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

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Identifying Traffic Congestion Through Vehicle Counting and Motion Estimation 7th

Identifying Traffic Congestion Through Vehicle Counting and ...

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7th International Conference on Green Technology and Sustainable Development

作者： Minh-Thien Duong Thanh-Danh Phan Van-Binh Nguyen My-Ha Le HCMC Univ Technol & Educ Intelligent Syst Lab Ho Chi Minh City Vietnam Soongsil Univ Seoul South Korea Chungbuk Natl Univ Cheongju South Korea Thu Dau Mot Univ Thu Dau Mot City Binh Duong Prov Vietnam

ISBN: (纸本)9783031761966;9783031761973

A series of arterial roads and major intersections in most major cities in the world often fall into traffic congestion, slowing socioeconomic growth and negatively impacting the environment. Therefore, this article presents a solution to identify traffic congestion by leveraging the view of many cameras at intersections in the city to recognize the amount and volume of vehicles moving and whether or not traffic congestion will occur. Total Vehicles and Traffic Velocity are two essential features considered as an evaluation index of traffic conditions. Our proposed solution encompasses three main stages: vehicle detection, motion estimation, and identification. To begin with, we introduce the improved YOLOv4-CSP model and OC-SORT tracking algorithm to detect and count total vehicles with the training dataset derived from the HCMAI Challenge competition. For the motion estimation, the feature-matching method extracts the keypoints of detected vehicles. Subsequently, we calculate the Euclidean distance of the corresponding keypoints in the next frame to estimate traffic velocity. Finally, we combine the two preceding stages and abide by the following rule to identify the traffic state. A traffic state will be normal if the total number of vehicles is dense but moving steadily. On the contrary, if the vehicle density is prolonged but the vehicles move very slowly, this traffic state is identified as traffic congestion. Experimental results demonstrate that our study obtained satisfactory results and suggest that it is prospective for practical applications.

关键词： Traffic Congestion Vehicle Counting Traffic Velocity Motion Estimation Fusion Method

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A Graph-Based Approach for Searching and Visualizing of Resources and Concepts in Data Science 12th

A Graph-Based Approach for Searching and Visualizing of Reso...

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

作者： Morales-Quezada, David Chicaiza, Janneth Univ Tecn Particular Loja Dept Ciencias Computac Loja Ecuador

ISBN: (纸本)9783031602207;9783031602214

The paper presents a resource search and visualization approach for learning data science fundamentals. We implement a web prototype that uses a knowledge graph built from the topics of the domain and a metadata repository of resources related to these topics. The application allows the graphical and interactive visualization of the graph and its semantic relationships, as well as the exploration, search, and visualization of concepts and resources. The results of the preliminary validation show its potential to improve the understanding of data science topics and promote free access to educational resources such as datasets, notebooks, and multimedia material.

关键词： Learning data science knowledge graphs search engine visualization of educational resources

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The Impact of Islamic Resilience on Student Spirituality While Engaging in Digital Activities 9th

The Impact of Islamic Resilience on Student Spirituality Whi...

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

作者： Suud, Fitriah M. Salsabillah, Wahyu Thalia Univ Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (纸本)9789819735587;9789819735594

Islamic resilience in digital activities is the ability of endurance and toughness that is inherent in a person's spirituality to be able to overcome challenges in digital activities and be resistant to the influence of social media. This research aims to examine the Islamic resilience of high school students to protect themselves during digital activities. The method for collecting data is carried out through in-depth interviews with previously determined respondents, observing digital activities and Islamic resilience activities of students, as well as collecting data through track records of activities through documentation. The informants in this research were students, teachers, and school principals. The research results show that in digital activities, students use their gadgets more to search for the latest information, play online games, and use them to search for learning materials. To protect themselves from the tendency to be involved in negative digital activities, students carry out prayer activities, recite, and listen to the Qur'an. Teachers also take on the role of helping students strengthen their Islamic resilience through digital activities and positive activities at school. This research finds the connection between digital resilience elements and increasing Islamic resilience for digital Muslim teenagers.

关键词： Islamic resilience Digital resilience Digital activities School Student

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Habitat Suitability Assessment of Three Passerine Birds Using Ensemble Learning with Diverse Models 12th

Habitat Suitability Assessment of Three Passerine Birds Usin...

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

作者： El Alaoui, Omar Idri, Ali Mohammed V Univ Rabat ENSIAS Rabat Morocco Mohammed VI Polytech Univ Benguerir Ben Guerir Morocco

ISBN: (纸本)9783031602207;9783031602214

The application of machine learning (ML) for predicting species habitat suitability has become increasingly popular. However, using a singleML algorithm may not provide optimal predictions for a given dataset, making it challenging to achieve high accuracy. Therefore, this study proposes a novel approach to assess habitat suitability of three redstarts species (P. Moussieri, P. Ochruros, and P. Phoenicurus) based on ensemble learning techniques. Initially, eight ML models namely MLP, SVM, KNN, Decision Trees (DT), Gradient Boosting Classifier (GB), Random Forest (RF), AdaBoost (AB), and Quadratic Discriminant Analysis (QDA) were trained individually. Then, based on the diversity of these base-learners, seven heterogeneous ensembles of two up to eight models were constructed for each species dataset. This study presents a thorough modeling framework for implementing heterogeneous ensembles and enhancing the overall comprehension of their performance in comparison to single models. The performance of this experiment was evaluated using: (1) six performance measures (AUC, sensitivity, specificity, accuracy, Kappa, and TSS), (2) Borda Count ranking method, and (3) Scott Knott statistical test. Results showed the potential of heterogeneous ensembles for predicting habitat suitability of the three redstarts birds. The proposed ensembles consistently outperformed single models across all datasets.

