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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]

A Multimodal Sentiment Analysis Model for Graphic Texts Based on Deep
Feature Interaction Networks
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  Abstract: With the widespread adoption of social networks, image-text comments have become a prevalent mode of emotional expression when compared to traditional text descriptions. However, there are currently two major challenges. First is how to effectively extract rich representations from both text and images, and second is how to extract cross-modal shared emotion features. We propose a multimodal sentiment analysis method based on a deep attention interaction network (DFINet). It leverages word-to-word graphs and deep attention interaction networks to effectively learn text representations from multiple subspaces. Additionally, we introduce 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: 0-0
  PubDate: 2024-01-01T05:00:00Z
  DOI: 10.4018/IJACI.355192
  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)
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)
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)

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