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Prevalence and predictors of smartphone addiction and insomnia among nurses working in the outpatient department after the second wave of the coronavirus disease 2019 pandemic

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Journal of Integrative Nursing 2023年第4期5卷 273-279页

作者： Manisha MEHrA Poonam joshi Surya Kant TIWArI Praveen AggrAWAL Kamlesh CHANDELIA Srinithya rAgHAVAN Department of Nursing Services All India Institute of Medical SciencesNew DelhiIndia College of Nursing All India Institute of Medical SciencesKalyaniWest BengalIndia College of Nursing All India Institute of Medical SciencesRaebareliUttar PradeshIndia Department of Emergency Medicine All India Institute of Medical SciencesNew DelhiIndia Department of In-Service Education All India Institute of Medical SciencesNew DelhiIndia

Objectives:The present study aims to assess the prevalence and predictors of smartphone addiction and insomnia among nurses working in the outpatient department(OPD)after the second wave of the coronavirus disease 2019(COVID-19)*** and Methods:A descriptive,cross-sectional study was carried out among 117 OPD nurses between October and December 2021 using a purposive sampling *** self-reported standardized scales,the Smartphone Addiction Scale-ShortVersion and Insomnia Severity Index were ***–Smirnov test,Mann–Whitney U,and Kruskal–Wallis Htest were ***’s correlation and Scatter plot were used to determine the relationship between the study variables.A stepwise multiple linear regression analysis was also ***:The majority of participants had slight smartphone addiction(78.6%)and suffered from sub-threshold to severe forms of insomnia(73.5%).A significant mild positive correlation was found between smartphone addiction and insomnia(r=0.195,Priate logistic regression analysis predicted factors such as female gender and exposure to smartphones for more than 5 years influencing smartphone addiction.A strong influence of exposure to the smartphone for more than 5 years was found on insomnia ***:Smartphone addiction and insomnia were identified problems among nurses working in the OPD after the second wave of the COVID-19 pandemic,requiring an urgent need to identify and manage various factors responsible for smartphone addiction and insomnia such as female gender and years of exposure to smartphones.

关键词： Coronavirus disease 2019 insomnia nurses sleeping disturbances smartphone addiction

Long-term photometric study of a faint W UMa binary in the direction of M31

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research in Astronomy and Astrophysics 2017年第11期17卷 59-70页

作者： Yogesh Chandra joshi rukmini Jagirdar Aryabhatta research Institute of Observational Sciences Manora Peak Nainital 263002 India Center for Advanced Study in Astronomy Osmania University 500007 India

We carry out a re-analysis of the photometric data in rclc bands which were taken during the Nainital Microlensing Survey from 1998 to 2002 with the aim to detect gravitational microlensing events in the direction of M31. Here, we do photometric analysis of a faint W UMa binary CSS_JO04259.3＋410629 identified in the target field. The orbital period of this star is found to be 0.266402±0.000018 d. The photometric mass ratio, q, is found to be 0.28±0.01. The photometric light curves are investigated using the Wilson-Devinney （WD） code and absolute parameters are determined using empirical relations which provide masses and radii of the binary as M1 = 1.19±0.09M⊙, M2 = 0.33±0.02M⊙ and r1 = 1.02±0.04r⊙, r2 = 0.58±0.08re respectively based on rc band data. Quite similar values are found by analyzing/c band data. From the photometric light curve examination, the star is understood to be a low mass-ratio overcontact binary of A-subtype with a high fill-out factor of about 47%. The binary system is found to be located approximately at a distance of 2.64±0.03 kpc having a separation of 2.01 ±0.05 re between the two components.

关键词： methods: observational -- techniques: photometric -- binaries: eclipsing -- stars: funda- mental parameters

Numerical Modeling of Neotectonic Movements and State of Stresses in the Central Seismic gap region,garhwal Himalaya

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Journal of Mountain Science 2008年第4期5卷 279-298页

作者： ganesh raj joshi Daigoro HAYASHI Simulation Tectonics Laboratory Faculty of ScienceUniversity of the RyukyusOkinawa 903-0213Japan

This paper presents finite element modeling(FEM) to simulate the present-day stress field and crustal deformation using NE-SW structural section in the central Seismic gap region of the garhwal *** study deals with the effect of geometrical characteristics and rock layer parameters on the upper *** results show that two types of tectonic regimes developed in the central Seismic gap region:the geotectonics of the northern part has been controlled by regional compression,whereas southern part is characterized by regional ***,thrust faults are induced in the northern part and normal faults are extensively developed in the southern *** evidences noticeably indicate that the compressive tectonic environment of the Himalaya becomes change into the extensional tectonic regime in its *** computed shear stress accumulation along the northern flat of Main Himalayan Thrust(MHT) implies that considerable amount of interseismic stress is building up along the MHT system in the Himalaya,which ultimately release through the possible future great Himalayan earthquake(M>8).The comparison between our modeled stress field,faulting pattern and horizontal shortening rate with the distribution of the microseismic events,focal mechanism solutions,active faulting and gPS data in the central Seismic gap region shows good agreement.

