scholarly journals Artificial intelligence, a possible solution for agriculture and animal husbandry sector?

2021 ◽  
Vol 78 (2) ◽  
pp. 1
Author(s):  
Ancuţa ROTARU ◽  
Anamaria VÂTCĂ ◽  
Ioana POP ◽  
Luisa ANDRONIE
Keyword(s):  
Artificial Intelligence ◽  
Perception And Action ◽  
New Technologies ◽  
Animal Husbandry ◽  
Data Sets ◽  
Aggregated Data ◽  
Livestock Sector ◽  
Share Data ◽  
Closed Systems ◽  
The Voice

This paper aims at making a review of the artificial intelligence concept, its global scope from the agro-livestock sector perspective and the understanding, approach and application of this concept Romania in early 2021. Artificial intelligence is a computer science sub-field that is materialized by algorithms developed starting from the logical or mathematical models of the cognition, perception and action processes. Globally, large agricultural companies are trying to grasp concepts such as big data, artificial intelligence (AI), machine learning and analysis. These areas have moved rapidly towards the agro-livestock sector too, but most companies have not been prepared to deal thoroughly with these new technologies. It really sounds interesting, but what does it take to take the next steps? The voice of the expert says: “If we really want to have a global impact on food sustainability, production and safety, we need to think about data standards, data sharing, benchmarking and analysis on aggregated data sets. Today, we see farmers who are reluctant to share data with agritech companies that have developed closed systems, which will hinder the evolution of things” (Claudia Roessler, IT specialist, Microsoft).

scholarly journals Worth of Artificial Intelligence in the Epoch of Modern Livestock Farming: A Review

2021 ◽  
Author(s):  
Bhavna Aharwal ◽  
Biswajit Roy ◽  
Somesh Meshram ◽  
Aayush Yadav
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Body Condition Score ◽  
Compliance Rate ◽  
Animal Husbandry ◽  
Dairy Farms ◽  
Individual Performance ◽  
Animal Origin ◽  
Livestock Farming ◽  
Measuring Device

Artificial intelligence (AI) is a human intelligence in machine encountered daily and impacts our lives. It is expected that the use of such technology in the livestock industry will automate the livestock processes and easy to manage. Biometric identification plays a key role in artificial intelligence which shows the individual identity, helps in the process of insurance and claim leakages, continue monitoring of farm animal is essential can be done with new technologies. Infra red temperature measurement camera is the newly added technology with sensor system in (AI). It is a temperature measuring device in the form of electromagnetic waves and the infrared radiation intensity. AI system consists of agent, sensor, actuators and effectors which are connected to cloud. It helps in the detection of estrus, animal diseases, body condition score and various physiological parameters using video surveillance data collection method. Artificial neural network is a branch of artificial intelligence (AI) which is based on a collection of connected units or nodes called artificial neurons and stored in a central database system. Sustainable economic future of dairy farms and to achieve 100% compliance rate. Modern dairy farms uses robotic system to deliver vaccines, machine milking and measurement of feed as per individual performance of the animal. AI analyzes the animal origin food quality traceability method from farm to fork. AI helps in the complete mechanized animal husbandry right from the birth of animal to production and food product. The future of AI in animal sector is not predictable, but advantages and daily increasing demand of AI over other sector will ensure future in animal sector as well.

scholarly journals Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Nagasundaram Nagarajan ◽  
Edward K. Y. Yapp ◽  
Nguyen Quoc Khanh Le ◽  
Balu Kamaraj ◽  
Abeer Mohammed Al-Subaie ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Drug Discovery ◽  
Computational Biology ◽  
New Drugs ◽  
Pharmaceutical Companies ◽  
Data Sets ◽  
Aggregated Data ◽  
Usable Knowledge ◽  
Knowledge Of Cancer ◽  
Generation Sequencing

Artificial intelligence (AI) proves to have enormous potential in many areas of healthcare including research and chemical discoveries. Using large amounts of aggregated data, the AI can discover and learn further transforming these data into “usable” knowledge. Being well aware of this, the world’s leading pharmaceutical companies have already begun to use artificial intelligence to improve their research regarding new drugs. The goal is to exploit modern computational biology and machine learning systems to predict the molecular behaviour and the likelihood of getting a useful drug, thus saving time and money on unnecessary tests. Clinical studies, electronic medical records, high-resolution medical images, and genomic profiles can be used as resources to aid drug development. Pharmaceutical and medical researchers have extensive data sets that can be analyzed by strong AI systems. This review focused on how computational biology and artificial intelligence technologies can be implemented by integrating the knowledge of cancer drugs, drug resistance, next-generation sequencing, genetic variants, and structural biology in the cancer precision drug discovery.

scholarly journals Sign Translation Via Natural Language Processing

2021 ◽  
pp. 1-7
Author(s):  
Shadman A. Khan ◽  
Zulfikar Ali Ansari ◽  
Riya Singh ◽  
Mohit Singh Rawat ◽  
Fiza Zafar Khan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
Sign Language ◽  
Language Processing ◽  
New Technologies ◽  
End User ◽  
User Input ◽  
Sign Recognition ◽  
Voice User ◽  
The Voice

