scholarly journals Overview of Smart Aquaculture System: Focusing on Applications of Machine Learning and Computer Vision

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2882
Author(s):  
Thi Thu Em Vo ◽  
Hyeyoung Ko ◽  
Jun-Ho Huh ◽  
Yonghoon Kim
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Sustainable Development ◽  
Species Classification ◽  
The Sustainable Development ◽  
Aquaculture System ◽  
Aquaculture Industry ◽  
Intelligent Technology ◽  
Applications Of Machine Learning ◽  
Aquaculture Production

Smart aquaculture is nowadays one of the sustainable development trends for the aquaculture industry in intelligence and automation. Modern intelligent technologies have brought huge benefits to many fields including aquaculture to reduce labor, enhance aquaculture production, and be friendly to the environment. Machine learning is a subdivision of artificial intelligence (AI) by using trained algorithm models to recognize and learn traits from the data it watches. To date, there are several studies about applications of machine learning for smart aquaculture including measuring size, weight, grading, disease detection, and species classification. This review provides and overview of the development of smart aquaculture and intelligent technology. We summarized and collected 100 articles about machine learning in smart aquaculture from nearly 10 years about the methodology, results as well as the recent technology that should be used for development of smart aquaculture. We hope that this review will give readers interested in this field useful information.

Introduction to Machine Learning and Its Application

2020 ◽  
pp. 262-290
Author(s):  
Ladly Patel ◽  
Kumar Abhishek Gaurav
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Learning Algorithm ◽  
Machine Learning Algorithms ◽  
Human Interaction ◽  
Machine Learning Algorithm ◽  
Past Data ◽  
Applications Of Machine Learning ◽  
Learning Frameworks ◽  
Learning Data

In today's world, a huge amount of data is available. So, all the available data are analyzed to get information, and later this data is used to train the machine learning algorithm. Machine learning is a subpart of artificial intelligence where machines are given training with data and the machine predicts the results. Machine learning is being used in healthcare, image processing, marketing, etc. The aim of machine learning is to reduce the work of the programmer by doing complex coding and decreasing human interaction with systems. The machine learns itself from past data and then predict the desired output. This chapter describes machine learning in brief with different machine learning algorithms with examples and about machine learning frameworks such as tensor flow and Keras. The limitations of machine learning and various applications of machine learning are discussed. This chapter also describes how to identify features in machine learning data.

Role of Artificial Intelligence in Modeling Psychometrics to Detect Neurodevelopmental Disorders

2020 ◽  
pp. 213-227
Author(s):  
Navjot Singh ◽  
Amarjot Kaur
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neurodevelopmental Disorders ◽  
Machine Learning Techniques ◽  
Diagnosis And Prognosis ◽  
Processing Power ◽  
Learning Techniques ◽  
Numerous Data ◽  
Applications Of Machine Learning ◽  
Micro Patterns

The objective of the present chapter is to highlight applications of machine learning and artificial intelligence (AI) in clinical diagnosis of neurodevelopmental disorders. The proposed approach aims at recognizing behavioral traits and other cognitive aspects. The availability of numerous data and high processing power, such as graphic processing units (GPUs) or cloud computing, enabled the study of micro-patterns hundreds of times faster compared to manual analysis. AI, being a new technological breakthrough, enables study of human behavior patterns, which are hidden in millions of micro-patterns originating from human actions, reactions, and gestures. The chapter will also focus on the challenges in existing machine learning techniques and the best possible solution addressing those problems. In the future, more AI-based expert systems can enhance the accuracy of the diagnosis and prognosis process.

scholarly journals Investigating a Serious Challenge in the Sustainable Development Process: Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis

2020 ◽  
Vol 12 (6) ◽  
pp. 2427 ◽  
Author(s):  
Behrouz Pirouz ◽  
Sina Shaffiee Haghshenas ◽  
Sami Shaffiee Haghshenas ◽  
Patrizia Piro
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Relative Humidity ◽  
Development Process ◽  
Binary Classification ◽  
Daily Temperature ◽  
Maximum Daily Temperature ◽  
The Sustainable Development ◽  
Epidemic Diseases

Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process was investigated using the classification of confirmed cases of COVID-19 (new version of Coronavirus) as one of the epidemic diseases. Hence, binary classification modeling was used by the group method of data handling (GMDH) type of neural network as one of the artificial intelligence methods. For this purpose, the Hubei province in China was selected as a case study to construct the proposed model, and some important factors, namely maximum, minimum, and average daily temperature, the density of a city, relative humidity, and wind speed, were considered as the input dataset, and the number of confirmed cases was selected as the output dataset for 30 days. The proposed binary classification model provides higher performance capacity in predicting the confirmed cases. In addition, regression analysis has been done and the trend of confirmed cases compared with the fluctuations of daily weather parameters (wind, humidity, and average temperature). The results demonstrated that the relative humidity and maximum daily temperature had the highest impact on the confirmed cases. The relative humidity in the main case study, with an average of 77.9%, affected positively, and maximum daily temperature, with an average of 15.4 °C, affected negatively, the confirmed cases.

Review and Applications of Machine Learning and Artificial Intelligence in Engineering

2020 ◽  
pp. 1-12
Author(s):  
Melda Yucel ◽  
Gebrail Bekdaş ◽  
Sinan Melih Nigdeli
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Artificial Neural Network ◽  
Development Process ◽  
Current Trend ◽  
Engineering Applications ◽  
The Past ◽  
Applications Of Machine Learning ◽  
Basic Features

This chapter presents a summary review of development of Artificial Intelligence (AI). Definitions of AI are given with basic features. The development process of AI and machine learning is presented. The developments of applications from the past to today are mentioned and use of AI in different categories is given. Prediction applications using artificial neural network are given for engineering applications. Usage of AI methods to predict optimum results is the current trend and it will be more important in the future.

scholarly journals Rise of Machine Agency: A Framework for Studying the Psychology of Human–AI Interaction (HAII)

2020 ◽  
Vol 25 (1) ◽  
pp. 74-88 ◽  
Author(s):  
S Shyam Sundar
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Media Effects ◽  
Interactive Media ◽  
Dual Process ◽  
User Perceptions ◽  
Human Control ◽  
Process Framework ◽  
Applications Of Machine Learning ◽  
Media And Communication

Abstract Advances in personalization algorithms and other applications of machine learning have vastly enhanced the ease and convenience of our media and communication experiences, but they have also raised significant concerns about privacy, transparency of technologies and human control over their operations. Going forth, reconciling such tensions between machine agency and human agency will be important in the era of artificial intelligence (AI), as machines get more agentic and media experiences become increasingly determined by algorithms. Theory and research should be geared toward a deeper understanding of the human experience of algorithms in general and the psychology of Human–AI interaction (HAII) in particular. This article proposes some directions by applying the dual-process framework of the Theory of Interactive Media Effects (TIME) for studying the symbolic and enabling effects of the affordances of AI-driven media on user perceptions and experiences.

scholarly journals Features of legal regulation of artificial intelligence as a guarantee of sustainable development of society

2020 ◽  
Vol 208 ◽  
pp. 06010
Author(s):  
N.V. Mishina ◽  
I.R. Shikula ◽  
S.A. Afanasyeva
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
A Priori ◽  
Legal Regulation ◽  
Theoretical Research ◽  
Axiomatic Method ◽  
The Sustainable Development ◽  
Modeling And Forecasting ◽  
Analysis And Synthesis ◽  
Legal Model

The authors of the article consider the features of the legal regulation of artificial intelligence that guarantee the sustainable development of society in the era of global digitalization. The artificial intelligence-induced transformation of the world-building is leading to a change in the legal landscape. In this regard, the authors investigate artificial intelligence as a subject and object of legal regulation. The article provides an overview of foreign and Russian legislation in artificial intelligence, based on which a legal model of a single codified act is proposed. The authors advert to the need for technical and public control when introducing artificial intelligence into operation, and also for a priori legal regulation of artificial intelligence. Based on theoretical research methods, such as the axiomatic method, analysis and synthesis, systematization, modeling and forecasting, the authors conclude that a comprehensive, consistent, systemic and prospective legal regulation can remove the possible risks of introducing AI technologies, the threat of human destruction and provide a guarantee for the sustainable development of society.

