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IAENG International Journal of Computer Science 2022年第1期49卷 140-148页

作者： Zhao, D. Liu, F. Wang, X. PhD candidate of Beijing Jiaotong University No.3 Shangyuancun Haidian District Beijing100044 China Professor of Computer and Information Technology Department Beijing Jiaotong University No.3 Shangyuancun Haidian District Beijing100044 China

Bearings are to machinery like joints to humans, which means bearings are an integral part of the machinery. Recently, with the rapid development of sensors and artificial intelligence, a data-driven machine learning-based model for bearing remaining useful life (RUL) has become a powerful tool in academia and industry. However, there are also some existing problems, for example, the pre-set state-related threshold need to be manually determined, the bearing object being studied is under a single operating condition, RUL estimation in the entire life span in many studies is ignored and only a few samples as observed data to predicted and tested, which are all not conducive to the achievements transformation in actual engineering projects. In this paper, a novel generalized framework based on neural networks is proposed to solve these obstacles. Firstly, convolutional neural networks (CNN) and deep encoder (DE) are respectively used to extract features and reduce dimensions, obtaining dense and low dimensions health indicators (HIs). Secondly, Gated recurrent units (GRUs) are used to investigate timeseries information from dense and low dimensional HIs. Thirdly, the proposed method was verified on two platforms and experimental results show that the proposed method is effective and general, and superior to other baselines. © 2022. All Rights Reserved.

关键词： Convolutional neural networks

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The Way to Make Blind People Use the Email System: Voice Based Email Generating System Using Artificial Intelligence

The Way to Make Blind People Use the Email System: Voice Bas...

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Rajput, Gaurav Kumar Sharma, Sachin Dash, Bibhu Prasad Ansari, Meraj Farheen Sharma, Pawankumar Shukla, Surendra Kumar Teerthanker Mahaveer University College of Computing Science and Information Technology Uttar Pradesh Moradabad India Dev Bhoomi Uttarakhand University Department of Computer Science and Engineering Uttarakhand Dehradun India University of the Cumberland's School of Computer and Information Sciences WilliamsburgKY40769 United States University of the Cumberland's School of Computer and Information Sciences Department of Information Technology WilliamsburgKY40769 United States Walmart. University of the Cumberland's PhD Candidate Department of Information Technology United States Graphic Era Deemed to Be University Department of Cse Uttarakhand Dehradun India

ISBN: (纸本)9798350322309

People are becoming used to fake world and vocal communication as technology advances. There are a few ways to communicate with people online in this modern invention. A large number of individuals often choose and use the simplest form of reporting, namely email. The era of encrypted email allows users to communicate with other people by posting signals and also facilitates cross-border corporate communication. Some individuals are unable to take advantages of this technology due to their ignorant or lack the necessary visible screen ability. Therefore, a Speech completely messaging device is suggested using Py but instead Ai to save time for externally examined people. Its device gives those who have been evaluated on the outside some power of contact and considerably increases their sense of stability as objectivity. With the use of that invention, blind persons will indeed be able to send out emails just like other regular citizens. Voice-based messaging systems use cutting-edge technology to ensure their legitimacy to people who have been vetted on the outside. © 2023 IEEE.

关键词： Patents and inventions

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Plug-and-Play with POA based Maximum a Posteriori Denoisers for Image

Plug-and-Play with POA based Maximum a Posteriori Denoisers ...

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Mysore Sub Section International Conference (MysuruCon), IEEE

作者： Adithya Padthe Sapna Kadakadiyavar Ramya Thatikonda Madhura G K Department of Information Technology University of the Cumberlands USA AI &ML Department Vemana Institute of Technology Kormangala Bangalore PhD in Information Technology at University of the Cumberlands AI &ML Department Nitte Meenakshi Institute of Technology Bengaluru

