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Impact of Robotic Process Automation on Enterprise Resource Planning Systems

Impact of Robotic Process Automation on Enterprise Resource ...

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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Blockchain Technology in Biometric Database System 3

Blockchain Technology in Biometric Database System

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3rd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2022

作者： Singh, Anamika Dhanaraj, Rajesh Kumar Ali, Md. Akkas Balusamy, Balamurugan Sharma, Vandana Galgotias University PhD Scholar School of Computing Science and Engineering U.P Greater Noida India Galgotias University School of Computing Science and Engineering U.P Greater Noida India Shiv Nadar University Associate Dean Student U.P Greater Noida India Amity University Amity Institute of Information Technology U.P Greater Noida India

ISBN: (数字)9781665453196

ISBN: (纸本)9781665453196

The Biometric system can be understood as a system that deals with an automated recognition of individual based on their physiological aspects (face, fingerprints, iris, retina) and behavioral patterns (signature, posture etc.). Biometric system works on feature extraction and feature matching. The feature is extracted in the form of fingerprints, iris and retina and then it is matched by the information stored by measuring the same patterns of particular individual, this process is feature matching. Between the two, works template database which is a central point from where every time the feature extracted is matched for confirming the identity of a person.. If the database is breached by the hacker, then the data could be used for falsifying the identity of the person. The paper focuses to implement blockchain technology in a biometric system in a manner that every record of individual is maintained using a blockchain so that it can't be hampered by the hacker. Blockchain works as adecentralized repository of data which we assume to be the most suitable approach to hold the credentials of individuals and thus avoiding an unauthorized access to the systems. Making changes to blockchain is a complex and time-consuming task for any unwanted user. Many researchers contributed their work highlighting the security issues of the biometric system when applied practically. They noted that the fingerprint of an individual remains the same over life and once applied can't be modified when compares with non-biometric systems which makes use of passwords and if forgotten or breached could be changed. Some of them conveyed that the biometric system is safe when only considering its physical implementation but the database created is still under threat. © 2022 IEEE.

关键词： Blockchain

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Assessment of Safety of a Retrofitted Damaged Reinforced Concrete Column Based on the Bond Stress and the Stress Transfer at the Interface of the Reinforced Concrete Jacket and the Old Concrete

Assessment of Safety of a Retrofitted Damaged Reinforced Con...

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International Conference on Advanced Research and Innovations in Civil engineering, ARICE 2019

作者： Guruprasad, Y.K. Jayasimha, K.S. Former Researcher and former PhD Research Scholar Department of Civil Engineering Indian Institute of Science Bangalore India STEDRANT Techno Clinic Private Ltd. Bangalore India

ISBN: (纸本)9789811556432

Reinforced concrete columns in buildings undergo damage due to earthquakes, under-designed or erroneous designs, exposure to high temperatures, or due to overloading. Damaged reinforced concrete columns affect the safety and stability of the overall building. Hence, damaged reinforced columns are retrofitted to restore them, from strength and stability aspects, to improve their load-carrying capacity. In this study, retrofitting of an existing damaged reinforced concrete column of a commercial building has been carried out. The bond stress developed at the interface of the reinforced concrete jacket and the old concrete corresponding to the damaged reinforced concrete column is assessed by carrying out a three-dimensional finite element analysis. Based on the magnitude of the developed bond stress, the number of shear connectors to be provided to anchor the old and new concrete in the reinforced concrete jacket is decided. The shear and axial stresses developed in the shear connectors are also checked with the corresponding permissible material strength values. The safety of the retrofitted reinforced concrete column is assessed based on the bond stress values;the shear and axial stress developed in the shear connectors;and the number of shear connectors provided at the interface of the damaged reinforced concrete column and the reinforced concrete jacket. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Retrofitting

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A novel hybrid machine learning model for shopping trip estimation: A case study of Tehran, Iran

Transportation Engineering

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Transportation engineering 2023年 14卷

作者： Dasoomi, MohammadHanif Naderan, Ali Allahviranloo, Tofigh PhD. Candidate Department of Civil Engineering Science and Research Branch Islamic Azad University Tehran14778-93855 Iran Assistant Professor Department of Civil Engineering Science and Research Branch Islamic Azad University Tehran14778-93855 Iran Professor Department of Mathematical Sciences Science and Research Branch Islamic Azad University Tehran14778-93855 Iran Professor Faculty of Engineering and Natural Sciences Istinye University Istanbul Turkey

