Bodily Processing: What Progress Has Been Made in Understanding the Embodiment of Computing Systems?

2021 ◽  
Vol 66 (2 supplement) ◽  
pp. 181-190
Author(s):  
Martina Properzi
Keyword(s):  
Artificial Intelligence ◽  
Recent Trend ◽  
State Of The Art ◽  
Point Of View ◽  
Computing Systems ◽  
Disciplinary Field ◽  
Morphological Computation ◽  
Unconventional Computation ◽  
Artificial Intelli ◽  
Made In

" In this article I will address the issue of the embodiment of computing sys-tems from the point of view distinctive of the so-called Unconventional Computation, focusing on the paradigm known as Mor-phological Computation. As a first step, I will contextualize Morphological Computa-tion within the disciplinary field of Embod-ied Artificial Intelligence: broadly con-ceived, Embodied Artificial Intelligence may be characterized as embracing both conventional and unconventional ap-proaches to the artificial emulation of natu-ral intelligence. Morphological Computa-tion stands out from other paradigms of unconventional Embodied Artificial Intelli-gence in that it discloses a new, closer kind of connection between embodiment and computation. I will further my investigation by briefly reviewing the state-of-the-art in Morphological Computation: attention will be given to a very recent trend, whose core concept is that of “organic reconfigu-rability”. In this direction, as a final step, two advanced cases of study of organic or living morphological computers will be pre-sented and discussed. The prospect is to shed some light on our title question: what progress has been made in understanding the embodiment of computing systems? Keywords: Embodied Artificial Intelligence; Morphological Computation; Reservoir Compu-ting Systems; Organic Reconfigurability; 3D Bio-Printed Synthetic Corneas; Xenobots "

The Technique of Raman Spectroscopy: A State-of-the-Art Comparison to Infrared

1971 ◽  
Vol 25 (4) ◽  
pp. 430-439 ◽  
Author(s):  
Howard J. Sloane
Keyword(s):  
Raman Spectroscopy ◽  
State Of The Art ◽  
The State ◽  
Point Of View ◽  
Complementary Information ◽  
Future Outlook ◽  
Sample Handling ◽  
Advantages And Disadvantages ◽  
Sampling Procedures ◽  
Made In

This paper in a tabulated summary format discusses the state-of-the-art of Raman spectroscopy for commercially available instrumentation. A comparison to infrared is made in terms of (I) instrumentation, (II) sample handling, and (III) applications. Although the two techniques yield similar and often complementary information, they are quite different from the point of view of instrumentation and sampling procedures. This leads to various advantages and disadvantages or limitations for each. These are discussed as well as the future outlook.

scholarly journals Artificial Intelligence and Learning Activities: A Match Made in Heaven?

2020 ◽  
pp. 198-206
Author(s):  
Henrik Køhler Simonsen ◽  
José Manuel Emiliano Bidarra de Almeida
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Practical Experience ◽  
Point Of View ◽  
Learning Activities ◽  
Learning Design ◽  
The United Kingdom ◽  
Artificial Intelligence In Education ◽  
Made In ◽  
Applications Of Ai

Artificial Intelligence in Education (AIED) may be described as the next big disruptor in higher education, however, AIED still only remains “evidence of a potential” Balslev (2020). Practical experience with AI in higher education is very limited and potential pedagogical applications of AI has so far not been given much attention. The objective of this paper is to analyse and discuss concrete applications of AI to support different learning activities in higher education using the ABC Learning Design approach Young and Perovic (2016). The purpose of the paper is to contribute to research in the practical use of AI in higher education by presenting the AI Pedagogy Planner and to start the important theoretical discussion of AI applications from a pedagogical point of view. The paper is based on empirical data from nine selected cases of AI use in higher education in Portugal, the United Kingdom and Denmark, respectively. The analysis demonstrated that there is a need for new views on the pedagogical use of AI in higher education. However, the paper goes further and outlines an AI Pedagogy Planner combining six overall learning activities with eight types of AI applications.

scholarly journals State-of-the-Art of Artificial Intelligence

2021 ◽  
Author(s):  
Ramjee Prasad ◽  
Purva Choudhary
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
State Of The Art ◽  
Turing Test ◽  
Rapid Progress ◽  
Current State ◽  
Recent Developments ◽  
Historical Developments ◽  
Insight Into ◽  
Made In

