scholarly journals Bubbles, Foam Formation, Stability and Consumer Perception of Carbonated Drinks: A Review of Current, New and Emerging Technologies for Rapid Assessment and Control

Foods ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 596 ◽  
Author(s):  
Claudia Gonzalez Viejo ◽  
Damir D. Torrico ◽  
Frank R. Dunshea ◽  
Sigfredo Fuentes
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Emerging Technologies ◽  
Descriptive Analysis ◽  
Bubble Formation ◽  
Rapid Assessment ◽  
Chemical Components ◽  
Sparkling Wine ◽  
Foam Formation ◽  
Carbonated Beverages

Quality control, mainly focused on the assessment of bubble and foam-related parameters, is critical in carbonated beverages, due to their relationship with the chemical components as well as their influence on sensory characteristics such as aroma release, mouthfeel, and perception of tastes and aromas. Consumer assessment and acceptability of carbonated beverages are mainly based on carbonation, foam, and bubbles, as a flat carbonated beverage is usually perceived as low quality. This review focuses on three beverages: beer, sparkling water, and sparkling wine. It explains the characteristics of foam and bubble formation, and the traditional methods, as well as emerging technologies based on robotics and computer vision, to assess bubble and foam-related parameters. Furthermore, it explores the most common methods and the use of advanced techniques using an artificial intelligence approach to assess sensory descriptors both for descriptive analysis and consumers’ acceptability. Emerging technologies, based on the combination of robotics, computer vision, and machine learning as an approach to artificial intelligence, have been developed and applied for the assessment of beer and, to a lesser extent, sparkling wine. This, has the objective of assessing the final products quality using more reliable, accurate, affordable, and less time-consuming methods. However, despite carbonated water being an important product, due to its increasing consumption, more research needs to focus on exploring more efficient, repeatable, and accurate methods to assess carbonation and bubble size, distribution and dynamics.

МЕТОДЫ ДОСТИЖЕНИЯ МАКСИМАЛЬНОЙ ЭФФЕКТИВНОСТИ ПЛАТФОРМЫ ПРОТОТИПИРОВАНИЯ ВЫСОКОПРОИЗВОДИТЕЛЬНЫХ СИСТЕМ НА КРИСТАЛЛЕ НА ЗАДАЧАХ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА

2020 ◽  
Vol 96 (3s) ◽  
pp. 585-588
Author(s):  
С.Е. Фролова ◽  
Е.С. Янакова
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Computer Vision ◽  
High Performance ◽  
Systems On Chip ◽  
High Performance Systems ◽  
On Chip ◽  
Network Technologies ◽  
Neural Network Technologies

Предлагаются методы построения платформ прототипирования высокопроизводительных систем на кристалле для задач искусственного интеллекта. Изложены требования к платформам подобного класса и принципы изменения проекта СнК для имплементации в прототип. Рассматриваются методы отладки проектов на платформе прототипирования. Приведены результаты работ алгоритмов компьютерного зрения с использованием нейросетевых технологий на FPGA-прототипе семантических ядер ELcore. Methods have been proposed for building prototyping platforms for high-performance systems-on-chip for artificial intelligence tasks. The requirements for platforms of this class and the principles for changing the design of the SoC for implementation in the prototype have been described as well as methods of debugging projects on the prototyping platform. The results of the work of computer vision algorithms using neural network technologies on the FPGA prototype of the ELcore semantic cores have been presented.

scholarly journals Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

2020 ◽  
Vol 6 ◽  
pp. 205520762096835
Author(s):  
C Blease ◽  
C Locher ◽  
M Leon-Carlyle ◽  
M Doraiswamy
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Medical Profession ◽  
Descriptive Analysis ◽  
Psychiatric Practice ◽  
Limited Attention ◽  
Written Responses ◽  
Future Technology ◽  
Qualitative Descriptive ◽  
The Impact

