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

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Predicting Virality of Tweets Using ML Algorithms and Analyzing Key Determinants of Viral Tweets 1

引用

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

作者： Arunkumar, Preeti Jadhav, Anil Symbiosis Int Deemed Univ Symbiosis Ctr Informat Technol Pune Maharashtra India

ISBN: (数字)9789819984763

ISBN: (纸本)9789819984756;9789819984763

Social media is no longer just a medium for socialization but has become a medium for business. There has been an exponential growth of user-generated content in both volume and significance. Researchers have studied the behavioral side of social media, reviews, and social network communities. Some researchers have analyzed tweets and found that only the content with strong negative emotions gets retweeted. There is a lack of research focusing on other factors like the length of a tweet, user's follower counts, etc., affecting the success of a tweet. Advancements in technology help us to use machine learning algorithms to predict if the post will go viral or not. This research paper also finds and verifies the key determinants that contribute to a tweet's success. This paper also concludes with the most appropriate machine learning model for predicting the Virality of a tweet.

关键词： Machine learning Virality Social media Twitter

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Computer Vision and Convolutional Neural Network for Dense Crowd Count Detection

Computer Vision and Convolutional Neural Network for Dense C...

引用

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

作者： Sirisha, D. Prasad, S. Sambhu Kumar, Subodh Nadimpalli Satyanarayana Raju Inst Technol Dept Comp Sci Engn Visakhapatnam AP India Nadimpalli Satyanarayana Raju Inst Technol Dept Mech Engn Visakhapatnam AP India Pragati Engn Coll Dept Elect & Commun Engn Surampalem AP India

ISBN: (纸本)9789819984787;9789819984794

Crowd counting is an approach for the process of counting the people in an image. Extensive studies on crowd detection and density estimation are being carried out for crime prevention, crowd irregularities, public safety, visual monitoring, and urban planning. Approaches to detect crowd count are available in the literature;however, available algorithms could not detect the accurate number of people. Therefore, in the current work, computer vision techniques in fusion with convolutional neural networks (CNNs) are employed to produce impressively precise estimates. The proposed work will precisely detect count of the persons in an image using computer vision and CNN. Pattern recognition techniques are employed for crowd count detection by using face detection. However, detecting a face in the crowd is complex as inconsistency prevails in human faces comprising of color, pose, expression, position, orientation, and illumination. Congested Scene Recognition Network (CSRNet) attains 47.3% lower mean absolute error compared with existing techniques. The current work is also extended to various intended applications such as vehicles. The experimental results reveal that CSRNet has shown significant improvement in the output by 15.4% better MAE than existing contemporary approaches.

关键词： Deep convolutional neural networks Crowd counting Density detection Faster R-CNN

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Real-Time Video Processing in Fuzzy Posture-Based Ergonomic Analysis in a Disassembly Cell

Real-Time Video Processing in Fuzzy Posture-Based Ergonomic ...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Amirnia, Ashkan Ghorbani, Elham Keivanpour, Samira Polytech Montreal Montreal PQ H3T 1J4 Canada

ISBN: (纸本)9783031671913;9783031671920

Traditional ergonomic evaluations often overlook the dynamic and uncertain nature of human movements, leading to potential musculoskeletal disorders (MSDs) and impacting worker health, efficiency, and company costs. Disassembly cells, crucial for sustainability and circular economy efforts, pose unique challenges and opportunities for ergonomic optimization. This study introduces an innovative approach for ergonomic risk assessment in the manufacturing industry, particularly within disassembly cells, by integrating real-time video processing and fuzzy logic. Our research fills a significant gap in ergonomic assessment by utilizing a multi-camera computer vision technique to capture and analyze worker motions in real-time, allowing for dynamic ergonomic risks assessment in a disassembly cell. The fuzzy logic inference enhances the system's ability to handle the variability and subjectivity of human posture, offering a more nuanced and accurate risk assessment than binary logic systems. Experimental validation in a laboratory setting confirms the feasibility of our approach, demonstrating its potential to improve worker safety and productivity by providing a more responsive and adaptable tool for ergonomic assessment in industrial environments. This work marks a significant advancement in the field, suggesting a path forward for the development of ergonomic interventions that are both more effective and applicable in diverse manufacturing settings.

