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ESG in Advertising Narratives: Case Analysis of Golden Lion Winning Campaigns at Cannes 2022 1

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

作者： de Araujo, Daniel Ladeira Garcia, Jorge Esparteiro Serra da Fonseca, Manuel Jose Andrade, Jose Gabriel Inst Super Ciencias Empresariais & Turismo Porto Portugal Inst Politecn Viana do Castelo Viana Do Castelo Portugal Inst Politecn Viana do Castelo ADiT LAB Viana Do Castelo Portugal INESC TEC Porto Portugal UNIAG Unidade Invest Aplicada Gestao Viana Do Castelo Portugal Univ Minho Campus Gualtar P-4710057 Braga Portugal CECS Ctr Estudos Comunicacao & Soc Braga Portugal

ISBN: (数字)9783031456510

ISBN: (纸本)9783031456503;9783031456510

The key question that will be addressed in this research is whether advertising narratives feature initiatives within the ESG - Environment, Social and Governance - framework. Investors increasingly value companies that promote sustainable impact actions, something that the promoting companies report in detail in their ESG reports directed at corporate stakeholders. To identify and understand how brands present such initiatives to the consumer market, we checked campaigns awarded with the Golden Lion of Advertising at Cannes 2022. The methodological cut involved three award categories, being analyzed 19 campaigns from 10 different countries. Besides the bibliographical survey on discourse analysis and content analysis, this exploratory qualitative and quantitative research had the inductive method to direct the individual analysis of each campaign. As a result, we identified that more than half of the campaigns address aspects related to ESG initiatives, being the social scope addressed by most of the campaigns. A result that provokes new hypotheses and possibilities of research continuity.

关键词： ESG advertising narrative sustainability social media outdoor

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CorSub: Corpus-Based Semantic Topic Matching for Subscriptions 9th

CorSub: Corpus-Based Semantic Topic Matching for Subscriptio...

引用

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

作者： Piller, Tobias Christian Kestner, Christian Khelil, Abdelmajid Landshut Univ Inst Data & Proc Sci Lurzenhof 1 D-84036 Landshut Germany

ISBN: (纸本)9789819735556;9789819735563

The number of smart devices is growing exponentially in both industrial and private environments. The Message Queuing Telemetry Transport (MQTT) is an established messaging protocol in the Internet of Things. However, the increased volume of communication also leads to larger amounts of data that need to be processed. In this work we propose CorSub, a novel approach as a future solution for designing intelligent infrastructure for information and communication, that combines word and sentence embeddings with a specific preprocessing to enable semantic subscription of MQTT Topics. The performance evaluation shows that CorSub's time complexity is O(n log n) and its average accuracy of 94%, which demonstrates the suitability of CorSub for a timely and accurate flexible subscriptions in MQTT.

关键词： Internet of Things (IoT) Message Queuing Telemetry Transport (MQTT) Publish-subscribe systems Semantic subscriptions Topic matching Corpus-based semantic similarity

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SmartEval: A New Hybrid Quality Assessment System (Online/Paper-and-Pencil) 4th

SmartEval: A New Hybrid Quality Assessment System (Online/Pa...

引用

4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Lahbi, Zakaria Hamdi, Ayoub Sabbane, Mohamed Moulay Ismail Univ Fac Sci Modeling Anal & Control Syst Lab Meknes Morocco

ISBN: (纸本)9783031686528;9783031686535

This study is carried out within the project objectives of CORETEV in collaboration with ANEAQ and four Moroccan universities. The project is geared towards integrating technologies in teaching and learning assessment. For this reason, a hybrid platform, namely SmartEval, has been put together, which combines the two modalities of the evaluation: online and paper-based. Using the CGQTSMethodology by J-L Gilles, this platform wants to develop a modern way of evaluation and tackle exammanagement issues, especially post-COVID-19. The first aim of this platform is to increase quality learning and teaching outcomes in Moroccan universities. The integration of ICT with CGQTS shows a strategic and innovative movement in tackling the contemporary education challenges in Morocco.

关键词： COVID-19 CORETEV QUALITY Online education Assessment CGQTS Phenomenology

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Combined ECG Analysis Approach Based on Detection of Deviation from the Personal or Population Norm Using Wearable Devices 9th

Combined ECG Analysis Approach Based on Detection of Deviati...

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

作者： Malanin, Vladyslav Chaikovsky, Illya NAS Ukraine VM Glushkov Inst Cybernet Kyiv Ukraine

ISBN: (纸本)9789819732883;9789819732890

This paper presents a strategy for developing a real-time electrocardiogram (ECG) monitoring and analysis system using wearable devices, emphasizing personalization and continuous cardiac health management. The proposed methodology introduces a two-stage approach: generating a personal ECG norm model and establishing a robust monitoring architecture. The process involves systematic ECG data collection, pre-processing to eliminate noise, training a personalized model, and periodically updating this model with new data to establish a baseline for individual cardiac activity. The conceptual architecture assures consistent ECG monitoring, immediate data processing, and comprehensive analysis to detect any abnormalities in the ECG data, thereby providing timely and reliable ECG assessments. Expected outcomes include accurate detection of cardiac events, immediate intervention capabilities, and continuous monitoring. The implementation presents several challenges such as maintaining data quality and model accuracy, ensuring user compliance, safe-guarding data privacy, and navigating the technical limitations of wearable devices. Solutions like employing advanced and adaptive algorithms, providing user training, employing robust data encryption methods, and developing optimized algorithms are discussed to mitigate these challenges. The paper concludes by identifying future research and development directions, including improving model efficacy, enhancing user interaction, bolstering data security, and refining algorithms, positioning the personalized, real-time ECG monitoring system as a crucial element in individualized healthcare and management of cardiac health.