scholarly journals Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals

2021 ◽  
Vol 13 (16) ◽  
pp. 9165
Author(s):  
Shin-Cheng Yeh ◽  
Ai-Wei Wu ◽  
Hui-Ching Yu ◽  
Homer C. Wu ◽  
Yi-Ping Kuo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Public Perception ◽  
Sustainable Development Goals ◽  
College Major ◽  
Demographic Variables ◽  
High Tech ◽  
The Sustainable Development ◽  
Quality Water ◽  
Development Goals

Artificial Intelligence (AI) will not just change our lives but bring about revolutionary transformation. AI can augment efficiencies of good and bad things and thus has been considered both an opportunity and risk for the sustainable development of humans. This study designed a survey to collect 1018 samples of educated people with access to the internet in Taiwan regarding their perceptions of AI and its connections to the Sustainable Development Goals (SDGs). The respondents showed high confidence in their AI knowledge. They had a very positive attitude toward AI but at the same time thought AI was risky. In general, people in Taiwan could be “rational optimists” regarding AI. We also examined how people think of the linkages between AI and the SDGs and found that SDG 4, SDG 9, and SDG 3 had the highest “synergy” and lowest rates of “trade-off”. Significant differences for some key questions were also identified concerning the demographic variables such as gender, age, education, and college major. According to the data analysis, education played as the base to construct a sustainable AI-aided town with an embedded innovative circular economy and high-quality water and energy services, making the residents live healthier lives. The findings of this study can be referred to when the perceptions of AI and sustainability issues are of interest for an emerging high-tech economy such as Taiwan and other Asian countries.

scholarly journals Performance of Sustainable Development and Technological Innovation Based on Green Manufacturing Technology of Artificial Intelligence and Block Chain

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiangyu Jiang ◽  
Gu-Hong Lin ◽  
Jui-Chan Huang ◽  
I-Hsiang Hu ◽  
Yen-Chun Chiu
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Manufacturing Industry ◽  
Technology Innovation ◽  
Green Manufacturing ◽  
Green Technology ◽  
Manufacturing Technology ◽  
The Sustainable Development ◽  
Blockchain Technology ◽  
Green Manufacturing Technology

The powerful advanced manufacturing industry is the most powerful driving force for economic development and growth, and it is also the main source of environmental pollution. Artificial intelligence and blockchain technology are recognized as a breakthrough technology that can be widely used, changing the way the entire society and economy operate. The main constraints affecting the sustainable development of the manufacturing industry are ecological deterioration and resource shortage, but the development of artificial intelligence and blockchain technology provides new ideas for solving manufacturing problems. Based on this, this paper proposes a research on the sustainable development performance of green manufacturing technology innovation based on artificial intelligence and blockchain technology. This paper deeply grasps the essence and connotation of artificial intelligence and blockchain technology, analyzes its specific application form and research background, searches for the effective effect of manufacturing technology innovation and green manufacturing performance path, and clarifies the mechanism between the two. All measurement items in the questionnaire used in this article use Likert5 scale and use 1–5 options to indicate the degree of conformity with the actual situation of the enterprise. The results show that the average green manufacturing capacity of each measurement item is between 3.18∼3.97, indicating that the company's green manufacturing capacity is relatively high. Among them, the ability of green technology innovation is relatively high, indicating that most companies have noticed that the improvement of the ability of green technology innovation plays a vital role in the future sustainable development of enterprises. Moreover, more and more companies are paying attention to the latest applications of blockchain technology, which can effectively promote the development of enterprises.

scholarly journals Using artificial intelligence technologies for sustainable development

2021 ◽  
Vol 291 ◽  
pp. 04010
Author(s):  
Anton Nazarov ◽  
Denis Kovtun ◽  
Stefan Talu
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Sustainable Development ◽  
United Nations ◽  
Human Behavior ◽  
International Community ◽  
Point Of View ◽  
High Quality ◽  
The United Nations ◽  
Digital Computers

Artificial intelligence as a simulator of human behavior and thinking emerged as a result of machine learning. Through AI, they recognize and interpret data, on the basis of which programs of various types of activities are subsequently built. The rapid introduction of artificial intelligence-based technologies into the economic and social spheres of the international community has not been left out of the United Nations’ view from the point of view of using the capabilities of digital computers to solve problems at the level of intelligent beings in order to achieve the goals of sustainable development. The article discusses the specific aspects of I, the application of which will make the process of achieving the SDGs more effective and of high-quality.

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