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Detecting Web Tracking at the Network Layer 1

引用

38th International Conference on information Security and Privacy Protection (SEC)

作者： Wittig, Maximilian Kesdogan, Dogan Univ Regensburg Regensburg Germany

ISBN: (数字)9783031563263

ISBN: (纸本)9783031563287;9783031563263;9783031563256

Third-party tracking allows companies to identify users and track their online activity across different websites or digital services. This paper presents a first experimental study to detect advertisements and tracker by inspecting fully encrypted network transactions at the TCP/IP network level associated with a website. The first results are encouraging and motivate to extend this first proof-of-concept study even further in the future. A classical application area in the future would be the use in areas where communication can only be accessed on encrypted TCP/IP level (keyword secure IoT environments) or the presented approach is used simply to enable a classical extension of the portfolio for tracker detection.

关键词： Online tracking Network Traffic Classification Privacy

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WEEE Flow for Magnets 43rd

WEEE Flow for Magnets

引用

43rd ifip WG 5.7 International Conference on advances in Production Management Systems (APMS)

作者： Bitsis, Kyriakos Spanos, Alexandros Kaparis, Konstantinos Zois, Georgios Univ Macedonia Dept Business Adm Quantitat Methods & Decis Anal Lab Thessaloniki 54636 Greece Athens Univ Econ & Business Dept Management Sci & Technol ELTRUN Res Lab Athens 10434 Greece

ISBN: (纸本)9783031716249;9783031716225;9783031716218

The recovery of Waste from Electrical and Electronic Equipment (WEEE) poses a significant challenge in the realm of solid waste management. With the global urgency to develop innovative disposal methods for WEEE, the creation of value chains that facilitate the recovery of valuable secondary raw materials is crucial. This paper explores a value network formulated specifically for the recovery and reuse of magnets from WEEE. To this direction, we introduce a holistic Mixed Integer Linear Programming (MILP) model, capable to optimise the material flows and the total cost incurred within the value network. Interestingly, our model integrates the proposed policies and directives of the European Commission (EC), aiming to devise a strategy that efficiently blends secondary and virgin magnetic materials to minimize total energy costs. We validate our modeling approach through a set of computational results, applying sensitivity analysis to assess the robustness of the proposed solutions under specific fluctuations in the energy cost. We conclude with the introduction of a two-stage stochastic model that extends the deterministic framework of the MILP, offering broader applicability and resilience in planning.

关键词： WEEE Permanent magnets Mixed Integer Linear Programming Network flow Circularity

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Radiation Tolerant 14T SRAM Cell for Avionics Applications 31st

Radiation Tolerant 14T SRAM Cell for Avionics Applications

引用

31st International Conference on Very Large Scale Integration

作者： Ahmed, Sagheer Ambulkar, Jayesh Mondal, Debabrata Shah, Ambika Prasad Indian Inst Technol Jammu Dept Elect Engn IC ResQ Lab Jammu 181221 Jammu & Kashmir India

ISBN: (纸本)9783031709494;9783031709470;9783031709463

The impact of high-energy particles in space like cosmic rays and alpha particles flips the stored data in an SRAM cell. This chapter proposes a highly reliable soft error immune with enhanced critical charge 14T (SIC14T) SRAM cell that is radiation-hardened by design and has an increased critical charge that can withstand both single-event upsets (SEU) and single-event multi-node upsets (SEMNU). We compare the performance of the proposed cell with that of other considered SRAM cells, such as the SRRD12T, RSP14T, SEA14T, and 6T SRAM cell which were simulated in 45-nm CMOS technology in Cadence Virtuoso with a supply voltage of 1V and 27 degrees C operating temperature. Both SEU and SEMNU caused at the storage node of SIC14T are successfully recovered. The proposed SRAM cell has 1.02x, 0.6x, 0.72x, and 4.64x better write stability, read access time, leakage power, and critical charge than the SRRD12T with 1.68x area overhead. We also investigated the effect of supply voltage and temperature variations on SRAM stability. For the process variations analysis, we performed 2000 Monte Carlo simulations for the leakage power dissipation for all the considered circuits.

关键词： RHBD SRAM SEU SEMNU soft-error Static noise margin

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Lenses on Data: Toward an Application Perspective on Data in Manufacturing 43rd

Lenses on Data: Toward an Application Perspective on Data in...

引用

43rd ifip WG 5.7 International Conference on advances in Production Management Systems (APMS)

作者： Albers, Alexander Netland, Torbjorn Swiss Fed Inst Technol Weinbergstr 56-58 CH-8092 Zurich Switzerland

ISBN: (纸本)9783031716355;9783031716331;9783031716324

Data is becoming increasingly important in manufacturing, enabling visions like cyber-physical production systems and digital twins. However, companies still struggle to effectively leverage data to drive process improvements and productivity gains. One reason is that there are many implicit assumptions and perspectives on what data fundamentally represents. This paper explores five distinct "lenses" through which data can be viewed, drawing from the fields of information theory, information systems, accounting, management theory, and economics. While each lens offers valuable insights, we argue that manufacturing requires a more application-oriented understanding of data that accounts for the socio-technical nature of factories. We discuss six key attributes of data from a manufacturing perspective, including cost, coverage, fidelity, timeliness, accuracy, and accessibility. We argue that rather than pursuing an all-encompassing digital replica, the focus of manufacturers should be on collecting just enough relevant data to enable specific manufacturing applications while prioritizing coverage of the entire shop floor.

