IJAMSR - INTERNATIONAL JOURNAL OF ADVANCED MULTIDISCIPLINARY SCIENTIFIC RESEARCH

Engineering
Life Sciences
Health Sciences
Physical & Chemical Sciences
Social Sciences & Humanities

Multidisciplinary
Engineering
Life Sciences
Health Sciences
Physical Sciences
Chemical Sciences
Social Sciences & Humanities

UPDATES

IJAMSR associated with CrossRef DOI, IJAMSR DOI: https://doi.org/10.31426/ijamsr and Index Copernicus International ( ICI)
International Scientific Indexing (ISI)
Impact Factor 8.535

Past Issues

2024 Past Issues

Volume 7 ---> Issue 7
Volume 7 ---> Issue 6
Volume 7 ---> Issue 5
Volume 7 ---> Issue 4
Volume 7 ---> Issue 3
Volume 6 ---> Issue 9
Volume 6 ---> Issue 8
Volume 6 ---> Issue 7
Volume 6 ---> Issue 4
Volume 6 ---> Issue 3
Volume 3 ---> Issue 12
Volume 2 ---> Issue 3

2023 Past Issues

2022 Past Issues

Volume 5 ---> Issue 10
Volume 5 ---> Issue 9
Volume 5 ---> Issue 8
Volume 5 ---> Issue 7
Volume 5 ---> Issue 6
Volume 5 ---> Issue 5
Volume 5 ---> Issue 4
Volume 5 ---> Issue 3
Volume 5 ---> Issue 2
Volume 5 ---> Issue 1
Volume 3 ---> Issue 11
Volume 3 ---> Issue 9
Volume 3 ---> Issue 3
Volume 2 ---> Issue 12
Volume 2 ---> Issue 4
Volume 1 ---> Issue 10
Volume 1 ---> Issue 8
Volume 1 ---> Issue 5
Volume 2 ---> Issue 1

2021 Past Issues

Volume 4 ---> Issue 12
Volume 4 ---> Issue 11
Volume 4 ---> Issue 10
Volume 4 ---> Issue 9
Volume 4 ---> Issue 8
Volume 4 ---> Issue 7
Volume 4 ---> Issue 6
Volume 4 ---> Issue 5
Volume 4 ---> Issue 4
Volume 4 ---> Issue 3
Volume 4 ---> Issue 2
Volume 4 ---> Issue 1
Volume 3 ---> Issue 10
Volume 2 ---> Issue 5
Volume 2 ---> Issue 3
Volume 2 ---> Issue 2
Volume 1 ---> Issue 10
Volume 1 ---> Issue 4
Volume 2 ---> Issue 1

2020 Past Issues

Volume 3 ---> Issue 12
Volume 3 ---> Issue 11
Volume 3 ---> Issue 10
Volume 3 ---> Issue 9
Volume 3 ---> Issue 8
Volume 3 ---> Issue 7
Volume 3 ---> Issue 6
Volume 3 ---> Issue 5
Volume 3 ---> Issue 4
Volume 3 ---> Issue 2
Volume 3 ---> Issue 1
Volume 2 ---> Issue 2
Volume 1 ---> Issue 10
Volume 1 ---> Issue 9
Volume 1 ---> Issue 3

2019 Past Issues

Volume 2 ---> Issue 12
Volume 2 ---> Issue 11
Volume 2 ---> Issue 10
Volume 2 ---> Issue 9
Volume 2 ---> Issue 6
Volume 2 ---> Issue 5
Volume 2 ---> Issue 4
Volume 2 ---> Issue 3
Volume 2 ---> Issue 2
Volume 2 ---> Issue 8
Volume 2 ---> Issue 1

2018 Past Issues

Volume 1 ---> Issue 10
Volume 1 ---> Issue 8
Volume 1 ---> Issue 9
Volume 1 ---> Issue 7
Volume 1 ---> Issue 6
Volume 1 ---> Issue 5
Volume 1 ---> Issue 4
Volume 1 ---> Issue 3
Volume 1 ---> Issue 2
Volume 1 ---> Issue 1

