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Optimal Control of Service Rates of Discrete-Time(s,Q)Queueing-Inventory Systems with Finite Buffer

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Journal of Systems Science and Systems Engineering 2024年第3期33卷 261-280页

作者： L.Iniya B.sivakumar G.Arivarignan School of Mathematics Madurai Kamaraj UniversityMaduraiTamilnaduIndia Department of Statistics Manonmaniam Sundaranar UniversityTirunelveliTamilnaduIndia

This article,we develop an optimal policy to control the service rate of a discrete time queueing-inventory system with finite buffer.The customers arrive according to a Bernoulli process and the service time for the customers are geometric.Whenever the buffer size attains its maximum,any arriving new customers are considered to be lost.The customers are served one by one according to FCFS rule and each customers request random number of items.The inventory is replenished according to a(s,Q)inventory policy with geometric lead time.The main objectives of this article are to determine the service rates to be employed at each slot so that the long run expected cost rate is minimized for fixed inventory level and fixed buffer size and to minimize the expected waiting time for a fixed inventory level and fixed buffer size.The problems are modelled as Markov decision problem.We establish the existence of a stationary policy and employ linear programming method to find the optimal service rates.We provide some numerical examples to illustrate the behaviour of the model.

关键词： Queueing-inventory system discrete time batch demand-Markov decision process

Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

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Computers, Materials & Continua 2024年第1期78卷 1189-1205页

作者： K.Akilandeswari Nithya Rekha.sivakumar Hend Khalid Alkahtani Shakila Basheer Sara Abdelwahab Ghorashi Department of Computer Sciences Government Arts College(Autonomous)Salem636007India Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and recovery.The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance.Although many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during analysis.Therefore,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare Monitoring.At first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction process.Here,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable devices.To attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced features.After that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and overhead.Experimental evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several instances.The quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

关键词： Internet of Things smart health care monitoring human activity recognition intelligent agent learning statistical partial regression support vector

The theory of pathological simile:unveiling the essence of homoeopathy

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History & Philosophy of Medicine 2024年第1期6卷 1-2页

作者： Sibin Ramabhadran Anandavally Sruthi Krishna Gopukumar sivakumar Thangam Nivedha Krishnamoorthy Sajitha Kumari Department of Organon of Medicine Sarada Krishna Homoeopathic Medical College(Affiliated to The Tamil Nadu Dr.M.G.R.Medical UniversityChennai)Tamilnadu 629161India Department of Repertory Sarada Krishna Homoeopathic Medical College(Affiliated to The Tamil Nadu Dr.M.G.R.Medical UniversityChennai)Tamilnadu 629161India Research Facilitation Centre Sarada Krishna Homoeopathic Medical College(Affiliated to The Tamil Nadu Dr.M.G.R.Medical UniversityChennai)Tamilnadu 629161India

Background Homoeopathy,a therapeutic method based on the principle of‘Similia Similibus Curentur’(like cures like),has been widely practiced and studied since its discovery by Dr.Samuel Hahnemann in the late 18th century.Over time,numerous homoeopathic stalwarts have contributed to the development and understanding of this system of medicine.Dr.Richard Hughes,a remarkable figure in the field of homoeopathy,has left an indelible mark on the development and understanding of this extraordinary system of medicine.

关键词： simile has since

Insights into the anorexic mechanism of Khat:an integrated in vivo,ex vivo,and in silico investigations

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Traditional Medicine Research 2024年第10期9卷 36-51页

作者： Ahmed Ali Jerah Manal Mohamed Elhassan Taha Abdullah Farasani sivakumar Sivagurunathan Moni Emad Sayed Shaheen Andleeb Khan Ibrahim Abdo Khardali Magbool Oraiby Heyam Mohamed Ali Sidahmed Siddig Ibrahim Abdelwahab Department of Medical Laboratory Technology College of Applied Medical SciencesJazan UniversityJazan 45142Saudi Arabia Health Research Centre Jazan UniversityJazan 45142Saudi Arabia Department of Pharmaceutics College of PharmacyJazan UniversityJazan 45142Saudi Arabia Department of Biosciences Faculty of ScienceIntegral UniversityLucknow 226026India Poison Control and Medical Forensic Chemistry Center General Directorate of Health AffairsJazan 45142Saudi Arabia Department of Pharmaceutical Chemistry Faculty of PharmacyAl-Neelain UniversityKhartoum 16458Sudan