Online and offline shopping trips have a profound impact on various facets of urban life, including e-commerce, transportation systems, and sustainability. To assess the factors shaping consumers' decisions, we introduce a novel hybrid machine learning model that integrates the Gray Wolf Optimization (GWO) algorithm with a deep Convolutional Neural Network (CNN). This model is applied to predict shopping behavior based on a survey of 1000 active e-commerce users residing in areas 2 and 5 of Tehran. These individuals have made successful purchases through both online and offline services during the final 20 days of 2021. The GWO algorithm plays a pivotal role in selecting optimal features and hyperparameters for the deep Convolutional Neural Network, which is a powerful deep learning model for image recognition and classification. Notably, our model achieves an impressive accuracy of 97.81% while maintaining a MSE of 0.325, having identified seven out of ten key features as the most influential. To gage the effectiveness of our approach, we conduct a comparative analysis with alternative methods. The results unequivocally showcase the superiority of our proposed algorithm, which attains an accuracy of 97.81%. In contrast, other models such as CNN, LSTM, MLP, DT, and KNN yield accuracies of 95.63%, 94.04%, 90.12%, 86.49%, and 80.16%, respectively. This study offers valuable insights for transportation planners, e-commerce managers, and policymakers. Its primary objective is to assist them in formulating effective strategies aimed at reducing transportation costs, curbing pollutant emissions, mitigating urban traffic congestion, and enhancing user satisfaction all while fostering sustainable development. © 2023 The Author(s)

关键词： Neural network models

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Piezoelectricity of strain-induced overall water splitting of Ni(OH)2/MoS2 heterostructure

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Journal of Materials Chemistry A 2023年第7期11卷 3481-3492页

作者： Le, Kim Tuyen Pham, Nguyet N. T. Liao, Yin-Song Ranjan, Ashok Lin, Hsun-Yen Chen, Po-Han Nguyen, Hoang Lu, Ming Yen Lee, Seung Geol Wu, Jyh Ming Department of Materials Science and Engineering National Tsing Hua University 101 Section 2 Kuang Fu Road Hsinchu300 Taiwan Department of Chemistry University of Science Vietnam National University Ho Chi Minh City Viet Nam School of Chemical Engineering Pusan National University 2 Busandaehak-ro 63 beon-gil Geumjeong-gu Busan46241 Korea Republic of Department of Organic Material Science and Engineering Pusan National University 2 Busandaehak-ro 63 beon-gil Geumjeong-gu Busan46241 Korea Republic of PhD Program in Prospective Functional Materials Industry National Tsing Hua University 101 Section 2 Kuang Fu Road Hsinchu300 Taiwan High Entropy Materials Center National Tsing Hua University 101 Section 2 Kuang Fu Road Hsinchu300 Taiwan Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam

In this study, we synthesized several active sites of molybdenum disulfide (MoS2) nanoflowers (NFs) decorated with Ni(OH)2 nanoparticles (NPs) to form heterostructures. Our results revealed that Ni(OH)2/MoS2 NF heterostructures caused the splitting of water into hydrogen (H2) and oxygen (O2) gas. The Ni(OH)2/MoS2 NF interface exhibited strain-induced piezoelectric potential (piezopotential) that promoted charge separation, reducing the kinetic barrier in the water splitting process and promoting the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER). In high-resolution transmission microscopy images, the measured lattice fringe d spacing was approximately 0.67 nm, which was higher than the reported value. The calculated tensile strain of Ni(OH)2/MoS2 NF heterostructures was approximately 3.5%. The findings based on density-functional theory and using the finite element method indicated that the interfacial piezopotential generated between Ni(OH)2 and MoS2 NFs enhanced charge transfer and electrochemical reactions. To obtain a current density up to 10 mA cm−2, we set the overpotential and Tafel slope of Ni(OH)2/MoS2 NF heterostructures at 155 mV and 62.1 mV dec−1 for the HER and 328 mV and 69.3 mV dec−1 for the OER, respectively. Moreover, a high Faraday efficiency (84.1%) was observed over 48 h, with no significant decline in the HER and OER. © 2023 The Royal Society of Chemistry.

关键词： Molybdenum disulfide

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Consumer Behavior in the Post-Pandemic Era: Insights from Machine Learning and AI-Driven Analytics

Consumer Behavior in the Post-Pandemic Era: Insights from Ma...