Background The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics. Objective This study aimed to explore psychiatrists’ opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice Methods In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descriptive analysis of written responses (“comments”) to three open-ended questions in the survey. Results Comments were classified into four major categories in relation to the impact of future technology on: (1) patient-psychiatrist interactions; (2) the quality of patient medical care; (3) the profession of psychiatry; and (4) health systems. Overwhelmingly, psychiatrists were skeptical that technology could replace human empathy. Many predicted that ‘man and machine’ would increasingly collaborate in undertaking clinical decisions, with mixed opinions about the benefits and harms of such an arrangement. Participants were optimistic that technology might improve efficiencies and access to care, and reduce costs. Ethical and regulatory considerations received limited attention. Conclusions This study presents timely information on psychiatrists’ views about the scope of artificial intelligence and machine learning on psychiatric practice. Psychiatrists expressed divergent views about the value and impact of future technology with worrying omissions about practice guidelines, and ethical and regulatory issues.

scholarly journals Deep learning-enabled medical computer vision

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Andre Esteva ◽  
Katherine Chou ◽  
Serena Yeung ◽  
Nikhil Naik ◽  
Ali Madani ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Computer Vision ◽  
Deep Learning ◽  
Medical Imaging ◽  
Real World ◽  
Recent Progress ◽  
Medical Applications ◽  
Modern Computer ◽  
Medical Computer

AbstractA decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered by deep learning—for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit—including cardiology, pathology, dermatology, ophthalmology–and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies.

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 Merging Artificial Intelligence and Blockchain Technologies to Solve Academic Qualification Forgery Issues

2020 ◽  
Author(s):  
Manju Jose
Keyword(s):  
Artificial Intelligence ◽  
Industrial Revolution ◽  
Emerging Technologies ◽  
Integrated System ◽  
Future Research ◽  
Group Discussions ◽  
Academic Qualification ◽  
Negative Impacts ◽  
Economy And Education ◽  
Academic Qualifications

This paper emphasizes the possibility of merging artificial intelligence and Blockchain technologies to solve academic qualifications forgery issues in the educational sectors. Empirical data is collected through interviews with specialists and technical people who are interested in the emerging technologies of the Fourth Industrial Revolution and focus group discussions in the field, as well as from reports in the reviewed literary articles. Scientific journals have also been accessed to analyse the paper goals and objectives. The findings suggest that emerging technologies can be integrated to become more efficient and effective in detecting fraud and forgery before it occurs. Considerable attention should be given to reducing and combating these issues because they have significant negative impacts on the economy and education. Accordingly, the study makes recommendations based on the results and areas of future research, considering the establishment of a unified and integrated system. Initially it will be applied as a pilot in Sultanate of Oman, then gradually it will be extended to the Gulf Cooperation Council States (GCC) and internationally particularly the affiliated and the recognized educational institutions to avoid the phenomena that affects the reputation and quality of education institutions and academic qualifications. The conclusion considers the impacts of the proposed system in the education and economy as well in general.

scholarly journals From Data Journalism to Artificial Intelligence: Challenges Faced by La Nación in Implementing Computer Vision in News Reporting

2021 ◽  
Vol 24 (3) ◽  
pp. 1-40
Author(s):  
Mathias-Felipe de-Lima-Santos ◽  
Ramón Salaverría
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Latin American ◽  
Implementation Process ◽  
Media Industry ◽  
Technological Infrastructure ◽  
News Reporting ◽  
Technological Advances ◽  
High Resolution Imagery ◽  
Data Journalism

Journalism is at a radical point of change that requires organizations to come up with new ideas and formats for news reporting. Additionally, the notable surge of data, sensors and technological advances in the mobile segment has brought immeasurable benefits to many fields of journalistic practice (data journalism in particular). Given the relative novelty and complexity of implementing artificial intelligence (AI) in journalism, few areas have managed to deploy tailored AI solutions in the media industry. In this study, through a mixed-method approach that combines both participant observations and interviews, we explain the hurdles and obstacles to deploying computer vision news projects, a subset of AI, in a leading Latin American news organization, the Argentine newspaper La Nación. Our results highlight four broad difficulties in implementing computer vision projects that involve satellite imagery: a lack of high-resolution imagery, the unavailability of technological infrastructure, the absence of qualified personnel to develop such codes, and a lengthy and costly implementation process that requires significant investment. This article concludes with a discussion of the centrality of AI solutions in the hands of big tech corporations.

scholarly journals Sensory evaluation of mono-varietal juices from columnar apple fruits

