatments. © 2023, CC BY.

关键词： Diseases

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ADAS: Adjust directional antenna with sensor hints

ADAS: Adjust directional antenna with sensor hints

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Xiaonan Guo Kaishun Wu Qian Zhang Singapore Management University Guangzhou HKUST Fok Ying Tung Research Institute College of Computer Science and Software Engineering Shenzhen University Hong Kong University of Science and Technology

Recently, directional antenna has shown great potential to deploy in indoor environments and significantly improve wireless network capacity. Due to its directionality, the orientation of antenna becomes a critical issue especially for moving devices while exchanging data with directional AP. Previous work largely focused on scenarios, in which the clients are stable at most of the time and addressed the issue of moving device by remeasurement of the whole network information such as received signal strength, conflict graph. However, re-collection of such information will introduce significant overhead. To adjust directional antenna quickly and wisely in real-time, in this paper, we introduce ADAS, a system that adjust orientation of directional antenna with sensor hints from mobile devices. The key idea of ADAS system is to obtain the movement behavior and location information from sensors equipped in mobile devices, then the AP adapts its orientation accordingly. We implement ADAS system on commercial directional antenna and evaluate its performance under different configurations. The experiment results demonstrate that directional AP in ADAS system could adapt to mobility with less overhead.

关键词： Directional antennas Acceleration Directive antennas Portable computers Accelerometers Smart phones

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Comparison of Particle Swarm Optimization algorithms in Wireless Sensor Network node localization

Comparison of Particle Swarm Optimization algorithms in Wire...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Cen Cao Qingjian Ni Xushan Yin School of Computer Science and Engineering Southeast University Nanjing China College of Software Engineering Southeast University Nanjing China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China

The node localization in Wireless Sensor Network (WSN) presently plays an important role in the field of applications. Particle Swarm Optimization (PSO) algorithm is a typical swarm intelligence method. Researchers propose many PSO variants and try to apply PSO algorithm to the related problems in WSN. This paper focuses on the WSN node localization using PSO algorithm. This paper conducts the experiment simulation, comparison and evaluation work in the node localization using PSO algorithm. The performance of different PSO variants with different population topologies is analyzed. Experiment simulations show that WSN node localization using PSO algorithm can get good performance in ring topology and square topology. In particular, the two newly proposed PSO variants (GDPSO and LDPSO) have good performance on this problem. This paper proposes some useful conclusions, which will provide a valuable reference to WSN engineering field.

关键词： Topology Wireless sensor networks Sociology Statistics Heuristic algorithms Particle swarm optimization Standards

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Surface Reconstruction from Normals: A Robust DGP-based Discontinuity Preservation Approach

Surface Reconstruction from Normals: A Robust DGP-based Disc...

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IEEE/CVF Conference on computer Vision and Pattern Recognition

作者： Wuyuan Xie Miaohui Wang Mingqiang Wei Jianmin Jiang Jing Qin College of Computer and Software Engineering Shenzhen University (SZU) Guangdong Key Laboratory of Intelligent Information Processing College of Information Engineering School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics School of Nursing Hong Kong Polytechnic University

ISBN: (纸本)9781728132945

In 3D surface reconstruction from normals, discontinuity preservation is an important but challenging task. However, existing studies fail to address the discontinuous normal maps by enforcing the surface integrability in the continuous domain. This paper introduces a robust approach to preserve the surface discontinuity in the discrete geometry way. Firstly, we design two representative normal incompatibility features and propose an efficient discontinuity detection scheme to determine the splitting pattern for a discrete mesh. Secondly, we model the discontinuity preservation problem as a light-weight energy optimization framework by jointly considering the discontinuity detection and the overall reconstruction error. Lastly, we further shrink the feasible solution space to reduce the complexity based on the prior knowledge. Experiments show that the proposed method achieves the best performance on an extensive 3D dataset compared with the state-of-the-arts in terms of mean angular error and computational complexity.

关键词： Surface reconstruction discontinuities angular misalignment Solution space CONSERVATION optimum performance Arts complexity classes

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Re-Smote: A Novel Imbalanced Sampling Method Based on Smote with Radius Estimation

SSRN

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SSRN 2023年

作者： Huiyuan, Jiang Yiyang, Li Baoyu, Liu Keming, Mao Yuhai, Zhao Software College Northeastern University Shenyang China College of Computer Science and Engineering Northeastern University Shenyang China Shenyang Edge Computing Technology Innovation Center Shenyang China

