scholarly journals Drown Alerting, Preventing And Autonomous Rescue System using Ardiuno, Tacticle switche (weight sensors) and Artificial Intelligence

2021 ◽  
Vol 10 (2) ◽  
pp. 762-766
Keyword(s):  
Artificial Intelligence ◽  
Swimming Pool ◽  
Human Intervention ◽  
Present Design ◽  
Rescue System ◽  
Novel Method ◽  
Processor Board

This paper introduces a novel method of automatic lifesaving swimming pool design to save a drowning victim in a helpless condition by using latest ardiuno(IoT) processor board and the framework. This method utilizes artificial intelligence to save drowning victims without the need of a life-guard(human intervention) from fatal death and also associated specific alerting mechanisms like a loudspeaker. In the present paper, a swimming pool framework is proposed with a responsive elevator assebly surface which is covering entire pool bottom, housing several weight sensitive waterproofed tactical switches arranged to sense any individual or any object incidence(falling) on bottom of the pool ,and associated alerting devices like loud speakers, and a drain motor control.The automatic rescue designs have not been tried succesfull so far in literature effectively so far. The present design delt with simplest algorithm and latest mechanical supporting strucures, and fast responding ardiuno processor. The finished prototype has given promising results in solving defined problem.

scholarly journals Robust Drown Alerting, Preventing and Autonomous Rescue System

2021 ◽  
Vol 21 (1) ◽  
pp. 22-25
Author(s):  
Pillalamarri Laxman ◽  
Anuj Jain
Keyword(s):  
Artificial Intelligence ◽  
Life Saving ◽  
Rescue System ◽  
Novel Method

Abstract This paper introduces a novel method of automatic life-saving mechanism to save a drowning victim in a helpless condition. The realization of this method may be done by an Arduino Board or an embedded microcontroller. This method utilizes artificial intelligence to save drowning victims from fatal death and rings a loudspeaker.

scholarly journals A novel method for dried chili pepper classification using artificial intelligence

2021 ◽  
Vol 3 ◽  
pp. 100099
Author(s):  
O. Cruz-Domínguez ◽  
J.L. Carrera-Escobedo ◽  
C.H. Guzmán-Valdivia ◽  
A. Ortiz-Rivera ◽  
M. García-Ruiz ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Chili Pepper ◽  
Novel Method

The intervention of artificial intelligence in the recruitment function in UAE’s hospitality industry

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Bharti Pandya ◽  
Maryam Mohammed Al Janahi
Keyword(s):  
Artificial Intelligence ◽  
Thematic Analysis ◽  
Hospitality Industry ◽  
Descriptive Analysis ◽  
Recruitment Strategies ◽  
Human Intervention ◽  
Job Descriptions ◽  
Job Advertisements ◽  
Routine Tasks ◽  
Hospitality Sector

Artificial Intelligence (AI) is not a new concept for Hospitality Industry and Recruitment functions. AI has displaced the human intervention in routine tasks. In few years, AI will take over several jobs (Kubler, 2018). Recently AI technologies support application screening, data analysis, and preliminary interviews, saving time of recruiters. Chatbots are now designated recruitment officers supporting candidates. Researchers have studied the influence of AI on Recruitment, but only a few focused on the AI displacing human in the recruitment function performed in UAE’s hospitality industry. This research aims to understand the transformation in the recruitment function of UAE’s hospitality industry due to AI intervention. Using concurrent mixed-methods, data was collected by interviewing 10 UAE HR leaders and surveying 135 HR professionals. The inductive-deductive thematic analysis was conducted for subjective measures and descriptive analysis was performed for scaled measures. This study found that UAE’s hospitality sector deployed AI technologies in recruitment areas such as job advertisements, collecting applications, maintaining profiles, and storing the applications. The routine, repetitive, and heavy-volume tasks in the recruitment are delegated to AI while strategic roles are retained for human professionals including development of strategies, and creation of job descriptions and specifications. While the literature review suggested a wider application of AI in recruitment function, UAE’s hospitality sector seems to be lagging. The recommendations will benefit industry leaders, HR professionals, recruitment consultants, and AI developers to rethink on the recruitment strategies, operations, and administration and to embrace the intervention of AI in recruiting the best talent proficiently.

scholarly journals 195 The Application of Radiomics in Laryngeal Cancer: The Forgotten Cohort

2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
A Rajgor ◽  
A McQueen ◽  
T Ali ◽  
E Aboagye ◽  
B Obara ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Head And Neck ◽  
Laryngeal Cancer ◽  
Prognostic Value ◽  
Head And Neck Cancers ◽  
High Dimensional ◽  
Naked Eye ◽  
Online Databases ◽  
Novel Method

