scholarly journals Design and Development of Leg-Wheel Hybrid Hexapod along with Machine Learning Algorithm implementation

2015 ◽  
Vol 4 (4) ◽  
pp. 262
Author(s):  
Harikrishnan Madhusudanan
Keyword(s):  
Concurrent Engineering ◽  
Learning Algorithm ◽  
Legged Robot ◽  
Robotic Platform ◽  
Design And Development ◽  
Design Metrics ◽  
Advantages And Disadvantages ◽  
Wheeled Robot ◽  
Primary Focus ◽  
Algorithm Implementation

The conventional mobile robotic platforms which either uses wheels or legs are quite familiar and each one of them has its own advantages and disadvantages. The wheeled robot is suitable for only plain and smooth terrain, whereas the legged robot can travel in any kind of terrain but is comparatively slower than the wheeled robot. So, a hybrid of both wheeled and legged platform would be quite suitable for any kind of terrain. The primary focus of this paper is to design and develop a leg-wheel hybrid robotic platform with a concurrent engineering and mechatronics approach to produce results with optimised design metrics at each and every stage of its development. An overall view of the entire mechatronics system is considered for design and development of the robot at each and every stage rather than a sequential engineering approach.

Design of Leg Wheel Hybrid Hexapod with C-Leg Analysis

2016 ◽  
Vol 852 ◽  
pp. 832-838
Author(s):  
S. Vasanth ◽  
M. Harikrishnan ◽  
K. Abbhivignesh ◽  
B. Karthikeyan ◽  
M. Vignesh
Keyword(s):  
Finite Element Analysis ◽  
Concurrent Engineering ◽  
Legged Robot ◽  
Robotic Platform ◽  
Element Analysis ◽  
Design Metrics ◽  
Advantages And Disadvantages ◽  
The Finite Element Analysis ◽  
Wheeled Robot ◽  
Primary Focus

The conventional mobile robotic platforms which either uses wheels or legs are quite familiar and each one of them has its own advantages and disadvantages. The wheeled robot is suitable for only plain and smooth terrain, whereas the legged robot can travel in any kind of terrain but is comparatively slower than the wheeled robot. So, a hybrid of both wheeled and legged platform would be quite suitable for any kind of terrain. The primary focus of this paper is to design and develop a leg-wheel hybrid robotic platform with a concurrent engineering and mechatronics approach to produce results with optimised design metrics at each and every stage of its development. An overall view of the entire mechatronics system is considered for design and development of the robot at each and every stage rather than a sequential engineering approach. This paper details the Finite Element Analysis (FEA) of the C – Legs which are used in the robot.

Least Square Regression with lp-Coefficient Regularization

2010 ◽  
Vol 22 (12) ◽  
pp. 3221-3235 ◽  
Author(s):  
Hongzhi Tong ◽  
Di-Rong Chen ◽  
Fenghong Yang
Keyword(s):  
Error Analysis ◽  
Learning Algorithm ◽  
Learning Rate ◽  
Least Square ◽  
Explicit Learning ◽  
Regularization Term ◽  
Least Square Regression ◽  
Primary Focus ◽  
Selection Of

The selection of the penalty functional is critical for the performance of a regularized learning algorithm, and thus it deserves special attention. In this article, we present a least square regression algorithm based on lp-coefficient regularization. Comparing with the classical regularized least square regression, the new algorithm is different in the regularization term. Our primary focus is on the error analysis of the algorithm. An explicit learning rate is derived under some ordinary assumptions.

scholarly journals Research and Implementation of the Text Matching Algorithm in the Field of Housing Law and Policy Based on Deep Learning

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yin Xu ◽  
Hong Ma
Keyword(s):  
Deep Learning ◽  
Affordable Housing ◽  
Legal System ◽  
Learning Algorithm ◽  
Matching Algorithm ◽  
Advantages And Disadvantages ◽  
Housing Security ◽  
Law And Policy ◽  
Depth Learning ◽  
Text Matching

Machine learning enables machines to learn rules from a large amount of data input from the outside world through algorithms, so as to identify and judge. It is the main task of the government to further emphasize the importance of improving the housing security mechanism, expand the proportion of affordable housing, increase financial investment, improve the construction quality of affordable housing, and ensure fair distribution. It can be seen that the legal system of housing security is essentially a system to solve the social problems brought by housing marketization, and it is an important part of the whole national housing system. More and more attention has been paid to solving the housing difficulties of low- and middle-income people and establishing a housing security legal system suitable for China’s national conditions and development stage. Aiming at the deep learning problem, a text matching algorithm suitable for the field of housing law and policy is proposed. Classifier based on matching algorithm is a promising classification technology. The research on the legal system of housing security is in the exploratory stage, involving various theoretical and practical research studies. Compare the improved depth learning algorithm with the general algorithm, so as to clearly understand the advantages and disadvantages of the improved depth learning algorithm and depth learning algorithm. This paper introduces the practical application of the deep learning model and fast learning algorithm in detail. Creatively put forward to transform it into an independent public law basis or into an independent savings system.

Role of Molecular Docking in Computer-Aided Drug Design and Development

2016 ◽  
pp. 1-28
Author(s):  
Rahul Agarwal ◽  
Ashutosh Singh ◽  
Subhabrata Sen
Keyword(s):  
Molecular Docking ◽  
Drug Design ◽  
Protein Binding ◽  
Design And Development ◽  
Advantages And Disadvantages ◽  
Computer Aided ◽  
Drug Designing ◽  
Near Future

Molecular Docking is widely used in CADD (Computer-Aided Drug Designing), SBDD (Structure-Based Drug Designing) and LBDD (Ligand-Based Drug Designing). It is a method used to predict the binding orientation of one molecule with the other and used for any kind of molecule based on the interaction like, small drug molecule with its protein target, protein – protein binding or a DNA – protein binding. Docking is very much popular technique due to its reliable prediction properties. This book chapter will provide an overview of diverse docking methodologies present that are used in drug design and development. There will be discussion on several case studies, pertaining to each method, followed by advantages and disadvantages of the discussed methodology. It will typically aim professionals in the field of cheminformatics and bioinformatics, both in academia and in industry and aspiring scientists and students who want to take up this as a profession in the near future. We will conclude with our opinion on the effectiveness of this technology in the future of pharmaceutical industry.