关键词： Electrocardiogram (ECG) Artificial intelligence (AI) Wearable devices Healthcare technology Cardiac health management Signal processing Population norm Real-time monitoring Automated ECG analysis

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COV19Sim Morocco: A Web-Based Application for Simulating COVID-19 Dynamics 4th

COV19Sim Morocco: A Web-Based Application for Simulating COV...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Jdid, Touria Benbrahim, Mohammed Kabbaj, Mohammed Nabil Sidi Mohamed Ben Abdellah Univ Fac Sci LIMAS Fes Morocco

ISBN: (纸本)9783031686740;9783031686757

Infectious diseases present significant threats to humanity, with the COVID-19 pandemic wreaking havoc globally. Even though there are considerable educational resources to learn the fundamentals of epidemic modeling, a notable disparity exists between the relatively simple models employed for theoretical exposition and those utilized in practical applications to model COVID-19 dynamics. Comprehending these models demands substantial prerequisite knowledge and can be daunting for individuals new to epidemiological modeling and governing bodies. This study introduces COV19Sim Morocco, a web application designed to simulate COVID-19 dynamics using compartmental models. Through an interactive and user-friendly interface, the application presents a versatile tool for exploring COVID-19 data, simulating the spread of the virus, fitting models to available data, and generating predictions.

关键词： Epidemiology COVID-19 Compartmental models R shiny application Software

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Fortifying Machine Learning-Powered Intrusion Detection: A Defense Strategy Against Adversarial Black-Box Attacks 9th

Fortifying Machine Learning-Powered Intrusion Detection: A D...

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

作者： Pujari, Medha Sun, Weiqing Western New England Univ Springfield MA 01119 USA Univ Toledo Toledo OH 43606 USA

ISBN: (纸本)9789819732883;9789819732890

Intrusion detection systems (IDSs) powered by machine learning (ML) techniques have greatly advanced in detecting security threats. However, with advancements come new challenges and vulnerabilities. As most of the ML-based IDSs prioritize performance, their robustness and security are in question, which becomes an advantage for bad actors to exploit the vulnerabilities and target IDS models. It is a serious concern in the cybersecurity domain. This paper emphasizes the impact of adversarial machine learning (AML)-a well-known vulnerability of ML techniques-and proposes a defense mechanism to improve the robustness of ML-powered IDSs to adversarial black-box attacks. The primary motive of this research is to defend the defenders of cybersecurity, in particular, the IDSs. The paper provides a background of the elements involved in the experimentation, presents the methodology followed for the experiments, and analyzes the evaluation results obtained. Further, it discusses the directions and possibilities for future endeavors.

关键词： Intrusion detection systems Machine learning Adversarial machine learning Black-box attacks Defense mechanism Research dataset

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Utilizing CFD Technology in the Design of the Combustion Chamber for the Hydrogen-Powered Hybrid Energy System

Utilizing CFD Technology in the Design of the Combustion Cha...

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International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering - Synergetic Engineering (ICTM)

作者： Shmarkov, Oleksandr Serbin, Serhiy Bondarenko, Mykola Admiral Makarov Natl Univ Shipbldg UA-54025 Mykolaiv Ukraine

ISBN: (纸本)9783031614149;9783031614156

Addressing issues related to the enhancement of existing thermal engines and combustion processes in their combustion chambers (CC), as well as deepening our understanding of potential challenges in the improvement of gas turbine installations, opens new horizons in modern energy. Hybrid gas-steam power systems utilizing hydrogen gases and pure hydrogen offer a wide range of possibilities and potential technical solutions related to decarbonization. The paper presents the results of using Computational Fluid Dynamics (CFD) technology in the design of the combustion chamber of a hybrid gas-steam power plant with a modular construction that combines two gas turbine engines: a) utilizing the heat of exhaust gases, and b) contact type with steam injection into the combustion chamber. The main characteristics of the gas turbine combustion chamber were determined when implementing steam injection and operating the installation on pure hydrogen. Parameters of the tubular-ring combustion chamber were studied, as well as the influence of separate steam injection into different zones of the chamber to ensure its stable operation without the occurrence of flame blowout zones. Using modern computer design technologies, the impact of the distribution of environmental and energy steam on the ecological performance of a prospective hybrid gas-steam power plant has been investigated.