Artificial Intelligence (AI) as a technology has existed for less than a century. In spite of this, it has managed to achieve great strides. The rapid progress made in this field has aroused the curiosity of many technologists around the globe and many companies across various domains are curious to explore its potential. For a field that has achieved so much in such a short duration, it is imperative that people who aim to work in Artificial Intelligence, study its origins, recent developments, and future possibilities of expansion to gain a better insight into the field. This paper encapsulates the notable progress made in Artificial Intelligence starting from its conceptualization to its current state and future possibilities, in various fields. It covers concepts like a Turing machine, Turing test, historical developments in Artificial Intelligence, expert systems, big data, robotics, current developments in Artificial Intelligence across various fields, and future possibilities of exploration.

scholarly journals Change Detection Based on Artificial Intelligence: State-of-the-Art and Challenges

2020 ◽  
Vol 12 (10) ◽  
pp. 1688 ◽  
Author(s):  
Wenzhong Shi ◽  
Min Zhang ◽  
Rui Zhang ◽  
Shanxiong Chen ◽  
Zhao Zhan
Keyword(s):  
Artificial Intelligence ◽  
Change Detection ◽  
State Of The Art ◽  
Implementation Process ◽  
Heterogeneous Data ◽  
Point Of View ◽  
Detection Methods ◽  
Wide Range ◽  
Disaster Assessment ◽  
Open Datasets

Change detection based on remote sensing (RS) data is an important method of detecting changes on the Earth’s surface and has a wide range of applications in urban planning, environmental monitoring, agriculture investigation, disaster assessment, and map revision. In recent years, integrated artificial intelligence (AI) technology has become a research focus in developing new change detection methods. Although some researchers claim that AI-based change detection approaches outperform traditional change detection approaches, it is not immediately obvious how and to what extent AI can improve the performance of change detection. This review focuses on the state-of-the-art methods, applications, and challenges of AI for change detection. Specifically, the implementation process of AI-based change detection is first introduced. Then, the data from different sensors used for change detection, including optical RS data, synthetic aperture radar (SAR) data, street view images, and combined heterogeneous data, are presented, and the available open datasets are also listed. The general frameworks of AI-based change detection methods are reviewed and analyzed systematically, and the unsupervised schemes used in AI-based change detection are further analyzed. Subsequently, the commonly used networks in AI for change detection are described. From a practical point of view, the application domains of AI-based change detection methods are classified based on their applicability. Finally, the major challenges and prospects of AI for change detection are discussed and delineated, including (a) heterogeneous big data processing, (b) unsupervised AI, and (c) the reliability of AI. This review will be beneficial for researchers in understanding this field.

BIO-ENERGY FROM PHOTOSYNTHETIC ALLOYS FOR USE IN BIOGUALS AND BIOPRODUCTS

2019 ◽  
pp. 613-618
Author(s):  
Petar Kazakov ◽  
Atanas Iliev ◽  
Emil Ivanov ◽  
Dobri Rusev
Keyword(s):  
Technical Progress ◽  
Point Of View ◽  
Energy Sustainability ◽  
International Activities ◽  
Made In

Significant technical progress has been made in recent years in the development of algae-based bioenergy, and much of industrial and academic R&D projects have diverged from the biofuels strategy. This report summarizes the conclusions of a recently concluded symposium analyzing the prospects for using micro- and macroalgae as a feedstock for biofuels and bioenergy. It discusses international activities for the development of bio-energy and non-energy algae bioproducts, advances in the use of macroalgae (both non-cultivated and cultivated algae). Applications for various biochemical and thermochemical uses, bio-refining capabilities for various products, as well as an in-depth review of the process from the point of view of economy and energy sustainability are also given.

Biological Production of (S)-acetoin: A State-of-the-Art Review

2019 ◽  
Vol 19 (25) ◽  
pp. 2348-2356 ◽  
Author(s):  
Neng-Zhong Xie ◽  
Jian-Xiu Li ◽  
Ri-Bo Huang
Keyword(s):  
Side Effects ◽  
Chemical Synthesis ◽  
State Of The Art ◽  
Optically Active ◽  
Considerable Progress ◽  
Future Prospects ◽  
Chiral Compound ◽  
Biological Production ◽  
Acetoin Production ◽  
Made In

Acetoin is an important four-carbon compound that has many applications in foods, chemical synthesis, cosmetics, cigarettes, soaps, and detergents. Its stereoisomer (S)-acetoin, a high-value chiral compound, can also be used to synthesize optically active drugs, which could enhance targeting properties and reduce side effects. Recently, considerable progress has been made in the development of biotechnological routes for (S)-acetoin production. In this review, various strategies for biological (S)- acetoin production are summarized, and their constraints and possible solutions are described. Furthermore, future prospects of biological production of (S)-acetoin are discussed.

