This paper studies the application of digital emotion modeling in computer-aided design of modern products. First, the fuzzy reasoning method is used to realize the inference of students' expectation of learning e...
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This paper first designs a hardware acceleration algorithm based on high-performance electronic devices to optimize the processing efficiency of computationally intensive tasks. By designing a specific algorithm archi...
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The article aims to study the integration of metaverse technology and geographic information system technology in cultural tourism industry innovation. Analyzed the correlation between meta space technology and touris...
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ISBN:
(纸本)9798400709784
The article aims to study the integration of metaverse technology and geographic information system technology in cultural tourism industry innovation. Analyzed the correlation between meta space technology and tourism geographic information systems. The focus is on data integration and interoperability, spatial data visualization and immersive experience, location awareness and augmented reality. It focuses on the innovative application of metaverse digital technology in personalized customized travel experiences, immersive interactive experiences, and visual presentation of tourist destinations. In addition, innovative applications of metaverse technology in virtual tour guides and real-time positioning services, cross platform interaction technology, virtual social and multiplayer collaborative experiences, 3D modeling and virtual map technology, visual display, and exploration of tourism system development were explored. Analyzed the challenges of data privacy and security, technical standards and interoperability, as well as user experience and demand balance in the field, revealing the future development trends and application prospects of the integration of meta space technology and tourism geographic information systems.
Air pollution poses significant challenges to public health and ecological equilibrium globally, with particulate matter (PM) 2.5 emerging as a major concern due to its adverse health effects. Traditional air quality ...
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ISBN:
(纸本)9798350381771;9798350381764
Air pollution poses significant challenges to public health and ecological equilibrium globally, with particulate matter (PM) 2.5 emerging as a major concern due to its adverse health effects. Traditional air quality monitoring systems face limitations in cost, coverage, and data latency, necessitating innovative solutions. This paper introduces M-Care, a low-cost air quality monitoring system designed to monitor PM 2.5 levels, temperature, humidity, and pressure in real-time with web and mobile applications, collectively known as Yakkaw. Leveraging LoRa technology and IoT advancements, M-Care offers a scalable and easily deployable solution, addressing existing monitoring system constraints. The system's hardware design, web application interface, and mobile app functionality are detailed, alongside a case study in Northern Thailand showcasing its efficacy. Evaluation through field testing validates M-Care's accuracy and reliability, enabling informed decision-making and proactive pollution mitigation measures. Additionally, experiments assessing communication range highlight the system's performance limits. Visual analyses of hourly and daily PM2.5 data reveal patterns and fluctuations, aiding in identifying pollution trends and guiding policy decisions. Furthermore, seasonal variations in PM2.5 concentrations underscore the impact of agricultural burning and forest fires, emphasizing the importance of effective monitoring and management strategies. The findings contribute to advancing air quality monitoring technologies, offering insights for addressing environmental challenges and safeguarding public health.
In today's world, there is a growing need to analyze data stored in a Data Lake, which is a collection of large, heterogeneous databases. Our work is part of a medical application that aims to help healthcare prof...
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ISBN:
(纸本)9798350319439
In today's world, there is a growing need to analyze data stored in a Data Lake, which is a collection of large, heterogeneous databases. Our work is part of a medical application that aims to help healthcare professionals analyze complex data for decision-making. We propose mechanisms that promote data accessibility. The data are stored in a Data Warehouse (DW) that is periodically built from a data lake. Depending on the needs of the decision-maker, data are extracted from the DW and transferred to a Data Mart (DM) for querying. In this paper, we present a schema recommendation system based on the principle of collaborative filtering. This system can predict the DM schemas that were developed in the past that best match the data need expressed by a decision-maker. It does this by comparing the attributes present in the schemas with the attributes deduced from the need to propose a list of predictions for the most suitable schemas. The technique used is simple, while allowing us to solve the problem of periodic updates to the source data. An experiment was conducted for a medical application.
Intrusion Detection (ID), as an effective network security protection technology, is an important means to ensure network security. In order to solve the problem that traditional intrusion detection technology is diff...
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The paper expounds the main provisions of original author's devisings devoted to composing of a special information control system for automation of control processes in foundry production, where the problem of qu...
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With the continuous expansion of the power grid scale, the power dispatching has put forward higher requirements for the preparation of operation tickets. Currently, the digitalization and intelligence of the operatio...
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作者：
Solainayagi, P.
Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India
Accurate diagnosis and treatment for patients depend on highly developed prediction models, which are becoming more important in the field of biological signal categorization among healthcare professionals. This resea...
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Supporting Question Answering (QA) tasks is the next step for lifelog retrieval systems, similar to the progression of the parent field of information retrieval. In this paper, we propose a new pipeline to tackle the ...
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ISBN:
(数字)9783031564352
ISBN:
(纸本)9783031564345;9783031564352
Supporting Question Answering (QA) tasks is the next step for lifelog retrieval systems, similar to the progression of the parent field of information retrieval. In this paper, we propose a new pipeline to tackle the QA task in the context of lifelogging, which is based on the open-domain QA pipeline. We incorporate this pipeline into a multimodal lifelog retrieval system, which allows users to submit questions prevalent to a lifelog and then suggests possible text answers based on multimodal data. A test collection is developed to facilitate the user study, the aim of which is to evaluate the effectiveness of the proposed system compared to a conventional lifelog retrieval system. The results show that the proposed system is more effective than the conventional system, in terms of both effectiveness and user satisfaction. The results also suggest that the proposed system is more valuable for novice users, while both systems are equally effective for experienced users.
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