Biomimetics and the Evolution of Robotics and Intelligent Systems

2018 ◽  
pp. 1-25
Author(s):  
Maki K. Habib ◽  
Fusaomi Nagata
Keyword(s):  
Intelligent Systems ◽  
Research Field ◽  
Biologically Inspired ◽  
Intelligent Machines ◽  
Interdisciplinary Field ◽  
Research Activities ◽  
Engineering Sciences ◽  
Application Potential ◽  
Design Ideas ◽  
Scientific Ideas

Biologically inspired systems, known as “biomimetics” or the “mimicry of nature,” is an interdisciplinary scientific research field inspired by nature and featured by the technology outcome (hardware and software) and lies at the interface of biology, physics, chemistry, information, and engineering sciences. Biomimetics is initiated by making nature a model of inspiration that would immensely help conscious abstraction of new innovative principles and creative design ideas and concepts that help developing new techniques and functionalities, seeking new paradigms and methods, designing new materials, and developing new streams of intelligent machines, robots, systems, devices, algorithms, etc. Biologically inspired approaches create a new reality with great development and application potential with the goal of identifying specific desirable qualities and attributes in biological systems and using them in the design of new products and systems. This chapter provides the importance of biomimetic as an interdisciplinary field and its evolution, advances, challenges, and constraints along with the associated enabling technologies supporting its growth. In addition, it introduces scientific ideas and directions of research activities in the field. The chapter also presents key developments in the field of biomimetic robots and underlines the challenges facing it.

THE CONCEPT OF AUTONOMOUS SYSTEMS IN INDUSTRY 4.0

2019 ◽  
Vol 12 (1) ◽  
pp. 77-87
Author(s):  
György Kovács ◽  
Rabab Benotsmane ◽  
László Dudás
Keyword(s):  
Industry 4.0 ◽  
Intelligent Systems ◽  
Autonomous Systems ◽  
Essential Element ◽  
Industrial Sector ◽  
Life Cycles ◽  
Multi Agent Systems ◽  
New Paradigm ◽  
Intelligent Machines ◽  
Digital Network

Recent tendencies – such as the life-cycles of products are shorter while consumers require more complex and more unique final products – poses many challenges to the production. The industrial sector is going through a paradigm shift. The traditional centrally controlled production processes will be replaced by decentralized control, which is built on the self-regulating ability of intelligent machines, products and workpieces that communicate with each other continuously. This new paradigm known as Industry 4.0. This conception is the introduction of digital network-linked intelligent systems, in which machines and products will communicate to one another in order to establish smart factories in which self-regulating production will be established. In this article, at first the essence, main goals and basic elements of Industry 4.0 conception is described. After it the autonomous systems are introduced which are based on multi agent systems. These systems include the collaborating robots via artificial intelligence which is an essential element of Industry 4.0.

scholarly journals Findings from the Section on Bioinformatics and Translational Informatics

2017 ◽  
Vol 26 (01) ◽  
pp. 188-192 ◽  
Author(s):  
H. Dauchel ◽  
T. Lecroq
Keyword(s):  
Intelligent Systems ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clinical Care ◽  
Evaluation Process ◽  
Omics Data ◽  
Health Domain ◽  
Medical Genomics ◽  
Research Activities ◽  
Translational Informatics

Summary Objective: To summarize excellent current research and propose a selection of best papers published in 2016 in the field of Bioinformatics and Translational Informatics with applications in the health domain and clinical care. Methods: We provide a synopsis of the articles selected for the IMIA Yearbook 2017, from which we attempt to derive a synthetic overview of current and future activities in the field. As in 2016, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section coverage. Each section editor evaluated separately the set of 951 articles returned and evaluation results were merged for retaining 15 candidate best papers for peer-review. Results: The selection and evaluation process of papers published in the Bioinformatics and Translational Informatics field yielded four excellent articles focusing this year on the secondary use and massive integration of multi-omics data for cancer genomics and non-cancer complex diseases. Papers present methods to study the functional impact of genetic variations, either at the level of the transcription or at the levels of pathway and network. Conclusions: Current research activities in Bioinformatics and Translational Informatics with applications in the health domain continue to explore new algorithms and statistical models to manage, integrate, and interpret large-scale genomic datasets. As addressed by some of the selected papers, future trends would include the question of the international collaborative sharing of clinical and omics data, and the implementation of intelligent systems to enhance routine medical genomics.

