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Automatic Rule Discovery for Data Transformation Using Fusion of Diversified Feature Formats

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Computers, Materials & Continua 2024年第7期80卷 695-713页

作者： G.Sunil santhosh Kumar M.Rudra Kumar Department of CSE Jawaharlal Nehru Technological UniversityAnantapur515002India Department of CSE Marri Laxman Reddy Institute of Technology and ManagementHyderabad500043India Department of Information Technology Mahatma Gandhi Institute of TechnologyHyderabad500075India

This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost,a machine learning algorithm renowned for its efficiency and *** framework proposed herein utilizes the fusion of diversified feature formats,specifically,metadata,textual,and pattern *** goal is to enhance the system’s ability to discern and generalize transformation rules fromsource to destination formats in varied ***,the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the *** sections expound on the mechanism of feature optimization using Recursive Feature Elimination(RFE)with linear regression,aiming to retain the most contributive features and eliminate redundant or less significant *** core of the research revolves around the deployment of the XGBoostmodel for training,using the prepared and optimized feature *** article presents a detailed overview of the mathematical model and algorithmic steps behind this ***,the process of rule discovery(prediction phase)by the trained XGBoost model is explained,underscoring its role in real-time,automated data *** employingmachine learning and particularly,the XGBoost model in the context of Business Rule Engine(BRE)data transformation,the article underscores a paradigm shift towardsmore scalable,efficient,and less human-dependent data transformation *** research opens doors for further exploration into automated rule discovery systems and their applications in various sectors.

关键词： XGBoost business rule engine machine learning categorical query language humanitarian computing environment

Design of a Multi-Stage Ensemble Model for Thyroid Prediction Using Learning Approaches

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Intelligent Automation & Soft Computing 2024年第1期39卷 1-13页

作者： M.L.Maruthi Prasad R.santhosh Department of Computer Science and Engineering Faculty of EngineeringKarpagam Academy of Higher EducationCoimbatoreTamil NaduIndia

This research concentrates to model an efficient thyroid prediction approach,which is considered a baseline for significant problems faced by the women *** major research problem is the lack of automated model to attain earlier *** existing model fails to give better prediction ***,a novel clinical decision support system is framed to make the proper decision during a time of *** stages are followed in the proposed framework,which plays a substantial role in thyroid *** steps include i)data acquisition,ii)outlier prediction,and iii)multi-stage weight-based ensemble learning process(MS-WEL).The weighted analysis of the base classifier and other classifier models helps bridge the gap encountered in one single classifier *** classifiers aremerged to handle the issues identified in others and intend to enhance the prediction *** proposed model provides superior outcomes and gives good quality prediction *** simulation is done in the MATLAB 2020a environment and establishes a better trade-off than various existing *** model gives a prediction accuracy of 97.28%accuracy compared to other models and shows a better trade than others.

关键词： Thyroid machine learning pre-processing classification prediction rate

Enhancing Security in QR Code Technology Using AI: Exploration and Mitigation Strategies

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International Journal of Intelligence Science 2024年第2期14卷 49-57页

作者： Saranya Vaithilingam santhosh Aradhya Mohan Shankar Department of Information Technology University of the Cumberlands Williamsburg KY USA

The widespread adoption of QR codes has revolutionized various industries, streamlined transactions and improved inventory management. However, this increased reliance on QR code technology also exposes it to potential security risks that malicious actors can exploit. QR code Phishing, or “Quishing”, is a type of phishing attack that leverages QR codes to deceive individuals into visiting malicious websites or downloading harmful software. These attacks can be particularly effective due to the growing popularity and trust in QR codes. This paper examines the importance of enhancing the security of QR codes through the utilization of artificial intelligence (AI). The abstract investigates the integration of AI methods for identifying and mitigating security threats associated with QR code usage. By assessing the current state of QR code security and evaluating the effectiveness of AI-driven solutions, this research aims to propose comprehensive strategies for strengthening QR code technology’s resilience. The study contributes to discussions on secure data encoding and retrieval, providing valuable insights into the evolving synergy between QR codes and AI for the advancement of secure digital communication.

