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dLMNN Based Heart disease Prediction with Pd-SS Optimization Algorithm

Intelligent Automation & Soft Computing 2023年第2期35卷 1353-1368页

作者： S.Raghavendra Vasudev Parvati R.Manjula Ashok Kumar Nanda Ruby Singh d.lakshmi S.Velmurugan department of Information and Communication Technology Manipal Institute of TechnologyManipal Academy of Higher EducationManipal576104India department of Information Science and Engineering SDM College of Engineering and TechnologyDharwad580002India department of Computer Science and Engineering School of ComputingSRM Institute of Science and TechnologyKattankulathurChennai603203India department of Computer Science and Engineering B.V Raju Institute of TechnologyTelangana502313India Faculty of Engineering and Technology SRM Institute of Science and TechnologyNCR CampusUttar Prasesh201204India School of Computing Science and Engineering VIT Bhopal UniversityMadhya Pradesh466114India department of Computer Science and Engineering Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India

In contemporary medicine,cardiovascular disease is a major public health *** diseases are one of the leading causes of death *** are classiﬁed as vascular,ischemic,or *** information contained in patients’Electronic Health Records(EHR)enables clin-icians to identify and monitor heart *** failure rates have risen drama-tically in recent years as a result of changes in modern *** diseases are becoming more prevalent in today’s medical *** year,a substantial number of people die as a result of cardiac *** primary cause of these deaths is the improper use of pharmaceuticals without the supervision of a physician and the late detection of *** improve the efﬁciency of the classiﬁcation algo-rithms,we construct a data pre-processing stage using feature ***-ments using unidirectional and bidirectional neural network models found that a deep Learning Modiﬁed Neural Network(dLMNN)model combined with the Pet dog-Smell Sensing(Pd-SS)algorithm predicted the highest classiﬁcation performance on the UCI Machine Learning Heart disease *** dLMNN-based PdSS achieved an accuracy of 94.21%,an F-score of 92.38%,a recall of 94.62%,and a precision of 93.86%.These results are competitive and promising for a heart disease *** demonstrated that a dLMNN framework based on deep models may be used to solve the categorization problem for an unbalanced heart disease *** proposed approach can result in exceptionally accurate models that can be utilized to analyze and diagnose clinical real-world data.

关键词： Machine learning random forest coronary heart disease cardiovascular optimization algorithm

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Hybrid Bacterial Foraging Optimization with Sparse Autoencoder for Energy Systems

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Computer Systems Science & Engineering 2023年第4期45卷 701-714页

作者： Helen Josephine V L Ramchand Vedaiyan V.M.Arul Xavier Joy Winston J A.Jegatheesan d.lakshmi Joshua Samuel Raj Business Analytics School of Business and ManagementChrist UniversityBangalore560029India department of Computer Science and IT School of SciencesJain Deemed to be UniversityBangalore560027India department of Computer Science and Engineering Karunya Institute of Technology and SciencesCoimbatore641114India College of Computer Studies University of Technology Bahrain18041Bahrain Institute of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India department of Computer Science and Engineering Panimalar Institute of TechnologyChennai600123India department of Information Science&Engineering CMR Institute of TechnologyBengaluru560037India

The Internet of Things(IoT)technologies has gained significant interest in the design of smart grids(SGs).The increasing amount of distributed generations,maturity of existing grid infrastructures,and demand network transformation have received maximum *** essential energy storing model mostly the electrical energy stored methods are developing as the diagnoses for its procedure was becoming further *** dynamic electrical energy stored model using Electric Vehicles(EVs)is comparatively standard because of its excellent electrical property and flexibility however the chance of damage to its battery was there in event of overcharging or deep discharging and its mass penetration deeply influences the *** paper offers a new Hybridization of Bacterial foraging optimization with Sparse Autoencoder(HBFOA-SAE)model for IoT Enabled energy *** proposed HBFOA-SAE model majorly intends to effectually estimate the state of charge(SOC)values in the IoT based energy *** accomplish this,the SAE technique was executed to proper determination of the SOC values in the energy ***,for improving the performance of the SOC estimation process,the HBFOA is *** addition,the HBFOA technique is derived by the integration of the hill climbing(HC)concepts with the BFOA to improve the overall *** ensuring better outcomes for the HBFOA-SAE model,a comprehensive set of simulations were performed and the outcomes are inspected under several *** experimental results reported the supremacy of the HBFOA-SAE model over the recent state of art approaches.

关键词： Internet of things energy systems state of charge estimation machine learning deep learning metaheuristics

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A comprehensive study on IoT privacy and security challenges with focus on spectrum sharing in Next-Generation networks(5G/6G/beyond)

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High-Confidence Computing 2024年第2期4卷 33-49页

作者： lakshmi Priya Rachakonda Madhuri Siddula Vanlin Sathya department of Computer Science North Carolina A&T State UniversityGreensboro 27401USA Celona Inc. San Francisco 95008USA

The emergence of the Internet of Things(IoT)has triggered a massive digital transformation across numerous *** transformation requires efficient wireless communication and connectivity,which depend on the optimal utilization of the available spectrum *** the limited availability of spectrum resources,spectrum sharing has emerged as a favored solution to empower IoT deployment and connectivity,so adequate planning of the spectrum resource utilization is thus essential to pave the way for the next generation of IoT applications,including 5G and *** article presents a comprehensive study of prevalent wireless technologies employed in the field of the spectrum,with a primary focus on spectrum-sharing solutions,including shared *** highlights the associated security and privacy concerns when the IoT devices access the shared *** survey examines the benefits and drawbacks of various spectrum-sharing technologies and their solutions for various IoT ***,it identifies future IoT obstacles and suggests potential research directions to address them.