scholarly journals Diagnostics of psychological readiness of high school students for research activities in mathematics in the design context of a hybrid intellectual learning environment

2021 ◽  
Vol 54 (6) ◽  
pp. 192-210
Author(s):  
Svetlana N. Dvoryatkina ◽  
◽  
Vera S. Merenkova ◽  
Eugeny I. Smirnov ◽  
◽  
...  
Keyword(s):  
High School Students ◽  
Learning Environment ◽  
Boundary Conditions ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Educational Institution ◽  
Value Orientations ◽  
School Students ◽  
Research Activities ◽  
Scientific Potential

Introduction. The problem of improving the process of organizing and supporting the project and research activities of schoolchildren through intelligent management for the purpose of self-organization of the individual, understanding and comprehending complex mathematical knowledge as a principle of personal development is relevant and far from solved. Intelligent systems provide the process of individualization of learning, the establishment of personalized and computerized feedback of cognitive and creative processes. The purpose of the article is to assess the student's readiness for research activities in the context of designing a hybrid intelligent learning environment. Materials and methods. The assessment of the student's psychological readiness for research activities in the conditions of using a hybrid intellectual environment was carried out on an experimental representative sample of students of 1-2 courses of secondary vocational education (n1=42) and students of the senior classes of secondary schools (n2=30). The diagnosis was carried out using the intelligence structure test of R. Amthauer, the creativity questionnaire of D. Johnson, the test "Individual styles of thinking" by A. Alekseev, L. Gromova, the methods of value orientations by M. Rokich, etc. The significance of the differences was established by means of Student's t-test, Fisher's angular transformation, χ2-test. The results of the study. The assessment of psychological readiness for research activities in mathematics was carried out on the basis of the developed nine parameters of scientific potential. The presented results allow us to pre-set the framework of boundary conditions in order to minimize the imprinting time of a hybrid intelligent system (including the selection of the neural network topology). For all three groups of criteria, differences by gender were established, for example, by the parameter "value orientations" (temp  = 2.26 > tcr = 2.02); by the parameter "creativity" (χemp2 = 6,02 ≥ χcr2 (0,05;2) = 5,99). And also by the type of educational institution, for example, by the parameter “motivation to achieve the result” (φemp = 0,186 > φcr = 1,64). Conclusion. The results of the research are of practical value, as they serve as a technological basis for establishing the boundaries and boundary conditions of the most significant parameters for the effective realization of scientific potential, expressed in the work of a specialized web interface created with the student's personal account.

Opinion Dynamics

2013 ◽  
pp. 311-332 ◽  
Author(s):  
Haoxiang Xia ◽  
Huili Wang ◽  
Zhaoguo Xuan
Keyword(s):  
Social Sciences ◽  
Social Dynamics ◽  
Opinion Dynamics ◽  
Research Field ◽  
Physical Models ◽  
Modeling Tools ◽  
Future Directions ◽  
Academic Field ◽  
Interdisciplinary Field ◽  
The Social

As a key sub-field of social dynamics and sociophysics, opinion dynamics utilizes mathematical and physical models and the agent-based computational modeling tools, to investigate the spreading of opinions in a collection of human beings. This research field stems from various disciplines in social sciences, especially the social influence models developed in social psychology and sociology. A multidisciplinary review is given in this paper, attempting to keep track of the historical development of the field and to shed light on its future directions. In the review, the authors discuss the disciplinary origins of opinion dynamics, showing that the combination of the social processes, which are conventionally studied in social sciences, and the analytical and computational tools, which are developed in mathematics, physics and complex system studies, gives birth to the interdisciplinary field of opinion dynamics. The current state of the art of opinion dynamics is then overviewed, with the research progresses on the typical models like the voter model, the Sznajd model, the culture dissemination model, and the bounded confidence model being highlighted. Correspondingly, the future directions of this academic field are envisioned, with an advocation for closer synthesis of the related disciplines.

