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检索条件"丛书名=Communications in Computer and Information Science"

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Real-Time Detection of the Colta's Lagoon Surface Contamination Using a Unmanned Aerial Vehicle (UAV)-Based Machine Learning

Real-Time Detection of the Colta's Lagoon Surface Contaminat...

引用

4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Valle-Onate, Paulina Sofia Jinez-Tapia, Jose Luis Santillan-Valdiviezo, Luis Gonzalo Penafiel-Ojeda, Carlos Ramiro Cuzco, Giovanny Univ Estatal Milagro Fac Ciencias & Ingn Carrera Software Milagro Ecuador Univ Nacl Chimborazo Fac Ingn Carrera Telecomunicac Grp Invest GI CT 2I Riobamba Ecuador Univ Nacl Chimborazo Fac Ingn Carrera Telecomunicac Grp Invest Telecomunicac Informat Ind & Construcc Riobamba Ecuador

ISBN: (纸本)9783031834318;9783031834325

The main goal of this research is to determine the level of surface contamination in a considerable area of land covered with water, such as the Colta Lagoon, through the implementation of recognised use drone cameras, by integrating machine learning techniques with computer vision, which can detect objects, track various materials, and classify them accurately in real-time or not, allowing the determination of the type of pollutants existing in these experimental spaces after analysis, with autonomous flight capabilities. The system comprises a convolutional neural network (CNN) and an AlexNet network that has already been trained. The objectives are to achieve near real-time performance and the highest accuracy possible by building a database of specific images with transfer learning terms. It is therefore determined that the accuracy of the system is extraordinary both under real conditions and when using a standard dataset. This high rate of precision in applying the proposed model to real data leads us to develop a method for use in video-based artificial vision applications.

关键词： Unmanned Aerial Vehicle Artificial Intelligence Convolutional Neural Netwotks System

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Selection of Facts Placements for Optimal Control of Power System Modes 2nd

Selection of Facts Placements for Optimal Control of Power S...

引用

2nd International Conference on information Technologies and Their Applications

作者： Balametov, Ashraf Halilov, Elman Isayeva, Tarana Yaqublu, Tofiq Azerbaijan Sci Res & Design Prospecting Power Eng Baku Azerbaijan Azerbaijan State Oil & Ind Univ Baku Azerbaijan

ISBN: (纸本)9783031734168;9783031734175

Modern power systems are highly complex. Power electronic based systems and other static equipment that provide controllability of power flow and voltage are named Alternative Current Transmission System (FACTS) Controllers. FACTS is one of the most popular electrical grid technologies, the aim of which is that the electrical network from a passive device for transporting electricity transforms into an instrument that actively participates in controlling the operating regimes of electrical networks. Exists four main types of FACTS controllers are series devices, shunt devices, combined series - shunt devices, combined series - series devices. The optimal allocation of Thyristor Controlled Series Compensations (TCSC) and STATCOM can improve the transmission capacity. The controllability also ensures improvement of security of power systems under contingency conditions where power system stability is threatened. Power system voltage stability is one of the main areas of focus when there is a mismatch between generation and demand. A major function of a FACTS Controller is power oscillation damping involving flow frequency oscillations that threaten system security under peak power flow conditions. It is proposed to improve the damping of low-frequency oscillations by placing a unified power flow controller in the power system. The effectiveness of the application is demonstrated on a test example of a network with a voltage of 220, 330 and 500 kV.

关键词： power system control equation power oscillation damping regimes

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GHG Web Portal Dashboard: A Scalable and Flexible Digital Platform for Efficient Environmental Monitoring 1

引用

4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Bastos, Goncalo Martinho, Ricardo Ferrao, Silvia Martinho, Rita Matias, Hugo Polytech Univ Leiria ESTG Leiria Portugal Polytech Univ Leiria INESCC DL ESTG Leiria Portugal CoLAB NET4CO2 Network Sustainable CO2 Econ Porto Portugal

ISBN: (数字)9783031832079

ISBN: (纸本)9783031832062;9783031832079

The importance of efficient digital platforms for monitoring greenhouse gas (GHG) indicators cannot be overstated in contemporary environmental management and sustainability efforts. Such platforms are crucial for accurate, real-time data collection and integration, facilitating regulatory compliance, and enabling strategic decision-making. However, developing a usable digital platform for GHG monitoring is challenging due to the complexity of integrating diverse data sources, ensuring data accuracy and reliability, and providing user-friendly interfaces for varied stakeholders. Despite the availability of multiple official data sources on GHG emissions, no specific digital platform exists to comprehensively aggregate and manage this data. Existing systems often lack the flexibility to incorporate new indicators and adapt to evolving regulatory requirements. This paper presents a digital platform capable of seamlessly integrating data from various sources and offering robust usability, to enhance the effectiveness of GHG emission monitoring. The platform can be valuable to stakeholders, including regulatory bodies, industry leaders, environmental organizations, and the general public to address the complexities of environmental data and advancing global sustainability efforts.