Abstract Background Radiomics is a novel method of extracting data from medical images that is difficult to visualise through the naked eye. This technique transforms digital images that hold information on pathology into high-dimensional-data for analysis. Radiomics has the potential to enhance laryngeal cancer care and to date, has shown promise in various other specialties. Aim The aim of this review is to summarise the applications of this technique to laryngeal cancer and potential future benefits. Method A comprehensive systematic review-informed search of the MEDLINE and EMBASE online databases was undertaken. Keywords ‘laryngeal cancer’ OR ‘larynx’ OR ‘larynx cancer’ OR ‘head and neck cancer’ were combined with ‘radiomic’ OR ‘signature’ OR ‘machine learning’ OR ‘artificial intelligence’. Additional articles were obtained from bibliographies using the ‘snowball method’. Results Seventeen articles were identified that evaluated the role of radiomics in laryngeal cancer. Two studies affirmed the value of radiomics in improving the accuracy of staging, whilst fifteen studies highlighted the potential prognostic value of radiomics in laryngeal cancer. Twelve (of thirteen) studies incorporated an array of different head and neck cancers in the analysis and only one study assessed laryngeal cancer exclusively. Conclusions Literature to date has various limitations including, small and heterogeneous cohorts incorporating patients with head and neck cancers of distinct anatomical subsites and stages. The lack of uniform data on solely laryngeal cancer and radiomics means drawing conclusions is difficult, although these studies have affirmed its value. Further large prospective studies exclusively in laryngeal cancer are required to unlock its true potential.

scholarly journals Artificial Intelligence and Intellectual Property Law

2018 ◽  
Vol 7 (1) ◽  
pp. 83-98
Author(s):  
Swapnil Tripathi ◽  
Chandni Ghatak
Keyword(s):  
Artificial Intelligence ◽  
Intellectual Property ◽  
Property Rights ◽  
Intellectual Property Rights ◽  
Criminal Liability ◽  
Property Law ◽  
Human Intervention ◽  
Intellectual Property Law ◽  
Insight Into ◽  
Artificial Intelligence Systems

Artificial intelligence systems have been gaining widespread momentum in today’s progressing tech-savvy world. With sophisticated technologies being incorporated in the same, it is only a matter of time these systems start to produce marvelous inventions without human intervention of any kind. This brings forth pertinent questions concerning Intellectual Property Rights, (IPR) for, it challenges not only traditional notions of concepts such as patents and copyrights, but also leads to the emergence of questions related to the regulation of such creations amidst others. This paper seeks to provide insight into the expanding scope of IPR laws and artificial intelligence, along with the inevitable challenges it brings from a worldwide lens on the matter. It also attempts to provide suggestions transcending IPR, and seeks to address questions concerning criminal liability for the content created by such technologies.

scholarly journals Artificial intelligence in artistic practices

2021 ◽  
pp. 41-50
Author(s):  
Asmati Chibalashvili
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Visual Arts ◽  
Human Condition ◽  
Human Intervention ◽  
Basic Principles ◽  
Generative Art ◽  
Works Of Art ◽  
Artificial Intelligence Technology ◽  
Emotionally Intelligent

The article considers methods of involving artificial intelligence in artistic practices. Based on the analysis of ways to use this technology in visual arts and music, the basic principles of working with artificial intelligence technology are identified, including: imitation of historical art, implemented in projects The Next Rembrandt and Choral; generative art, which is found in the works “Hyperbolic Composition І” and “Hyperbolic Composition ІІ” of S. Eaton and also in the AIVA program (Artificial Intelligence Virtual Artist). The importance of the mechanisms of neurobiology in the process of working with artificial intelligence on the example of the project “Neural Zoo” of S. Crespo, Iamus program, in which the development of musical material is based on the principle of evolution, is stated. In the application Endel and in the opera “Emotionally intelligent” Artificially Intelligent Brainwave Opera» of E. Perlman, a neural network is used to read information about the human condition and its further processing for modification into a sound landscape or image. The development of artificial intelligence and its use in artistic practices opens up new opportunities, expanding both the field of authors of artistic content and attracting new audience. This phenomenon provokes many issues, including: the ability to think artificially of artificial intelligence, the ability to create works of art without human intervention, as well as issues related to copyright.

scholarly journals AIoT Application for Food Recommendation based on Emotion Analysis

