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Application of blockchain technology in railway information sharing research 5

Application of blockchain technology in railway information ...

引用

5th international conference on Computer Information Science and Application technology, CISAT 2022

作者： Liu, Hengjiang Zheng, Yunshui College of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou China

ISBN: (纸本)9781510660076

As new information technology, blockchain has produced a new computing model and penetrated various industries, realizing the transformation from information Internet to value Internet and triggering a new round of technological innovation and revolution. Blockchain has great potential and a wide range of applications. Currently, its application fields are constantly expanding and there are application scenarios in many fields. It has also been widely used in the railway industry. For example, information sharing of data generated in railway construction and security guarantee of data flow are important development directions of railway construction in the future. All these require data exchange between the railway and other industries, but data exchange is difficult in the following aspects: (1) the traditional data exchange process requires the exchange service manager, who can access, utilize and control all exchanged data. No matter which party chooses to assign the role to the manager, other business parties will lose the effective supervision and management of exchanged data;(2) there is business competition between the railway and other transportation industries. the mining and analysis of exchange data by competitors make all parties face pressure. How establish an effective trust mechanism is a difficult problem. (3) through the traditional centralized database to achieve data sharing, hackers only need to attack the exchange database to obtain data, which increases the risk of data leakage. In this paper, the Byzantine redundant error algorithm (PBFT) is used to ensure the safety and accuracy of the system. © 2022 SPIE.

关键词： Blockchain

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An Exploration of Photovoltaic Performance of the Rb2SnI6using DFT and SCAPS-1D 5

An Exploration of Photovoltaic Performance of the Rb2SnI6usi...

引用

5th international conference on Devices for Integrated Circuit, DevIC 2023

作者： Ravidas, Babban Kumar Das, Abhijit Roy, Mukesh Kumar Samajdar, Dip Prakash PDPM Indian Institute of Information Technology Design and Manufacturing Department of Natural Science Jabalpur482005 India PDPM Indian Institute of Information Technology Design and Manufacturing Department of Electronics and Communication Engineering Jabalpur482005 India

ISBN: (纸本)9798350347265

Perovskite with organic and lead-based cations work well, but their toxicity and stability have hindered their commercialization. In this study, we used WIEN2k software to perform first-principles calculations based on density functional theory (DFT) framework to determine the optical and electronic properties of the proposed perovskite material Rb2SnI6 to be used as an absorber for solar cells (SCs). the DFT results for band gap, carrier mobility, effective densities, and absorption spectra are put into the SCAPS (Solar Cell Capacitance Simulator)-lD software to estimate how well the proposed perovskite solar cell (PSC) structure (FTO/TiO2/Rb2SnI\epsilon/PTAA/Au) will work as a photovoltaic device. TiO2 and PTAA are employed as electron and hole transport materials respectively. We have also investigated the device performance with different organic hole transport layers (HTLs). the optimized series resistance (Rs) of 1 \Omega. cm2, Shunt resistance (Rsh) of 1 0^4\Omega. cm2, defect density of 1013cm -3, and thickness of 0.8 µm was used for the final simulation. the proposed device after optimization exhibits a Jsc of 40.4 mA/cm 2,Voc of 0. 72V, FF of 79.7 %, and PCE of 22.4 %. We also investigated the quantum efficiency (QE) of the proposed PSCs. Combination of this computational and simulation analysis of non-toxic Rb2SnI6 double perovskite (DP) reveals that it is advantageous for potential SC applications. © 2023 IEEE.

关键词： Density functional theory

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Detection and Prognosis of Pulmonary Tuberculosis Using ML Classifiers with Soft Computing 5

Detection and Prognosis of Pulmonary Tuberculosis Using ML C...

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5th IEEE international conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Bisht, Girish Singh Ganesh, D. Kumar, Santosh Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Department of Internet of Things Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350383522

Several intriguing research works on soft computing techniques have recently been presented and for the creation of a pulmonary TB diagnosis system, researchers continue to build an accurate and trustworthy intelligent decision-making approach. the current diagnostic testing system processes are cumbersome and time-consuming to analyse. Since increased sensitivity and specificity can be attained, the diagnosis of TB still has to be improved upon using new speedy and accurate diagnostic models and procedures, which will help with disease prevention and control. therefore, this review paper's significance lies in its ability to discriminate between the many soft computing methodologies used to help the diagnosis, identification, prediction, and intelligent categorization of pulmonary TB illness. Researchers and medical professionals anticipate employing soft computing methods in the field. 'Artificial neural networks, genetic algorithms, support vector machines, fuzzy logic', and others are a few of these. the most recent diagnostic techniques involve artificial neural networks. Predictive inference accuracy and easy-to-optimize, adoptable non-linear modelling of large data sets are some additional advantages of artificial neural networks, showing that they could be an important decision support tool in a variety of industries, including medicine. © 2024 IEEE.