Restoring damaged images has been an issue in the fields of image processing and basic computer vision for decades. Due to their improved performance, techniques based on discriminative convolutional neural networks (CNNs) have recently garnered a lot of interest. However, most of these frameworks only operate well on one type of picture restoration assignment, hence their performance on other types of image restoration is usually subpar. Research techniques leverage the fact that the Maximum a Posteriori (MAP) optimisation may be broken down into smaller sub-problems, such as a MAP denoising optimisation, to resolve this issue. We introduce the first full-stack method for MAP estimation in deep neural network image denoising. We prove that our approach will always result in a smaller MAP denoising goal, which can subsequently be employed in the general picture restoration optimisation technique known as the Puzzle Optimisation technique (POA). Our technique is theoretically analysed, and its quantitative efficacy is demonstrated through a number of tests. Our experiments validate the theoretical foundations of MAP and demonstrate that the suggested approach can reach 70x quicker presentation than the state-of-the-art.

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Behind the Screen: Unraveling the Relationship Between Cyberbullying and Student Achievement Across the Globe Using TIMMS 2019 Data

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International Journal of Bullying Prevention 2025年 1-23页

作者： Bhutoria, Aditi Aljabri, Nayyaf Choudhary, Utkarsh Alrubian, Ali Indian Institute of Management Calcutta Kolkata India Education and Training Evaluation Commission Riyadh Saudi Arabia Department of Educational Administration College of Education Taibah University Madinah Saudi Arabia PhD Scholar IFMR GSB Krea University SriCity India Department of Information and Communication Technology Prince Sattam Bin Abdulaziz University Al Kharj Saudi Arabia

The burgeoning landscape of education technology has coincided with the concerning proliferation of cyberbullying, a global threat that is increasingly impacting student well-being and academic performance. Leveraging TIMSS 2019 data, we investigate the association between cyberbullying and eighth-grade mathematics and science test scores across 38 countries and seven provinces. To mitigate potential confounding factors and selection bias, we have employed a propensity score matching (PSM) approach and allied matching methods commonly used in the economics of education literature. Our findings reveal a demonstrably negative association between cyberbullying and test scores, with victims experiencing an average score reduction of up to 10 percentage points in mathematics and 12 percentage points in science. Notably, students from the Middle East and Africa regions exhibited a disproportionately greater vulnerability to this adverse effect. Furthermore, the frequency of cyberbullying incidents is found to be directly correlated with the magnitude of score reduction, regardless of the cyberbullying type. Intriguingly, heterogeneity analysis revealed a nuanced picture with regard to socioeconomic status and gender. In most countries, no significant differential effect of cyberbullying emerged across socioeconomic strata. However, gender effects were country-specific, with girls demonstrating lower test scores in some contexts but not in others. Robustness checks employing inverse probability-weighted regression (IPW), augmented IPW, and entropy balancing lend support to the findings. Collectively, these results highlight the gravity of cyberbullying as a detrimental influence on academic performance across the globe. Further research is warranted to fully understand and address this multifaceted challenge, necessitating prompt intervention from schools and education policymakers. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Cyberbullying Propensity score matching Student achievement TIMSS

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Impact of Robotic Process Automation on Enterprise Resource Planning Systems

Impact of Robotic Process Automation on Enterprise Resource ...

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2023 International Conference on the Confluence of Advancements in Robotics, Vision and Interdisciplinary technology Management, IC-RVITM 2023

作者： Yendluri, Dileep Kumar Ponnala, Jainath Thatikonda, Ramya Kempanna, M. Tatikonda, Reshmi Bhuvanesh, A. University of the Cumberlands Masters in Computer Science United States Jawaharlal Technological University Bachelors in Ece Hyderbad India University of the Cumberlands PhD in Information Technology Williamsburg United States Bangalore Institute of Technology Department of Artificial Intelligence and Machine Learning Karnataka Bengaluru India University of the Central Missouri Masters in Computer Information Systems Warrensburg United States Psn College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350306088

ERP systems are merging their powers to generate a dynamic collaboration. By examining the integration between RPA (Robotic Process Automation) and ERP (Enterprise Resource Planning) systems, we can identify their shared potential for enhancing process flow. Combining automation and ERP integration makes RPA a powerful tool for process management across multiple industries. The paper examines the basics of RPA and its ERP integration, highlighting the advantages of enhanced productivity and fewer errors. Addressing security, compliance, and change management issues simultaneously. In addition to top-down and bottom-up methods, process analysis and selecting suitable processes are covered. Practical examples offer insightful observations on this integration's success. The union of RPA and ERP creates a powerful combination that can elevate operational effectiveness, facilitate strategic insights, and reshape the workplace. © 2023 IEEE.