关键词：地震变形应力分布有限元分析

Deep Learning Enabled Disease Diagnosis for Secure Internet of Medical Things

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Computers, Materials & Continua 2022年第10期73卷 965-979页

作者： Sultan Ahmad Shakir Khan Mohamed Fahad Al.Ajmi Ashit Kumar Dutta L.Minh Dang gyanendra Prasad joshi Hyeonjoon Moon Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia College of Pharmacy King Saud UniversityRiyadh11451Saudi Arabia Department of Computer Science and Information System College of Applied SciencesAlMaarefa UniversityRiyadh11597Saudi Arabia Department of Information Technology FPT UniversityHo Chi Minh CityVietnam Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

In recent times,Internet of Medical Things(IoMT)gained much attention in medical services and healthcare management *** healthcare sector generates massive volumes of data like personal details,historical medical data,hospitalization records,and discharging records,IoMT devices too evolved with potentials to handle such high quantities of *** and security of the data,gathered by IoMT gadgets,are major issues while transmitting or saving it in *** advancements made in Artificial Intelligence(AI)and encryption techniques find a way to handle massive quantities of medical data and achieve *** this view,the current study presents a new Optimal Privacy Preserving and Deep Learning(DL)-based Disease Diagnosis(OPPDL-DD)in IoMT ***,the proposed model enables IoMT devices to collect patient data which is then preprocessed to optimize *** order to decrease the computational difficulty during diagnosis,radix Tree structure is *** addition,Elgamal public key cryptosystem with rat Swarm Optimizer(EIg-rSO)is applied to encrypt the *** the transmission of encrypted data to cloud,respective decryption process occurs and the actual data gets ***,a hybridized methodology combining gated recurrent Unit(grU)with Convolution Neural Network(CNN)is exploited as a classification model to diagnose the *** sets of simulations were conducted to highlight the performance of the proposed model on benchmark *** experimental outcomes ensure that the proposed model is superior to existing methods under different measures.

关键词： Internet of medical things privacy security encryption radix tree deep learning

A comparative evaluation of microstructural and mechanical behavior of fiber laser beam and tungsten inert gas dissimilar ultra high strength steel welds

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Defence Technology（防务技术） 2016年第6期12卷 464-472页

作者： Jaiteerth r. joshi Mastanaiah POTTA Kumar ADEPU ramesh Kumar KATTA Madhusudhan reddy gANKIDI Defence research and Development Laboratory Kanchanbagh Hyderabad Telangana 500058 India National Institute of Technology Warangal Telangana 502205 India Defence Metallurgical research Laboratory Kanchanbagh Hyderabad Telangana 500058 India

The influence of different welding processes on the mechanical properties and the corresponding variation in the microstructural features have been investigated for the dissimilar weldments of 18% Ni maraging steel 250 and AISI 4130 steel. The weld joints are realized through two different fusion welding processes, tungsten inert arc welding(TIg) and laser beam welding(LBW), in this study. The dissimilar steel welds were characterized through optical microstructures, microhardness survey across the weldment and evaluation of tensile properties. The fiber laser beam welds have demonstrated superior mechanical properties and reduced heat affected zone as compared to the TIg weldments.

关键词： TIg welding Fiber laser AISI 4130 steel Laser beam welding Maraging steel

Effect of hole-transporting materials on the photovoltaic performance and stability of all-ambient-processed perovskite solar cells

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Journal of Energy Chemistry 2017年第3期26卷 584-591页

作者： Nanaji Islavath S Saroja K Srinivas reddy P C Harikesh g Veerappan Shrikant V joshi Easwaramoorthi ramasamy Centre for Solar Energy Materials International Advanced Research Centre for Powder Metallurgy and New Materials(ARCI)Hyderabad 500005India

High-efficiency perovskite solar cells（PSCs） reported hitherto have been mostly prepared in a moisture and oxygen-free glove-box atmosphere, which hampers upscaling and real-time performance assessment of this exciting photovoltaic technology. In this work, we have systematically studied the feasibility of allambient-processing of PSCs and evaluated their photovoltaic performance. It has been shown that phasepure crystalline tetragonal MAPbI;perovskite films are instantly formed in ambient air at room temperature by a two-step spin coating process, undermining the need for dry atmosphere and ***-ambient-processed PSCs with a configuration of FTO/TiO;/MAPbI;/Spiro-OMeTAD/Au achieve opencircuit voltage（990 mV） and short-circuit current density（20.31 mA/cm;） comparable to those of best reported glove-box processed devices. Nevertheless, device power conversion efficiency is still constrained at 5% by the unusually low fill-factor of 0.25. Dark current–voltage characteristics reveal poor conductivity of hole-transporting layer caused by lack of oxidized spiro-OMe TAD species, resulting in high seriesresistance and decreased fill-factor. The study also establishes that the above limitations can be readily overcome by employing an inorganic p-type semiconductor, copper thiocyanate, as ambient-processable hole-transporting layer to yield a fill-factor of 0.54 and a power conversion efficiency of 7.19%. The present findings can have important implications in industrially viable fabrication of large-area PSCs.

