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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9905 条记录，以下是2181-2190 订阅

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Next-Generation Surveillance: Exploring the Intersection of Artificial Intelligence and Security

Next-Generation Surveillance: Exploring the Intersection of ...

引用

Intelligent systems Conference

作者： Ribeiro, Tiago Oliveira, Pedro Rodrigues, Manuel Univ Minho LASI ALGORITMI Ctr Guimaraes Portugal

ISBN: (纸本)9783031664274;9783031664281

Smart surveillance systems are transforming the landscape of surveillance, offering a wide range of applications that include the detection of violence, recognition of anomalies, identification of handguns, and monitoring of parking occupancy. This survey examines the current state of Smart Surveillance, emphasizing the integration of advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and edge computing, which enhance the effectiveness of real-time surveillance, accuracy, and efficiency. The implementation of AI-driven approaches has significantly enhanced the accuracy of recognition, ensuring reliable surveillance outcomes. Practical testing demonstrated that these systems can be trusted in real-world scenarios, confirming the potential of these approaches for practical deployment. Efficiency is a crucial aspect of smart surveillance systems, making them suitable for applications in smart cities. This survey highlights the versatility and potential of smart surveillance systems, shedding light on their impact in various domains and their future prospects, particularly in the context of smart cities and intelligent surveillance systems.

关键词： Smart surveillance Artificial intelligence Internet of Things Edge computing

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An Early Detection of Autism Spectrum Disorder Using PDNN and ABIDE I&II Dataset

An Early Detection of Autism Spectrum Disorder Using PDNN an...

引用

International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Lamani, Manjunath Ramanna Benadit, P. Julian Christ Deemed Be Univ Mysor Rd Bangalore 560074 Karnataka India

ISBN: (纸本)9789819984787;9789819984794

The current study's objective was to use deep learning methods to separate valetudinarians amidst autism spectrum disorders (ASDs) from controls employing just the patients' brain activation patterns from a dataset of large brain images. We examined brain imaging data from ASD patients from the global, multi-site ABIDE dataset (Autism Brain Imaging Data Exchange). Social impairments and repetitive behaviors are hallmarks of the brain condition known as autism spectrum disorder (ASD). ASD affects one in every 68 kids in the USA, as of the most recent data from the Disease Control Centers. To understand the neurological patterns that arose from the categorization, we looked into functional connectivity patterns that can be used to diagnose ASD participants precisely. The outcomes raised the state of the art by correctly identifying 72.10% of ASD patients in the sample vs. control patients. The classification patterns revealed an anti-correlation between the function of the brain's anterior and posterior regions;this anti-correlation supports the empirical data currently showing achingly ASD impedes communication between the livid brain's anterior and posterior areas. We found and pinpointed brain regions damn frolic, distinguishing ASD among typically developing reign according to our deep learning model.

关键词： ASD fMRI ABIDE I ABIDE II rsfMRI DL ML

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Third-Party Data Leaks in the Websites of Finnish Social and Healthcare Districts 12th

Third-Party Data Leaks in the Websites of Finnish Social and...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Puhtila, Panu Vuorinen, Esko Rauti, Sampsa Univ Turku Turku 20014 Finland

ISBN: (纸本)9783031602146;9783031602153

With digitalization, the use of essential social and healthcare services online has become increasingly prevalent. In this paper, we conduct a survey on the websites of Finnish social and healthcare districts and determine to what extent, if any, they leak their users' personal data to third parties through the use of the collection and tracking of user data and actions with the web analytics tools. Our findings show that 82.6% of the studied websites leaked personal data to outside actors, but the extent and contents of these data leaks varied. Our study also demonstrates that in many cases, privacy policies of the studied websites do not always report personal data items transferred to third parties and fail to adequately inform users. The cookie banners of the studied websites were also found to contain several dark patterns.

关键词： social and health websites data leaks data concerning health online privacy third-party services SOTE

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Home Education that is Not Friendly to Generation Z Children in the Digital Age in Indonesia 9th

Home Education that is Not Friendly to Generation Z Children...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Rahmatullah, Azam Syukur Laili, Nurul Fithriyah Awaliatul Aziz, Akbar Nur Magister Studi Islam Univ Muhammadiyah Yogyakarta Yogyakarta Indonesia Univ Islam Negeri Sunan Kalijaga Yogyakarta Indonesia

ISBN: (纸本)9789819735556;9789819735563

This study aims to explore what behaviors cause social pathology in the digital era carried out by Generation Z children. This type of research is qualitative research that is directly studied in the field to find out about the true effect of home education that is not friendly to children in this digital era. The research approach is phenomenology because it wants to thoroughly explore the four (4) informants who carry out digital-based social deviations. The four (4) were taken from the Yogyakarta region of Indonesia and were interviewed directly by researchers. The data obtained are then analyzed in depth by phenomenological analysis. The results showed some digital-based deviant behavior. The result of unfriendly home education is homosexual applications, open BO (Booking Online) services, online plus-plus footing, online perverted friendships, online gambling, and online games. The results showed that digital-based social pathology behavior was caused by family dysfunction, including Divorce victims, parents, unfriendly parents, inhuman parents, parents who do not think about children's finances, and abusive parents who are willing to win themselves and are anti-critical.