Background:Chewing Khat(Catha edulis)releases cathine and cathinone,which may reduce appetite via an unknown mechanism.This study investigated the peripheral and central effects of fresh leaves and buds of Catha edulis water extract(CEWE)on appetite biomarkers,gene expression,and body weight,using in vivo,ex vivo,and in silico models.Methods:Rats of both sexes were orally administered CEWE at different doses and durations in three different experiments.Liquid chromatography-mass spectroscopy(LC-MS)-MS was used to detect cathinone and cathine in the murine blood.The effect of Khat on serotonin receptors was studied in isolated rat fundus samples.Docking of the two Khat ligands was performed on G(The 5-hydroxytryptamine-type 2C receptor(5-HT2C)in an agonist-bound active conformation)and H(5-HT2C in an antagonist-bound inactive conformation)proteins to determine which ligands are most likely to act as agonists or antagonists.Results:Significant differences(P0.05).The expression of the ghrelin and leptin genes was also unaffected,but the expression of the 5-hydroxytryptamine(5-HT)gene decreased(P<0.05)with CEWE treatment.CEWE antagonizes 5-HT receptors in isolated rat fundus samples.Docking findings indicated that the khat ligands bound to 5-HT2C receptors.Cathine and cathinone levels in rat plasma were measured.Conclusion:Khat extract may suppress appetite by antagonizing the 5-HT receptors.Further research is required to understand its mechanism and potential applications.

关键词： Catha edulis appetite leptin ghrelin 5-hydroxytryptamine molecular docking

Strength Characteristics of Treated Soil with Proposed Layer Formation

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Journal of Wuhan University of Technology(Materials Science) 2023年第1期38卷 117-135页

作者： N sivakumar A Mandal Srinivasan venkatraman Department of Civil Engineering Visvesvaraya National Institute of TechnologyNagpur-440010India

The engineering characteristics of the soil,soil-fly ash and fly ash-lime,were examined to utilize as base layer material in civil construction.The influence of fly ash percentage and the effect of curing on California bearing ratio(CBR)and unconfined compressive strength(UCS),of soil and soil-fly ash mixing and layered system were examined to estimate the optimum quantity.The volumetric swelling of the optimal mixture was estimated to be within the allowable limits.Scanning microscope analysis and X-ray diffraction tests were performed.A model test analyses with three layers were conducted by finite element method and stress-strain behavior was observed.

关键词： Scanning electron microscopy simulation sustainable materials waste reduction X-ray diffraction

Ensemble Deep Learning for IoT Based COVID 19 Health Care Pollution Monitor

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Intelligent Automation & Soft Computing 2023年第2期35卷 2383-2398页

作者： Nithya Rekha.sivakumar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Internet of things(IoT)has brought a greater transformation in health-care sector thereby improving patient care,minimizing treatment costs.The pre-sent method employs classical mechanisms for extracting features and a regression model for prediction.These methods have failed to consider the pollu-tion aspects involved during COVID 19 prediction.Utilizing Ensemble Deep Learning and Framingham Feature Extraction(FFE)techniques,a smart health-care system is introduced for COVID-19 pandemic disease diagnosis.The Col-lected feature or data via predictive mechanisms to form pollution maps.Those maps are used to implement real-time countermeasures,such as storing the extracted data or feature in a Cloud server to minimize concentrations of air pol-lutants.Once integrated with patient management systems,this solution would minimize pollution emitted via patient’s sensors by offering spaces in the cloud server when pollution thresholds are reached.Second,the Gini Index factor infor-mation gain technique eliminates unimportant and redundant attributes while selecting the most relevant,reducing computing overhead and optimizing system performance.Finally,the COVID-19 disease prognosis ensemble deep learning-based classiﬁer is constructed.Experimental analysis is planned to measure the prediction accuracy,error,precision and recall for different numbers of patients.Experimental results show that prediction accuracy is improved by 8%,error rate was reduced by 47%and prediction time is minimized by 36%compared to exist-ing methods.