Artificial Intelligence (AI) technologies are new technologies with new complicated features emerging quickly. Technology adoption has been beneficial for many general models. The models help in train the voice user-interface assistance (Alexa, Cortona, Siri). Voice assistants are easy to use, and thus millions of devices incorporate them in households nowadays. The primary purpose of the sign language translator prototype is to reduce interaction barriers between deaf and mute. To overcome this problem, we have proposed a prototype. It is named sign language translator with Sign Recognition Intelligence which takes the user input in sign language and processes it, and returns the output in voice out load to the end-user.

Humor, Ethics, and Dignity: Being Human in the Age of Artificial Intelligence

2019 ◽  
Vol 33 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Sean Kanuck
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Ethical Reasoning ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
Data Sets ◽  
Human Beings ◽  
Human In The Loop ◽  
Software Algorithms ◽  
Decision Making Processes

AbstractThe growing adoption of artificial intelligence (AI) raises questions about what comparative advantage, if any, human beings will have over machines in the future. This essay explores what it means to be human and how those unique characteristics relate to the digital age. Humor and ethics both rely upon higher-level cognition that accounts for unstructured and unrelated data. That capability is also vital to decision-making processes—such as jurisprudence and voting systems. Since machine learning algorithms lack the ability to understand context or nuance, reliance on them could lead to undesired results for society. By way of example, two case studies are used to illustrate the legal and moral considerations regarding the software algorithms used by driverless cars and lethal autonomous weapons systems. Social values must be encoded or introduced into training data sets if AI applications are to be expected to produce results similar to a “human in the loop.” There is a choice to be made, then, about whether we impose limitations on these new technologies in favor of maintaining human control, or whether we seek to replicate ethical reasoning and lateral thinking in the systems we create. The answer will have profound effects not only on how we interact with AI but also on how we interact with one another and perceive ourselves.

scholarly journals Interpreting, analyzing and distributing information: A big data framework for competitive intelligence

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Eduardo Luis Casarotto ◽  
Guilherme Cunha Malafaia ◽  
Marta Pagán Martínez ◽  
Erlaine Binotto
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Technological Innovation ◽  
New Technologies ◽  
Decision Makers ◽  
Strategic Decision ◽  
Competitive Intelligence ◽  
Technological Innovations ◽  
Data Sets ◽  
Data Framework

This paper aimed to develop a data-based technological innovation frameworkfocused on the competitive intelligence process. Technological innovations increasinglytransform the behavior of societies, affecting all sectors. Solutions such as cloud computing, theInternet of Things, and artificial intelligence provide and benefit from a vast generation of data:large data sets called Big Data. The use of new technologies in all sectors increases in the faceof such innovation and technological mechanisms of management. We advocated that the use ofBig Data and the competitive intelligence process could help generate or maintain a competitiveadvantage for organizations. We based the proposition of our framework on the concepts of BigData and competitive intelligence. Our proposal is a theoretical framework for use in thecollection, treatment, and distribution of information directed to strategic decision-makers. Itssystematized architecture allows the integration of processes that generate information fordecision making.

scholarly journals LIVESTOCK IN KAZAKHSTAN: DEVELOPMENT PROBLEMS

2022 ◽  
Vol 16 (4) ◽  
pp. 122-129
Author(s):  
Sanat Seitov
Keyword(s):  
New Technologies ◽  
Live Weight ◽  
Animal Husbandry ◽  
International Standards ◽  
Weak Base ◽  
Aggregated Data ◽  
Fodder Production ◽  
Physical Volume ◽  
Data Production ◽  
The Republic

The research was carried out in order to highlight the main problems that impede the increase in the competitiveness of Kazakhstani animal husbandry. The indicators of productivity (milk yield, shearing of wool from one sheep, etc.), as well as aggregated data (production volumes, indices of the physical volume of gross production) were used as criteria for assessing the development of the industry. In Kazakhstan, the share of beef pedigree cattle in 2019 accounted for only 11.5% of the total cattle population. The average live weight of cattle was 336 kg, the average slaughter weight was 175 kg, which is 2 times lower than world standards, the average live weight of 1 bird was 2.2 kg. The republic has a weak base for the production of basic feed for the fattening contingent, due to which its supply with such feed is at the level of 57.8% of the scientifically grounded norm. The share of breeding stock of dairy cattle (as of January 1, 2018) is 2.8%, birds of all types - 12.3% of the total livestock, sheep - 14.8%. In modern conditions, in order to increase competitiveness, it is necessary to focus efforts on solving such problems as providing highly productive breeding cattle and poultry; improving the fodder base by expanding the crops of corn, soybeans, alfalfa, chickpea; strengthening of preventive work against especially dangerous animal diseases; adaptation of scientific developments in the field of genetics, selection and fodder production to the current economic conditions in animal husbandry; accelerating the transfer of animal husbandry to new technologies; implementation of international standards for product quality and management

