scholarly journals Research on artificial intelligence safety prediction and intervention model based on ship driving habits

2022 ◽  
Vol 355 ◽  
pp. 03032
Author(s):  
Runnan Liu ◽  
Guangze Liu ◽  
Pengfei He ◽  
Xingzhi Lin
Keyword(s):  
Artificial Intelligence ◽  
Small World ◽  
Electrical Equipment ◽  
Intervention Model ◽  
Safe Driving ◽  
Safe Navigation ◽  
Intelligent Analysis ◽  
Development Direction ◽  
Processing Platform ◽  
Ship Safety

Based on the analysis of the causes of ship accidents, the development prospect and development direction of ship intelligent safe driving, the artificial intelligence safety prediction and intervention model is put forward. This model solves the problem of ship intelligent safety prediction by using intelligent analysis technology and network technology, and promotes the development of ship intelligence and ship safety navigation technology. Additionally, it expands the channels of obtaining information, connects the ship's mechanical and electrical equipment, collects, stores and analyzes the data reasonably, and constructs the intelligent analysis and processing platform of ship small-world data processing to implement intelligent intervention. What is impressive is that it makes ship navigation safer, more economical, more reasonable and optimized, and accelerates the development of ship artificial intelligence safe navigation.

Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence

2021 ◽  
pp. 1-11
Author(s):  
Lei Wu ◽  
Juan Wang ◽  
Long Jin ◽  
P. Hemalatha ◽  
R Premalatha
Keyword(s):  
Artificial Intelligence ◽  
Vital Role ◽  
Performance Ratio ◽  
Psychological Experience ◽  
The Public ◽  
Usable Knowledge ◽  
Intelligent Analysis ◽  
Accuracy Ratio ◽  
Depression Level ◽  
Predictive Research

Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.

Intelligent Analysis Method of Artistic Environment Construction Style Based on Artificial Intelligence Technology

2021 ◽  
Vol 7 (5) ◽  
pp. 4101-4110
Author(s):  
Song Nan ◽  
Zhang Xiaodong ◽  
Peng Changrong
Keyword(s):  
Artificial Intelligence ◽  
Spatial Structure ◽  
Environmental Design ◽  
Environmental Art ◽  
Analysis Method ◽  
Environmental Space ◽  
Intelligent Analysis ◽  
Artificial Intelligence Technology ◽  
Art Design

Environmental art mainly uses the collocation of color and spatial structure for landscape layout. Different environmental styles have different artistic characteristics. In order to better design the environmental space, this paper puts forward the intelligent analysis method of artistic environmental construction style based on artificial intelligence technology. By analyzing the environment into characteristics and the environmental style into process, the direction of environmental art design is innovated while the environmental design is carried out reasonably.

The Ship Domain – A Criterion of Navigational Safety Assessment in an Open Sea Area

2008 ◽  
Vol 62 (1) ◽  
pp. 93-108 ◽  
Author(s):  
Zbigniew Pietrzykowski ◽  
Janusz Uriasz
Keyword(s):  
Artificial Intelligence ◽  
Safety Assessment ◽  
Research Results ◽  
Safe Navigation ◽  
Number Of Factors ◽  
Open Sea ◽  
Sea Area ◽  
Point Of Departure ◽  
Shape And Size

One of the basic tasks in shipping is to ensure safe navigation of vessels. The concept of the ship domain is of major importance in the assessment of a navigational situation and the avoidance of ship collisions. It is difficult to determine a ship domain as its shape and size depend on a number of factors. One question to be answered before the determination of the ship domain is which method to use: statistical, analytic, or expert method using artificial intelligence tools; other questions are connected with domain interpretation. The authors have analyzed the ship domain as a criterion for the assessment of ship navigational safety in an encounter situation in the open sea. The research results are used to answer some of the questions.Part 2 includes definitions of the ship domain and ship fuzzy domain. Part 3, in turn, presents methods of their determination as well as relevant questions. The results of the authors' research, described in Part 4, make up a basis for the determination of the domain and ship fuzzy domain. These have been determined with the so-called dynamic domains as a point of departure. The criteria of ship domain and closest point of approach are compared and discussed. Encounters of various size ships are considered in Part 5. The research and its results are described. Both ship domains and ship fuzzy domains of encountering ships are analyzed. Then, conclusions have been formulated in relation to the effect of the sizes of encountering ships on the shapes and sizes of their domains. Final conclusions are given in Part 6.

scholarly journals Research on load balancing technology for microservice architecture

2021 ◽  
Vol 336 ◽  
pp. 08002
Author(s):  
Hao Wang ◽  
Yong Wang ◽  
Guanying Liang ◽  
Yunfan Gao ◽  
Weijian Gao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Load Balancing ◽  
High Availability ◽  
Software Architectures ◽  
Delayed Response ◽  
Urgent Problem ◽  
Service Load ◽  
Development Direction ◽  
Service Capability ◽  
Microservice Architecture

