scholarly journals Applications of Artificial Intelligence in Agriculture: A Review

2019 ◽  
Vol 9 (4) ◽  
pp. 4377-4383 ◽  
Author(s):  
N. C. Eli-Chukwu
Keyword(s):  
Artificial Intelligence ◽  
Weed Management ◽  
High Performance ◽  
Agricultural Sector ◽  
Special Focus ◽  
Main Concept ◽  
Pest Infestation ◽  
Performance Accuracy ◽  
Data Requirements ◽  
Applications Of Ai

The application of Artificial Intelligence (AI) has been evident in the agricultural sector recently. The sector faces numerous challenges in order to maximize its yield including improper soil treatment, disease and pest infestation, big data requirements, low output, and knowledge gap between farmers and technology. The main concept of AI in agriculture is its flexibility, high performance, accuracy, and cost-effectiveness. This paper presents a review of the applications of AI in soil management, crop management, weed management and disease management. A special focus is laid on the strength and limitations of the application and the way in utilizing expert systems for higher productivity.

scholarly journals Quality Inspection of Food and Agricultural Products using Artificial Intelligence

2021 ◽  
Author(s):  
Maimunah Mohd Ali ◽  
Norhashila Hashim ◽  
Samsuzana Abd Aziz ◽  
Ola Lasekan
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Food Quality ◽  
High Performance ◽  
Agricultural Products ◽  
Special Focus ◽  
Quality Inspection ◽  
Big Data Technologies ◽  
Artificial Neural Network Ann ◽  
Non Destructive

A rising awareness for quality inspection of food and agricultural products has generated a growing effort to develop rapid and non-destructive techniques. Quality detection of food and agricultural products has prime importance in various stages of processing due to the laborious processes and the inability of the system to measure the whole of the food production. The detection of food quality has previously depended on various destructive techniques that require sample destruction and a large amount of postharvest losses. Artificial Intelligence (AI) has emerged with big data technologies and high-performance computation to create new opportunities in the multidisciplinary agri-food domain. This review presents the key concepts of AI comprising an expert system, artificial neural network (ANN), and fuzzy logic. A special focus is laid on the strength of AI applications in determining food quality for producing high and optimum yields. It was demonstrated that ANN provides the best result for modelling and effective in real-time monitoring techniques. The future use of AI for assessing quality inspection is promising which could lead to a real-time as well as rapid evaluation of various food and agricultural products.

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.

Application of High Performance Electro-Hydraulic Synchronous Servo System on NC Broaching Machine

2013 ◽  
Vol 721 ◽  
pp. 497-500
Author(s):  
Guo Jin Chen ◽  
Jing Ni ◽  
Ting Ting Liu ◽  
Ming Xu
Keyword(s):  
High Performance ◽  
Control Process ◽  
Servo System ◽  
Numerical Control ◽  
Servo Drive ◽  
Loop Control ◽  
Performance Accuracy ◽  
Drive Control ◽  
Hydraulic Servo ◽  
Output Quantity

Aiming at the lower performance, accuracy and efficiency of the existing motion control process for the traditional broaching machine, the paper studies the high-performance dual-hydraulic synchronous servo drive control technology. The synchronous electro-hydraulic servo system forms the closed loop control by the detection and feedback of the output quantity. It eliminates and restrains largely the influence of the adverse factors to obtain the high-precision synchronous driving performance. The numerical control system based on the real-time error compensation and the intelligent control to the auxiliary machinery is developed. It is used for the CNC broaching machine to make the steady-state synchronous displacement error of the double cylinders be ≤ 0.5mm.

Sports Medicine and Artificial Intelligence: A Primer

2021 ◽  
pp. 036354652110086
Author(s):  
Prem N. Ramkumar ◽  
Bryan C. Luu ◽  
Heather S. Haeberle ◽  
Jaret M. Karnuta ◽  
Benedict U. Nwachukwu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sports Medicine ◽  
Injury Risk ◽  
Industrial Revolution ◽  
Improve Patient Care ◽  
Great Promise ◽  
Patient Reported ◽  
Athlete Injury ◽  
Improve Patient ◽  
Applications Of Ai

Artificial intelligence (AI) represents the fourth industrial revolution and the next frontier in medicine poised to transform the field of orthopaedics and sports medicine, though widespread understanding of the fundamental principles and adoption of applications remain nascent. Recent research efforts into implementation of AI in the field of orthopaedic surgery and sports medicine have demonstrated great promise in predicting athlete injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting the patient experience. Not unlike the recent emphasis thrust upon physicians to understand the business of medicine, the future practice of sports medicine specialists will require a fundamental working knowledge of the strengths, limitations, and applications of AI-based tools. With appreciation, caution, and experience applying AI to sports medicine, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. In this Current Concepts review, we discuss the definitions, strengths, limitations, and applications of AI from the current literature as it relates to orthopaedic sports medicine.

scholarly journals Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Vital Role ◽  
Human Machine Interaction ◽  
The Future ◽  
Level Of Knowledge ◽  
Electronic Questionnaires ◽  
Machine Interaction ◽  
Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

scholarly journals Reliability-Oriented Design of Inverter-Fed Low-Voltage Electrical Machines: Potential Solutions