关键词： Home education Generation Z Digital age Open BO services Pijit plus-plus

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Multicriteria Evaluation of the Stability of an IT Project Team 13th

Multicriteria Evaluation of the Stability of an IT Project T...

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13th Computer Science Online Conference

作者： Maksim, Ardatovsky Tatyana, Maximova ITMO Univ 3 Linia VO 8 St Petersburg 199004 Russia

ISBN: (纸本)9783031705946;9783031705953

This paper presents an innovative approach to optimizing the decision-making process in IT team management through the application of the X-test method. By automating the process of determining team stability, the study argues for enhanced decision-making quality, increased team performance, and the fostering of a more transparent communication environment within IT teams. Furthermore, it highlights the utility of automated decision support systems in allowing managers to analyze performance outcomes and make data-driven decisions. The paper introduces a novel method for assessing IT team stability, grounded in expert evaluations and geometric interpretation, aimed at enabling managers to proactively identify issues within the team workflow. This method promises not only to improve the efficacy of IT teams but also to enhance the overall success of IT projects by providing a structured and quantifiable measure of team stability. Through a comprehensive analysis, this study contributes to the field of project management and decision support, offering a practical tool for IT managers seeking to navigate the complexities of team dynamics and project execution effectively.

关键词： Project management decision support performance automation

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Comparative Performance of Multi-level Pre-trained Embeddings on CNN, LSTM and CNN-LSTM for Hate Speech and Offensive Language Detection 6th

Comparative Performance of Multi-level Pre-trained Embedding...

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6th International Conference on Soft Computing and Data Mining (SCDM)

作者： Aziz, Noor Azeera Abdul Zainal, Anazida Al-Rimy, Bander Ali Saleh Ghaleb, Fuad Abdulgaleel Abdoh Univ Tunku Abdul Rahman Dept Internet Engn & Comp Sci Lee Kong Chian Fac Engn & Sci Bandar Sungai Long Kajang Selangor Malaysia Univ Teknol Malaysia Fac Comp Johor Baharu Johor Malaysia Univ Portsmouth Sch Comp Buckingham BldgLion Terrace Portsmouth PO1 3HE Hants England Birmingham City Univ Coll Comp & Digital Technol Birmingham B4 7XG W Midlands England

ISBN: (纸本)9783031669644;9783031669651

With growing concerns over hate speech, social media platforms provide policies for monitoring hate content. Nowadays, platforms like Twitter and Facebook rely on humans and machines as content moderators. As for machine moderators, many studies proposed hate speech detection using machine learning approaches. This study investigated which pre-trained text embedding (Word2Vec, GloVe, FastText, Elmo, and BERT) is the best for each tokenization level (word, subword, and character) and which neural network architecture (CNN, LSTM, and CNN-LSTM) is the best as an encoding method for hate speech and offensive language detection. The character-level GloVe with CNN-LSTM performed best among all tested methods. GloVe (character level) scored 93% for Fl-score and 92% for accuracy. At the word level, BERT word embedding with CNNLSTM had the best classification scores of 90% Fl-score and 91% accuracy. At the subword level, CNN-LSTM and CNN fared best with BERT word embed dings, which had 86% for both accuracy and Fl-score. The performance findings show that pre-trained embeddings at different tokenization levels capture diverse information. Moreover, with an average of 85% for Fl-score and 86% for accuracy, CNN-LSTM yielded the best score for almost all text embedding regardless of the tokenization level compared to CNN and LSTM. These results show that CNN-LSTM complements each other to capture sequential and local patterns in the input text.

关键词： Hate speech detection text embedding neural network text classification

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Affecta-Context: The Context-Guided Behavior Adaptation Framework 18th

Affecta-Context: The Context-Guided Behavior Adaptation Fram...