关键词： Integration

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Diagnosis of Liver Tumor from CT Scan Images using Deep Segmentation Network with CMBOA based CNN

Diagnosis of Liver Tumor from CT Scan Images using Deep Segm...

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Mysore Sub Section International Conference (MysuruCon), IEEE

作者： Ramya Thatikonda Sapna Kadakadiyavar Adithya Padthe Madhura G K Software Engineer PhD in Information Technology at University of the Cumberlands USA AI &ML Department Vemana Institute of Technology Kormangala Bangalore Department of Information Technology University of the Cumberlands USA AI & ML Department Nitte Meenakshi Institute of Technology Bengaluru

Accurate segmentation and categorization of liver tumours are crucial for the diagnosis and management of carcinoma or metastases. The liver tumour presents a challenging problem for precise and automated tumour segmentation and classification because of its blurry boundaries and large variety of potential forms, sizes, and placements. New AI models have emerged as computer technology has progressed. The NLP community has had such success with the transformer paradigm that the CV community has adopted it as well. Although established methods exist for categorising the liver, especially in clinical settings, they might be refined to be more accurate. Two deep learning-based models are used to do the segmentation and classification of the liver tumour in this study. As a first step, the input photos are median filtered and their histograms are equalised to prepare them for further processing. Then, Deep Segmentation Network (DSegNet) extracts the liver from the input pictures. The tumour is then categorised using an Optimised Convolutional Neural Network (OCNN) model, with the CNN's weight chosen using a Cat and Mouse Based Optimisation Algorithm (CMBOA). Two openly accessible datasets are used for the experimental study, with a focus on certain key metrics. The results demonstration that associated to pre-existing deep learning representations, the suggested model is about 98% more accurate in its classifications.

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ADOBSVM: Anomaly detection on block chain using support vector machine

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Measurement: Sensors 2022年 24卷

作者： Rwibasira, Michel R, Suchithra PhD Scholar in Computer Science and Information Technology Jain University Karnataka Bangalore India Head of Department of Computer Science and Information Technology Jain University Karnataka Bangalore India

Bitcoins are cryptocurrencies that make use of blockchain technology, which consists of network nodes and permanent ledgers of events. Theft and illicit actions are referred to as abnormalities in the financial network. Members of the network want to figure out what's up as quickly as possible to avoid conflicts in the community and maintain the network's integrity. Using an unconstrained machine learning technique, this research aims to discover anomalies in bitcoin transactions. Anomaly detectors play a critical role in defending networks and systems from unexpected threats, typically by identifying as well as screening problems efficiently. Various strategies have been developed over the years, all with the goal of lowering the number of false positives. Furthermore, no proposals so far talked about blockchain-based system-based attacks were considered. The Support Vector Machine (SVM) for anomalies is described in this article. In comparison to other existing approaches, SVM provides good security with a shorter execution time. The effectiveness of the SVM approach is evaluated using attack detection rate, error rate, execution time, and power consumption;and it is compared to existing methods. According to experimental results, the best results from existing approaches are obtained using SVM. © 2022 The Authors

关键词： Anomaly detection

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The Impact of Blockchain and AI in the Healthcare

The Impact of Blockchain and AI in the Healthcare

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International Conference on Electrical Power and Energy Systems (ICEPES)

作者： Ramya Thatikonda M. Kempanna Reshmi Tatikonda A. Bhuvanesh PhD in Information Technology University of the Cumberlands Williamsburg USA Department of Artificial Intelligence and Machine Learning Bangalore Institute of Technology Bengaluru Karnataka India Masters in Computer Information Systems University of the Central Missouri Warrensburg USA Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tirunelveli Tamil Nadu India