关键词： Ergonomic risk disassembly cell fuzzy logic computer vision

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An Excel Motion Profile Optimization (MoPO) Tool for 1-DOF Mechatronic systems 1

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3rd International Symposium on Industrial Engineering and Automation

作者： Van Oosterwyck, Nick Maes, Brecht De Laet, Robbe Derammelaere, Stijn Univ Antwerp Dept Electromech Cosys Lab Groenenborgerlaan 171 B-2020 Antwerp Belgium Flanders Make Strateg Res Ctr Mfg Ind AnSyMo CoSys Lommel Belgium

ISBN: (数字)9783031704659

ISBN: (纸本)9783031704642;9783031704659

Repetitive positioning applications are of significant importance in industrial machinery. The electric actuators driving these movements account for a substantial portion of worldwide energy usage. Therefore, it is valuable to consider optimizing the point-to-point movements of these 1-DOF mechanisms. In this context, motion profile optimization is a cost-effective solution, allowing for more energy-efficient machines without additional hardware investments. The state-of-the-art contains several valuable optimization algorithms to reduce energy usage, resulting in torque savings up to 45.4%. However, these methods rely on specific software which might require expertise and additional license investments. The latter hinders the adoption of motion profile optimization in many companies' engineering workflow. After surveying 36 machine builders, it became clear that only 11% of them confirmed having in-depth expertise to perform motion profile optimizations. Therefore, an exclusively Excel-based Motion Profile Optimization (MoPO) tool is introduced which is able to achieve identical savings as commercial optimization software such as MATLAB. After proposing the techniques, 74.1% of the machine builders rate the applicability as good or very good.

关键词： Excel tool motion profile optimization energy-efficient trajectory planning mechatronic systems

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A Web-Based Disease Prediction System Using Machine Learning Algorithms and PCA 1

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2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Khan, Anushey Huseyinov, Ilham Istanbul Aydin Univ Grad Inst Sci Artificial Intelligence & Data Sci TR-34295 Istanbul Turkiye Istanbul Aydin Univ Software Engn Dept TR-34295 Istanbul Turkiye

ISBN: (数字)9783031628719

ISBN: (纸本)9783031628702;9783031628719

This work presents a web-based disease prediction system to diagnose diseases using machine learning algorithms and principal component analysis (PCA). Using web technology made the system accessible from any place, at any time. An ensemble of classifiers such as Gaussian Naive Bayes, Support Vector Machines, and Random Forest, have been applied to predict the diseases. Also, PCA is utilized to find influential symptoms for a certain type of disease. The performance of the system is evaluated before and after applying PCA to the dataset in terms of accuracy, precision, recall, and F1-score. As a result, the impact of PCA on the system performance is illustrated.

关键词： Web Technology Gaussian Naive Bayes Support Vector Machines Random Forest PCA Mode Prediction

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Need for Cultural Sensitivity in the Design and Development of Technology to Aid in Dementia Care: A Review of Literature

Need for Cultural Sensitivity in the Design and Development ...

引用

Computing Conference

作者： Khan, Arshia Rao, Sakina Parvez, Alfia Univ Minnesota Duluth MN 55812 USA

ISBN: (纸本)9783031622793;9783031622779;9783031622762

This prospective paper delves into the critical necessity of integrating cultural sensitivity and adaptability into the design of technology, particularly in the context of dementia care. Despite the increasing prevalence of technology-driven solutions for dementia, a substantial gap persists in acknowledging and addressing the diverse cultural backgrounds of individuals affected by the condition. Our analysis reveals that a mere 3.5% of research papers focusing on technology for dementia explicitly mention cultural sensitivity, highlighting a significant oversight in the current discourse. This paper not only outlines the existing gaps in current research but also identifies the ethical implications of neglecting cultural sensitivity in technology design for dementia care and makes recommendations to develop technology that is culturally adaptive for dementia care. As individuals progress through the stages of dementia, a phenomenon commonly observed is their tendency to revert to cultural roots. This paper explores how the lack of cultural awareness in technology design hampers the effectiveness and inclusivity of interventions, resulting in missed opportunities to enhance the quality of care for diverse populations. We argue that a paradigm shift is imperative, urging researchers and designers to adopt a more holistic approach that considers the unique needs, values, and preferences associated with diverse cultural backgrounds. In conclusion, this paper advocates for a comprehensive and culturally sensitive approach to technology design in dementia care, underscoring the need for further research, awareness, and collaboration among stakeholders to bridge existing gaps and ensure the development of technologies that truly cater to the diverse needs of individuals affected by dementia.

关键词： Cultural sensitivity Technology Dementia Healthcare

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Optimisation of Fiber Laser Cutting of Stainless Steel Using TOPSIS - Shannon Entropy Method 10th

Optimisation of Fiber Laser Cutting of Stainless Steel Using...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Begic-Hajdarevic, Derzija Muhamedagic, Kenan Cekic, Ahmet Husic, Maida Cohodar Univ Sarajevo Fac Mech Engn Dept Mech Prod Engn Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

Fiber laser cutting can be applied to achieve a very precise cut of various material by selecting the appropriate cutting parameters. In this study, the influence of three main cutting parameters including laser power, assist gas pressure and cutting speed on the cut quality performance during laser cutting of stainless steel was analyzed. TOPSIS-Shannon entropy method based on Box-Behnken experimental design was applied to find optimal combination of cutting parameters. The optimal cutting condition was obtained at 1000 W of laser power, 320 mm/s of cutting speed and 1.5 bar of assist gas pressure.