关键词： Perovskite Ambient processing Solar cell Hole transport Series resistance

Design of QoS Aware routing Protocol for IoT Assisted Clustered WSN

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Computers, Materials & Continua 2022年第5期71卷 3785-3801页

作者： Ashit Kumar Dutta S.Srinivasan Bobbili Prasada rao B.Hemalatha Irina V.Pustokhina Denis A.Pustokhin gyanendra Prasad joshi Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityRiyadh13713Kingdom of Saudi Arabia Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha NagarThandalamChennai602105India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Electronics and Communication Engineering Thirumalai Engineering CollegeKancheepuram631551India Department of Entrepreneurship and Logistics Plekhanov Russian University of Economics117997MoscowRussia Department of Logistics State University of Management109542MoscowRussia Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

In current days,the domain of Internet of Things(IoT)and Wireless Sensor Networks(WSN)are combined for enhancing the sensor related data transmission in the forthcoming networking *** and routing techniques are treated as the effective methods highly used to attain reduced energy consumption and lengthen the lifetime of the WSN assisted IoT *** this view,this paper presents an Ensemble of Metaheuristic Optimization based QoS aware Clustering with Multihop routing(EMOQoSCMr)Protocol for IoT assisted *** proposed EMO-QoSCMr protocol aims to achieve QoS parameters such as energy,throughput,delay,and *** proposed model involves two stage processes namely clustering and ***,the EMO-QoSCMr protocol involves crossentropy rain optimization algorithm based clustering(CErOAC)technique to select an optimal set of cluster heads(CHs)and construct ***,oppositional chaos game optimization based routing(OCgOr)technique is employed for the optimal set of routes in the IoT assisted *** proposed model derives a fitness function based on the parameters involved in the IoT nodes such as residual energy,distance to sink node,*** proposed EMOQoSCMr technique has resulted to an enhanced NAN of 64 nodes whereas the LEACH,PSO-ECHS,E-OEErP,and iCSHS methods have resulted in a lesser NAN of 2,10,42,and 51 *** performance of the presented protocol has been evaluated interms of energy efficiency and network lifetime.

关键词： Internet of things wireless sensor networks clustering routing metaheuristics cluster head selection QoS parameters

DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems

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Computers, Materials & Continua 2023年第3期74卷 6429-6444页

作者： A.Arokiaraj Jovith S.rama Sree gudikandhula Narasimha rao K.Vijaya Kumar Woong Cho gyanendra Prasad joshi Sung Won Kim Department of Networking and Communications College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science Engineering Aditya Engineering CollegeSurampalemAndhra Pradesh533437India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering Vignan’s Institute of Engineering for WomenVisakhapatnam530049India Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

The exponential growth of data necessitates an effective data storage scheme,which helps to effectively manage the large quantity of *** accomplish this,Deoxyribonucleic Acid(DNA)digital data storage process can be employed,which encodes and decodes binary data to and from synthesized strands of *** quantization(VQ)is a commonly employed scheme for image compression and the optimal codebook generation is an effective process to reach maximum compression *** article introduces a newDNAComputingwithWater StriderAlgorithm based Vector Quantization(DNAC-WSAVQ)technique for Data Storage *** proposed DNAC-WSAVQ technique enables encoding data using DNA computing and then compresses it for effective data ***,the DNAC-WSAVQ model initially performsDNA encoding on the input images to generate a binary encoded *** addition,aWater Strider algorithm with Linde-Buzo-gray(WSA-LBg)model is applied for the compression process and thereby storage area can be considerably *** order to generate optimal codebook for LBg,the WSA is applied to *** performance validation of the DNAC-WSAVQ model is carried out and the results are inspected under several *** comparative study highlighted the improved outcomes of the DNAC-WSAVQ model over the existing methods.

关键词： DNA computing data storage image compression vector quantization ws algorithm space saving

Effective return rate Prediction of Blockchain Financial Products Using Machine Learning

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Computers, Materials & Continua 2023年第1期74卷 2303-2316页

作者： K.Kalyani Velmurugan Subbiah Parvathy Hikmat A.M.Abdeljaber T.Satyanarayana Murthy Srijana Acharya gyanendra Prasad joshi Sung Won Kim Pg and research Department of Computer Science Marudupandiyar College(Affiliated to Bharathidasan UniversityTiruchirappalli)Thanjavur613403India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and EducationKrishnankoil626126TamilnaduIndia Department of Computer Science Faculty of Information TechnologyApplied Science Private UniversityAmmanJordan Department of Information Technology Chaitanya Bharathi Institute of TechnologyHyderabadTelangana500075India Department of Convergence Science Kongju National UniversityGongju32588Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced *** successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial *** stockholders focused on the prediction of return rate and risk rate of financial ***,an automatic return rate bitcoin prediction model becomes essential for BC financial *** newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive *** study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial *** presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial ***,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification *** application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return *** experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many *** experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal rMSE of 0.1562.

关键词： Financial products blockchain return rate prediction model machine learning parameter optimization