关键词： Artificial Neural Network Fuzzy and Fuzzy Logic Genetic Algorithm Pulmonary Tuberculosis Support Vector Machine

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SAR data Expansiontechnology Based on Improved DCGAN 8

SAR Data Expansiontechnology Based on Improved DCGAN

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8th international conference on Information Systems engineering, ICISE 2023

作者： Qiu, Jiangxin Army Aviation Institute Beijing China

ISBN: (纸本)9798350307009

Due to the difficulty of obtaining SAR images for non-cooperative targets, the application and development of SAR target recognition technology is greatly limited. this paper proposes a method based on improved DCGAN for SAR image data augmentation. By making appropriate improvements to the DCGAN network, the quality of the SAR images generated by the network under small sample conditions is effectively improved. Finally, the experimental results of the sample data set expansion effect are verified by YOLO v5. the experiments show that compared with two typical GAN models, DCGAN and WGAN, the SAR sample data set expanded by the improved DCGAN not only has high image quality, but also can effectively improve the recognition effect of the recognition network. © 2023 IEEE.

关键词： Synthetic aperture radar

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Android Malware Detection based on Feature-pair Bonding: A Hybrid Detection Model 5

Android Malware Detection based on Feature-pair Bonding: A H...

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5th IEEE international conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Gupta, Rahul Sharma, Kapil Garg, R.K. Delhi Technological University Department Of Information Technology New Delhi India Deenbandu Chhotu Ram University Of Science & Technology Department Of Mechanical Engineering Sonipat India

ISBN: (纸本)9798350330861

Android has emerged as the dominant operating system over the past decade, enjoying widespread usage. However, its popularity has also made it an attractive target for malware proliferation. One reason behind this vulnerability is Android's acceptance of app installations from unauthorized sources, which gives a window to malicious code writers to disseminate applications malicious in nature which in turn compromise the Android device. To tackle this issue, much research in the literature tried to develop malware analysis and detection systems that employ both static and dynamic analysis techniques. these approaches aim to identify and mitigate malware threats. However, existing research in this field still faces challenges in terms of efficiently and accurately detecting malware. Moreover, achieving accurate malware detection often requires significant resources, which can be a concern on resource-limited mobile devices. Despite advancements, the current state of research struggles to strike a balance between detection accuracy and resource utilization, particularly in the context of mobile devices with limited capabilities. In the current research paper, we present a new methodology for constructing a hybrid malware detection model that operates independently without relying on a pre-existing Machine Learning classifier. Our proposed model operates by leveraging the concept of feature-pairs, where pairs of features that exhibit strong correlations are identified. By calculating the feature-pair scores, we determine whether an application is benign or malicious based on these scores. this self-sufficient model eliminates the need for an external classifier, offering a unique approach to malware detection. © 2023 IEEE.

关键词： Mobile security

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A Review on Diabetes Prediction Using Machine Learning Techniques 5th

A Review on Diabetes Prediction Using Machine Learning Techn...

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5th international conference on Entrepreneurship, Innovation, and Leadership, ICEIL 2023

作者： Tanwar, Alka Bhatia, Pradeep Kumar Department of Computer Science and Engineering Guru Jambheshwar University of Science and Technology Hisar India

ISBN: (纸本)9789819716814

Diabetes is a chronic disease that affects a large number of people worldwide. If you have this illness even once, you will have it for the rest of your life. According to the World Health Organization (WHO), it is one of the top ten deadliest illnesses in the world. Having an excess of glucose in the blood can harm health and cause heart disease, kidney disease, nerve problems, and many other high-risk problems. However, diabetes can be a serious condition if not handled properly. Many of these issues can be prevented with effective management and regular checkups. Machine learning and data mining techniques have emerged as powerful tools for diabetes prediction, leveraging the analysis of large-scale datasets to identify patterns and risk factors. the goal of this study is to analyze different existing research and find a more efficient model in this field. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Forecasting

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Research on spatial development strategy of Daxu ancient town scenic spot based on big data analysis 22

Research on spatial development strategy of Daxu ancient tow...

引用

5th international conference on Computer Science and Software engineering, CSSE 2022

作者： Sun, Shuo School of Tourism and Landscape Architecture Guilin University of Technology China Guangxi Institute of Tourism Industry Guilin University of Technology China

ISBN: (纸本)9781450397780

In the era of big data and information, it is of great significance to apply big data to the study of tourism spatial development strategies of scenic spots for effective protection and rational utilization of resources. Daxu Ancient Town is a typical representative of Guilin Lijiang River Scenic Area that pays equal attention to history and culture. this paper selects it as the research object, crawls the big data of tourists' travel notes in recent years from Ctrip Travel, uses ROST Content Mining 6 software to conduct text analysis on the data of tourists' travel notes in Daxu Ancient Town, deeply analyzes tourists' image perception of the ancient town from key word frequency, semantic emotion and other aspects, and clarifies the existing problems in the scenic spot, Explore the core resources of scenic tourism, and then put forward suggestions on space protection and development. © 2022 ACM.