关键词： Data Visualization Greenhouse gas (GHG) emissions Interactive Dashboard Usability

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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Zhang, Jing Wang, Jiankun Xu, Lu Zhou, Ting Gu, Junwei Wang, Yu Zhuhai Wanda Intelligent Commercial Technol Co Lt Zhuhai 519000 Peoples R China Xi An Jiao Tong Univ Dept Mech Engn Xian 710049 Peoples R China

ISBN: (纸本)9789819770069;9789819770076

Traditional collaborative filtering techniques deal with no time-effect data. For recommender systems, as user preferences change over time, it can-make the preferences of recommendation results change. In addition, the data explosion makes the model process more and more data over time, which greatly increases the computational cost. To solve the above problems, a similarity index time-effect collaborative filtering algorithm based on Attentional Double BP Network (SITCF-ADBP) is proposed. Firstly, three time-effect functions are proposed for processing evaluation metrics of user preferences changed over time. Secondly, after clustering the training samples using K-Nearest Neighbor (KNN), a set of similarity index screening principles is specified, and only one sample with high similarity is retained to reduce the input of the model. Finally, a Double BP Network incorporating a channel attention mechanism is designed to process the adequately processed data. Experiments were conducted on the MovieLens datasets (ml-1m) and (ml-100k), wherein our proposed approach was benchmarked against several state-of-the-art (SOTA) deep learning methods. The obtained results indicate that the model can effectively cope with the time-effect and data explosion of the recommender system.

关键词： Collaborative Filtering Similarity Index Time-effect Attention Mechanism

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Robotic Process Automation Application in Healthcare 4th

Robotic Process Automation Application in Healthcare

引用

4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Guarda, Teresa Univ Estatal Peninsula Santa Elena La Libertad Ecuador Minho Univ Algoritmi Ctr Guimaraes Portugal

ISBN: (纸本)9783031832093;9783031832109

The evolution of technology has provided the business world with substantial improvements in the execution of its activities. This evolution has allowed the simplification of the execution of activities, ensuring greater security in carrying out corporate processes. Robotic Process Automation (RPA) is a technology that has become increasingly relevant in everyday business life and has reached more and more areas. RPA has stimulated the advancement of digital transformation in all aspects of business, providing digital solutions that have supported the exponential development of organizations, directing them towards the desired results, and providing greater efficiency and productivity, through the collection of information between systems, and processes with mechanical and repetitive activities. The application of this technology brings benefits to the companies that adopt it. In this scenario, despite it being a sector that is still leading in adopting this technology, the aim of this study is to show how RPA is being utilized in the healthcare industry.

关键词： RPA Application in Healthcare Efficiency Improvement Ethical Issues

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Contextuality, Cognitive Engagement, and Active Inference 5th

Contextuality, Cognitive Engagement, and Active Inference

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5th International Workshop on Active Inference

作者： Guenin-Carlut, Avel Univ Sussex Dept Engn & Informat Brighton E Sussex England Kairos Res Dayton OH 45458 USA Act Inference Inst Davis CA 95616 USA

ISBN: (纸本)9783031771378;9783031771385

We revisit existing criticism of the Free Energy Principle and Active Inference through the concept of cognitive contextuality. Contextuality describe the property of physical states which are brought about by the very act of their observation, such as the position or momentum of individual particles in quantum settings. Based on conceptual and physical argument, we propose that contextuality drives the construction of cognitive semiotics. As such, it constitutes a fundamental component of cognition which any formal theory thereof must capture. At a conceptual level, Active Inference seems to capture the inherently contextual nature of cognitive engagement with the world. However, the Free Energy Principle cannot formalize this intuition due to its definition in terms of Dynamical Systems Theory, which comes with a well-defined space of possible states with no contextual properties. We describe the duality between agent-driven interaction and the construction of cognitive spaces which is implicit in the very concept of cognitive contextuality. In consequence, we emphasize the importance of the ontic regime called "Participatory Realism", and consider some ways that the FEP could integrate it.

关键词： Active Inference Free Energy Principle Physics of cognition Contextuality Participatory realism Open-ended evolution Quantum information theory

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Mobile Application for Managing Service Payments in SMEs

Mobile Application for Managing Service Payments in SMEs

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Guevara, Abel Ballena, Harvy Mansilla-Lopez, Juan Portugal, Christian Cipriano Univ Peruana Ciencias Aplicadas Lima Peru Cranfield Univ Cranfield Beds England

ISBN: (纸本)9783031834349;9783031834356

This study identifies the problems faced by small and medium-sized enterprise (SME) sector, which represent 95.6% of micro enterprises, 3.8% of small- sized, and 0.1% of medium-sized companies in Peru. In addition, SMEs account for 45.9% of the economically active population (EAP) in 2022. The heads of SMEs face challenges in managing their payments for services such as electricity and water. We reviewed studies focused on SMEs in Peru. However, we found only one relevant study, which was conducted in 2023 on drug management in the health sector. Therefore, we developed a mobile application that helps in managing service payments. The app was developed using the Flutter framework and Azure DevOps cloud deployment for SMEs. This study aims to reduce the burden of manual management, avoid human errors, and automate service payment processes for users. The app aims to avoid overpayments, optimize finances, reduce costs, and reduce employee time per day. In addition, the app was validated by conducting a case study with importing companies. The results revealed that the average time to register services in person was 22.75 min, which decreased to 13 min after using the mobile application. In addition, the app facilitated successful transactions and reduced monthly costs by 2.59% monthly by alerting the users of late payments. In conclusion, the application facilitates an efficient payment of services in SMEs, reducing waiting times and excessive costs.

