scholarly journals KEBOT: An Artificial Intelligence Based Comprehensive Analysis System for FUE Based Hair Transplantation

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 200461-200476
Author(s):  
Koray Erdogan ◽  
Onur Acun ◽  
Ayhan Kucukmanisa ◽  
Ramazan Duvar ◽  
Alp Bayramoglu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Comprehensive Analysis ◽  
Hair Transplantation ◽  
Analysis System

scholarly journals Kantian Moral Agency and the Ethics of Artificial Intelligence

Problemos ◽  
2021 ◽  
Vol 100 ◽  
pp. 139-151
Author(s):  
Riya Manna ◽  
Rajakishore Nath
Keyword(s):  
Artificial Intelligence ◽  
Moral Agency ◽  
Deterministic Model ◽  
Comprehensive Analysis ◽  
Kantian Ethics ◽  
Freedom Of Will ◽  
Machine Morality ◽  
Human Tendency ◽  
Natural Necessity

This paper discusses the philosophical issues pertaining to Kantian moral agency and artificial intelligence (AI). Here, our objective is to offer a comprehensive analysis of Kantian ethics to elucidate the non-feasibility of Kantian machines. Meanwhile, the possibility of Kantian machines seems to contend with the genuine human Kantian agency. We argue that in machine morality, ‘duty’ should be performed with ‘freedom of will’ and ‘happiness’ because Kant narrated the human tendency of evaluating our ‘natural necessity’ through ‘happiness’ as the end. Lastly, we argue that the Kantian ‘freedom of will’ and ‘faculty of choice’ do not belong to any deterministic model of ‘agency’ as these are sacrosanct systems. The conclusion narrates the non-feasibility of Kantian AI agents from the genuine Kantian ethical outset, offering a utility-based Kantian ethical performer instead.

scholarly journals Leveraging Urban Sounds: A Commodity Multi-Microphone Hardware Approach for Sound Recognition

Proceedings ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 55
Author(s):  
Fabrizio Tappero ◽  
Rosa Alsina-Pagès ◽  
Leticia Duboc ◽  
Francesc Alías
Keyword(s):  
Artificial Intelligence ◽  
Hardware Implementation ◽  
Noise Analysis ◽  
Fog Computing ◽  
Sound Recognition ◽  
Sound Processing ◽  
Sound Analysis ◽  
Specific Focus ◽  
Analysis System ◽  
Government Legislation

City noise and sound are measured and processed with the purpose of drawing appropriate government legislation and regulations, ultimately aimed at contributing to a healthier environment for humans. The primary use of urban noise analysis is carried out with the main purpose of reporting or denouncing, to the appropriate authorities, a misconduct or correct a misuse of council resources. We believe that urban sounds carry more information than what it is extracted to date. In this paper we present a cloud-based urban sound analysis system for the capturing, processing and trading of urban sound-based information. By leveraging modern artificial intelligence algorithms running on a FOG computing city infrastructure, we will show how the presented solution can offer a valuable solution for exploiting urban sound information. A specific focus is given to the hardware implementation of the sound sensor and its multimicrophone architecture. We discuss how the presented architecture is designed to allow the trading of sound information between independent parties, transparently, using cloud-based sound processing APIs running on an inexpensive consumer-grade microphone.

scholarly journals Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food

2021 ◽  
Vol 3 ◽  
Author(s):  
Marieke van Erp ◽  
Christian Reynolds ◽  
Diana Maynard ◽  
Alain Starke ◽  
Rebeca Ibáñez Martín ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Domain Knowledge ◽  
State Of The Art ◽  
Interdisciplinary Approach ◽  
Comprehensive Analysis ◽  
The State ◽  
Use Cases

In this paper, we discuss the use of natural language processing and artificial intelligence to analyze nutritional and sustainability aspects of recipes and food. We present the state-of-the-art and some use cases, followed by a discussion of challenges. Our perspective on addressing these is that while they typically have a technical nature, they nevertheless require an interdisciplinary approach combining natural language processing and artificial intelligence with expert domain knowledge to create practical tools and comprehensive analysis for the food domain.

scholarly journals A Landscape Analysis of Standardisation in the Field of Artificial Intelligence

2020 ◽  
Author(s):  
Wolfgang Ziegler
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Main Part ◽  
Comprehensive Analysis ◽  
International Level ◽  
Ongoing Work ◽  
Working Groups ◽  
Funded Project ◽  
European Standards ◽  
Respective State

While projects, developments and applications addressing and using artificial intelligence (AI) are rather multifaceted and their number is constantly increasing, the standardisation activities in the field of artificial intelligence are limited, their number is significantly lower and does not increase at the same pace. The European funded project StandICT.eu aims at supporting European experts’ presence in and contributions to international standardisation activities in ICT. The focus of the project is on the 5 priority domains identified by the European Commission (Cloud Computing, IoT, Big Data, Cyber Security, 5G) and on Artificial Intelligence while being open for other relevant topics defined in the annual European Rolling Plan for ICT Standardisation. The project has two main outcomes: (i) increased contribution of European experts in international standardisation through support by providing grants for planned contributions of successful applications of experts, and (ii) an online observatory of published standards and ongoing standardisation activities in the areas mentioned before. This observatory (called Standards Watch) is accessible through the project’s web site and open for contributions and comments from registered users. As part of the effort for the Standards Watch the projects has prepared a comprehensive analysis of the international standardisation landscape in the AI field, that comprises a description of the ICT standards and ongoing work at international level in the field of AI across the standardisation organisations already active in the field. In this article we will present results of our work where we have analysed the work of the 5 international and European Standards Development Organisations (SDOs) IEEE,1 ISO/IEC,2 ITU-T,3 ETSI4 and CEN-CENELEC5 developing standards in the field of AI. The first 4 bodies have already been active several years in AI standardisation at the time of writing this article. CEN-CENELEC has launched a focus group in 2019 which aims at producing a roadmap for AI standardisation. For these 4 SDOs information on their active groups, details of their work and the respective state/outcome is provided in the main part of this article. Followed by the same exercise for the two identified Standards Settings Organisations (SSOs): W3C6 and IRTF,7 their active groups and the respective state/outcome. With this information an initial analysis of the AI standardisation landscape as Q3 2019 is performed with the main outcomes that (i) the number of working groups chaired by Europeans is significant and (ii) that there is room for European experts contributing to ongoing and future standardisation work. The article is concluded by considerations on future priorities.

scholarly journals Data analysis in Cashless Payment Systems

2021 ◽  
Vol 320 ◽  
pp. 03005
Author(s):  
Alexey Bataev ◽  
Antonina Glushkova
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Information System ◽  
Data Analysis ◽  
Financial Institutions ◽  
Comprehensive Analysis ◽  
Investment Model ◽  
Payment Systems ◽  
Payments System

The use of artificial intelligence in the financial sphere are analyzed in this study. One of the possible areas of using neural network in financial institutions is the system of cashless payments. One of the main problems in introducing innovative projects is to evaluate the efficiency of the implemented information system. In this regard, the construction of an investment model that allows evaluating the implementation and use of artificial intelligence in the cashless payments system of financial institutions is proposed in this article. Based on the constructed model, an analysis is made of the dependence of the effectiveness of the system with artificial intelligence on the size of the client base of a credit organization, while the minimum and maximum possible efficiency parameters of the implemented system are evaluated. Based on a comprehensive analysis, recommendations are given on perspectives of introducing such systems into credit organizations.

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