关键词： CFD Technology Hybrid Energy System Combustion Chamber

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Understanding the Defence of Operational Technology (OT) systems: A Comparison of Lockheed Martin's Cyber Kill Chain, MITRE ATT&CK Framework, and Diamond Model

Understanding the Defence of Operational Technology (OT) Sys...

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2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Kareem, Kamor Naik, Nitin Jenkins, Paul Grace, Paul Song, Jingping Meritgate Consulting Birmingham W Midlands England Aston Univ Sch Comp Sci & Digital Technol Birmingham W Midlands England Cardiff Metropolitan Univ Cardiff Sch Technol Cardiff Wales Northeastern Univ Software Coll Shenyang Peoples R China

ISBN: (纸本)9783031744426;9783031744433

As organisations worldwide strive to optimise processes and digitise systems, Operational Technologies (OT) are increasingly being integrated with Information Technologies (IT). Consequently, this complex amalgamation is challenging cybersecurity professionals to understand and analyse both the attack surfaces and attack vectors that threat actors could potentially exploit. Cybersecurity professionals have been driven to explore different attack models to understand and analyse various cyberattacks and their attack vectors. There are several attack models that have already been developed and are being used in the analysis of different cyberattacks and their mitigations. Each of these attack models has some specific characteristics, strengths and limitations. It is therefore crucial to study the use of the most common attack models for operational technologies in order to comprehend their effectiveness for analysing cyberattacks on OT systems. This paper will analyse the features, strengths, and limitations of three widely recognised attack models: Lockheed Martin's Cyber Kill Chain, MITRE ATT&CK Framework and Diamond Model for OT systems. It conducts a comparative analysis of these three attack models to provide a complete evaluation of the most suitable model for OT systems.

关键词： Operational Technology OT Cyber Attack Model Lockheed Martin's Cyber Kill Chain MITRE ATT&CK Framework Diamond Model

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Resource Productivity Taught Well: How Learning Factories Can Support Knowledge Transfer on a Multifaceted Subject 14th

Resource Productivity Taught Well: How Learning Factories Ca...

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14th International Conference on Learning Factories (CLF)

作者： Rudele, Kai Hammer, Markus Wolf, Matthias Graz Univ Technol Inst Innovat & Ind Management Kopernikusgasse 24 A-8010 Graz Austria McKinsey & Co Inc Schottenring 19 A-1010 Vienna Austria

ISBN: (纸本)9783031654107;9783031654114

Resource productive operations are about more than just reducing waste and improving energy efficiency;they can create long-term advantages in costs, risk reduction, and innovation resulting in financial benefits and decreased environmental impact of industrial processes. Designed as an analytics-supported operations management approach that uses performance metrics, they assist decision making and can lead to operational excellence. We demonstrate how experiences from the process industry were incorporated into a new learning module of the LEAD Factory at Graz University of Technology. By introducing the key concepts of 'profit per hour' and 'theoretical limit', participants are sensitized to 'variable cost opportunities' and can experience the complexity of multi-parameter systems and trade-offs between process variables. To master the complexity, a KPI tree and bubble diagram are developed during the learning module to identify patterns and interrelations of settings that influence profitability.

关键词： resource productive operations process control operations management multi-parameter systems learning factory

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Enhanced MSME Support Allocation with Integrated K-means and Tukey's Outlier Detection

Enhanced MSME Support Allocation with Integrated K-means and...

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Intelligent systems Conference

作者： Hartomo, Kristoko Dwi Arthur, Christian Satya Wacana Christian Univ Salatiga Indonesia Brawijaya Univ Malang Indonesia

ISBN: (纸本)9783031663284;9783031663291

The pandemic caused by the Covid-19 virus has resulted in Indonesia experiencing a slowdown in economic growth. MSMEs (Micro, Small and Medium Enterprises) as the majority contributor to the National GDP and absorb more than 117 million workers have not been spared the negative impacts of the pandemic. This study addresses the challenge of misdirected governmental support to MSMEs (Micro, Small, and Medium Enterprises) in Indonesia during the COVID-19 pandemic, a period marked by significant economic downturns. Despite the government's efforts to bolster MSMEs through various incentives and subsidies, discrepancies in aid distribution were evident, with 414,612 non-targeted beneficiaries receiving funds. To enhance the precision of aid allocation, this research employs a novel approach by integrating the K-means clustering algorithm with Tukey's method for outlier removal. This methodology effectively segments Indonesian MSMEs into three distinct clusters based on annual sales, total assets, and workforce size, thereby facilitating more targeted support strategies. The clusters are prioritized for assistance, with Cluster 3 identified as the highest priority due to its lowest sales figures, followed by Cluster 2 and Cluster 1, based on their respective economic performances. The study's findings, underscored by a Silhouette Coefficient of 0.526, confirm the efficacy of this approach. Furthermore, it suggests specific sectors and regions for focused support, highlighting wholesale, retail trade, and repair services of cars and motorcycles in East Kalimantan as primary beneficiaries. This research contributes to the optimization of MSME support mechanisms during crises, offering a replicable model for targeted assistance based on empirical data analysis.

关键词： Clustering Economy Data mining K-means MSME

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