Artificial Intelligence as a Technological Innovation to Accelerate Economic Development

2019 ◽  
Vol 12 (3) ◽  
pp. 125-133
Author(s):  
S. V. Shchurina ◽  
A. S. Danilov
Keyword(s):  
Artificial Intelligence ◽  
Economic Development ◽  
Technological Innovation ◽  
Manufacturing Industry ◽  
New Technologies ◽  
Retail Trade ◽  
High Tech ◽  
Industrial Complex ◽  
Technological Gap ◽  
The Government

The subject of the research is the introduction of artificial intelligence as a technological innovation into the Russian economic development. The relevance of the problem is due to the fact that the Russian market of artificial intelligence is still in the infancy and the necessity to bridge the current technological gap between Russia and the leading economies of the world is coming to the forefront. The financial sector, the manufacturing industry and the retail trade are the drivers of the artificial intelligence development. However, company managers in Russia are not prepared for the practical application of expensive artificial intelligence technologies. Under these circumstances, the challenge is to develop measures to support high-tech projects of small and medium-sized businesses, given that the technological innovation considered can accelerate the development of the Russian economy in the energy sector fully or partially controlled by the government as well as in the military-industrial complex and the judicial system.The purposes of the research were to examine the current state of technological innovations in the field of artificial intelligence in the leading countries and Russia and develop proposals for improving the AI application in the Russian practices.The paper concludes that the artificial intelligence is a breakthrough technology with a great application potential. Active promotion of the artificial intelligence in companies significantly increases their efficiency, competitiveness, develops industry markets, stimulates introduction of new technologies, improves product quality and scales up manufacturing. In general, the artificial intelligence gives a new impetus to the development of Russia and facilitates its entry into the five largest world’s economies.

The Future of Human Workers

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Mental Capacity ◽  
Machine Intelligence ◽  
The Internet ◽  
Traditional Model ◽  
Global Workforce ◽  
Repetitive Tasks ◽  
The Internet Of Things

New technologies like artificial intelligence, robotics, machine intelligence, and the Internet of Things are seeing repetitive tasks move away from humans to machines. Humans cannot become machines, but machines can become more human-like. The traditional model of educating workers for the workforce is fast becoming irrelevant. There is a massive need for the retooling of human workers. Humans need to be trained to remain focused in a society which is constantly getting bombarded with information. The two basic elements of physical and mental capacity are slowly being taken over by machines and artificial intelligence. This changes the fundamental role of the global workforce.

AI Narratives

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Ancient Greece ◽  
Historical Overview ◽  
Intelligent Machines ◽  
Narrative History ◽  
History Of ◽  
Imaginative Thinking ◽  
The Relationship ◽  
Insight Into

This book is the first to examine the history of imaginative thinking about intelligent machines. As real artificial intelligence (AI) begins to touch on all aspects of our lives, this long narrative history shapes how the technology is developed, deployed, and regulated. It is therefore a crucial social and ethical issue. Part I of this book provides a historical overview from ancient Greece to the start of modernity. These chapters explore the revealing prehistory of key concerns of contemporary AI discourse, from the nature of mind and creativity to issues of power and rights, from the tension between fascination and ambivalence to investigations into artificial voices and technophobia. Part II focuses on the twentieth and twenty-first centuries in which a greater density of narratives emerged alongside rapid developments in AI technology. These chapters reveal not only how AI narratives have consistently been entangled with the emergence of real robotics and AI, but also how they offer a rich source of insight into how we might live with these revolutionary machines. Through their close textual engagements, these chapters explore the relationship between imaginative narratives and contemporary debates about AI’s social, ethical, and philosophical consequences, including questions of dehumanization, automation, anthropomorphization, cybernetics, cyberpunk, immortality, slavery, and governance. The contributions, from leading humanities and social science scholars, show that narratives about AI offer a crucial epistemic site for exploring contemporary debates about these powerful new technologies.

Imbalanced Data Detection Kernel Method in Closed Systems

2013 ◽  
Vol 756-759 ◽  
pp. 3652-3658
Author(s):  
You Li Lu ◽  
Jun Luo
Keyword(s):  
Kernel Methods ◽  
Kernel Method ◽  
Imbalanced Data ◽  
Data Detection ◽  
Data Sets ◽  
System Call ◽  
Data Set ◽  
Imbalanced Data Sets ◽  
Lower Complexity ◽  
Closed Systems

Under the study of Kernel Methods, this paper put forward two improved algorithm which called R-SVM & I-SVDD in order to cope with the imbalanced data sets in closed systems. R-SVM used K-means algorithm clustering space samples while I-SVDD improved the performance of original SVDD by imbalanced sample training. Experiment of two sets of system call data set shows that these two algorithms are more effectively and R-SVM has a lower complexity.

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