引用

18th International Conference on Intelligent Autonomous systems (IAS)

作者： Frederiksen, Morten Roed Stoy, Kasper Univ Copenhagen IT Copenhagen Denmark

ISBN: (纸本)9783031449802;9783031449819

This paper presents Affecta-context, a general framework to facilitate behavior adaptation for social robots. The framework uses information about the physical context to guide its behaviors in human-robot interactions. It consists of two parts: one that represents encountered contexts and one that learns to prioritize between behaviors through human-robot interactions. As physical contexts are encountered the framework clusters them by their measured physical properties. In each context, the framework learns to prioritize between behaviors to optimize the physical attributes of the robot's behavior in line with its current environment and the preferences of the users it interacts with. This paper illlustrates the abilities of the Affecta-context framework by enabling a robot to autonomously learn the prioritization of discrete behaviors. This was achieved by training across 72 interactions in two different physical contexts with 6 different human test participants. The paper demonstrates the trained Affecta-context framework by verifying the robot's ability to generalize over the input and to match its behaviors to a previously unvisited physical context.

关键词： Human robot interaction

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Solving the Crossword Generation Problem Using Parallel Programming in Moderns Browsers: A Case Study 9th

Solving the Crossword Generation Problem Using Parallel Prog...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Rodrigues, Daniel T. Bianchini, Calebe P. Univ Prebiteriana Mackenzie Comp & Informat Dept Sao Paulo Brazil

ISBN: (纸本)9789819735556;9789819735563

The use of modern browsers reveals itself more and more essential to the world. Features like Web Workers are becoming more adopted over the most used browsers of the Internet, enabling performance enhancements in web applications. As consequence, execution of tasks with higher computational demand inside the browser. Technique of task parallelization using Web Workers, presenting as study case an algorithm of crossword generation, being executed in a browser context. The results show even superlinear speedups for a parallel version of the algorithm.

关键词： Parallel programming Rust Web Workers WebAssembly

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Drivers of Long-Term Work from Home Adoption in Small and Medium-Sized Enterprises: A Managerial Perspective 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Ropke, Ann-Kathrin Naranjo-Zolotov, Mijail NOVA Informat Management Sch NOVA IMS Campus Campolide P-1070312 Lisbon Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The pandemic shifted the labor market resulting in an increased demand for work from home (WFH), leading companies to be pressured into implementing it to stay competitive and attractive to employees. Nevertheless, the managers make the decision regarding employees' requests to conduct their tasks from home and therefore play a crucial part in the adoption of WFH in enterprises. This study explores the factors that influence its long-term adoption from a managerial perspective. We propose and qualitatively evaluate a model, guided by the task-technology fit theory, to examine the role of the individual, technological, organizational, and task characteristics for long-term adoption. The findings show that individual factors are weighted highest by managers for their decision-making. Those factors include their experiences with working from home and the corresponding trust toward employees, which are prerequisites for the implementation and shape the attitude of managers. Technological, organizational, and task characteristics are key enablers for WFH and are the building stock for its effective long-term adoption. If trust and positive experiences exist, the interviewed managers indicated that they strive to introduce a hybrid model, in the long term, to cope with the changes in the labor market by staying competitive and attractive to qualified employees.

关键词： Work from home adoption Managerial perspective Small and medium-sized enterprises Task-Technology Fit

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Applications of Machine Learning Methods for Positioning in Scanning Electrochemical Microscope 28th

Applications of Machine Learning Methods for Positioning in ...

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2024 International Conference Automation

作者： Ivinskij, Vadimas Pandey, Vijitashwa Morkvenaite-Vilkonciene, Inga Vilnius Gediminas Tech Univ LT-10223 Vilnius Lithuania Oakland Univ Rochester MI 48309 USA State Res Inst Ctr Phys Sci & Technol Vilnius Lithuania

ISBN: (纸本)9783031782657;9783031782664

A typical scanning electrochemical microscope (SECM) consists of a three-axis positioning system, usually with stepper motors and potentiostat. Working at a micro and nanoscale, the most consistent problem is vibrations, which an antivibration table can solve. However, this is not a solution for some devices placed in small environments. Therefore, we suggest reducing vibrations by machine learning methods, making SECM more modular. In this paper, we compare and evaluate the use of neural networks within similar systems that have specialized architecture requirements, the use of samples that require a specialized approach to attribute extraction concerning feature fidelity for learning algorithms, control-machine learning combination methods for static and dynamic applications in electrochemical systems as well as application of neural network functions as stand-alone packages. The results were taken for the application of prototyping a tangible and portable electrochemical scanning device system. Potential improvements, such as micro stepping instead of time delay between steps, are considered. The proposed methods in this paper are aimed at countering the disturbances caused by transient processes during actuation and control tuning using non-evasive methods for cheaper solution alternatives.

关键词： Scanning electrochemical systems Machine learning Control systems

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