关键词： fiber laser stainless steel cut quality TOPSIS Shannon entropy

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A Focused Systematic Review of the Regulation for the Crypto Asset in Peru and Its Limits 13th

A Focused Systematic Review of the Regulation for the Crypto...

引用

13th Computer Science Online Conference

作者： Arias, Renato Arias, Ricardo Ochoa, Kelly Univ Autonoma Peru Lima Peru Univ Tecnol Peru Lima Peru Univ Pompeu Fabra Barcelona Spain

ISBN: (纸本)9783031705175;9783031705182

This research article evaluates the current legislative proposal for a crypto-assets law in Peru. It is noteworthy that various regulatory entities within the country's financial system have explicitly expressed their opposition to the legislative proposal. Despite this, the Peruvian Congressional Commission responsible for evaluating the approval has overlooked the pronouncements of regulatory entities, basing its decision on similar legislative initiatives in various South American countries. Therefore, the purpose of this research is to highlight the deficiencies of the legislative proposal and the potential consequences of its regulation under these terms, as well as to make recommendations and gather international experience in the regulation of crypto assets. In this regard, a systematic analysis of official documents from Peru and the content of 169 research articles retrieved from the ScienceDirect, Scopus and IEEE database has been conducted. It is worth noting that for this analysis, a systematic review of primary sources and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Abstract (PRISMA-A) and Population, Intervention, Comparison and Outcome (PICO) guideline were used, enabling a rigorous and transparent investigation to showcase influential and important studies addressed from 2020 to the present. In summary, this research presents the deficiencies in the legislative proposal, along with the most recent trends in the regulation of crypto assets. Furthermore, we suggest that legislators be more critical when proposing such legislative initiatives, and we believe that this article could serve as a basis for future study on the regulation of crypto assets.

关键词： Crypto assets Cryptocurrencies Regulation Legal framework Regulatory authorities

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The Be-Hive Project-Counting Bee Traffic Based on Deep Learning and Pose Estimation

The Be-Hive Project-Counting Bee Traffic Based on Deep Learn...

引用

Intelligent systems Conference (IntelliSys)

作者： Padubidri, Chirag Kamilaris, Andreas Charalambous, Alexis Lanitis, Andreas Constantinides, Marios CYENS Ctr Excellence Nicosia Cyprus Cyprus Univ Technol Limassol Cyprus Univ Twente Enschede Netherlands

ISBN: (纸本)9783031477232;9783031477249

Beekeeping is an important practice for ensuring the abundance of pollinators and for honey production. Traditionally, beekeepers inspect hives regularly to monitor their bees' populations, but this method is invasive and can cause stress to the bees. It is also impractical, for beekeepers having hundreds or thousands of beehives. In recent decades, various attempts have been made to automate the monitoring of bee colonies using emerging technologies. These technologies include sensors that collect micro-climate parameters, photos, video and audio from inside the hives and the nearby environment, which are then analyzed using automatic or manual methods. The beehive project aims a range of sensing technologies (image, sound, temperature, humidity, weight), together with state-of-the-art computer vision technologies and remote-sensing imagery to create a smart beehive system and monitor beehive on real-time. In this paper, we present the preliminary results of the BEHIVE, a smart beehive monitoring system. We present the monitoring system developed and the deep learning algorithm used to count bee traffic using the image from the camera placed at the entrance of the hive. For bee traffic estimation, we employ a counting algorithm that predicts the pose of individual bees and tracks them in subsequent frames. To reduce the annotation overhead of the key-points for pose estimation, we generate synthetic data to train our algorithm. The results show that the key-point detection model achieves an Intersection Over Union (IOU) of 86% when trained only on synthetic data and a traffic count mean absolute error of 5.7. These results indicate that the proposed approach can be used to monitor the bee activity remotely, increasing convenience and productivity.

关键词： Smart beehive IoT Deep learning Bees' traffic counting

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Phishing and Human Error. Beyond Training and Simulations 1

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

作者： Cano, Jeimy J. M. Univ Los Andes Fac Derecho Cra 1E 18A-10 Bogota Colombia

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

Phishing is catalogued in the literature as one of the most common and at the same time most effective attacks at the time of realizing an adverse event in an organization. It is an action based on intelligence, deception and distraction that focuses on individuals to motivate them to take actions that end up with the compromise of their sensitive data. In this sense, companies have focused their efforts to prevent this type of attacks based on training and simulations, understanding phishing as a result contrary to what is expected by the corporation, which has ended up being ineffective. Consequently, this article proposes the understanding of phishing as a consequence, where the context and everything that involves the individual is what is relevant to explain the unexpected behavior, following the theory of human error that, without releasing the person from responsibility for their actions, understands and highlights aspects that go beyond the regular and standard training, to motivate a vigilant and more resistant to deception posture.

关键词： Phishing Human Error Training Context

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