Replicating the Role of the Human Retina for a Cortical Visual Neuroprosthesis

2013 ◽  
pp. 1532-1551
Author(s):  
Samuel Romero ◽  
Christian Morillas ◽  
Antonio Martínez ◽  
Begoña del Pino ◽  
Francisco Pelayo ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Significant Degree ◽  
Research Field ◽  
Human Retina ◽  
Direct Stimulation ◽  
Biologically Inspired ◽  
Visual Inputs ◽  
Response Modeling ◽  
Stimulation Of

Neuroengineering is an emerging research field combining the latest findings from neuroscience with developments in a variety of engineering disciplines to create artificial devices, mainly for therapeutical purposes. In this chapter, an application of this field to the development of a visual neuroprosthesis for the blind is described. Electrical stimulation of the visual cortex in blind subjects elicits the perception of visual sensations called phosphenes, a finding that encourages the development of future electronic visual prostheses. However, direct stimulation of the visual cortex would miss a significant degree of image processing that is carried out by the retina. The authors describe a biologically-inspired retina-like processor designed to drive the implanted stimulator using visual inputs from one or two cameras. This includes dynamic response modeling with minimal latency. The outputs of the retina-like processor are comparable to those recorded in biological retinas that are exposed to the same stimuli and allow estimation of the original scene.

What’s your type? An examination of first-year doctoral student motivation

2020 ◽  
Vol 36 (4) ◽  
pp. 371-387
Author(s):  
Africa S. Hands
Keyword(s):  
Doctoral Students ◽  
Student Motivation ◽  
Academic Motivation ◽  
Information Science ◽  
Doctoral Student ◽  
Autonomous Motivation ◽  
Educational Process ◽  
Interdisciplinary Field ◽  
Research Activities ◽  
Motivational Support

Educators often ask how to motivate PhD students. Before addressing how to motivate students, we should know what motivates prospective doctoral students. Motivational support has been shown to lead to overall satisfaction with the educational process, better engagement, and persistence. Using the interdisciplinary field of library and information science, this research offers insight on doctoral student motivation through quantitative analysis of results from administration of the Academic Motivation Scale. The instrument measures and classifies motivation from the perspective of self-determination theory. Results suggest PhD students are motivated by several types of intrinsic motivation as well as identified regulation, a type of extrinsic yet autonomous motivation. Findings can be used by program administrators, faculty, and other stakeholders to address the “how” of motivation through better alignment of teaching practices, research activities, and student services based on students’ motivation types.

Topic extraction to provide an overview of research activities: The case of the high-temperature superconductor and simulation and modelling

2020 ◽  
pp. 016555152092079
Author(s):  
Ritsuko Nakajima ◽  
Nobuyuki Midorikawa
Keyword(s):  
High Temperature ◽  
Large Scale ◽  
High Temperature Superconductors ◽  
Review Literature ◽  
Research Field ◽  
Scientific Field ◽  
Research Trends ◽  
Research Articles ◽  
Research Activities ◽  
Simulation And Modelling

For those who are not experts in a particular scientific field, it is difficult to understand scientific research trends. Although studies on the extraction of research trends have been conducted, most focus on extracting global trends from large-scale data, and the methods are often complicated. The purpose of this study is to develop a method of obtaining overviews of a scientific field for non-experts by capturing research trends simply and then to verify the method. To extract research topics which should express research trends, text analysis was performed using abstracts over 12 years of articles on high-temperature superconductors. We characterised three topics for the extracted word groups that frequently occurred. For these topics, we studied their appropriateness using a method that has been little used: examining research articles, review literature and co-citations among research articles used to extract the words, comparisons with controlled index terms assigned to the articles and confirming that there were no contradictions. Based on the established method, we have also applied this method to another research field: ‘simulation and modelling’. Although the method used in this article is simple, important topics were extracted, and the relations with the original articles are clear, which can lead to further investigation of the extracted topics.

