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Features Responsible for Spread of Zoonotic Disease Brucella: A Study on Central India Population

SN computer science 2025年第1期6卷 1-19页

作者： Namdev, Nishant Makhijani, Richa Dorshetwar, Kirti Parate, Mayur Shukla, Jayshree L. Husain, Aliabbas A. Kashyap, Rajpal S. Department of Basic Sciences Indian Institute of Information Technology Maharashtra Nagpur India Department of Computer Science and Engineering Indian Institute of Information Technology Maharashtra Nagpur India Department of Electronics and Communication Engineering Indian Institute of Information Technology Maharashtra Nagpur India Research Centre Central India Institute of Medical Sciences Maharashtra Nagpur India

Zoonotic diseases pose a growing health risk in developing nations because of the ongoing animal-human interaction. India has experienced significant urbanization in recent years, with a large population migration from rural to urban areas. One of the most common and feared risks to which humans are exposed is zoonotic diseases. Numerous studies conducted in India have identified specific zoonoses, such as Listeriosis, Brucellosis, and Bovine tuberculosis, as extremely important to human health. The rough set method is appropriate for several real-world applications and is a component of the computing strategy. Rough sets offer several noteworthy benefits. The rough sets encounter small data sets and provide helpful techniques for revealing hidden patterns in data. In this work, a cross-sectional study was conducted to investigate the prevalence of zoonosis in the Central India Population. Three states were studied for zoonotic infection prevalence, including Maharashtra, Madhya Pradesh, and Chhattisgarh. A total of 7026 samples were recruited by inclusion and exclusion criteria for the study. The lifestyle and animal exposure data of this population was collected and tested for Brucella. On this data, the rough set approach yielded an accuracy of 87.5% for the Brucella-infected case. Our approach has resulted in selecting features responsible for diagnosing the lifestyle parameters which could result in the spread of Brucella. This research also follows the UNSDG goal of good health, essential to sustainable development. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Brucella Feature selection Pattern recognition Rough sets Zoonotic disease

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RAISE:A Resilient Anonymous Information Sharing Environment

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computer Modeling in engineering & sciences 2023年第12期137卷 2743-2759页

作者： Ning Hu Ling Liu Xin Liu Kaijun Wu Yue Zhao Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China Science and Technology on Communication Security Laboratory The 30th Research Institute of China Electronics Technology Group CorporationChengdu610041China College of Computer Engineering and Applied Math Changsha UniversityChangsha410022China

With the widespread application of cloud computing and network virtualization technologies,more and more enterprise applications are directly deployed in the ***,the traditional TCP/IP network transmission model does not fully consider the information security issues caused by the uncontrollable internet *** security communication solutions represented by encrypted virtual private networks(VPN)are facing multiple security *** fact,during the communication process,the user application needs to protect not only the content of the communication but also the behavior of the communication,such as the communication relationship,the communication protocol,and so *** by blockchain and software-defined networking technology,this paper proposes a resilient anonymous information sharing environment,*** RAISE system consists of user agents,a core switching network and a control cluster based on a consortium *** agents are responsible for segmenting,encrypting,and encapsulating user *** core switching network forwards user traffic according to the rules issued by the controller,and the controller dynamically calculates the forwarding rules according to the security *** from onion routing technology,RAISE adopts the controller to replace the onion routing model,which effectively overcomes the uncontrollability of *** dispersed computing model is introduced to replace the TCP/IP pipeline transmission models,which overcomes the problems of anti-tracking and traffic hijacking that cannot be solved by *** propose a blockchain control plane framework,design the desired consensus algorithmand deploy a RAISE systemconsisting of 150 nodes in an internet *** experimental results show that the use of blockchain technology can effectively improve the reliability and security of the control *** maintaining high-performance network transmission,it further provides network communicatio

关键词： Software-defined anonymous communication network blockchain network communication security

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The Design of Security Algorithm RPBB-24-2 in Circuitous Route Across the Distributed Ledger 8th

The Design of Security Algorithm RPBB-24-2 in Circuitous Rou...

