Aerospace medicine and biology: A continuing bibliography with indexes, supplement 129, June 1974

This special bibliography lists 280 reports, articles, and other documents introduced into the NASA scientific and technical information system in May 1974

2016 IMSAloquium, Student Investigation Showcase

Welcome to the twenty-eighth year of the Student Inquiry and Research Program (SIR)! This is a program that is as old as IMSA. The SIR program represents our unending dedication to enabling our students to learn what it is to be an innovator and to make contributions to what is known on Earth.https://digitalcommons.imsa.edu/archives_sir/1026/thumbnail.jp

Simulation of Large Scale Computational Ecosystems with Alchemist: A Tutorial

Many interesting systems in several disciplines can be modeled as networks of nodes that can store and exchange data: pervasive systems, edge computing scenarios, and even biological and bio-inspired systems. These systems feature inherent complexity, and often simulation is the preferred (and sometimes the only) way of investigating their behavior; this is true both in the design phase and in the verification and testing phase. In this tutorial paper, we provide a guide to the simulation of such systems by leveraging Alchemist, an existing research tool used in several works in the literature. We introduce its meta-model and its extensible architecture; we discuss reference examples of increasing complexity; and we finally show how to configure the tool to automatically execute multiple repetitions of simulations with different controlled variables, achieving reliable and reproducible results

Investigating Sensorimotor Control in Locomotion using Robots and Mathematical Models

Locomotion is a very diverse phenomenon that results from the interactions of a body and its environment and enables a body to move from one position to another. Underlying control principles rely among others on the generation of intrinsic body movements, adaptation and synchronization of those movements with the environment, and the generation of respective reaction forces that induce locomotion. We use mathematical and physical models, namely robots, to investigate how movement patterns emerge in a specific environment, and to what extent central and peripheral mechanisms contribute to movement generation. We explore insect walking, undulatory swimming and bimodal terrestrial and aquatic locomotion. We present relevant findings that explain the prevalence of tripod gaits for fast climbing based on the outcome of an optimization procedure. We also developed new control paradigms based on local sensory pressure feedback for anguilliform swimming, which include oscillator-free and decoupled control schemes, and a new design methodology to create physical models for locomotion investigation based on a salamander-like robot. The presented work includes additional relevant contributions to robotics, specifically a new fast dynamically stable walking gait for hexapedal robots and a decentralized scheme for highly modular control of lamprey-like undulatory swimming robots

2014 IMSAloquium, Student Investigation Showcase

The ability to work with professionals is a life-changing experience for our students. Working with world-class scholars and advisors, students have contributed to advances in a variety of fields from science, technology, engineering and mathematics, to the performing arts and history.https://digitalcommons.imsa.edu/archives_sir/1006/thumbnail.jp

05. 2014 IMSAloquium Student Investigation Showcase

https://digitalcommons.imsa.edu/class_of_2015/1003/thumbnail.jp

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 203

This bibliography lists 150 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1980

An application of the whale optimization algorithm with Levy flight strategy for clustering of medical datasets

Clustering, which is handled by many researchers, is separating data into clusters without supervision. In clustering, the data are grouped using similarities or differences between them. Many traditional and heuristic algorithms are used in clustering problems and new techniques continue to be developed today. In this study, a new and effective clustering algorithm was developed by using the Whale Optimization Algorithm (WOA) and Levy flight (LF) strategy that imitates the hunting behavior of whales. With the developed WOA-LF algorithm, clustering was performed using ten medical datasets taken from the UCI Machine Learning Repository database. The clustering performance of the WOA-LF was compared with the performance of k-means, k-medoids, fuzzy c-means and the original WOA clustering algorithms. Application results showed that WOA-LF has more successful clustering performance in general and can be used as an alternative algorithm in clustering problems