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Spleen-preserving distal pancreatectomy from multi-port to reducedport surgery approach

World Journal of Gastrointestinal Surgery 2023年第7期15卷 1501-1511页

作者： Ching-Lung Hsieh Tung-Sheng Tsai Cheng-Ming Peng Teng-Chieh Cheng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724TaiwanChina Department of Surgery Chung Shan Medical University HospitalTaichung 40201TaiwanChina PhD Program of Electrical and Communications Engineering Feng Chia UniversityTaichung 40724Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Da Vinci Minimally Invasive Surgery Center Chung Shan Medical University HospitalTaichung 40201Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

BACKGROUND Minimally invasive pancreatic surgery via the multi-port approach has become a primary surgical method for distal pancreatectomy(DP)due to its advantages of lower wound pain and superior cosmetic *** studies have applied reduced-port techniques for DP in an attempt to enhance cosmetic outcomes due to the minimally invasive *** recent review studies have compared multi-port laparoscopic DP(LDP)and multi-port robotic DP(RDP);most of these studies concluded multi-port RDP is more beneficial than multi-port LDP for spleen ***,there have been no comprehensive reviews of the value of reduced-port LDP and reduced-port *** To search for and review the studies on spleen preservation and the clinical outcomes of minimally invasive DP that compared reduced-port DP surgery with multi-port DP *** The PubMed medical database was searched for articles published between 2013 and *** search terms were implemented using the following Boolean search algorithm:(“distal pancreatectomy”OR“left pancreatectomy”OR“peripheral pancreatic resection”)AND(“reduced-port”OR“single-site”OR“single-port”OR“dual-incision”OR“single-incision”)AND(“spleen-preserving”OR“spleen preservation”OR“splenic preservation”).A literature review was conducted to identify studies that compared the perioperative outcomes of reduced-port LDP and reduced-port *** Fifteen articles published in the period from 2013 to 2022 were retrieved using three groups of search *** studies were added after manually searching the related ***,10 papers were selected after removing case reports(n=3),non-English language papers(n=1),technique papers(n=1),reviews(n=1),and animal studies(n=1).The common items were defined as items reported in more than five papers,and data on these common items were extracted from all *** ten studies included a total of 337 patients(females/males:231/106)who underwent *** total,166 patients(females/male

关键词： Minimally invasive surgery Robotic distal pancreatectomy Laparoscopic distal pancreatectomy Spleen preservation Reduced-port Multi-port

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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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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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Analysis of Pixel Intensity Variation by Performing Morphological Operations for Image Segmentation on Cervical Cancer Pap Smear Image

Analysis of Pixel Intensity Variation by Performing Morpholo...

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2021 International Conference on Computational Intelligence and Computing Applications, ICCICA 2021

作者： Dilip Nandanwar, Pratiksha Wadhai, Vijay M. Chanchlani, Akshita S. Thakare, Vilas M. Savitribai Phule Pune University PhD Research Scholar AISSMS IOT Department of Electronics and Telecommunication Engineering Pune India Principal D.Y.PATIL College of Engineering Department of ETC Pune India SGBA University PhD Research Scholar Department Computer Science and Engineering Amravati India

ISBN: (纸本)9781665420402

Cervical cancer is the second largely hazardous metastatic tumor that develops in a woman's cervix. If it is detected at the premature stage and treated correctly then there can be less mortality ratio rate due to cervical *** preliminary stage Pap smear is the simple scrutiny test generally used for the revealing of cancer. For precise screening and detection, cervical cancer is categorized as normal and abnormal cancer which includes the cell and cytoplasm in the identical structure. It is complicated task to distinguish a cancerous nucleus in the cell. Medical image processing is mainly significant but time consuming and complicated task. Medical Image preprocessing of cervical cancer pap smear images and its scrutiny is act of investigating images for recognizing objects and evaluating their impact. The primary reason of Image processing is for discovering of various kinds of unnecessary cells and exposing the amount it spreads. So for the precise segmentation of cervical cells in Pap smear image becomes an essential job to automatically identify the precancerous transforms in the cervix. Image segmentation basically refers to method of division of the image into several segments for tracing objects and borders in image. Various Image processing and segmentation algorithms are utilized to section the nucleus alone in microscopic *** primary scope of this paper is to spotlight on how the morphological operations on cervical cancer pap smear images is achieved to fine-tune to appropriate pixel concentration and proper contrast for sorting out the tumor piece from an image. In the addressed proposed work morphological operations like erosion, dilation, opening, and closing are executed and implemented with the aid of structuring element entitled as kernel. Python libraries are used for implementation of proposed work. As the morphological transformation is applied, minimum and maximum pixel intensity is also been computed. © 2021 IEEE.