关键词： heterogenous ensemble learning species distribution modeling ecological niche models habitat suitability machine learning redstart birds

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Unveiling the Television News Puzzle: Tracking TV News Consumption Behaviors Amidst and Beyond the Covid-19 Pandemic 9th

Unveiling the Television News Puzzle: Tracking TV News Consu...

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

作者： Teng, Chan Eang Joo, Tang Mui TAR Univ Management & Technol Kuala Lumpur 53300 Malaysia

ISBN: (纸本)9789819745807;9789819745814

Concerns have been raised about the relevance of TV news with the fast growing of media technology. Increasing opportunities of choices have been held responsible for diverting viewers away from TV news. However, the Movement Control Order due to Covid-19 pandemic has paved a new life to TV news which was once claimed to be outdated and irrelevant as people started to select online platforms such as online news websites and social media as the main source of information. In view of the limited and insufficient research about TV news viewing where concerns are always placed on newspaper news, a survey was undertaken to determine the TV news viewing behavior in Sarawak during and after Covid-19 pandemic. A total of 306 respondents was collected through the use of snowball sampling from Central, Southern and Northern Sarawak. Despite bearing a paradox, the findings offer a paradigm shift to the previous research, as it indicates that watching TV news is still important to get the latest information. TV news via other devices only intensifies the shift of forms but not the content of the news. The content of the TV news is still the major consideration to stay engaged with the viewers. Result shows not much changes of the patterns of use of TV news during and after the Covid-19 pandemic. This implies the persistent importance and relevance of TV news in the daily life of people living in Sarawak. Producing quality content which suits the needs of the viewers is the only pathway to sustain the TV news.

关键词： TV news Uses and gratification theory Sarawak

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A WSN and IoT-Based Wire Consumption Monitoring System for Mobile Welding Machines 16th

A WSN and IoT-Based Wire Consumption Monitoring System for M...

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Mirani, Akseer Ali Awasthi, Anshul O'Mahony, Niall Walsh, Joseph Munster Technol Univ IMaR Res Ctr Tralee V92 CX88 Ireland CONFIRM Res Ctr Unit Pk Point 2 Dublin Rd Limerick V94 C928 Ireland

ISBN: (纸本)9783031775703;9783031775710

The convergence of Wireless Sensor networks (WSN) and the Internet of Things (IoT) technology in industrial applications brings remarkable innovations in the Industry 4.0 domain, resulting in improved industrial processes with better efficiency and productivity. This technological integration enables the remote monitoring and controlling of mobile industrial assets, and the welding machine is one asset that benefits from this technology. In the contemporary world, the Metal Inert Gas (MIG) welding process is one of the standard techniques employed to join metal pieces in industries by utilizing consumable wire, resulting in satisfactory welding outcomes. However, modern industrial systems using this technique lack the ability to monitor wire consumption, which can help track machines' operational activities and manage the supply chain process. In this project, we design, develop, and implement a WSN and IoT-based system to monitor the wire consumption of a mobile welding machine on an indoor factory floor using edge and cloud user interfaces. In this article, we first discuss each component's hardware and software development in the proposed layered architecture, followed by the results obtained from our research during the evaluation and implementation phases. Finally, we conclude our research by identifying limitations and possible directions for future work.

关键词： Welding Wire Welding Process Wireless Sensor Neworks Internet of Things Industry 4.0 Edge User Interface

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ONOS SDN Framework: Assessing the Impact of Single and Multi-Controller Architectures on Network Efficiency 8th

ONOS SDN Framework: Assessing the Impact of Single and Multi...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Abraham, Adarsh Liju Hrishikesh, B. H. Atehar, Md Taseen Hegde, Bhagyashree Narayan Giri, Animesh PES Univ Bengaluru 560100 India

ISBN: (纸本)9789819713226;9789819713233

Software-Defined Networking (SDN) has transformed the computer network management by decoupling the control plane from the data plane, granting immense flexibility, and programmability. Within the SDN world, the Open Network Operating System (ONOS) controller and the Mininet emulator have emerged as pivotal tools. This research paper provides a comprehensive comparative analysis of single-controller and multi-controller architectures within the specific context of ONOS and Mininet, aiming to explore their respective strengths and weaknesses. Single-controller configurations centralize control, offering a simplified network management perspective, while multi-controller setups distribute control across multiple nodes, potentially enhancing scalability and fault tolerance. Our analysis comprises diverse performance metrics, including latency, throughput, and scalability, in addition to considerations such as fault tolerance, load balancing, and the complexity of management and configuration. By presenting the observed evidence derived from experimental setups and real-world use cases, this research paper offers valuable guidance to network administrators, engineers, and researchers with the decision of selecting the most suitable architectural approach for SDN deployments utilizing ONOS and Mininet. Moreover, it provides insights into the current state of SDN technology and a forward-looking perspective on potential advancements and challenges within this dynamic field of technology.