Call for Papers

Call for Papers Sep-2024

Paper Submission: 25-Sep-2024

Publication: 30-Sep-2024

Manual Article Submission

Email Us : editor@ijamsr.com

Track Your Article

Special Issue

Special Archives

Downloads

Article Template
Covering Letter Tempalte
Copyright Template

Past Issues

Jean Watsonâ€™s Middle Range Theory of Human Caring: A Critique

Ms. Kholoud Najeh Alharbi, Dr. Omar Ghazi Baker,

CrossRef DOI : 10.31426/ijamsr.2020.3.1.3011

CrossRef DOI URL : https://doi.org/10.31426/ijamsr.2020.3.1.3011

Download PDF Google Search Abstract

There are different terms that are related to care in the nursing profession such as nursing care, care, care givingâ€¦..etc (Blasdell, 2017). â€œCaring is a nurturing way of relating to a valued other toward whom one feels a personal sense of commitment and responsibilityâ€ (Swanson, 1991, p. 162). Dr. Jean Watson is a professor and nursing theorist and the director of the Watson Caring Science Institute. She is known for her Theory of Human Caring. Between 1975 and 1979, Watson established the Theory of Human Caring from her personal views of nursing. She developed this middle-range theory to combine nursing with education, practice and social psychology studies (Watson, n.d.). There are three main conceptual elements in both the original and evolving theory. The concepts are evolved based on Dr. Watsonâ€™s experience and background. The three concepts of Watsonâ€™s Theory of Human Caring include carative factors, a caring relationship, and caring moments.

Design Of Local Thresholding Based Retinal Vessel Separation

Mohammad Sami, Dr. Avinash Gour

CrossRef DOI : 10.31426/ijamsr.2020.3.1.3012

CrossRef DOI URL : https://doi.org/10.31426/ijamsr.2020.3.1.3012

Download PDF Google Search Abstract

Limitation and division are significant errand in clinical picture examination. As we probably am aware identification of optic nerves is additionally a significant issue in mechanized retinal picture investigation framework. Picture division of clinical picture is exceptionally unpredictable and vital advance, in this arrangement division of retinal picture is more mind boggling in examination of others. For the retinal picture division, we use angle drop technique. Late exploration is centre around better exactness rate. This paper gives a superior over all the discovery procedure toward reasonable division of optic nerves utilizing inclination drop technique (GDM). For instatement of nearby form, we utilize Signed weight power work (SPF) which is district based dynamic shape model.

Spectral Coordinate Channel And Cosine Finder Additionally Accept Gaussian Conveyances For The Objectivity And Foundation Of Pixels

Sunil Singarapu, Dr. Avinash Gour

CrossRef DOI : 10.31426/ijamsr.2020.3.1.3013

CrossRef DOI URL : https://doi.org/10.31426/ijamsr.2020.3.1.3013

Download PDF Google Search Abstract

Comprehensive assessment using the hyper spectral datasets reveals the effective analyzes of spectral specifics from hyper spectral images by this review paper. The hyper spectral data sets are determined over the distorted Gaussian Processes related to those hyper spectral data sets and the resulting image is built by linking the structures with the unique Procedures. The Gaussian Processes are included in sets using groups of hyper spectral training data sets. In this paper we are going to review how to analyze spectral details from hyper spectral images using well-known spectral analyses by Gaussian Processes and combining them with the hyper spectral images. Each data set is distorted to match the spectral quantization of the test input hyper spectral image. This review and implementation utilize process Kernels to analyze the comparative smoothness of hyper spectral reflectance, and eliminates errors in resulting signals for better estimation of the hyper spectral reflectance result. This review concludes the anticipated Gaussian Processes and combined kernel based analyzing hyper spectral reflectance.

Information for Authors

Publication Ethics
Peer Review Process
Anti-Plagiarism Policy

Search Article

Join as Reviewer

Multidisciplinary Subjects

Engineering
Life Sciences
Health Sciences
Physical & Chemical Sciences
Social Sciences & Humanities

SignUp for Newsletters

and Stay informed about our updates

Contact

Address:
8- 284, Srinivasa Nagar, Tadigadapa,
Penamalur, Vijayawada,
Andhra Pradesh, India

Phone: +91 9705743501

Email: editor@ijamsr.com

Social Links

Twitter
Facebook
Linked In

Multidisciplinary Subjects

Engineering
Life Sciences
Health Sciences
Physical & Chemical Sciences
Social Sciences & Humanities

Home
Conference
Contact