关键词： big data

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Exploration of Multi-objective Soft Subspace Clustering Based on data Reliability 5

Exploration of Multi-objective Soft Subspace Clustering Base...

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5th international conference on Advances in Electrical engineering and Computer Applications, AEECA 2024

作者： Mao, Lina Tang, Linyan Guangdong Light Industry Vocational and Technical University Guangzhou China

ISBN: (纸本)9798350355253

With the advent of the era of information and data, a large amount of data has been accumulated in various fields. How to use these data effectively and tap its potential value has become an urgent problem. Cluster analysis is an important method in data mining, its purpose is to group similar objects into one class, so that objects in the same class are as similar as possible, and objects in different classes are as different as possible. However, traditional clustering methods are often based on full space, which may lead to unsatisfactory results in the face of complex data sets, especially in high-dimensional space. therefore, subspace clustering has become a research hotspot in recent years. the purpose of subspace clustering is to find the local structure of the data, so as to obtain more accurate clustering results. In addition, the reliability of data is also a factor that cannot be ignored in cluster analysis. the quality of data is often uneven due to possible errors and noise during data collection, storage and processing. Using this data directly for clustering can result in incorrect clustering results. therefore, how to effectively consider data reliability and integrate it into subspace clustering algorithm is a problem worth studying. In this paper, a filtered multi-objective soft subspace clustering algorithm framework R-MOSSC based on data reliability is proposed, and an algorithm example AMGA2SC is given. © 2024 IEEE.

关键词： data reliability

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A Review on Internet of things: Communication Protocols, Wireless Technologies, and Applications 5th

A Review on Internet of Things: Communication Protocols, Wir...

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5th international conference on Communication, Device and Networking, ICCDN 2021

作者： Garg, Meenu Kaur, Gurjinder Singh, Gurmehr Sandhu, Gursharan Gupta, Sheifali Nayak, Soumya Ranjan Ijaz, Muhammad Fazal Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Amity School of Engineering and Technology Amity University Uttar Pradesh Noida India Department of Intelligent Mechatronics Engineering Sejong University Seoul05006 Korea Republic of

ISBN: (纸本)9789811920035

Internet of things (IoT) is a cloud-based "extensive global network" that connects numerous devices. Various devices are connected to the Internet for acquiring and storing the data. With the growth of technology, wireless networks, and affordable computer chips, everything can be integrated into the IoT. Wireless IoT can utilize a variety of different wireless communication technologies and protocols to connect various smart devices. Recent advancements in communication protocols and data processing permit the description of a new sort of restricted communication in terms of how objects communicate with one another on the Internet of things. this review paper presents a novel classification for the various traditional IoT network protocols and highlights different wireless IoT technologies along with their applications. In addition, comparative analysis of different features of IoT communication protocols is also presented. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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SELMAnalyzer: An APP Privacy Leakage Analysis Method Based on Program Execution Logic 5

SELMAnalyzer: An APP Privacy Leakage Analysis Method Based o...

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5th international conference on Advances in Electrical engineering and Computer Applications, AEECA 2024

作者： Li, Jingwei Liu, Tao Zhang, Ruoding Zhang, Yan Song, Xiaoyi Shang, Chong University of Chinese Academy of Sciences Institute of Information Engineering Chinese Academy of Sciences School of Cyberspace Security Beijing China MIIT China Academy of Information and Communications Technology Key Laboratory of Mobile Application Innovation and Governance Technology Beijing China University of Chinese Academy of Sciences China Telecom Co. Ltd. School of Cyberspace Security Beijing China Chinese Academy of Sciences Institute of Information Engineering Beijing China

ISBN: (纸本)9798350355253

Mobile phones have become an indispensable part of people's daily lives, but many mobile applications continue to obtain and use people's private data through malicious behaviors hidden behind normal functions. Existing work provides many methods to detect malicious applications' behaviors. However, the analysis and detection technology for the logic triggering process and implementation methods of potential malicious behaviors still need further improvement. this paper proposes an APP privacy leakage analysis method called SELMAnalyzer. this method builds a software execution logic analysis model SELM(Software Execution Logical Model) based on a graph structure to model the dynamic execution logic and implementation methods of Android applications and mine the privacy leakage problems of applications hidden behind normal UI function interfaces or normal components. At the same time, the method proposed in this paper is verified using a real Android application dataset with an accuracy rate of 89%. Compared with similar methods, it can intuitively display the complete calling process of privacy theft behavior from the UI interface to the underlying functional functions and effectively detect hidden malicious behaviors. © 2024 IEEE.

关键词： Information leakage

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