Imbalance is a distinctive feature of many datasets, and how to make the dataset balanced become a hot topic in machine learning field. Synthetic Minority Oversampling Technique (SMOTE) is the classical method to solve this problem. Although there are many researches about SMOTE, there is still problem of synthetic sample singularity. In order to solve the issues of class imbalance and diversity of generated samples, this paper proposes a hybrid resampling method for binary imbalanced data sets, RE-SMOTE, which is designed based on the improvements of two oversampling methods PF-SMOTE and SMOTE-WENN. First, the minority class sample points are divided into safe minority and boundary minority as used in PF. The boundary minority samples are re-organized by linear interpolation with nearest majority class samples, and the safe minority samples are re-organized by circle range that take the initial safe minority samples as center and the distance from the nearest majority samples as radius. Second, the noise samples are further cleaned according to relative density with WENN. Relative density is computed by ratio between number of majority sample and minority sample among reverse k-nearest neighbor samples. To verify the effectiveness and robustness of the proposed model, we conducted a comprehensive experimental study on 40 datasets selected from real applications. The experimental results show the superiority of RE-SMOTE over other state-of-the-art methods. © 2023, The Authors. All rights reserved.

关键词： Nearest neighbor search

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Detection of Deepfakes: Protecting Images and Vedios Against Deepfake

Detection of Deepfakes: Protecting Images and Vedios Against...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Ying Tian Wang Zhou Amin Ul Haq Intelligent Policing Key Laboratory of Sichuan Province Sichuan Police College LuZhou China School of Computer and Software Engineering Xihua University Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

In recent years, with the rapid development of deep learning and computer vision technology, the forgery technology of images and videos has become increasingly mature, posing new challenges to information security and social stability. Behind the re-evolution of deepfake lies the rampant proliferation of fake content, which is used for election tampering, identity fraud, fraud, spreading fake news, and so on. To address these challenges, researchers are constantly exploring and developing image-based deepfake detection techniques, which aim to effectively identify and prevent deepfake content in images and videos. This article will introduce the current development status of deepfake detection technology, present its principles and methods in detail, and look ahead to its future development directions.

关键词： Deep learning Deepfakes computer vision Voting Neural networks Information security Information processing Forgery Fraud computer security

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Timely Status Update in Relay-Assisted Cooperative Communications

arXiv

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arXiv 2023年

作者： Pan, Haoyuan Feng, Jian Chan, Tse-Tin Leung, Victor C.M. Li, Jianqiang The College of Computer Science and Software Engineering Shenzhen University Shenzhen China The Department of Mathematics and Information Technology The Education University of Hong Kong Hong Kong

We investigate the age of information (AoI) of a relay-assisted cooperative communication system, where a source node sends status update packets to the destination node as timely as possible with the aid of a relay node. For time-slotted systems without relaying, prior works have shown that the source should generate and send a new packet to the destination every time slot to minimize the average AoI, regardless of whether the destination has successfully decoded the packet in the previous slot. However, when a dedicated relay is involved, whether the relay can improve the AoI performance requires an in-depth study. In particular, the packet generation and transmission strategy of the source should be carefully designed to cooperate with the relay. Depending on whether the source and the relay are allowed to transmit simultaneously, two relay-assisted schemes are investigated: time division multiple access (TDMA) and nonorthogonal multiple access (NOMA) schemes. In TDMA, the source generates and sends a new packet every other time slot to avoid possible simultaneous transmission with the relay. In NOMA, the source generates and sends a new packet every time slot, thus possibly forming simultaneous transmission from the relay and the source. A key challenge in deriving their theoretical average AoI is that the destination has different probabilities of successfully receiving an update packet in different time slots. We model each scheme using a Markov chain to derive the corresponding closed-form average AoI. Interestingly, our theoretical analysis indicates that the relay-assisted schemes can only outperform the non-relay scheme in average AoI when the signal-to-noise ratio of the source-destination link is below −2dB. Furthermore, comparing the merits of relay-assisted schemes, simulation results show that the TDMA scheme has a lower energy consumption, while the NOMA counterpart typically achieves a lower average AoI. Copyright © 2023, The Authors. All rights res

关键词： Time division multiple access

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Security analysis of delegable and proxy provable data possession in public cloud storage

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Journal of computers (Taiwan) 2017年第4期28卷 23-30页

作者： Ren, Yong-Jun Shen, Jian Wang, Jin Fang, Li-Ming Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China School of Information Engineering Yangzhou University Yangzhou China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China

Cloud storage is now an important development trend in information technology. However, information security has become an important problem to impede it for commercial application, such as data con-fidentiality, integrity, and availability. In this paper, we revisit the two private PDP schemes. We show that the property of correctness cannot be achieved when active adversaries are involved in these auditing systems. More specifically, an active adversary can arbitrarily tamper the cloud data and produce a valid auditing. Moreover, the malicious CSS can put the auditing right to entrust to anyone and control the delegation key and lead to the failure of the subsequent validation work. Finally, we propose a solution using key agreement to resolve the weakness. Our scheme is high efficiency due to removing expensive bilinear computing. Moreover, the verifier is stateless and independent from cloud storage server, which is an important secure property in PDP schemes.

关键词： Cloud storage

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