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Assessment of Dental Caries and Oral Hygiene Status Among Twins

Journal of Forensic Science and Medicine 2018年第1期4卷 18-22页

作者： priya subramaniam K L Girish Babu Bharath Vardhana Department of Pedodontics and Preventive Dentistry The Oxford Dental College and HospitalBengaluru1Departmentof DentistryHassan Institute of Medical SciencesHassanKarnatakaIndia

The study of twins provides a unique opportunity to evaluate the genetic and nongenetic contributions to a variance of multitude of *** research has revealed the impact of a strong genetic component to the variance of many dental *** present study was conducted to assess the dental caries and oral hygiene status in monozygotic(MZ)and dizygotic(DZ)twins.A random sample of 129 MZ and DZ twin pairs aged 6-15 years were included in this *** zygosity of twin pairs was initially recorded by facial appearance and later determined by *** caries and oral hygiene status were recorded in these twin pairs and the data were subjected to statistical *** significant difference was observed in the mean decayed,extracted due to caries and filled teeth(deft)in primary dentition and decayed,missing and filled(DMFT)in permanent dentition scores and oral hygiene status in MZ and DZ twin pair&The similarity observed in oral health status reflects the effects of a shared environment in MZ and DZ twin pairs.

关键词： Dental caries dermatoglyphics facial appearance oral hygiene index-simplified zygosity

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Reinforcement Learning to Improve QoS and Minimizing Delay in IoT

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Intelligent Automation & Soft Computing 2023年第5期36卷 1603-1612页

作者： Mahendrakumar subramaniam V.Vedanarayanan Azath Mubarakali S.Sathiya priya Department of Electronics and Communications Engineering Velalar College of Engineering and TechnologyErodeTamil NaduIndia Department of Electronics and Communication Engineering Sathyabama Institute of Science and TechnologyChennaiTamil NaduIndia College of Computer Science King Khalid UniversityAbhaSaudi Arabia Department of Electronics and Communications

Machine Learning concepts have raised executions in all knowledge domains,including the Internet of Thing(IoT)and several business *** of Service(QoS)has become an important problem in IoT surrounding since there is a vast explosion of connecting sensors,information and ***-sor data gathering is an efﬁcient solution to collect information from spatially dis-seminated IoT *** Learning Mechanism to improve the QoS(RLMQ)and use a Mobile Sink(MS)to minimize the delay in the wireless IoT s proposed in this ***,we use machine learning concepts like Rein-forcement Learning(RL)to improve the QoS and energy efﬁciency in the Wire-less Sensor Network(WSN).The MS collects the data from the Cluster Head(CH),and the RL incentive values select *** incentives value is computed by the QoS parameters such as minimum energy utilization,minimum bandwidth utilization,minimum hop count,and minimum time *** MS is used to col-lect the data from CH,thus minimizing the network *** sleep and awake scheduling is used for minimizing the CH dead in the *** work is simu-lated,and the results show that the RLMQ scheme performs better than the base-line *** prove that RLMQ increased the residual energy,throughput and minimized the network delay in the WSN.

关键词： Wireless sensor network quality of service parameters Internet of things reinforcement learning mobile sink

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