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Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Divya Nimma Ch. Anudeep Tripti Sahu Nusrat Hamid Shah Lubna Hamid Shah B Kiran Bala PhD in Computational Science University of Southern Mississippi Data Analyst in UMMC USA Department of Management studies Shri Vishnu Engineering college for women (A) Bhimavaram India MIMA Institute of Management Pune Maharashtra India College of Engineering and Computer Science Jazan University Kingdom of Saudi Arabia Department of Management and Marketing College of Business Jazan University Kingdom of Saudi Arabia Department of AI & DS K.Ramakrishnan College of Engineering Trichy India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

COVID-19 has been the disruptor in the world, and the society has been changed from one perspective of the consumer behavior in terms of digital platforms and their preferences for safety, convenience and sustainability. It is therefore very important for any business to acquaint itself with these changes so that may be in a position to effectively compete for the market within the current ever-changing business environment. Conventional consumer behavior models, on the other hand, rely on fragmented data sources and analytical tools that may not reflect the current post-pandemic consumption patterns. Such models are also incapable of incorporating multiple data types and can also fail to address changing social factors. In response, a Multi-Modal Consumer Behavior Prediction Framework (MCBP) that considers a vast array of data sources is introduced. BERT and GNNs are used to give a detailed, real-time interpretation of consumer behaviour accomplished by the MCBP framework. It uses BERT to extract and analyze sentiment and topics of the textual data and GNNs to capture influence and peer effects on purchase decisions. The findings of the study show the effectiveness of the proposed framework with an accuracy of 99%. 5% and the implementation is done using Python. The high level of accuracy shown assures the success of the MCBP model in measuring and forecasting consumers' behaviors in the post-pandemic world.

关键词： Consumer behavior Accuracy Soft sensors Predictive models Data models Social factors Real-time systems Safety Sustainable development Business

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Demonstrating Galileo Has in Single Point Positioning

Demonstrating Galileo Has in Single Point Positioning

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Metrology for Automotive (MetroAutomotive), IEEE International Workshop on

作者： Giovanni Cappello Antonio Angrisano Silvia Ascione Silvio Del Pizzo Ciro Gioia Gabriele Portelli Melania Susi Salvatore Gaglione Department of Science and Technology International PhD Programme / UNESCO Chair "Environment Resources and Sustainable Development" Parthenope University of Naples Naples Italy Department of Engineering Messina University Messina Italy Department of Science and Technology International PhD Programme/"Environmental Phenomena and Risks (EnPheR)" Parthenope University of Naples Naples Italy Department of Science and Technology Parthenope University of Naples Naples Italy Independert Researcher Ispra Italy Joint Research Centre Italy

The importance of an accurate PNT (Position, Navigation, Timing) information is nowadays consolidated in the navigation field. Easy of use and robustness make Single Point Positioning (SPP) one of the most used techniques to compute navigation information, on the other hand, employing SPP may not lead to the achievement of the required performance, especially in challenging scenario. Different techniques or services could be used in order to achieve the target performance; in particular, the recent Galileo High Accuracy Service (HAS) could enhance the position accuracy. Several applications can benefit of HAS in particular geomatics, automotive, aviation, and maritime. This novel service provides corrections for orbits, code, phase, and satellite clock for Galileo and GPS (Global Positioning System) systems. Corrections are broadcast through the Galileo E6-B signal or other means (i.e., internet), and they have a global coverage. Even if HAS corrections are meant for the PPP (Precise Point Positioning) technique, in this study, they are applied to the SPP technique in order to assess the possible improvements in solution accuracy.

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Innovative Horizons in Agricultural Technology with TSA Based StrawberrySqueezeNet Classification Model

Innovative Horizons in Agricultural Technology with TSA Base...

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Data science and Network Security (ICDSNS), International Conference on

作者： H M Manoj Priyanka Pramod Pawar R Krupa Piyush Kumar Pareek Deepak Kumar G B Vindhya Computer Science and Engineering BMS Institute of Technology and Management Bengaluru India PhD Information Technology University of the Cumberlands Mechanical Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Artificial Intelligence & Machine Learning Nitte Meenakshi Institute of Technology Bengaluru India Channabasaveshwara Institute of technology Gubbi Tumkur

ISBN: (数字)9798350373110

ISBN: (纸本)9798350373127

A fruit plant with sufficient value is the strawberry plant. High concentrations of fibre, antioxidants, potassium, vitamin C, and folic acid can be found in strawberry fruit. Because bacteria, pests, and microbes frequently impact strawberry plants, cultivating strawberries is a simple operation. Digital image processing will be used to introduce strawberry disease initially and limit its spread in strawberry plants. To improve strawberry disease diagnosis, a multi-pronged strategy was used, starting with the application of a carefully selected dataset. The dataset was then enriched and diversified using data augmentation techniques, which made it easier to build a reliable and complex model. For classification, the StrawberrySqueezeNet architecture was used, utilising its inherent capacity to identify complex patterns in the data. For hyperparameter tuning, a Tangent Search technique was used to maximise the model's performance. In order to get higher classification accuracy, the iterative optimisation procedure dynamically adjusted parameters as it explored the hyperparameter space. The result of these efforts was an astounding accuracy of 98.3%, which beat the industry standards set by other models.