关键词： Business Analytics Knowledge Management Digital Twin & Industrial Metaverse

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Assessing Trustworthy Artificial Intelligence of Voice-Enabled Intelligent Assistants for the Operator 5.0 43rd

Assessing Trustworthy Artificial Intelligence of Voice-Enabl...

引用

43rd ifip WG 5.7 International Conference on advances in Production Management Systems (APMS)

作者： Bousdekis, Alexandros Mentzas, Gregoris Apostolou, Dimitris Wellsandt, Stefan Natl Tech Univ Athens NTUA Inst Commun & Comp Syst ICCS Informat Management Unit IMU Athens Greece Univ Piraeus Dept Informat Piraeus Greece Univ Bremen BIBA Bremer Inst Prod & Logist GmbH Bremen Germany

ISBN: (纸本)9783031658969;9783031658945;9783031658938

The concept of Trustworthy Artificial Intelligence (TAI) focuses on the establishment of trust in AI systems' development, deployment, and use. In this realm, the European Commission (EC) developed the Assessment List for Trustworthy Artificial Intelligence (ALTAI) in order to enable the assessment of trustworthiness in the AI systems under development. Since this is an emerging topic, there is little evidence on how to apply ALTAI. In this paper, we present the application of ALTAI on a Digital Intelligent Assistant (DIA) for manufacturing. In this way, we aim at contributing to the enrichment of ALTAI applications and to the drawing of remarks regarding its applicability to diverse domains. We also discuss our responses to the ALTAI questionnaire, and present the score and the recommendations derived from the ALTAI web application.

关键词： Trustworthy AI voice assistant AI ethics Assessment List for Trustworthy Artificial Intelligence ALTAI Industry 5.0

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Open Data Framework for Energy Management and ISO Certification in Smart Manufacturing Systems 43rd

Open Data Framework for Energy Management and ISO Certificat...

引用

43rd ifip WG 5.7 International Conference on advances in Production Management Systems (APMS)

作者： Khare, Samartha Katyarmal, Om Kumaraguru, Senthilkumaran Indian Inst Informat Technol Design & Mfg Kanchee Dept Mech Engn Chennai 600127 Tamil Nadu India

ISBN: (纸本)9783031716393;9783031716379;9783031716362

Since published in 2011, ISO50001 has become the fastest-growing ISO management standard. However, its implementation and integration within the organisation have been fuzzy and overlooked ever since. This research literature aims to understand the current implementation of ISO 50001, its benefits and improvements, gaps in its integration, drawbacks, and challenges. This paper also then presents a methodology that allows the implementation of an energy management system following the ISO 50001 standard by suggesting an open data framework that layouts a detailed plan for shortlisting the most relevant and goal-oriented energy performance indicators (EnPIs) using multi-criteria decision-making technique (MCDM) and an information model to establish relationships between EnPIs and their data entities. Next, an architecture that provides a road map for the effective implementation of ISO 50001 is presented. This architecture identifies elements of the open data framework for processes like data collection, analysis, normalisation, and insightful visualisation. This architecture presented will be helpful in managing performance metrics and enabling organisations to manage energy performance using an open data approach.

关键词： ISO 50001 Energy Performance Indicator (EnPI) Energy Management System (ENMS) Data Analysis

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Upcycling of Food Waste Through Bioconversion by Insect Larvae: Conceptual Model and Research Agenda for a Circular Food Supply Chain 43rd

Upcycling of Food Waste Through Bioconversion by Insect Larv...

引用

43rd ifip WG 5.7 International Conference on advances in Production Management Systems (APMS)

作者： Romsdal, Anita Dreyer, Heidi Carin Bakker, Steffen J. S. Carvajal, Ana NTNU N-7491 Trondheim Norway SINTEF Ocean POB 4760 N-7465 Trondheim Norway

ISBN: (纸本)9783031716249;9783031716225;9783031716218

The transition towards a circular economy in the food sector is crucial to meet society's sustainability challenges. One promising approach is upcycling of food loss and waste sidestreams (FLWS) which can be converted into raw materials for another cycle. This paper focuses on the circular supply chain involved in upcycling of FLWS through bioconversion by insect larvae. Using a two-step upcycling strategy, FLWS is converted into substrates for insect larvae. The larvae are subsequently processed into protein meal that is used as ingredients in livestock feed, thus creating a circular supply chain. The paper explores the consequences this approach has for the development of the circular food supply chain and reverse logistics. The study provides an overview of the current state of knowledge, presents a case study from a poultry supply chain, and synthesizes key concepts and insights into a conceptual logistics model. The model outlines the actors, processes, and material flows involved in the circular supply chain. A research agenda proposes topics to guide future studies towards full-scale realization of the concept, highlighting both structural and planning issues. Topics include development of suitable systems for reverse material flows and sorting and storage solutions, determination of how to integrate FLWS and circular materials into existing production capacities, and planning issues related to balancing supply and demand, particularly related to the predictability of volumes, timing, and yield. The paper concludes by highlighting the theoretical contributions and practical implications of the study.

