Engineering Universe For Scientific Research And Management Beta

ISSN (Online): 2319-3069
(International Journal)






Notice Board :

Call for Paper
Vol. 16 Issue 4

Submission Start Date:
April 01, 2024

Acceptence Notification Start:
April 10, 2024

Submission End:
April 25, 2024

Final MenuScript Due:
April 30, 2024

Publication Date:
April 30, 2024
                         Notice Board: Call for PaperVol. 16 Issue 4      Submission Start Date: April 01, 2024      Acceptence Notification Start: April 10, 2024      Submission End: April 25, 2024      Final MenuScript Due: April 30, 2024      Publication Date: April 30, 2024




Volume XII Issue XI

Paper Title
A FRAMEWORK FOR MULTI-OBJECTIVE GENETIC ALGORITHM BASED SELF OPTIMAL CLUSTERING TECHNIQUE
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

Paper Title
A SURVEY ON WIRELESS SENSOR NETWORKS ROUTING PROTOCOLS
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

Paper Title
CHRONIC KIDNEY DISEASE RISK PREDICTION USING MACHINE LEARNING ALGORITHM
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

Paper Title
Rail Projects through 5D-BIM A Conceptual Governance Framework
Author Name
Dinesh Kumar, Arun kumar Jadon
Year Of Publication
2020
Volume and Issue
Volume 12 Issue 11
Abstract
Inefficiencies in Indian metro rail projects, characterized by delays and cost overruns, necessitate a deeper understanding of the root causes. This study employs a meticulously designed questionnaire to gather insights from a diverse range of stakeholders – clients, contractors, and consultants. The questionnaire delves into eight critical categories of delay factors, encompassing client-related issues like land acquisition delays and scope changes, contractor-related issues like financial difficulties and rework, and external factors like unforeseen ground conditions and changes in government regulations. By leveraging a five-point Likert scale, the study gauges both the frequency of occurrence and the severity of impact associated with each factor. Additionally, a pilot survey refines the questionnaire and ensures clarity. A non-probabilistic sampling technique targets professionals with rail project experience. The anticipated analysis using the Relative Importance Index (RII) will
PaperID
2020/EUSRM/11/2020/58230a