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8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024

作者： Rajaprakash, S. Basha, C. Bagath Karthik Ali, Amjad Rahman, Sahil Siddique, Md. Irshad Saif, Afroj Ansari Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Kommuri Pratap Reddy Institute of Technology Autonomous Telagana Hyderabad India Aarupadai Veedu Institute of Technology Vinayaka Mission Research Foundation Chennai India

ISBN: (纸本)9789819795581

The technology known as Block Chain is one of the technologies that is seeing one of the fastest increase rates around the world. The technique known as blockchain is used to guarantee the security of a variety of data places, despite the fact that customers are not familiar with it. "ChaCha" and "RBJ25" are the names of the algorithms that the user in question continues to utilize, which are considered to be of a lower degree of security. Within the scope of this investigation, the RPBB-24-2 security technique is the one that is being presented. There are two components that are incorporated in the RPBB-24-2 method. These components include encryption and decryption. The RPBB-24-2 methodology has 4 processes. The 1st process is to assign the "Latin Alphabet code" to PT. The 2nd process is to multiply the 4 times using Eq. (1). The 3rd process is to swap the cell values using Encrypted data but start the 0th cell value from upper triangle cell value. The 4th process is to apply the "ChaCha" method in matrix. Finally, the plain text is converted to cipher text. This means that the procedure of decryption is the opposite of the encryption approach. When compared to the approach that is currently in use, the suggested method offers a higher level of security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Blockchain ChaCha Decryption Encryption Performance RBJ25 RPBB-24-2

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Advanced Fake Review Detection via Aspect Extraction and TPA-BiLSTM-CSSA 2

Advanced Fake Review Detection via Aspect Extraction and TPA...

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2nd IEEE International Conference on Data science and Network Security, ICDSNS 2024

作者： Thakkar, Nilam Kumar, Arvind Sukumar, P. Sarode, Deepika G. Patil, Harshal Vijayakumar, E. Ldrp - Institute of Technology & Research Ksv University Svkm Department of Information & Technology Gujarat India School of Computer Applications Mriirs Haryana Faridabad India Nandha Engineering College Department of Computer Science and Engineering Erode India Dr.D.Y.Patil Institute of Technology Department of Engineering Pune Pimpri India Iilm University Department of Computer Science and Engineering Greater Noida India KIT-Kalaignar Karunanidhi Institute of Technology Department of Mca Coimbatore India

ISBN: (纸本)9798350373110

In recent years, methods to detect bogus reviews have attracted the attention of numerous businesses and educational organizations. In order for reviews to accurately represent genuine user experiences and opinions, it is quite challenging to identify fake reviews. Supervised learning has been a popular approach to tackle the problem. The issue is that manually marking fake reviews with a degree of reliability that would be useful for training is very difficult, if not impossible. There are three phases to the suggested strategy preprocessing, feature extraction, and training the model. This proposed employs a series of preprocessing techniques to get the dataset's raw data ready for computational operations. Dimensionality reduction and the quantification of content-related and text-segment-related features comprise feature extraction. To train the model, a TPA-BiLSTM-CSSA was used. On average, the suggested method achieves a higher accuracy of 93.71% than BiLSTM and CSSA. © 2024 IEEE.

关键词： Fake detection

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Probability Based Regression Analysis for the Prediction of Cardiovascular Diseases

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computers, Materials & Continua 2023年第6期75卷 6269-6286页

作者： Wasif Akbar Adbul Mannan Qaisar Shaheen Mohammad Hijji Muhammad Anwar Muhammad Ayaz Department of Computer Science NFC Institute of Engineering and TechnologyMultanPakistan Faculty of Computer Science&Information Technology University of MalayaKuala LumpurMalaysia Department of Computer Science and Information Technology The Islamia University of BahawalpurRahim Yar Khan CampusPunjabPakistan Faculty of Computers and Information Technology University of TabukTabuk47512Saudi Arabia Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Sensor Networks and Cellular Systems(SNCS)research center University of TabukTabuk47512Saudi Arabia