关键词： Internet of Things Covid-19 ensemble deep learning framingham feature extraction

The 11th revision of the International Statistical Classification of Disease and Related Health Problems and Cholangiocarcinoma

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Hepatobiliary Surgery and Nutrition 2022年第2期11卷 276-279页

作者： Shijie Cai Shivan sivakumar Nuffield Division of Clinical Laboratory Sciences Radcliffe Department of MedicineUniversity of OxfordJohn Radcliffe HospitalOxfordUK Department of Oncology University of OxfordChurchill HospitalOxfordUK

The World Health Organisation(WHO)classifies clinical diagnoses with the International Statistical Classification of Disease and Related Health Problems(ICD).There have been various iterations of ICD since it is inception.For oncology,ICD-O was introduced in 1976 as a special adaption of ICD for cancers to facilitate greater coding detail of the topography,which describes the anatomical location of the tumour origin,and the morphology concerns the histology of a neoplasm.ICD-10 began in 1983 and was first used in 1994.At the same time,a code for cholangiocarcinoma(CCA)was also introduced(https://icd.***.int/browse10/2010/en).

关键词： clinical carcinoma neoplasm

Deep Neural Artificial Intelligence for IoT Based Tele Health Data Anal

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Computers, Materials & Continua 2022年第3期70卷 4467-4483页

作者： Nithya Rekha.sivakumar Ahmed Zohair Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances.It makes an effort to get the better of issues of health service delivery involving time factor,space and laborious terrains,validating cost-efficiency and finer ingress in both developed and developing countries.Tele health has been categorized into either real-time electronic communication,or store-andforward communication.In recent years,a third-class has been perceived as remote healthcare monitoring or tele health,presuming data obtained via Internet of Things(IOT).Although,tele health data analytics and machine learning have been researched in great depth,there is a dearth of studies that entirely concentrate on the progress of ML-based techniques for tele health data analytics in the IoT healthcare sector.Motivated by this fact,in this work a method called,Weighted Bayesian and Polynomial Taylor Deep Network(WB-PTDN)is proposed to improve health prediction in a computationally efficient and accurate manner.First,the Independent Component Data Arrangement model is designed with the objective of normalizing the data obtained from the Physionet dataset.Next,with the normalized data as input,Weighted Bayesian Feature Extraction is applied to minimize the dimensionality involved and therefore extracting the relevant features for further health risk analysis.Finally,to obtain reliable predictions concerning tele health data analytics,First Order Polynomial Taylor DNN-based Feature Homogenization is proposed that with the aid of First Order Polynomial Taylor function updates the new results based on the result analysis of old values and therefore provides increased transparency in decision making.The comparison of proposed and existing methods indicates that the WB-PTDN method achieves higher accuracy,true positive rate and lesser response time for IoT based tele health data analytics than the traditional methods.

关键词： Telehealth internet of things independent component weighted bayesian first order polynomial taylor deep neural network

Editorial on“Perihilar Cholangiocarcinoma-Novel Benchmark Values for Surgical and Oncological Outcomes From 24 Expert Centers”

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Hepatobiliary Surgery and Nutrition 2022年第3期11卷 422-424页

作者： Shivan sivakumar Flavio GRocha Lara Heij Department of Oncology University of OxfordOxfordUK Division of Surgical Oncology Knight Cancer InstituteOregon Health and Science UniversityPortlandORUSA Department of Surgery and Transplantation University Hospital RWTH AachenAachenGermany Institute of Pathology University Hospital RWTH AachenAachenGermany

Cholangiocarcinoma(CCA)is a rare and very aggressive malignancy arising from the biliary tract.Based on the location of the tumor,CCA can be divided in intrahepatic cholangiocarcinoma(iCCA),perihilar cholangiocarcinoma(pCCA)and distal cholangiocarcinoma(dCCA).Many other characteristics differentiate these groups,including pathological features,oncological approach and surgical techniques,which in turn influences patient outcomes.

关键词： hilar carcinoma Surgical