关键词： Artificial Intelligence Cyber Security QR Codes Quishing AI Framework Machine Learning AI-Enhanced Security

Laparoscopic management of remnant gall bladder with stones: Lessons from a tertiary care centre's experience

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Laparoscopic, Endoscopic and Robotic Surgery 2024年第1期7卷 27-33页

作者： Gilbert Samuel Jebakumar Jeevanandham Muthiah Loganathan Jayapal R.santhosh Kumar Siddhesh Tasgaonkar K.S.santhosh Anand J.K.A.Jameel Sudeepta Kumar Swain K.J.Raghunath Prasanna Kumar Reddy Tirupporur Govindaswamy Balachandar Department of Surgical Gastroenterology Apollo HospitalsChennai 600006India Department of General Surgery Apollo HospitalsChennai 600006India Department of Minimal Access Surgery Apollo HospitalsChennai 600006India

Objective:Laparoscopic cholecystectomy is currently the gold standard for treating symptomatic gallstone *** its success,approximately 10%of patients may experience persistent biliary symptoms,leading to the post-cholecystectomy syndrome.A remnant gallbladder with cystic duct or bile duct stones is one of the causes of this *** objective of this study was to shed light on the clinical manifestations,evaluation,therapeutic strategies,and outcomes associated with laparoscopic management of symptomatic remnant ***:This was a retrospective study,conducted over a five-year period(January 2017 to December 2022)at Apollo Hospitals in South *** patients who underwent laparoscopic completion cholecystectomy for a remnant gall bladder were *** following data were collected:patient demographics,symptoms,preoperative investigations,intraoperative details and post operative ***:In total,36 patients were included and *** majority of patients were male(25,69.4%),with a mean age of 50.7±12.1 *** most common presentation was pain in the upper abdomen or right upper quadrant region(24,66.7%).The laparoscopic approach was attempted in all patients,with a success rate of 94.4%.Two patients required conversion to open *** fistula to the colon was observed in one *** was observed in 7 patients(19.4%),and stone clearance was successfully achieved using endoscopic retrograde cholangiopancreatography in all patients ***:Incomplete gall bladder removal either intentionally or unintentionally leaves a remnant gall bladder that is at risk for stone formation and *** who have this clinical entity with symptoms require a redo or complete cholecystectomy,a complex procedure associated with certain *** study highlights the feasibility and safety of laparoscopic completion cholecystectomy for the management of remnant gallbladder

关键词： Remnant gall bladder Stump cholecystitis Subtotal cholecystectomy Laparoscopic completion cholecystectomy

Nonlinear dynamics and performance analysis of modified snap-through vibration energy harvester with time-varying potential function

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Applied Mathematics and Mechanics(English Edition) 2022年第2期43卷 185-202页

作者： K.DEVARAJAN B.santhosh Department of Mechanical Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamCoimbatore641112India

Vibration energy harvesting has emerged as a promising method to harvest energy for small-scale *** the performance of a vibration energy harvester(VEH)incorporating nonlinear techniques,for example,the snap-through VEH with geometric non-linearity,has gained attention in recent years.A conventional snap-through VEH is a bi-stable system with a time-invariant potential function,which was investigated extensively in the *** this work,a modified snap-through VEH with a time-varying potential function subject to harmonic and random base excitations is *** snap-through VEHs,such as the one considered in this study,are used in wave energy ***,the studies on their dynamics and energy harvesting under harmonic and random excitations are *** dynamics of the modified snap-through VEH is represented by a system of differential algebraic equations(DAEs),and the numerical schemes are proposed for its *** a harmonic excitation,the system exhibits periodic and chaotic motions,and the energy harvesting is superior compared with the conventional *** dynamics under a random excitation is investigated by the moment differential method and the numerical scheme based on the modified Euler-Maruyama *** Fokker-Planck equation representing the dynamics is derived,and the marginal and joint probability density functions(PDFs)are obtained by the Monte Carlo *** study shows that the modified snap-through oscillator based VEH performs better under both harmonic and random *** dynamics of the system under stochastic resonance(SR)is investigated,and performance enhancement is *** results from this study will help in the development of adaptive VEH techniques in the future.

关键词： snap-through vibration energy harvester(VEH) time-varying potential function bifurcation probability density function(PDF) Fokker-Planck equation

Cloud-Based Software Development Lifecycle:A Simplified Algorithm for Cloud Service Provider Evaluation with Metric Analysis

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Big Data Mining and Analytics 2023年第2期6卷 127-138页

作者： santhosh S Narayana Swamy Ramaiah Computer Science&Engineering Jain(Deemed-to-be University)Bangalore 562112India

At present,hundreds of cloud vendors in the global market provide various services based on a customer’s *** cloud vendors are not the same in terms of the number of services,infrastructure availability,security strategies,cost per customer,and reputation in the ***,software developers and organizations face a dilemma when choosing a suitable cloud vendor for their developmental ***,there is a need to evaluate various cloud service providers(CSPs)and platforms before choosing a suitable *** existing solutions are either based on simulation tools as per the requirements or evaluated concerning the quality of service ***,they require more time to collect data,simulate and evaluate the *** proposed work compares various CSPs in terms of major metrics,such as establishment,services,infrastructure,tools,pricing models,market share,etc.,based on the comparison,parameter ranking,and weightage ***,the parameters are categorized depending on the priority *** weighted average is calculated for each CSP,after which the values are sorted in descending *** experimental results show the unbiased selection of CSPs based on the chosen *** proposed parameter-ranking priority level weightage(PRPLW)algorithm simplifies the selection of the best-suited cloud vendor in accordance with the requirements of software development.