关键词： SME Mobile app Payment Security Framework

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Strategies and Tools to Support Place-Belongingness in Smart Cities 1

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8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Mohseni, Hesam Correia, Antonio Silvennoinen, Johanna Kujala, Tuomo Karkkainen, Tommi Univ Jyvaskyla Fac Informat Technol POB 35 Jyvaskyla 40014 Finland

ISBN: (数字)9783031826337

ISBN: (纸本)9783031826320;9783031826337

Smart cities have the potential to reduce socio-spatial barriers and foster place-belongingness among citizens. However, this potential remains largely unmapped. We conducted a literature review to address this gap. Our findings suggest that promoting inclusive dynamics and emphasizing urban identity are key strategies for supporting place-belongingness in smart cities. Additionally, digital platforms and information and communication technologies (ICTs), gamification, crowdsensing, urban heritage technologies, and digital placemaking are the most popular digital tools used to achieve this. This literature review indicates that place-belongingness is underexplored in smart city studies, and further research is needed to fully understand the potential of smart cities to support place-belongingness.

关键词： Smart Cities Place-Belongingness Crowdsensing Digital placemaking Wellbeing Socio-Spatial exclusion Urban Identity

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Automatic Generation of Summaries and Questions to Support the Reading Comprehension Process 10th

Automatic Generation of Summaries and Questions to Support t...

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10th International Conference on Technologies and Innovation

作者： Contreras-Arguello, Miriam Lizbeth Paredes-Valverde, Mario Andres Trinidad Vasquez, Aurelio Miguel Salas-Zarate, Maria del Pilar Tecnol Nacl Mexico ITS Teziutlan Fracc & 1 2 Puebla Mexico Colegio Educac Personalizada Ingenium AC San Pedro Garza Garcia Mexico

ISBN: (纸本)9783031757013;9783031757020

Reading comprehension is a flexible and ongoing cognitive and constructive process that directly impacts the academic performance and cognitive development of students at different educational levels. Supporting students to develop reading comprehension skills requires teachers conduct tasks such as read educational resources and generate summaries and questionnaires, which requires a significant amount of time. In recent years, Artificial Intelligence (AI) has impacted many areas of our daily lives including education. Nowadays, Natural Language Processing (NLP), an outstanding area of AI, allows to automatically generate summaries from a provided text, which is especially useful for students and professionals who need to understand a topic quickly without reviewing the entire text. In this sense, this work proposes a system that integrates NLP techniques to automatically generate summaries and questions from a text provided by the teacher. The system also provides the teacher with reports of the results obtained by students from reading comprehension lessons conducted through the original text and the automatically generated summary. This system aims to be a tool that allows teachers to save time required for the generation of educational resources and allow them to focus on other tasks such as the establishment of strategies for students with greater reading comprehension problems. The developed system was evaluated by a group of elementary school students, obtaining encouraging results regarding the use of summaries to improve reading comprehension.

关键词： Summary Automatic Generation Reading Comprehension Process Automatic Question Generation

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Enhancing Clinical Documentation Through NLP-Driven Disease Categorization and Visualization: A Case Study Utilizing the Llama2 AI Model 8th

Enhancing Clinical Documentation Through NLP-Driven Disease ...

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2024 World Congress in computer science, computer Engineering and Applied Computing-CSCE

作者： Singh, Bhavraaj Mohammad, Atif Farid Rahim, Muhammad Abdul Basit Ur Calif State Univ Long Beach Dept Comp Engn & Comp Sci Long Beach CA 90840 USA Univ Cumberlands Dept Comp Sci Cumberlands Williamsburg VA USA

ISBN: (纸本)9783031856273;9783031856280

Clinical documentation is integral to healthcare, providing essential information for patient care, billing and research purposes. However, the documentation process often encounters challenges such as inaccuracies, inconsistencies and inefficiencies. Leveraging advancements in Natural Language Processing (NLP) presents a promising solution to enhance clinical documentation practices. In this paper, we propose a novel approach utilizing an advanced AI model, specifically Llama2, to address these challenges and improve clinical documentation. Our methodology involves leveraging NLP techniques, including text categorization, data cleaning and visualization, to streamline the clinical documentation process. We present a case study utilizing a custom dataset of patient records to demonstrate the effectiveness of our approach. The results highlight significant improvements in categorization accuracy, data cleanliness and visualization of trends, underscoring the potential of NLP in driving clinical documentation improvement and enhancing healthcare delivery.

关键词： natural language processing clinical documentation improvement AI models text categorization data cleaning visualization

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