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International Journal of Ambient Computing and Intelligence
Journal Prestige (SJR): 0.161

Citation Impact (citeScore): 2
Number of Followers: 3

Full-text available via subscription

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ISSN (Print) 1941-6237 - ISSN (Online) 1941-6245
Published by IGI Global

[146 journals]

Intelligent Ship Collision Avoidance Support System Based on the Algorithm
of Anthropomorphic Physics
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  Authors: Feng; Guoxu, Gu, Songbo, Sun, Shihu
  Pages: 1 - 20
  Abstract: Most of the collision-related decisions of ships at sea depend on the working experience of drivers and determining a reasonable avoidance decision quickly when facing a multivessel encounter situation is difficult, so applying intelligent algorithms to assist these decisions is necessary. On the basis of this, the authors researched the construction of intelligent decision support systems for ship collision avoidance that relies on an anthropomorphic physics optimization algorithm. They used this algorithm to obtain the global range optimal solutions through iteration, which provides effective decisions for ship collision avoidance. The experiments were designed to simulate and analyze the ship collision avoidance decision model. The results showed that the decision-making system based on the anthropomorphic physics optimization algorithm can provide an effective collision avoidance decision scheme.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-20
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.365340
  Issue No: Vol. 15, No. 1 (2024)
Evaluation of Logistics Development Under the Visual Field of Low-Carbon
Environmental Protection Based on Hierarchical Methods
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  Authors: Wang; Jinjuan
  Pages: 1 - 16
  Abstract: The development of the modern logistics industry in China is relatively backward, and the logistics industry has always shown characteristics of high emissions, high energy consumption, and high pollution. The low-carbon transformation and development of the logistics industry has become a prominent issue. At present, research on low-carbon logistics mainly focuses on its definition and characteristics. The research on its influencing factors is mostly qualitative analysis, and there is relatively little research on performance evaluation. This article establishes a performance evaluation index system from the perspective of low-carbon environmental protection, including information technology level, warehousing, transportation, packaging, etc., and constructs a comprehensive evaluation model that combines an analytic hierarchy process with data envelopment analysis for low-carbon logistics performance evaluation. By reviewing the collected data and taking five logistics enterprises in China as examples, the feasibility of low-carbon logistics performance evaluation indicators and models was verified.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-16
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.360709
  Issue No: Vol. 15, No. 1 (2024)
RETRACTED: Design and Implementation of Folk Arts and Crafts Resource
Library System Based on Ontology Description and Random Matrix
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  Authors: Lei; Ping
  Pages: 1 - 16
  Abstract: This article first constructs an ontology, designs the ontology of the resource library, and then uses the ontology to generate formatted SMD. It uses semantic elements to standardize the description of system resources, organizes folk arts and crafts resources in a machine understandable manner, and presents semantic features to users in an intuitive manner. And use random matrix theory to extract the correlation between data from massive amounts of data. The experimental results show that the running time of the system algorithm reaches 1.8 seconds, effectively avoiding the algorithm's extended state estimation falling into local optima and greatly reducing the computational complexity of the algorithm. This study is conducive to promoting the role of resource library systems and improving retrieval efficiency.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-16
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.356277
  Issue No: Vol. 15, No. 1 (2024)
Threat Attribution and Reasoning for Industrial Control System Asset
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  Authors: Zhang; Shuqin, Shi, Peiyu, Du, Tianhui, Su, Xinyu, Han, Yunfei
  Pages: 1 - 27
  Abstract: Due to the widespread use of the industrial internet of things, the industrial control system has steadily transformed into an intelligent and informational one. To increase the industrial control system's security, based on industrial control system assets, this paper provides a method of threat modeling, attributing, and reasoning. First, this method characterizes the asset threat of an industrial control system by constructing an asset security ontology based on the asset structure. Second, this approach makes use of machine learning to identify assets and attribute the attacker's attack path. Subsequently, inference rules are devised to replicate the attacker's attack path, thereby reducing the response time of security personnel to threats and strengthening the semantic relationship between asset security within industrial control systems. Finally, the process is used in the simulation environment and real case scenario based on the power grid, where the assets and attacks are mapped. The actual attack path is deduced, and it demonstrates the approach's effectiveness.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-27
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.333853
  Issue No: Vol. 15, No. 1 (2024)
Analysis of Home Furnishing Marketing Based on Internet of Things in the
Intelligent Environment
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  Authors: Wang; Fang
  Pages: 1 - 16
  Abstract: How to improve marketing efficiency and how to formulate scientific, effective and practical marketing strategies according to changes in the market environment are important issues facing current smart home companies. This paper adopts the analysis methods such as PEST macro model analysis method, Porter's five forces model, SWOT analysis model and STP analysis, taking Suzhou as the research object, conducts an in-depth analysis of the development environment of smart home, and clarifies the suitable smart home market. From the aspects of 6P marketing mix (product, price, channel, promotion, public relations and political rights), it proposes a Suzhou smart home marketing mix strategy based on mid-to-high-end smart home products. The research results of this paper will promote the development of the city's smart home market and have important reference value for other cities to carry out smart home marketing and can also be used as a reference for relevant government departments to formulate policies.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-16