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4144
Author(s):  
Yatai Ji ◽  
Paolo Giangrande ◽  
Vincenzo Madonna ◽  
Weiduo Zhao ◽  
Michael Galea
Keyword(s):  
Power Density ◽  
High Speed ◽  
High Performance ◽  
Low Voltage ◽  
Electrical Machines ◽  
Design Stage ◽  
Switching Frequency ◽  
Special Focus ◽  
Electrical Machine ◽  
Engineering Approach

Transportation electrification has kept pushing low-voltage inverter-fed electrical machines to reach a higher power density while guaranteeing appropriate reliability levels. Methods commonly adopted to boost power density (i.e., higher current density, faster switching frequency for high speed, and higher DC link voltage) will unavoidably increase the stress to the insulation system which leads to a decrease in reliability. Thus, a trade-off is required between power density and reliability during the machine design. Currently, it is a challenging task to evaluate reliability during the design stage and the over-engineering approach is applied. To solve this problem, physics of failure (POF) is introduced and its feasibility for electrical machine (EM) design is discussed through reviewing past work on insulation investigation. Then the special focus is given to partial discharge (PD) whose occurrence means the end-of-life of low-voltage EMs. The PD-free design methodology based on understanding the physics of PD is presented to substitute the over-engineering approach. Finally, a comprehensive reliability-oriented design (ROD) approach adopting POF and PD-free design strategy is given as a potential solution for reliable and high-performance inverter-fed low-voltage EM design.

scholarly journals Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study

2020 ◽  
Author(s):  
Yuchen Luo ◽  
Yi Zhang ◽  
Ming Liu ◽  
Yihong Lai ◽  
Panpan Liu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
High Performance ◽  
Detection System ◽  
Random Order ◽  
Colon Polyps ◽  
Clinical Environment ◽  
Polyp Detection ◽  
Link Type ◽  
Polyp Detection Rate

Abstract Background and aims Improving the rate of polyp detection is an important measure to prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through deep learning methods, can learn and perform specific endoscopic tasks previously performed by endoscopists. The purpose of this study was to explore whether a high-performance, real-time automatic polyp detection system could improve the polyp detection rate (PDR) in the actual clinical environment. Methods The selected patients underwent same-day, back-to-back colonoscopies in a random order, with either traditional colonoscopy or artificial intelligence (AI)-assisted colonoscopy performed first by different experienced endoscopists (> 3000 colonoscopies). The primary outcome was the PDR. It was registered with clinicaltrials.gov. (NCT047126265). Results In this study, we randomized 150 patients. The AI system significantly increased the PDR (34.0% vs 38.7%, p < 0.001). In addition, AI-assisted colonoscopy increased the detection of polyps smaller than 6 mm (69 vs 91, p < 0.001), but no difference was found with regard to larger lesions. Conclusions A real-time automatic polyp detection system can increase the PDR, primarily for diminutive polyps. However, a larger sample size is still needed in the follow-up study to further verify this conclusion. Trial Registration clinicaltrials.gov Identifier: NCT047126265

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence

2020 ◽  
Vol 24 (01) ◽  
pp. 38-49 ◽  
Author(s):  
Natalia Gorelik ◽  
Jaron Chong ◽  
Dana J. Lin
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Bone Tumors ◽  
Image Interpretation ◽  
Bone Age ◽  
Musculoskeletal Imaging ◽  
Radiology Workflow ◽  
Disease Response ◽  
Osseous Metastases ◽  
Applications Of Ai

AbstractArtificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect and characterize abnormalities as well as monitor disease response. Many AI-based image interpretation tasks for musculoskeletal (MSK) pathologies have been studied, including the diagnosis of bone tumors, detection of osseous metastases, assessment of bone age, identification of fractures, and detection and grading of osteoarthritis. This article explores the applications of AI for image interpretation of MSK pathologies.

Why are companies still struggling to reach higher continuous improvement maturity levels? Empirical evidence from high performance companies

2015 ◽  
Vol 27 (3) ◽  
pp. 316-327 ◽  
Author(s):  
Daniel Jurburg ◽  
Elisabeth Viles ◽  
Carmen Jaca ◽  
Martin Tanco
Keyword(s):  
Continuous Improvement ◽  
Measurement System ◽  
High Performance ◽  
Basque Country ◽  
Holistic Approach ◽  
Special Focus ◽  
Structured Interviews ◽  
Northern Spain ◽  
Content Type ◽  
High Performing

Purpose – Continuous improvement (CI) is regarded as a powerful approach to achieve business excellence. However, the implementation is not simple as it involves managing a considerable amount of tangible and intangible factors throughout the whole organization. The purpose of this paper is to fill the gap by presenting first-hand information about how companies really implement and organize their CI processes. Design/methodology/approach – The study was based on semi-structured interviews in ten high performing companies in the Basque Country, a region in northern Spain well known for its business quality. The objective was to analyze the state of their CI processes, putting special focus on how the organizational structure integrates with the CI processes and what are the characteristics of the corresponding measurement system. Findings – The study shows a lack of company-wide focus on CI, little written evidence of previous improvement activities, unclear improvement process owner, and poor use of adequate measurement systems to monitor CI. Practical implications – Managers should understand that is not enough to guarantee their own commitment and provide the structure, since in order to become learning organization, a different holistic approach towards the CI process must be adopted. Originality/value – While most previous work on this field have focused primarily on how to implement different techniques in order to achieve better productive performance, this study presents empirical research from a more holistic approach, assessing the characteristics affecting CI by considering strategy, structure, and the measurement system.

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