2021 ◽  
pp. 44-53
Author(s):  
Shivangi Ruhela ◽  
Pragati Chaudhary ◽  
Rishija Shrivas ◽  
Deepti Chopra
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Data Exchange ◽  
The Internet ◽  
Human Intervention ◽  
User Interactions ◽  
Emotion Analysis ◽  
Efficiency Performance ◽  
Analyze Data

Artificial Intelligence(AI) and Internet of Things(IoT) are popular domains in Computer Science. AIoT converges AI and IoT, thereby applying AI into IoT. When ‘things’ are programmed and connected to the Internet, IoT comes into place. But when these IoT systems, can analyze data and have decision-making potential without human intervention, AIoT is achieved. AI powers IoT through Decision-Making and Machine Learning, IoT powers AI through data exchange and connectivity. With the AI’s brain and IoT’s body, the systems can have shot-up efficiency, performance and learning from user interactions. Some studies show that, by 2022, AIoT devices such as drones to save rainforests or fully automated cars, would be ruling the computer industries. The paper discusses AIoT at a greater depth, focuses on few case studies of AIoT for better understanding on practical levels, and lastly, proposes an idea for a model which suggests food through emotion analysis.

Cloud Load Balancing and Reinforcement Learning

2018 ◽  
pp. 266-291
Author(s):  
Abdelghafour Harraz ◽  
Mostapha Zbakh
Keyword(s):  
Artificial Intelligence ◽  
Reinforcement Learning ◽  
Load Balancing ◽  
Decision Process ◽  
Cloud System ◽  
Human Intervention ◽  
Q Learning ◽  
State Action ◽  
Learning Techniques ◽  
Markov Decision

Artificial Intelligence allows to create engines that are able to explore, learn environments and therefore create policies that permit to control them in real time with no human intervention. It can be applied, through its Reinforcement Learning techniques component, using frameworks such as temporal differences, State-Action-Reward-State-Action (SARSA), Q Learning to name a few, to systems that are be perceived as a Markov Decision Process, this opens door in front of applying Reinforcement Learning to Cloud Load Balancing to be able to dispatch load dynamically to a given Cloud System. The authors will describe different techniques that can used to implement a Reinforcement Learning based engine in a cloud system.

scholarly journals Solving Mathematical Puzzles: A Challenging Competition for AI

AI Magazine ◽  
2017 ◽  
Vol 38 (3) ◽  
pp. 83-96 ◽  
Author(s):  
Federico Chesani ◽  
Paola Mello ◽  
Michela Milano
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Scientific Community ◽  
Deep Understanding ◽  
Human Intervention ◽  
Foreseeable Future ◽  
Comprehensive Knowledge ◽  
Problem Solving Process ◽  
Significant Attention

Recently, a number of noteworthy results have been achieved in various fields of artificial intelligence, and many aspects of the problem solving process have received significant attention by the scientific community. In this context, the extraction of comprehensive knowledge suitable for problem solving and reasoning, from textual and pictorial problem descriptions, has been less investigated, but recognized as essential for autonomous thinking in Artificial Intelligence. In this work we present a challenge where methods and tools for deep understanding are strongly needed for enabling problem solving: we propose to solve mathematical puzzles by means of computers, starting from text and diagrams describing them, without any human intervention. We are aware that the proposed challenge is hard and of difficult solution nowadays (and in the foreseeable future), but even studying and solving only single parts of the proposed challenge would represent an important step forward for artificial intelligence.

scholarly journals Niépce–Bell or Turing: how to test odour reproduction

2016 ◽  
Vol 13 (125) ◽  
pp. 20160587 ◽  
Author(s):  
David Harel
Keyword(s):  
Artificial Intelligence ◽  
Artificial Intelligence System ◽  
Intelligence System ◽  
Alan Turing ◽  
Novel Method

Decades before the existence of anything resembling an artificial intelligence system, Alan Turing raised the question of how to test whether machines can think, or, in modern terminology, whether a computer claimed to exhibit intelligence indeed does so. This paper raises the analogous issue for olfaction: how to test the validity of a system claimed to reproduce arbitrary odours artificially, in a way recognizable to humans. Although odour reproduction systems are still far from being viable, the question of how to test candidates thereof is claimed to be interesting and non-trivial, and a novel method is proposed. Despite the similarity between the two questions and their surfacing long before the tested systems exist, the present question cannot be answered adequately by a Turing-like method. Instead, our test is very different: it is conditional, requiring from the artificial no more than is required from the original, and it employs a novel method of immersion that takes advantage of the availability of easily recognizable reproduction methods for sight and sound, a la Nicéphore Niépce and Alexander Graham Bell.

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