Reconstructive derivational analogy: A machine learning approach to automating redesign

1996 ◽  
Vol 10 (2) ◽  
pp. 115-126 ◽  
Author(s):  
B.D. Britt ◽  
T. Glagowski
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Design Tool ◽  
Design Reuse ◽  
Learning Approach ◽  
Machine Learning Algorithm ◽  
Machine Learning Approach ◽  
Design Plan ◽  
Primary Focus ◽  
Different Parts

AbstractThis paper describes current research toward automating the redesign process. In redesign, a working design is altered to meet new problem specifications. This process is complicated by interactions between different parts of the design, and many researchers have addressed these issues. An overview is given of a large design tool under development, the Circuit Designer's Apprentice. This tool integrates various techniques for reengineering existing circuits so that they meet new circuit requirements. The primary focus of the paper is one particular technique being used to reengineer circuits when they cannot be transformed to meet the new problem requirements. In these cases, a design plan is automatically generated for the circuit, and then replayed to solve all or part of the new problem. This technique is based upon the derivational analogy approach to design reuse. Derivational Analogy is a machine learning algorithm in which a design plan is saved at the time of design so that it can be replayed on a new design problem. Because design plans were not saved for the circuits available to the Circuit Designer's Apprentice, an algorithm was developed that automatically reconstructs a design plan for any circuit. This algorithm, Reconstructive Derivational Analogy, is described in detail, including a quantitative analysis of the implementation of this algorithm.

The State and Future of Blood-Based Biomarkers in the Health and Retirement Study

2011 ◽  
Vol 14 (3) ◽  
Author(s):  
Thomas McDade
Keyword(s):  
Survey Design ◽  
Low Cost ◽  
Reproductive Function ◽  
Health And Retirement Study ◽  
Sample Collection ◽  
Advantages And Disadvantages ◽  
Methods Development ◽  
Wide Range ◽  
Primary Focus ◽  
Retirement Study

The Health and Retirement Study (HRS) is an important national resource for policy makers and investigators across a wide range of disciplines, and it is critical that the study collects the best information possible on the health status of its participants within the constraints of the survey design, and without compromising the integrity of the sample. Potential directions for the collection and analysis of biomarker data in future waves of HRS are discussed, with a primary focus on blood-based biomarkers. Advantages and disadvantages of various methods for collecting blood in the home are considered, with particular attention given to the strengths and weaknesses of dried blood spot (DBS) sampling. DBS sampling has been widely applied in recent biosocial surveys due to the low cost and burden associated with sample collection, but these benefits need to be weighed against challenges associated with quantification in the laboratory. Attention is also given to additional biomarkers that may be of relevance to HRS, and that would expand the survey’s current focus on obesity and metabolic syndrome. Measures of inflammation, pathogen exposure, reproductive function, stress, and epigenetic modifications are suggested as potentially productive future directions for the study. In addition, the analysis concludes with the following recommendations for HRS: Continue to collect DBS samples, but consider alternatives; implement enhanced procedures for quality control; calibrate DBS results against plasma values, and invest in methods development.

scholarly journals Reviewing of Different Methods for Handling Longitudinal Count data

2021 ◽  
Vol 23 (08) ◽  
pp. 195-206
Author(s):  
Amany. M ◽  
◽  
Mousa ◽  
Ahmed. A ◽  
El sheikh ◽  
...  
Keyword(s):  
Method Of Moments ◽  
Count Data ◽  
Generalized Estimating Equations ◽  
Generalized Method Of Moments ◽  
Marginal Models ◽  
Advantages And Disadvantages ◽  
Population Average ◽  
Longitudinal Count Data ◽  
Quadratic Inference Functions ◽  
Primary Focus

In this paper, we will review the methods that used to handle longitudinal data in the case of marginal models when inferences about the population average are the primary focus [1] or when future applications of the results require the expectation of the response as a function of the current covariates [7]. We will review the generalized estimating equations method (GEE), quadratic inference functions (QIF), generalized quasi likelihood (GQL) and the generalized method of moments (GMM). These methods will be reviewed by discussing its advantages and disadvantages in more details.

scholarly journals Embedding ROS and AI-Based Perception Capabilities in a Novel Low-Cost Assistive Robotic Platform

2021 ◽  
Vol 7 (1) ◽  
pp. 12
Author(s):  
Jaime Mas-Santillán ◽  
Francisco Javier Acevedo-Rodríguez ◽  
Roberto Javier López-Sastre
Keyword(s):  
Operating System ◽  
Low Cost ◽  
Robotic Platform ◽  
Robot Operating System ◽  
Wheeled Robot ◽  
Assistive Robotic

This paper describes how we developed a novel low-cost assistive robotic platform, with AI-based perception capabilities, able to navigate autonomously using Robot Operating System (ROS). The platform is a differential wheeled robot, equipped with two motors and encoders, which are controlled with an Arduino board. It also includes a Jetson Xavier processing board on which we deploy all AI processes, and the ROS architecture. As a result of the work, we have a fully functional platform, able to recognize actions online, and navigate autonomously through environments whose map has been preloaded.

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