Notice Board :

Call for Paper
Vol. 12 Issue 12

Submission Start Date:
December 01, 2020

Acceptence Notification Start:
December 10, 2020

Submission End:
December 20, 2020

Final MenuScript Due:
December 22, 2020

Publication Date:
December 25, 2020
                         Notice Board: Call for PaperVol. 12 Issue 12      Submission Start Date: December 01, 2020      Acceptence Notification Start: December 10, 2020      Submission End: December 20, 2020      Final MenuScript Due: December 22, 2020      Publication Date: December 25, 2020




Volume XII Issue XI

Author Name
Lagan Tiwari, Ritesh Kumar Yadav, Varsha Namdeo
Year Of Publication
2020
Volume and Issue
Volume 12 Issue 11
Abstract
The self-ideal clustering strategy is another territory of exploration in information mining. The self ideal clustering procedure builds the productivity and versatility of segment grouping and mountain grouping strategy. The idea of the self ideal grouping method utilized the idea of heuristic capacity for the choice of bunch record and focus point. This work proposed a novel self ideal grouping strategy utilizing a multi-objective Genetic Algorithm. The multi-objective Genetic Algorithm works in two-stage in the primary stage the Genetic Algorithm work for the determination of focus point and combining the bunch record esteem dependent on characterized wellness limitation esteem. In the second period of the Genetic Algorithm check the allocated number of the estimation of K for the way toward clustering and approved the grouping as indicated by the information test. The proposed calculation was executed in MATLAB programming and utilized some rumored datasets from the UCI.
PaperID
2020/EUSRM/11/2020/58230

Author Name
Nikita Kumari, Ritesh Kumar Yadav, Varsha Namdeo
Year Of Publication
2020
Volume and Issue
Volume 12 Issue 11
Abstract
This paper presents a survey of state-of-the-art routing techniques in Wireless Sensor Networks (WSNs). Compared with traditional wireless networks, WSNs are characterized with denser levels of node deployment, higher unreliability of sensor nodes and severe power, computation and memory constraints. Various design challenges such as energy efficiency, data delivery models, quality of service, overheads etc., for routing protocols in WSNs are highlighted. We addressed most of the proposed routing methods along with scheme designs, benefits and result analysis wherever possible. The routing protocols discussed are classified into seven categories such as Data centric routing, Hierarchical routing, Location based routing, Negotiation based routing, Multipath based routing, Quality of Service (QoS) routing and Mobility based routing. This paper also compares the routing protocols against parameters such as power consumption, scalability, mobility, optimal routing and data aggregation. The
PaperID
2020/EUSRM/11/2020/58231

Author Name
Anita Kumari, Chinmay Bhatt2, Varsha Namdeo
Year Of Publication
2020
Volume and Issue
Volume 12 Issue 11
Abstract
The Chronic Kidney Disease (CKD) is a global public health issue with a growing incidence, pervasiveness, and high cost. To turn into more focus on real insinuation of CKD and health issues coupled with CKD patients, application of Machine Learning (ML) models becomes necessary. The chief objective of this research work is to evolve a better ML classifier framework for predicting possibility of CKD and its progression in patients with health issues like diabetes and hypertension. The early diagnosis can prevent disease progression and severity through suitable preventive measures and thus reduces treatment cost. In this work, framework for CKD risk prediction is proposed which is based on ranking of features done using Recursive Feature Elimination (RFE) method. The proposed framework employs RFE for eliminating the unrelated features from huge dataset of patients. The elimination of irrelevant features reduces the data to be considered and speeds up the execution of ML algorithms.
PaperID
2020/EUSRM/11/2020/59230