With the emergence and development of new software architectures such as microservices, how to effectively handle the service load and ensure the service capability of the system has become an urgent problem to be solved. Load balancing technology needs to achieve high availability of microservices without affecting the delayed response of requests. According to different principles of adoption, mainstream load balancing technologies have emerged, such as polling methods, hash algorithms, and artificial intelligence technologies. This article categorizes and summarizes load balancing technologies for microservice architecture, and elaborates the methods and characteristics of current mainstream load balancing technologies. Based on the comparative analysis of existing technologies, this paper summarizes and points out the future development direction of load balancing technology.

scholarly journals Machine Learning and Artificial Intelligence in Online Fake Transaction Alerting

2015 ◽  
Vol 3 (2) ◽  
pp. 115-126 ◽  
Author(s):  
Naresh Babu Bynagari
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Fraud Detection ◽  
Learning Ability ◽  
The Core ◽  
The Past ◽  
Music Selection ◽  
Intelligent Analysis ◽  
Set Up ◽  
Detection Mechanisms

Artificial Intelligence (AI) is one of the most promising and intriguing innovations of modernity. Its potential is virtually unlimited, from smart music selection in personal gadgets to intelligent analysis of big data and real-time fraud detection and aversion. At the core of the AI philosophy lies an assumption that once a computer system is provided with enough data, it can learn based on that input. The more data is provided, the more sophisticated its learning ability becomes. This feature has acquired the name "machine learning" (ML). The opportunities explored with ML are plentiful today, and one of them is an ability to set up an evolving security system learning from the past cyber-fraud experiences and developing more rigorous fraud detection mechanisms. Read on to learn more about ML, the types and magnitude of fraud evidenced in modern banking, e-commerce, and healthcare, and how ML has become an innovative, timely, and efficient fraud prevention technology.

scholarly journals Physician Confidence in Artificial Intelligence: An Online Mobile Survey (Preprint)

2018 ◽  
Author(s):  
Songhee Oh ◽  
Jae Heon Kim ◽  
Sung-Woo Choi ◽  
Hee Jeong Lee ◽  
Jungrak Hong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Online Survey ◽  
Medical Application ◽  
Disease Diagnosis ◽  
Medical Field ◽  
High Quality ◽  
Inadequate Information ◽  
Development Direction ◽  
The Future ◽  
Mobile Survey

BACKGROUND It is expected that artificial intelligence (AI) will be used extensively in the medical field in the future. OBJECTIVE The purpose of this study is to investigate the awareness of AI among Korean doctors and to assess physicians’ attitudes toward the medical application of AI. METHODS We conducted an online survey composed of 11 closed-ended questions using Google Forms. The survey consisted of questions regarding the recognition of and attitudes toward AI, the development direction of AI in medicine, and the possible risks of using AI in the medical field. RESULTS A total of 669 participants completed the survey. Only 40 (5.9%) answered that they had good familiarity with AI. However, most participants considered AI useful in the medical field (558/669, 83.4% agreement). The advantage of using AI was seen as the ability to analyze vast amounts of high-quality, clinically relevant data in real time. Respondents agreed that the area of medicine in which AI would be most useful is disease diagnosis (558/669, 83.4% agreement). One possible problem cited by the participants was that AI would not be able to assist in unexpected situations owing to inadequate information (196/669, 29.3%). Less than half of the participants(294/669, 43.9%) agreed that AI is diagnostically superior to human doctors. Only 237 (35.4%) answered that they agreed that AI could replace them in their jobs. CONCLUSIONS This study suggests that Korean doctors and medical students have favorable attitudes toward AI in the medical field. The majority of physicians surveyed believed that AI will not replace their roles in the future.

scholarly journals New human-computer interaction regulations for ship safe driving based on multi-mode data interconnection

2022 ◽  
Vol 355 ◽  
pp. 03033
Author(s):  
Yi Yang ◽  
Lixing Chen ◽  
Pengfei He ◽  
Xingzhi Lin
Keyword(s):  
Human Computer Interaction ◽  
Small World ◽  
Driving Behavior ◽  
Interaction Data ◽  
Safe Driving ◽  
Driving System ◽  
Driving Mode ◽  
Multi Mode ◽  
Electrical Data ◽  
Computer Interaction

Based on the analysis of the multi-mode data of ship mechatronics and the new human-computer interaction regulations for safety driving, a new safety driving regulation based on multi-mode data is put forward. The new regulations for ship safe driving use mechanical and electrical data to form small-world data interconnection. Artificial intelligence and human-computer interaction operation information are used to integrate and communicate, and human-computer interaction data are incorporated to standardize driving behavior to integrate historical driving data, and finally, the standardized automatic self-driving is formed. The new human-computer interaction regulations formed by the safe driving system make it possible to solve and optimize the ship safe driving mode.

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