2021 ◽  
pp. 48-55
Author(s):  
E. S. Salina
Keyword(s):  
Apple Juice ◽  
Sugar Content ◽  
Descriptive Analysis ◽  
Rapid Assessment ◽  
Sensory Level ◽  
Juice Quality ◽  
Sensory Panel ◽  
Yellow Colour ◽  
Biochemical Indices ◽  
Apple Fruits

Tis study presents the sensory and biochemical traits of mono-varietal juices from columnar apple fruits grown in the Orel Region. Fruit juices from the cultivars Valuta, Zvezda Efira, Orlovskaya Eseniya and Priokskoye have been assessed against the Antonovka Obyknovennaya juice as control. We used the emerging sensory scales and dictionaries to develop a sensory panel for the apple juice evaluation and analysed its main biochemical criteria. Te top descriptors in a five-point rating were used to develop the colour, flavour and aroma scales for a quick juice quality evaluation, with suitable descriptors for each sensory level. Analyses of sensory data showed more expert discrimination of flavour than aroma. Te cultivars were divided into three groups in terms of juice quality: transparent without opalescence (Zvezda Efira, Valuta), almost opaque with marked opalescence (Orlovskaya Eseniya, Antonovka Obyknovennaya) and medium-transparent juice with slight opalescence (Priokskoye). Zvezda Efira and Antonovka Obyknovennaya were more sour and tart, while the Valuta and Priokskoye varieties were the sweetest. Orlovskaya Eseniya had a balanced sweet-sour and least tart juice. A correlation has been determined between the point and descriptor scorings of apple juices, as well as between the flavour and biochemical indices. Te sensory panel developed identified the best sensory qualities of apple juice as high transparency, absent opalescence, intense straw-yellow colour, sour-sweet rich flavour and distinct apple aroma. Te most flavour-affecting biochemical indices were the sugar content (°Brix), sugar-acid ratio and P-active catechin amount. Te point and descriptive scorings produce fully accordant results. A descriptive analysis is industry-preferred for allowing a rapid assessment of various product characteristics and their adjustment upon need.

scholarly journals New risks related to emerging technologies and reputation for corporate governance

2020 ◽  
Vol 9 (2) ◽  
pp. 64-74
Author(s):  
Hugh Grove ◽  
Mac Clouse ◽  
Tracy Xu
Keyword(s):  
Artificial Intelligence ◽  
Corporate Governance ◽  
Boards Of Directors ◽  
Emerging Technologies ◽  
Research Question ◽  
World Intellectual Property Organization ◽  
Global Marketplace ◽  
Challenges And Opportunities ◽  
Potential Risks ◽  
Management Issues

Artificial intelligence (AI) has moved from theory into the global marketplace. The United Nations World Intellectual Property Organization released the first report of its Technology Trends series on January 31, 2019. It considered more than 340,000 AI-related patent applications over the last 70 years. 50 percent of all AI patents have been published in just the last five years. The challenges, potential risks, and opportunities for business and corporate governance from emerging technologies, especially artificial intelligence, have been summarized as whereby machines and software can analyze, optimize, prophesize, customize, digitize and automate just about any job in every industry. Boards of directors and executives need to recognize and understand the new risks associated with these emerging technologies and related reputational risks. The major research question of this paper is how boards of directors and executives can deal with both risk challenges and opportunities to strengthen corporate governance. Accordingly, the following sections of this paper discuss key risk management issues: deep shift risks, global risks, digital risks and opportunities, AI initiatives risks, business risks from millennials, business reputational risks, and conclusions.

scholarly journals APPLICATIONS OF COMPUTER VISION IN AGRICULTURE

2021 ◽  
Vol 5 (9) ◽  
Author(s):  
Pranav Ghadge ◽  
Riddhik Tilawat ◽  
Prasanna Sand ◽  
Parul Jadhav
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Computer Vision ◽  
Educational Technology ◽  
Satellite System ◽  
High Quality ◽  
Agricultural Applications ◽  
Efficient Processing

Satellite system advances, remote sensing and drone technology are continuing. These progresses produce high-quality images that need efficient processing for smart agricultural applications. These possibilities to merge computer vision and artificial intelligence in agriculture are exploited with recent deep educational technology. This involves essential phenomena of data and huge quantities of data stored, analysed and used when making decisions. This paper demonstrates how computer vision in agriculture can be used.

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