关键词： Spectrum sharing IoT devices Security Privacy

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Effectiveness of craniosacral therapy,Bowen therapy,static touch and standard exercise program on sleep quality in fibromyalgia syndrome:A randomized controlled trial

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Journal of Integrative Medicine 2024年第4期22卷 473-483页

作者： Reepa Avichal Ughreja Prem Venkatesan dharmanand Balebail Gopalakrishna Yogesh Preet Singh Vani lakshmi R department of Physiotherapy Manipal College of Health ProfessionsManipal Academy of Higher EducationManipal 576104KarnatakaIndia department of Rheumatology Manipal HospitalBengaluru 560052KarnatakaIndia department of Clinical Immunology and Rheumatology All India Institute of Medical SciencesBilaspur 174001Himachal PradeshIndia department of data Science Prasanna School of Public HealthManipal Academy of Higher EducationManipal 576104KarnatakaIndia

Background:Sleep disturbance is commonly seen in fibromyalgia syndrome (FMS);however,high quality studies involving manual therapies that target FMS-linked poor sleep quality are lacking for the Indian ***:Craniosacral therapy (CST),Bowen therapy and exercises have been found to influence the autonomic nervous system,which plays a crucial role in sleep *** the paucity of evidence concerning these effects in individuals with FMS,our study tests the effectiveness of CST,Bowen therapy and a standard exercise program against static touch (the manual placebo group) on sleep quality in ***,setting,participants and intervention:A placebo-controlled randomized trial was conducted on132 FMS participants with poor sleep at a hospital in *** participants were randomly allocated to one of the four study groups,including CST,Bowen therapy,standard exercise program,and a manual placebo control group that received static ***,Bowen therapy and static touch treatments were administered in once-weekly 45-minute sessions for 12 weeks;the standard exercise group received weekly supervised exercises for 6 weeks with home exercises until 12 *** 12 weeks,all study participants performed the standard exercises at home for another 12 *** outcome measures:Sleep quality,pressure pain threshold (PPT),quality of life and fibromyalgia impact,physical function,fatigue,pain catastrophizing,kinesiophobia,and positive–negative affect were recorded at baseline,and at weeks 12 and 24 of the ***:At the end of 12 weeks,the sleep quality improved significantly in the CST group (P=0.037) and Bowen therapy group (P=0.023),and the PPT improved significantly in the Bowen therapy group(P=0.002) and the standard exercise group (Pd to the static touch *** improvements were maintained at 24 *** between-group differences were observed for other secondary ***:CST and Bowen therapy improv

关键词： Chronic pain Complementary therapies Exercise Fibromyalgia Musculoskeletal manipulations Sleep

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Cellular interplay to 3d in vitro microphysiological disease model:cell patterning microbiota-gut-brain axis

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Bio-design and Manufacturing 2024年第3期7卷 320-357页

作者： Kamare Alam lakshmi Nair Souvik Mukherjee Kulwinder Kaur Manjari Singh Santanu Kaity Velayutham Ravichandiran Sugato Banerjee Subhadeep Roy department of Pharmacology and Toxicology National Institute of Pharmaceutical Education and ResearchKolkataWest Bengal 700054India department of Pharmaceutical Sciences Assam UniversitySilchar 788011India department of Pharmaceutical Sciences Guru Ghasidas UniversityKoniBilaspur 495009C.G.India School of Pharmacy and Biomolecular Sciences RCSI University of Medicine and Health SciencesDublin D02 YN77Ireland Tissue Engineering Research Group Department of Anatomy and Regenerative MedicineRCSI University of Medicine and Health SciencesDublin D02 YN77Ireland department of Pharmaceutics National Institute of Pharmaceutical Education and ResearchKolkataWest Bengal 700054India department of Natural Products National Institute of Pharmaceutical Education and ResearchKolkataWest Bengal 700054India

The microbiota-gut-brain axis(MGBA)has emerged as a key prospect in the bidirectional communication between two major organ systems:the brain and the *** between the two organ systems allows the body to function without disease,whereas dysbiosis has long-standing evidence of etiopathological *** most common communication paths are the microbial release of metabolites,soluble neurotransmitters,and immune ***,each pathway is intertwined with a complex *** the emergence of in vitro models and the popularity of three-dimensional(3d)cultures and Transwells,engineering has become easier for the scientific understanding of neurodegenerative *** paper briefly retraces the possible communication pathways between the gut microbiome and the *** further elaborates on three major diseases:autism spectrum disorder,Parkinson’s disease,and Alzheimer’s disease,which are prevalent in children and the *** diseases also decrease patients’quality of ***,understanding them more deeply with respect to current advances in in vitro modeling is crucial for understanding the *** of MGBA in the laboratory uses many molecular technologies and biomaterial *** and organoids provide a more realistic picture of the cell and tissue structure than *** them with the Transwell system offers the advantage of compartmentalizing the two systems(apical and basal)while allowing physical and chemical cues between ***-edge technologies,such as bioprinting and microfluidic chips,might be the future of in vitro modeling,as they provide dynamicity.

关键词： Microbiota-gut-brain axis Neurodegeneration 3d disease model Organoid Transwell system

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