关键词： cloud-based software development life cycle(SDLC) cloud evaluation parameter-ranking priority level weightage(PRPLW)algorithm cloud service providers software engineering

Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

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Intelligent Automation & Soft Computing 2023年第3期35卷 2963-2978页

作者： Anwar R Shaheen Sundar santhosh Kumar Department of Computer Science Alagappa UniversityKaraikudiIndia

Cloud computing plays a signiﬁcant role in Information Technology(IT)industry to deliver scalable resources as a *** of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task *** main advantage of this scheduling is to max-imize the performance and minimize the time *** researchers examined numerous scheduling methods to achieve Quality of Service(QoS)and to reduce execution ***,it had disadvantages in terms of low throughput and high response ***,this study aimed to schedule the task efﬁciently and to eliminate the faults in scheduling the tasks to the Virtual Machines(VMs).For this purpose,the research proposed novel Particle Swarm Optimization-Bandwidth Aware divisible Task(PSO-BATS)scheduling with Multi-Layered Regression Host Employment(MLRHE)to sort out the issues of task scheduling and ease the scheduling operation by load *** proposed efﬁcient sche-duling provides beneﬁts to both cloud users and *** performance evalua-tion is undertaken with respect to cost,Performance Improvement Rate(PIR)and makespan which revealed the efﬁciency of the proposed ***,comparative analysis is undertaken which conﬁrmed the performance of the intro-duced system than conventional system for scheduling tasks with highﬂexibility.

关键词： Task scheduling virtual machines(VM) particle swarm optimization(PSO) bandwidth aware divisible task scheduling(BATS) multi-layered regression

Integrated Privacy Preserving Healthcare System Using Posture-Based Classifier in Cloud

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Intelligent Automation & Soft Computing 2023年第3期35卷 2893-2907页

作者： C.santhosh Kumar K.Vishnu Kumar Department of Computer Science and Engineering Priyadarshini Engineering College635751TamilnaduIndia Department of Computer Science and Engineering KPR Institute of Engineering&TechnologyCoimbatore641407India

Privacy-preserving online disease prediction and diagnosis are critical issues in the emerging edge-cloud-based healthcare *** patient data pro-cessing from remote places may lead to severe privacy ***,the existing cloud-based healthcare system takes more latency and energy consumption during diagnosis due to ofﬂoading of live patient data to remote cloud *** the privacy *** proposed research introduces the edge-cloud enabled privacy-preserving healthcare system by exploiting additive homomorphic encryption *** can help maintain the privacy preservation and conﬁdentiality of patients’medical data during diagnosis of Parkinson’s *** addition,the energy and delay aware computational ofﬂoading scheme is proposed to minimize the uncertainty and energy consumption of end-user *** proposed research maintains the better privacy and robustness of live video data processing during prediction and diagnosis compared to existing health-care systems.

关键词： Peer-to-peer computing energy and delay aware ofﬂoading edge-cloud enabled healthcare system parkinson’s disease prediction

Modelling a Fused Deep Network Model for Pneumonia Prediction

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Computer Systems Science & Engineering 2023年第9期46卷 2725-2739页

作者： M.A.Ramitha N.Mohanasundaram R.santhosh Department of Computer Science and Engineering Karpagam Academy of Higher EducationCoimbatoreIndia

Deep Learning(DL)is known for its golden standard computing paradigm in the learning ***,it turns out to be an extensively utilized computing approach in the ML ***,attaining superior outcomes over cognitive tasks based on human *** primary benefit of DL is its competency in learning massive *** DL-based technologies have grown faster and are widely adopted to handle the conventional approaches ***,various DL approaches outperform the conventional ML approaches in real-time ***,various research works are reviewed to understand the significance of the individual DL models and some computational complexity is *** may be due to the broader expertise and knowledge required for handling these models during the prediction *** research proposes a holistic approach for pneumonia prediction and offers a more appropriate DL model for classification *** work incorporates a novel fused Squeeze and Excitation(SE)block with the ResNet model for pneumonia prediction and better *** expected model reduces the human effort during the prediction process and makes it easier to diagnose it intelligently as the feature learning is *** experimentation is carried out in Keras,and the model’s superiority is compared with various advanced *** proposed model gives 90%prediction accuracy,93%precision,90%recall and 89%*** proposed model shows a better trade-off compared to other *** evaluation is done with the existing standard ResNet model,GoogleNet+ResNet+DenseNet,and different variants of ResNet models.

关键词： Disease prediction pneumonia deep learning SE ResNet fused network model