关键词： SDN ONOS Mininet Docker Atomix

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Social Marketing Importance for the Sustainability of Third Sector Organizations 12th

Social Marketing Importance for the Sustainability of Third ...

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

作者： Fonseca, Susana M. S. R. Duarte, Filipe A. P. Carvalho, Ana Branca Guia, Ana Madeira, Maria Jose Machado, Geisa Polytech Inst Viseu CI&DEI Viseu Portugal UBI Univ Beira Interior NECE Res Ctr Covilha Portugal Polytech Inst Viseu CISeD Viseu Portugal Polytech Inst Viseu CERNAS Viseu Portugal Polytech Inst Viseu Viseu Portugal

ISBN: (纸本)9783031603273;9783031603280

Currently, there is an increasing need for us to reinvent ourselves, to find solutions that allow us to respond to and address the needs of organizations, especially those in the third sector that do not have profit as their fundamental premise. However, this does not mean that they do not need to be sustainable. Therefore, we should consider managing these organizations in a more professional manner. Marketing, as a management tool, allows the development of strategies to achieve proposed objectives and improve the organization's image, attracting potential clients and thus promoting increased sales force or service diffusion. It is important to integrate this tool into the daily activities of organizations. Social marketing aims to be a strategy that aligns the promotion of social causes with the values and principles advocated by organizations, benefiting both the organization and the cause. In addition to marketing, fundraising actions are necessary to promote the organization in society, taking it outside and thereby increasing donations. This study seeks to understand what is meant by socialmarketing, fundraising, and to assess the receptivity within the population, as well as the applicability of the actions. It also aims to identify the profile of donors to social causes, verifying whether social marketing and fundraising have implications for donations and the image of third-sector organizations. To achieve this objective, a non-probabilistic convenience sample was used, and a survey was developed, resulting in 110 completed surveys within the time frame defined between February 1 and May 31, 2022.

关键词： Social Marketing Fundraising Sustainability Third Sector Organizations

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Boruta Feature Selection Applied to Classification Algorithms for Intrusion Detection 9th

Boruta Feature Selection Applied to Classification Algorithm...

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

作者： Lifandali, Oumaima Chiba, Zouhair Abghour, Noreddine Hassan II Univ Casablanca Math & Comp Dept LIS Labs Fac Sci Ain Chock Casablanca Morocco

ISBN: (纸本)9789819732982;9789819732999

Today, cloud computing is a sure bet for companies that need to find modern, adaptable IT solutions to handle colossal amounts of business data, and can help companies improve efficiency and productivity, but on the other hand cloud computing is a constantly evolving technology, and attackers are constantly looking for new ways to compromise the security of data hosted in the cloud, for example, attackers can steal data hosted in the cloud by downloading or encrypting it, or even attackers can launch DDoS attacks against cloud infrastructures to make them inaccessible. In order to solve this type of problem, we propose the solution presented in this paper, intrusion detection in a cloud environment using amultiple classification algorithms, but to get more accurate results, we apply the step of selecting the relevant attributes of our dataset using the Boruta algorithm.

关键词： Cloud computing Boruta Classification IDS

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Boosting Customer Retention in Pharmaceutical Retail: A Predictive Approach Based on Machine Learning Models

Boosting Customer Retention in Pharmaceutical Retail: A Pred...

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Computing Conference

作者： Espinoza-Vega, Angel Roa, Henry N. Pontificia Univ Catolica Ecuador Fac Ingn Av 12 Octubre 1076 & Vicente Ramon Roca Quito Ecuador

ISBN: (纸本)9783031622793;9783031622779;9783031622762

Prediction models have acquired significant importance in business decision-making by allowing the use of data to generate strategic information. This study focuses on creating and evaluating a predictive model to identify possible customer abandonment in a pharmaceutical retail company to promote retention strategies. The approach is based on applying the Cross-Industry Standard Process for Data Mining (CRISP-DM) method and using Python as the primary data science tool. Three classification algorithms were considered to predict customer abandonment: neural networks, decision trees, and logistic regression. These algorithms were trained and evaluated using historical data from a pharmaceutical company. After an exhaustive analysis of the results, we concluded that the neural network model proves the most appropriate, reaching an impressive accuracy of 0.99 in the classification. The implementation of this model will allow the pharmaceutical retail company to identify in advance the customers with the highest risk of abandoning their services. This identification enables the marketing team to implement personalized and timely retention strategies, thus reducing the churn rate and improving the overall efficiency and effectiveness of the organization.

关键词： Data science Machine learning Classification models

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