Machine Learning(ML)has changed clinical diagnostic procedures *** in Cardiovascular Diseases(CVD),the use of ML is indispensable to reducing human *** studies focused on disease prediction but depending on multiple parameters,further investigations are required to upgrade the clinical ***-layered implementation of ML also called Deep Learning(DL)has unfolded new horizons in the field of clinical *** formulates reliable accuracy with big datasets but the reverse is the case with small *** paper proposed a novel method that deals with the issue of less data *** by the regression analysis,the proposed method classifies the data by going through three different *** the first stage,feature representation is converted into probabilities using multiple regression techniques,the second stage grasps the probability conclusions from the previous stage and the third stage fabricates the final *** experiments were carried out on the Cleveland heart disease *** results show significant improvement in classification *** is evident from the comparative results of the paper that the prevailing statistical ML methods are no more stagnant disease prediction techniques in demand in the future.

关键词： Machine learning heart disease cardiac disease deep regression regression learning

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Effective Integration of Text Diffusion and Pre-Trained Language Models with Linguistic Easy-First Schedule 30

Effective Integration of Text Diffusion and Pre-Trained Lang...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Ou, Yimin Jian, Ping School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology Beijing China

ISBN: (纸本)9782493814104

Diffusion models have become a powerful generative modeling paradigm, achieving great success in continuous data patterns. However, the discrete nature of text data results in compatibility issues between continuous diffusion models (CDMs) and pre-trained language models (PLMs). That is, the performance of diffusion models even degrades when combined with PLMs. To alleviate this issue, we propose to utilize a pre-trained decoder to convert the denoised embedding vectors into natural language instead of using the widely used rounding operation. In this way, CDMs can be more effectively combined with PLMs. Additionally, considering that existing noise schedules in text diffusion models do not take into account the linguistic differences among tokens, which violates the easy-first policy for text generation, we propose a linguistic easy-first schedule that incorporates the measure of word importance, conforming to easy-first-generation linguistic features and bringing about improved generation quality. Experiment results on the E2E dataset and five controllable tasks show that our approach can combine the merits of CDMs and PLMs, significantly outperforming other diffusion-based models. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Diffusion

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Simulation and Evaluation of GAN-based Implementation of Infrared Texture Generation

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Journal of engineering science and technology Review 2024年第1期17卷 122-130页

作者： Wu, Yunyun Liu, Han Kong, Xia Deng, Min Li, Youfeng School of Computer and Information Science Hubei Engineering University Hubei Xiaogan432000 China School of Artificial Intelligence Hubei University Hubei Wuhan430062 China Institute for AI Industrial Technology Research Hubei Engineering University Hubei Xiaogan432000 China

At present, the demand for the simulation technology of infrared view is markedly expanding. However, the related main research orientations are influenced by numerous factors. Thus, the availability of infrared images for special scenes is difficult to determine, and their practical applications are limited. This study proposed a method based on generative adversarial network (GAN) to reveal its influence on the generation of infrared texture and produce infrared texture in infrared view simulation. By combining the needs of texture generation in infrared simulation and the superiority of image style transfer in texture generation, three algorithms for style transfer based on GAN, namely, Algorithms I, II, and III, were introduced to establish pretrained models. Simulation results of the three models were then evaluated using histograms, structural similarity (SSIM), and peak signal-to-noise ratio (PSNR), and the effects of colors of the infrared images in the texture generation were compared. The validity of these models was also verified. Results demonstrate that infrared images in a specified scene can be simulated without the need for a large number of training datasets, and the simulation images generated by transferring in black-and-white infrared style images are better than those in color infrared style images. The histogram evaluation index shows that Algorithm III is higher than Algorithms I and II by approximately 0.06. The SSIM evaluation index reveals that Algorithm II is higher than Algorithms I and II by 0.09 and 0.06 dB, respectively. The PSNR evaluation index indicates that Algorithm III is higher than Algorithms I and II by approximately 0.31 dB. Thus, this study provides a practical value in the field of infrared simulation technology. © 2024 School of science, IHU. All rights reserved.