关键词： Food Upcycling Reverse logistics Circular supply chain

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Detecting Illicit Data Leaks on Android Smartphones Using an Artificial Intelligence Models 1

引用

20th International Conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Nikiema, Serge Lionel Sabane, Aminata Kabore, Abdoul-Kader Kafando, Rodrique Bissyande, Tegawende F. Ctr Excellence IA Dev CITADEL Ouagadougou Burkina Faso Univ Virtuelle Burkina Faso Ouagadougou Burkina Faso Univ Joseph Ki Zerbo UJKZ Ouagadougou Burkina Faso

ISBN: (数字)9783031632150

ISBN: (纸本)9783031632174;9783031632150;9783031632143

In today's digital landscape, hackers and espionage agents are increasingly targeting Android, the world's most prevalent mobile operating system. We introduce DeepDetector - a system based on artificial intelligence to recognize data thefts in Android. This model is based upon a large dataset comprising of clean and tainted network traffic trained using a Random Forest Classifier. DeepDetector scores high in two main areas as it achieves 82.9% accuracy for connection anomaly detection and 89.9% recall in connection anomaly detection whereas it gets 78.9% accuracy and 81.6 recall in terms of detection of under the system mounted with Raspberry Pi, automatic data collection, preparing of a dataset, training and testing of the model, as well as leak detection are ensured. In this regard, DeepDetector offers a viable way of enhancing Android user security.

关键词： Android mobile security data leak machine learning anomaly detection

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PTSD Detection Using Physiological Markers 6th

PTSD Detection Using Physiological Markers

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6th ifip WG 5.5 International Cross-Domain Conference on Internet of Things

作者： Rachakonda, Laavanya Bipin, K. C. Univ North Carolina Wilmington Dept Comp Sci Wilmington NC 28403 USA

ISBN: (纸本)9783031458842;9783031458828;9783031458811

This is an extended abstract for a Research Demo Session based on our published work [1]. PTSD has been a major problem in our society and much research has been done along the line to predict and diagnose PTSD. Our method helps to predict PTSD in its early stage with the help of physiological markers which combined with prior information about the patient like PTSD history, exposure to trauma, substance abuse disorder and other information helps to create a risk score with more accuracy. Due to the lack of a public dataset on this domain, we used different uni variate relationships of physiological markers with PTSD to create a multi-modal model using a slight modification of the naive Bayes algorithm. Implementation of a micro-controller along with the cloud IoT platform and a mobile app is created to demo the possibility of the system which helps healthcare providers and users to timely track and monitor PTSD risks with background information and priors accurately.

关键词： Internet of Things (IoT) Smart Healthcare PTSD Detection Post-Traumatic Stress Disorder Probability of PTSD Naive Bayes Machine Learning

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A Comparison of AI Methods for Groundwater Level Prediction in Burkina Faso 20th

A Comparison of AI Methods for Groundwater Level Prediction ...

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20th International Conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Bonkoungou, Abdoul Aziz Zio, Souleymane Sabane, Aminata Kafando, Rodrique Kabore, Abdoul Kader Bissyande, Tegawende F. Univ Virtuelle Burkina Faso Ctr Excellence CITADEL Ouagadougou Burkina Faso Ecole Polytech Ouagadougou Inst Genie Informat & Telecoms Ouagadougou Burkina Faso Univ Joseph KI ZERBO Dept Informat UFR SEA Ouagadougou Burkina Faso

ISBN: (纸本)9783031632211;9783031632198;9783031632181

Groundwater serves as a valuable resource to supplement surface water, and its extensive utilization underscores the importance of precise groundwater level predictions. Burkina Faso confronts a critical challenge in the domain of sustainable groundwater resource management, underscoring the need for accurate forecasts of groundwater levels to enable efficient resource allocation and ensure long-term sustainability. This study introduces a robust framework that uses state-of-the-art Artificial Intelligence methodologies to predict groundwater levels across six strategically located piezometers in Burkina Faso's Central Plateau region. The dataset combines piezometric Measurements, Rainfall, and vegetation indices that serve as a multifaceted feature space for model training. We systematically evaluated the performance of three specific machine learning models-NeuralProphet, XGBoost, and Long Short-Term Memory to determine which machine learning model offers the most robust predictions, enabling more effective and sustainable groundwater management. We observe that the XGBoost model outperforms its counterparts in terms of predictive accuracy. The findings of this study offer critical insights into the temporal variations in groundwater levels, thereby contributing to the formulation of more efficient water resource management strategies and facilitating data-driven decision-making processes in the target region.

关键词： Groundwater level prediction XGBoost LSTM NeuralProphet Satellite Time-Series Imagery

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