关键词： Accuracy Digital images Surveillance Data augmentation Data models Space exploration Reliability Tuning Standards Diseases

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Revolutionizing Image Analysis: The Integration of MLP and GRU Architectures in Advanced Computer Vision

Revolutionizing Image Analysis: The Integration of MLP and G...

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Green Industrial Electronics and Sustainable Technologies (GIEST), IEEE International Conference on

作者： Divya Nimma Alok Singh Sengar Chamandeep Kaur Shamim Ahmad Khan S.D.Anushna I Infant Raj PhD in Computational Science University of Southern Mississippi Data Analyst in UMMC USA Dept. of Computer Science School of Sciences Noida International University Greater Noida Uttar Pradesh India Department of Computer Science Jazan University Jazan Saudi Arabia Glocal School of Science & Technology Glocal University U.P India Department of CSE(Data Science) Sri Indu College of Engineering and Technology Hyderabad India Department of CSE K.Ramakrishnan College of Engineering Trichy Tamil Nadu India

ISBN: (数字)9798331540142

ISBN: (纸本)9798331540159

Although there have been significant advances in computer vision recently, there are still difficulties in efficiently interpreting dynamic and complicated visual input. Through the integration of Gated Recurrent Units (GRUs) and Multi-Layer Perceptrons (MLPs) in advanced picture analysis, this study suggests a novel way to overcome these issues. Utilizing the advantages of both systems, the integrated model seeks to improve visual information comprehension and interpretation. Computer vision applications involving temporal context and semantic understanding are sometimes difficult for traditional approaches to handle. MLPs are good at collecting spatial features; on the other hand, GRUs are efficient at processing data sequentially. This research aims to develop and evaluate an integrated MLP-GRU model for advanced image analysis, combining the strengths of MLPs and GRUs. The model aims to achieve superior performance in tasks like object detection, image classification, and semantic segmentation. The model combines MLPs for spatial feature extraction and GRUs for capturing temporal dependencies within sequential data. The experimental results show significant improvements in accuracy of 98%, compared to traditional approaches. The model also demonstrates the ability to discern complex visual patterns and make accurate predictions. This study highlights the potential of hybrid neural network architectures in image analysis, highlighting the paradigm shift in computer vision and their ability to analyze diverse and dynamic visual data.

关键词： Computer vision Visualization Accuracy Computational modeling Semantic segmentation Neural networks Semantics Computer architecture Object detection Predictive models

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Finite element modeling of an intact and cracked mandibular second molar under quantitative percussion diagnostics loading

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Journal of Prosthetic Dentistry 2024年

作者： Shen, Jie Taheri-Nassaj, Nasrin Sheets, Cherilyn G. Earthman, James C. PhD Candidate Department of Materials Science and Engineering University of California Irvine Irvine Calif United States Postdoctoral Researcher Department of Materials Science and Engineering University of California Irvine Irvine Calif United States Co-Executive Director Research and Teaching Divisions Newport Coast Oral Facial Institute Newport Beach Calif United States Professor Department of Materials Science and Engineering Department of Biomedical Engineering University of California Irvine Irvine Calif United States

Statement of problem: Quantitative percussion diagnostics (QPD) has been devised to nondestructively evaluate the mechanical integrity of human teeth and implants, the mechanical integrity of the underlying bone, and the presence of cracks, but the mechanism is not clearly understood. Purpose: The purpose of this study is to better understand the dynamic behavior of a tooth under conditions consistent with QPD by focusing on physiologically accurate 3D finite element models of a human mandibular second molar with surrounding tissues. Material and methods: Finite element analysis (FEA) was used to study the force response of dental structures measured by the sensor in a QPD handpiece. A defect-free (intact) and a cracked tooth model containing a vertical crack involving enamel, dentin, periodontal ligament, bone, and the QPD percussion rod were used for this purpose. Different crack gap spaces were studied for comparison. The FEA model was validated with clinical QPD data for a second mandibular molar containing a vertical crack that subsequently had to be extracted. The location and size of the vertical crack was determined once the tooth was extracted. Results: The present FEA results exhibited features consistent with those of corresponding clinical data, thus verifying the model. An examination of the relative acceleration of the crack faces with respect to each other revealed that an oscillation between the crack surfaces results in secondary peaks in the QPD energy return response compared with that of an intact tooth. Conclusions: The present FEA modeling can generate simulated QPD results that exhibit established distinguishing characteristics in clinical QPD data for intact and cracked second mandibular molars. The model results also give insight into how QPD detects the presence of cracks and show that the oscillation of crack surfaces can produce the multipeak QPD results for a cracked molar observed clinically. © 2024 Editorial Council for The Journal of

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