Innovative Marketing Strategies for Select E-Commerce Companies in India - A Review.

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Amit Kumar Bhanja ◽  
P.C Tripathy
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Business Environment ◽  
Marketing Strategies ◽  
Point Of View ◽  
Digital Marketing ◽  
Customer Base ◽  
Innovative Methods ◽  
Online Shoppers ◽  
Drastic Increase

Innovation is the key to opportunities and growth in today’s competitive and dynamic business environment. It not only nurtures but also provides companies with unique dimensions for constant reinvention of the existing way of performance which enables and facilitates them to reach out to their prospective customers more effectively. It has been estimated by Morgan Stanley that India would have 480 million shoppers buying products online by the year 2026, a drastic increase from 60 million online shoppers in the year 2016. E-commerce companies are aggressively implementing innovative methods of marketing their product offerings using tools like digital marketing, internet of things (IoT)and artificial intelligence to name a few. This paper focuses on outlining the innovative ways of marketing that the E-Commerce sector implements in orders to increase their customer base and aims at determining the future scope of this area. A conceptual comparative study of Amazon and Flipkart helps to determine which marketing strategies are more appealing and beneficial for both the customers and companies point of view.

scholarly journals Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

2021 ◽  
Vol 7 (1) ◽  
pp. 71
Author(s):  
Tan Yigitcanlar ◽  
Juan M. Corchado ◽  
Rashid Mehmood ◽  
Rita Yi Man Li ◽  
Karen Mossberger ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Local Government ◽  
Conceptual Framework ◽  
Research Agenda ◽  
Future Studies ◽  
Expert Team ◽  
Research Questions ◽  
Urban Problems ◽  
Technological Opportunities ◽  
Made In

The urbanization problems we face may be alleviated using innovative digital technology. However, employing these technologies entails the risk of creating new urban problems and/or intensifying the old ones instead of alleviating them. Hence, in a world with immense technological opportunities and at the same time enormous urbanization challenges, it is critical to adopt the principles of responsible urban innovation. These principles assure the delivery of the desired urban outcomes and futures. We contribute to the existing responsible urban innovation discourse by focusing on local government artificial intelligence (AI) systems, providing a literature and practice overview, and a conceptual framework. In this perspective paper, we advocate for the need for balancing the costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems in order to achieve responsible urban innovation. The statements made in this perspective paper are based on a thorough review of the literature, research, developments, trends and applications carefully selected and analyzed by an expert team of investigators. This study provides new insights, develops a conceptual framework and identifies prospective research questions by placing local government AI systems under the microscope through the lens of responsible urban innovation. The presented overview and framework, along with the identified issues and research agenda, offer scholars prospective lines of research and development; where the outcomes of these future studies will help urban policymakers, managers and planners to better understand the crucial role played by local government AI systems in ensuring the achievement of responsible outcomes.

scholarly journals Competing risks joint models using R-INLA

2021 ◽  
Vol 21 (1-2) ◽  
pp. 56-71
Author(s):  
Janet van Niekerk ◽  
Haakon Bakka ◽  
Håvard Rue
Keyword(s):  
Competing Risks ◽  
Count Data ◽  
Joint Model ◽  
Point Of View ◽  
Spatial Structures ◽  
Joint Models ◽  
Hazard Functions ◽  
Longitudinal Count Data ◽  
Non Gaussian ◽  
Made In

The methodological advancements made in the field of joint models are numerous. None the less, the case of competing risks joint models has largely been neglected, especially from a practitioner's point of view. In the relevant works on competing risks joint models, the assumptions of a Gaussian linear longitudinal series and proportional cause-specific hazard functions, amongst others, have remained unchallenged. In this article, we provide a framework based on R-INLA to apply competing risks joint models in a unifying way such that non-Gaussian longitudinal data, spatial structures, times-dependent splines and various latent association structures, to mention a few, are all embraced in our approach. Our motivation stems from the SANAD trial which exhibits non-linear longitudinal trajectories and competing risks for failure of treatment. We also present a discrete competing risks joint model for longitudinal count data as well as a spatial competing risks joint model as specific examples.

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