关键词： Generative adversarial networks

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Classification of Organic and Recyclable Waste Using a Deep Learning Approach 1

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2nd International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2023

作者： Graceline Jasmine, S. Jagadish, Tarun Shabrez, Md. Febin Daya, J.L. School of Computer Science and Engineering Vellore Institute of Technology—Chennai Campus Chennai India Electric Vehicles Incubation Testing and Research Center Vellore Institute of Technology—Chennai Campus Chennai India

ISBN: (数字)9789819995240

ISBN: (纸本)9789819995233

In this paper, we propose an automated waste classification system that uses the help of deep learning and image processing methods. The main objective of our proposed system is to streamline the classification of waste into organic and recyclable. To achieve this, we used image processing techniques to improve the image quality of recyclable and organic waste from a publicly available dataset and trained our model using convolutional neural networks (CNN). The model achieved a high validation accuracy of 90.65%. We compared this model with four pre-trained models based on their accuracy and loss. Our proposed model for automating waste classification holds the potential to improve waste management practices and can also reduce the amount of waste that ends up in landfills. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolution

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Prediction of the Pore-Pressure Built-Up and Temperature of Fire-Loaded Concrete with Pix2Pix

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computers, Materials & Continua 2024年第5期79卷 2907-2922页

作者： Xueya Wang Yiming Zhang Qi Liu Huanran Wang Mechanics and Materials Science Research Center Ningbo UniversityNingbo315211China Jinyun Institute Zhejiang Sci-Tech UniversityLishui321400China School of Civil Engineering and Architecture Zhejiang Sci-Tech UniversityHangzhou310018China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China

Concrete subjected to fire loads is susceptible to explosive spalling, which can lead to the exposure of reinforcingsteel bars to the fire, substantially jeopardizing the structural safety and stability. The spalling of fire-loaded concreteis closely related to the evolution of pore pressure and temperature. Conventional analytical methods involve theresolution of complex, strongly coupled multifield equations, necessitating significant computational efforts. Torapidly and accurately obtain the distributions of pore-pressure and temperature, the Pix2Pix model is adoptedin this work, which is celebrated for its capabilities in image generation. The open-source dataset used hereinfeatures RGB images we generated using a sophisticated coupled model, while the grayscale images encapsulate the15 principal variables influencing spalling. After conducting a series of tests with different layers configurations,activation functions and loss functions, the Pix2Pix model suitable for assessing the spalling risk of fire-loadedconcrete has been meticulously designed and trained. The applicability and reliability of the Pix2Pix model inconcrete parameter prediction are verified by comparing its outcomes with those derived fromthe strong couplingTHC model. Notably, for the practical engineering applications, our findings indicate that utilizing monochromeimages as the initial target for analysis yields more dependable results. This work not only offers valuable insightsfor civil engineers specializing in concrete structures but also establishes a robust methodological approach forresearchers seeking to create similar predictive models.

关键词： Fire loaded concrete spalling risk pore pressure generative adversarial network(GAN) Pix2Pix

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Improving Implicit Discourse Relation Recognition with Semantics Confrontation 30

Improving Implicit Discourse Relation Recognition with Seman...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Cai, Mingyang Yang, Zhen Jian, Ping School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology Beijing China

ISBN: (纸本)9782493814104

Implicit Discourse Relation Recognition (IDRR), which infers discourse logical relations without explicit connectives, is one of the most challenging tasks in natural language processing (NLP). Recently, pre-trained language models (PLMs) have yielded impressive results across numerous NLP tasks, but their performance still remains unsatisfactory in IDRR. We argue that prior studies have not fully harnessed the potential of PLMs, thereby resulting in a mixture of logical semantics, which determine the logical relations between discourse arguments, and general semantics, which encapsulate the non-logical contextual aspects (detailed in Sec.1). Such a mixture would inevitably compromise the logic reasoning ability of PLMs. Therefore, we propose a novel method that trains the PLMs through two semantics enhancers to implicitly differentiate logical and general semantics, ultimately achieving logical semantics enhancement. Due to the characteristic of PLM in word representation learning, these two semantics enhancers will inherently confront with each other, facilitating an augmentation of logical semantics by disentangling them from general semantics. The experimental results on PDTB 2.0 dataset show that the confrontation approach exceeds our baseline by 3.81% F1 score, and the effectiveness of the semantics confrontation method is validated by comprehensive ablation experiments. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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