scholarly journals Review of Metaheuristics Inspired from the Animal Kingdom

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2335
Author(s):  
Elena Niculina Dragoi ◽  
Vlad Dafinescu
Keyword(s):  
Metaheuristic Algorithms ◽  
Animal Kingdom ◽  
Biological Classification ◽  
Living Things

The search for powerful optimizers has led to the development of a multitude of metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom as a source of inspiration and performs an extensive, yet not exhaustive, review of the animal inspired metaheuristics proposed in the 2006–2021 period. The review is organized considering the biological classification of living things, with a breakdown of the simulated behavior mechanisms. The centralized data indicated that 61.6% of the animal-based algorithms are inspired from vertebrates and 38.4% from invertebrates. In addition, an analysis of the mechanisms used to ensure diversity was performed. The results obtained showed that the most frequently used mechanisms belong to the niching category.

Biological Systematics

2021 ◽  
Author(s):  
Andrew V. Z. Brower ◽  
Randall T. Schuh
Keyword(s):  
Phylogenetic Inference ◽  
Molecular Clocks ◽  
Practical Application ◽  
Character Analysis ◽  
Biological Classification ◽  
Living Things ◽  
Biological Systematics ◽  
Desk Reference ◽  
Systematic Biology

Understanding the history and philosophy of biological systematics (phylogenetics, taxonomy and classification of living things) is key to successful practice of the discipline. In this thoroughly revised third edition, the authors provide an updated account of cladistic principles and techniques, emphasizing their empirical and epistemological clarity. The book covers the history and philosophy of systematics; the mechanics and methods of character analysis, phylogenetic inference, and evaluation of results; the practical application of systematic results to biological classification, adaptation and coevolution, biodiversity, and conservation; along with new chapters on species and molecular clocks. The book is both a textbook for students studying systematic biology and a desk reference for practicing systematists. Part explication of concepts and methods, part exploration of the underlying epistemology of systematics, the edition addresses why some methods are more empirically sound than others.

scholarly journals Identification and Classification of Pathogenic Bacteria Using the K-Nearest Neighbor Method

2021 ◽  
Vol 5 (1) ◽  
pp. 60-70
Author(s):  
Diana Rahmawati ◽  
Mutiara Puspa Putri I ◽  
Miftachul Ulum ◽  
Koko Joni
Keyword(s):  
Pathogenic Bacteria ◽  
Nearest Neighbor ◽  
Ocular Lens ◽  
K Nearest Neighbor ◽  
Image Capture ◽  
Chebyshev Method ◽  
Living Things ◽  
Auto Focus ◽  
The Government

Bacteria are a group of living things or organisms that do not have a core covering. In the grouping, some bacteria are pathogenic. With a microscopic size, many pathogenic bacteria are found around and spread through the food eaten or by touching objects around them, then cause diseases such as diarrhea, vomiting, and others. As a more effective effort to help the government and society prevent disease caused by pathogenic bacteria, a system for the identification and classification of pathogenic bacteria K-Nearest Neighbor was created. This system uses a biological microscope that is attached to a webcam camera above the ocular lens as a tool to see bacterial objects and assist in bacterial capture. Rough player rotates automatically (auto-focus) in image capture. In the process of classification and identifying bacteria, the K-Nearest Neighbor method is used, which is a method with the calculation of the nearest neighbor or calculation based on the level of similarity to the dataset. In this study, the bacteria vibrio chlorae, staphylococcus aereus, and streptococcus m. with the highest accuracy is the K = 9 value of 97.77% using the Chebyshev method.

scholarly journals Management of vascular anomalies: Review of institutional management algorithm

2017 ◽  
Vol 50 (02) ◽  
pp. 193-200 ◽  
Author(s):  
Lalit K. Makhija ◽  
Sameek Bhattacharya
Keyword(s):  
Multidisciplinary Approach ◽  
Vascular Malformations ◽  
Treatment Protocol ◽  
Vascular Anomalies ◽  
Algorithmic Approach ◽  
Institutional Management ◽  
Management Algorithm ◽  
Biological Classification ◽  
Functional Consequences

ABSTRACT Introduction: Vascular anomalies are congenital lesions broadly categorised into vascular tumour (haemangiomas) and vascular dysmorphogenesis (vascular malformation). The management of these difficult problems has lately been simplified by the biological classification and multidisciplinary approach. To standardise the treatment protocol, an algorithm has been devised. The study aims to validate the algorithm in terms of its utility and presents our experience in managing vascular anomalies. Materials and Methods: The biological classification of Mulliken and Glowacki was followed. A detailed algorithm for management of vascular anomalies has been devised in the department. The protocol is being practiced by us since the past two decades. The data regarding the types of lesions and treatment modality used were maintained. Results and Conclusion: This study was conducted from 2002 to 2012. A total of 784 cases of vascular anomalies were included in the study of which 196 were haemangiomas and 588 were vascular malformations. The algorithmic approach has brought an element of much-needed objectivity in the management of vascular anomalies. This has helped us to define the management of particular lesion considering its pathology, extent and aesthetic and functional consequences of ablation to a certain extent.

Classification of living things

2001 ◽  
Vol 38 (07) ◽  
pp. 38-3879-38-3879
Keyword(s):  
Living Things
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