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.348964
  Issue No: Vol. 15, No. 1 (2024)
Construction of University Football Basic Teaching and Training System
Based on Object Detection and Tracking Algorithm
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  Authors: Yang; Di
  Pages: 1 - 17
  Abstract: Football, often referred to as soccer outside the UK and Europe, is a highly popular activity on many university campuses. As a result, football training programs are offered across many institutions, training students at a range of skill levels. Therefore, this paper investigates a deep learning (DL)-based algorithm for recognizing and tracking targets in sports training videos. The study specifically addresses those videos tailored to identifying small targets, by generating new multi-scale features and modifying anchor point generation rules. Experimental results demonstrate the algorithm's strong performance in tracking football targets. Compared to Histogram of Oriented Gradients, the DL-based model achieved a 29.58% increase in accuracy and a 39.68% decrease in error rates when recognizing football player movement features. This algorithm accurately locates the edge contours of a football player's movements, meaning that universities can, and should, actively reform football teaching and training to enhance teaching effectiveness by utilizing this powerful algorithm.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-17
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.356276
  Issue No: Vol. 15, No. 1 (2024)
Application of Traditional Elements in Film and Television Animation
Driven by Artificial Intelligence
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  Authors: Du; Min, Shao, Bozhang, Liu, Caixia
  Pages: 1 - 17
  Abstract: Traditional culture is gradually being forgotten in the process of modernization, leading to insufficient application of traditional elements in movies and animations, which in turn affects their artistic value and market performance. To avoid the dilemma of high and low development, Chinese film and animation production needs to find a healthier and more benign development path. Explored in this article is the application of traditional elements in AI driven film and television animations. To achieve this goal, in-depth research on element matching problems using a tensor canonical polyadic decomposition (CPD) model, sampling algorithm based on composite star structure, and maximum filtering method was conducted. Through these algorithms and models, a way to effectively utilize traditional elements in AI driven movies and TV animations can be found. This article provides new ideas and directions for the development of China's film and animation industry and offers new possibilities for the application of AI technology in the cultural realm.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-17
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.356381
  Issue No: Vol. 15, No. 1 (2024)
Teaching Model of Swimming Skills Training Under the Background of
Artificial Intelligence
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  Authors: Guo; Yujie
  Pages: 1 - 18
  Abstract: Global swimming competitiveness, driven by enhanced training science, necessitates innovative strategies. High-level swimmers worldwide follow common principles, underscoring AI's potential in training enhancement. Software engineering education actively seeks to align talent development with industry needs, particularly via AI-driven creation of immersive training environments for students. Despite UWB's prominence among wireless positioning technologies and ongoing Chinese research, its application in sports arenas is yet limited. This paper presents a graphical representation of AI in swimming training, proposing a 20% accuracy boost and data visualization, enriching discussions on AI-assisted learning platforms in software engineering and athletics.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-18
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.356382
  Issue No: Vol. 15, No. 1 (2024)
A Multimodal Sentiment Analysis Model for Graphic Texts Based on Deep
Feature Interaction Networks
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  Authors: Chang; Wanjun, Zhang, Dongfang
  Pages: 1 - 19
  Abstract: Due to the widespread adoption of social networks, image-text comments have become a prevalent mode of emotional expression compared to traditional text descriptions. However, there are currently two major challenges. The first is the question of how to extract rich representations effectively from both text and images, and the second is the question of how to extract cross-modal shared emotion features. This study proposes a multimodal sentiment analysis method based on a deep feature interaction network (DFINet). It leverages word-to-word graphs and deep attention interaction networks (DAIN) to learn text representations effectively from multiple subspaces. Additionally, it introduces a cross-modal attention interaction network to extract cross-modal shared emotion features efficiently. This approach helps alleviate the difficulties associated with acquiring image-text features and representing cross-modal shared emotion features. Experimental results on the Yelp dataset demonstrate the effectiveness of the DFINet method.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-19
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.355192
  Issue No: Vol. 15, No. 1 (2024)
Management of New Automatic Ticket Vending Machine System in Urban Rail
Transit
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  Authors: Li; Yanshuo, Zhu, Hao, Tian, Weigang, Xiao, Chengshun
  Pages: 1 - 15
  Abstract: The technology of automatic fare collection system for urban rail transit is an important technology for achieving automatic fare collection for public transportation facilities such as urban subways. This article studies the relevant characteristics of the AFC system. Through introducing queuing models, simulation comparative experiments, and neural network debugging, it is found that the automatic fare collection system for urban rail transit not only effectively helps station staff to allocate tickets in a timely and reasonable manner, adjust station ticket supply, but also facilitates station passengers to query tickets, and passengers can freely choose whether to take the train according to their actual needs. The experiment shows that the AFC system can effectively help passengers avoid traffic congestion during peak hours, greatly improve management level, and reduce labor intensity.
  Keywords: Artificial Intelligence; Computer Science & IT; Artificial Intelligence
  Citation: International Journal of Ambient Computing and Intelligence (IJACI), Volume: 15, Issue: 1 (2024) Pages: 1-15
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.344796
  Issue No: Vol. 15, No. 1 (2024)

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