ISBN: (数字)9798350390728

ISBN: (纸本)9798350390735

Integrating blockchain and artificial intelligence (AI) in healthcare presents a transformative opportunity. Therefore, this can revolutionize patient care by improving data management and medical research. Decentralization and invulnerability granted by blockchain technology foster improved data consistency and interoperability. AI enhances blockchain by streamlining data examination, automatic tasks, and decision-making processes, resulting in more precise medical diagnoses and tailored therapy programs. The intersection of blockchain and AI is explored, along with their potential benefits and practical applications in healthcare. The document examines the hurdles encountered when integrating innovations, including scalability, interoperability, and regulatory adherence issues. Additionally, the study investigates moral questions surrounding data ownership and patient consent, thereby protecting confidentiality and trust. The synergy between blockchain, AI, and healthcare will lead to transformative advancements. It pledges to fortify data safety and expedite information sharing. Consequently, this will result in an improved, price-effective, and patient-focused healthcare environment. Recommendations were made for additional research and practical implementation in healthcare technology. The study should concentrate on creating scalable and compatible blockchain systems. A vital factor for extensive use is tackling regulatory and moral issues. Hybrid blockchain designs and federated learning strategies will bolster information privacy and utility.

关键词： Technological innovation Ethics Privacy Federated learning Medical treatment Medical services Blockchains

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An Efficient Search Space Exploration Technique for High Utility Itemset Mining

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Procedia Computer Science 2023年 218卷 937-948页

作者： Suresh B Patel Sanjay M Shah Mahendra N Patel PhD Scholar Gujarat Technological University Ahmedabad India Computer Engineering L.D.C.E Ahmedabad India Information Technology Department GEC Gandhinagar Gujarat-India-380028

Data mining techniques discover the potentially helpful pattern concealed in a vast database for the decision support system in various real-life applications. One such technique is association rule mining. It finds the pattern from the transaction database to understand customer behavior. Frequent itemset mining (FIM) identifies a set of frequently purchased items together. One key drawback of FIM is that it ignores the item's importance. An item's importance plays a pivotal role in a real-world application. Therefore, it is necessary to discover the essential itemset from the transaction database that generate the high profit called the HUIM (High-Utility Itemset Mining) problem. From a transaction database, a variety of strategies can be used to find high utility itemset. The HUIM techniques that use the Utility list are recent and have better performance in terms of memory utilization and running time. The key limitation of these algorithms is performing costly utility list join operations. This paper proposes an efficient search space exploration technique to lessen the number of comparisons performed for utility list join operations. Hence, it reduces the cost of utility list join operations. In addition, the execution time of the proposed method is evaluated. Further, the same is compared with appropriate existing state-of-the-art methods. Finally, extensive experiments carried out on publicly available benchmark datasets show that the proposed support count ascending order (SCAO) based approach performs much better as oblivious to the state-of-the-art methods.

关键词： Mining algorithm High utility itemset mining pattern utility-list Transaction weighted utity

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Development of 5G Cyber-Physical Production System

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International Journal of Networked and Distributed Computing 2023年第1期11卷 9-19页

作者： Huang, Hsuan-Chao Tsai, Chun-Hsien Lin, Hsiung-Cheng Department of Computer Science and Information Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan PhD program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan Department of Electronic Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan

The cyber-physical production system (CPPS) was developed for the interconnection between operational technology (OT) and information and communication technology (ICT) among the machines and decentralized production control. However, OT and ICT are now getting more complex in the modern industry. To enhance industrial management and production process, the CPPS based on the 5G architecture under production environments can provide a more comprehensive solution in the context of Industry 4.0. For this purpose, a 5G CPPS model to improve the interoperability of CPPS in ICT and OT is proposed to build a virtualized Industry 4.0 asset management shell system. First, real-time task artifacts and 5G communication modules are bound in a certain form of virtualization. Second, task artifacts are released to the production line in a real-time scheduling. Third, an order is placed on a production line and split into multiple tasks for production process. Single-machine single-workpiece and multi-machine and multi-workpiece processing cases are used for testing in the production line. Experimental results show that the proposed 5G CPPS can efficiently achieve multi-machine work piece processing. © 2022, The Author(s).

关键词： 5G Cyber-physical production system (CPPS) Digital twin (DT) Industry 4.0 information technology Operational technology

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