关键词： Image segmentation

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Evaluating AI-Based Deep Learning Models for Enhancing English Reading Comprehension Skills in Students

Evaluating AI-Based Deep Learning Models for Enhancing Engli...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Divya Nimma V. Arunadevi Mehul Manu V. Selvi Prema S PhD in Computational Science University of Southern Mississippi Data Analyst in UMMC USA Department of Science and Humanities Dr. Mahalingam College of Engineering and Technology Pollachi India Allied Science (Physics) Graphic Era Hill University Bhimtal Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Science Mother Teresa Women's University Kodaikanal India Department of English Panimalar Engineering College Chennai India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

In the rapidly evolving field of natural language processing (NLP), enhancing model performance in understanding and generating human language has become increasingly critical. As the need for better language models increases, enhancing the current systems’ shortcomings becomes crucial. There are difficulties in existing models precisely due to the fundamental problem of striking a balance between the level of detail achievable and the amount of computational resources that a model requires for accurate estimation in practical settings. Current models, present several problems including but not limited to overfitting, average performance on out-of-sample data and less applicability for subtle linguistic features. Such obstacles limit their capability to execute in real conditions, where high degree of accuracy and precision is paramount. To overcome these challenges, this study introduces a novel framework that employs the BERT model which was developed to capture bidirectional context and achieve greater depth of the semantic relations between words. The proposed approach is designed to improve the model’s effectiveness to a considerable extent through the use of mechanisms such as attention as well as transformer architecture included in BERT. The proposed BERT model demonstrates exceptional results, achieving an accuracy of 99.10% and a precision of 98.30%. These metrics reflect the model's superior ability to understand and generate accurate language representations, surpassing existing models in both effectiveness and efficiency. This advancement underscores the potential of BERT to address critical challenges in NLP, offering a promising solution for applications requiring high precision and robust language comprehension.

关键词： Measurement Accuracy Computational modeling Semantics Estimation Bidirectional control Linguistics Transformers Encoding Natural language processing

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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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BRAIN-TO-TEXT BENCHMARK’24: LESSONS LEARNED

arXiv

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arXiv 2024年

作者： Willett, Francis R. Li, Jingyuan Le, Trung Fan, Chaofei Chen, Mingfei Shlizerman, Eli Chen, Yue Zheng, Xin Okubo, Tatsuo S. Benster, Tyler Lee, Hyun Dong Kounga, Maxwell Buchanan, E. Kelly Zoltowski, David Linderman, Scott W. Henderson, Jaimie M. Department of Neurosurgery Stanford University United States Department of Electrical & Computer Engineering University of Washington United States Department of Computer Science Stanford University United States Department of Applied Mathematics University of Washington United States China Neurosciences Phd Program Stanford University United States Wu Tsai Neurosciences Institute Department of Statistics Stanford University United States

Speech brain-computer interfaces aim to decipher what a person is trying to say from neural activity alone, restoring communication to people with paralysis who have lost the ability to speak intelligibly. The Brain-to-Text Benchmark’24 and associated competition was created to foster the advancement of decoding algorithms that convert neural activity to text. Here, we summarize the lessons learned from the competition ending on June 1, 2024 (the top 4 entrants also presented their experiences in a recorded webinar). The largest improvements in accuracy were achieved using an ensembling approach, where the output of multiple independent decoders was merged using a fine-tuned large language model (an approach used by all 3 top entrants). Performance gains were also found by improving how the baseline recurrent neural network (RNN) model was trained, including by optimizing learning rate scheduling and by using a diphone training objective. Improving upon the model architecture itself proved more difficult, however, with attempts to use deep state space models or transformers not yet appearing to offer a benefit over the RNN baseline. The benchmark will remain open indefinitely to support further work towards increasing the accuracy of brain-to-text algorithms. © 2024, CC BY.

关键词： Recurrent neural networks

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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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Segmenting Alzheimer's Disease MRI Slices for Hippocampal Volume Calculation

Segmenting Alzheimer's Disease MRI Slices for Hippocampal Vo...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Hsiao-Chuan Tan Gilang Titah Ramadhan Wei-Cheng Shen Wen-Thong Chang Chih-Yang Lin Ben-Yi Liau Yih-Kuen Jan Yori Pusparani Chi-Wen Lung Department of Artificial Intelligence PhD Program Asia University Taichung Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan Department of Creative Product Design Asia University Taichung Taiwan Department of Mechanical Engineering National Central University Taoyuan Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Department of Kinesiology and Community Health University of Illinois Urbana America Department of Digital Media Design Asia University Taichung Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

Alzheimer's is a neurodegenerative disease that quietly steals human memory. This study analyzed hippocampal volume in Alzheimer's Disease (AD), Mild Cognitive Impairment (MCI), and Normal Cognition (NC) using MRI image slices from the ADNI database and YOLOv8 instance segmentation. We used 300 images to segment the left and right hippocampal. This study focused on volume calculation from five MRI image slices. The results showed 0.98 (AD), 0.92 (MCI), and 0.90 (NC) and revealed significant volumetric differences showed in the NC class (P = 0.045). This suggests early neuroanatomical changes can occur without cognitive symptoms, highlighting the potential of deep learning in the early detection of neurodegenerative diseases.

关键词： Instance segmentation Deep learning Accuracy Databases Magnetic resonance imaging Cognition Alzheimer's disease

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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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