Object Categorization Using Biologically Inspired Nodemaps and the HITEC Categorization System

2009 ◽  
Vol 13 (5) ◽  
pp. 573-580
Author(s):  
Adam Csapo ◽  
◽  
Barna Resko ◽  
Domonkos Tikk ◽  
Peter Baranyi
Keyword(s):  
Visual Information ◽  
Scale Up ◽  
Research Field ◽  
Point Of View ◽  
Success Rates ◽  
Biologically Inspired ◽  
Text Documents ◽  
Independent Test ◽  
Categorization System

The computerized modeling of cognitive visual information has been a research field of great interest in the past several decades. The research field is interesting not only from a biological perspective, but also from an engineering point of view when systems are developed that aim to achieve similar goals as biological cognitive systems. This paper briefly describes a general framework for the extraction and systematic storage of low-level visual features, and demonstrates its applicability in image categorization using a linear categorization algorithm originally developed for the characterization of text documents. The performance of the algorithm together with the newly developed feature array was evaluated using the Caltech 101 database. Extremely high (95% and higher) success rates were achieved when distinguishing between pairs of categories using independent test images. Efforts were made to scale up the number of categories using a hierarchical, branch-and-bound decision tree, with limited success.

Complimentary Address

2017 ◽  
Vol 21 (1) ◽  
pp. 6-6
Author(s):  
Imre Rudas ◽  
Keyword(s):  
Soft Computing ◽  
Computational Intelligence ◽  
Fuzzy Inference ◽  
Leading Edge ◽  
Research Field ◽  
Green Energy ◽  
Power Grids ◽  
Biologically Inspired ◽  
Inference Systems ◽  
Self Driving Cars

  First of all it is my great pleasure to congratulate to the 20th anniversary of the Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII). The first volume of the journal was published in 1997 – and now twenty years later we reached the Vol. 21. Over these years JACIII was one of the forefront and determining journals of soft computing and intelligent informatics and focused to the most up-to-date topic despite the fast vary and evolvement of this research field through its regular and special sessions. One of the greatest merit of the journal is that it is able be serve as a common platform for the most relevant researchers and societies in order to expand the boundaries of many related fields including Fuzzy Logic, Neural Networks, Genetic and Evolutionary Computation, Biologically-Inspired Computation Systems and so on.   In these days the most up-coming challenges are connected to the topics of JACIII including the current special issue as well. Self-driving cars, Wearables, Internet-of-Things and many other phenomena are imaginable with the advanced <em>Computational Intelligence</em> behind the rooftop. Expert- and decision-making systems and effective usage of big data request the highly developed <em>Fuzzy Inference Systems</em>. Monitoring of social media in order to get useful information regarding the habits of human users and artificial robots cannot be realized without <em>Web and Artificial Intelligence</em>. Soft-computing based methods and many other intelligent and automated solutions are needed for eligible <em>Data mining</em> – and for the further preparation of the gathered data. Moreover, the demands of future smart city concepts, developed green energy producing solutions and connected power grids present the scientists with specific challenges whereon <em>Smart Grid</em> concept can be the only answer.   I would like to invite the Reader to an interesting reading which deals with the aforementioned challenges and scenarios.   Furthermore, I hope that JACIII can continue its contribution to the leading-edge research and we can celebrate the 30th anniversary together as well.

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