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TRIZ in Customer Experience Management - the Study of Current Research Problems 24th

TRIZ in Customer Experience Management - the Study of Curren...

引用

24th International TRIZ Future Conference

作者： Majchrzak, Joanna Ziomek, Joanna Poznan Univ Tech Plac M Sklodowskiej Curie 5 PL-60965 Poznan Poland

ISBN: (纸本)9783031759253;9783031759239;9783031759222

The issue addressed in this paper refers to the improvement of methods and tools for systematic innovation in the field of marketing management. The problem of Customer Experience (CE) and Customer Understanding in the area of new technologies in marketing of Big Data, Machine Learning, and Artificial Intelligence in considered. The main objective of this paper is to reflect the actual application of TRIZ in the problem-solving process related to new categories of marketing problems. The systematic review of the literature is conducted. The database of the publications, using the search terms related to Customer Experience and TRIZ and including sources of data such as Web of Science, is formulated. The bibliometric and content analysis of the selected subsets of most relevant publications is conducted. As the results, a set of problems raised in publications in which TRIZ is used in the area of the so-called customer driven quality management was identified. In the analyzed set of publications, TRIZ is integrated with tools supporting quality management, i.e., Failure Mode and Effect Analysis (FMEA), Quality Function Deployment (OFD), SERVQUAL, Kono Model, as well as Kansei engineering (KE) or Six Sigma and Lean Management concepts. The results of the research indicate that by integrating marketing elements included in quality management, it may be possible to solve current AI-based marketing management problems using specific TRIZ methods and tools.

关键词： Marketing Management Digital Marketing AI-based marketing management Customer Experience (CE) TRIZ OSTM Customer Driven Quality Management

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Research on Method of Flexible Mold Surface Formation Based on Point Cloud and Neural Network 24th

Research on Method of Flexible Mold Surface Formation Based ...

引用

24th International TRIZ Future Conference

作者： Li, Rongjian Zhang, Jiannan Zhang, Jianhui Wang, Zhongyou Guo, Xiangdong Hebei Univ Technol Sch Mech & Engn Tianjin Peoples R China Hebei Univ Technol Sch Artificial Intelligence Tianjin Peoples R China

ISBN: (纸本)9783031759253;9783031759239;9783031759222

Flexible molds, with their excellent adaptability and reconfigurability, can meet the production needs of curved products with varying models, shapes, and sizes flexibly. In the design process of flexible molds, accurately determining the position and quantity of surface formation points is crucial. Therefore, this study innovatively introduces the construction of a Flexible Mold Surface Formation Neural Network model based on point cloud and neural network technologies, specifically for the extraction and determination of surface formation points in the design of flexible molds. Based on the TRIZ theory, we utilized the tools of local idealization and technical contradiction resolution to analyze the function and architecture of the Flexible Mold Surface Formation Network. And we analyzed the characteristics of the point cloud that are pertinent to flexible molds. Next, for the processing of the raw point cloud data, we introduced a lower edge point screening module based on the Support Vector Machine (SVM) and a filtering module. We then incorporated the PointNet++ network and made improvements to it, including the addition of a surface formation feature information integration module and the enhancement of the point cloud sampling method, thereby establishing a comprehensive neural network model dedicated to the surface formation of flexible molds. Finally, experimental data indicate that the method we have developed offers high precision and effectiveness, providing a practical theoretical foundation for the critical step of determining surface formation points in the design of flexible molds.

关键词： Flexible Mold TRIZ Neural Network Point Cloud PointNet plus

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Multi-layered Model for Performance Evaluation of one M2M-Based IoT Solution 7th

Multi-layered Model for Performance Evaluation of one M2M-Ba...

引用

7th ifip WG 5.5 International Cross-Domain Conference on Internet of Things

作者： Medjhah, Samir Monteil, Thierry Peraldi-Frati, Marie-Agnes Liquori, Luigi Univ Paul Sabatier Univ Toulouse LAAS CNRS Toulouse France Univ Toulouse INSA IRIT Toulouse France Univ Cote dAzur Inria Nice France

ISBN: (纸本)9783031819025;9783031819001;9783031818998

In this paper we evaluate the impact of standards in terms of performance and their applicability in the field of IoT system design and deployment. We focus on the global IoT one M2M standard. Our objective is to evaluate a one M2M-based IoT solution regarding different relevant Key Performance Indicators. We propose a multi layered-model of an IoT standardized solution, able to tackle applicative, infrastructure and deployment aspects. Based on this model, we are able to globally evaluate and analyze, through simulation, the adequacy of a deployment with respect to the initial applicative constraints and the chosen one M2M standard implementation. In our case, the constraints are mix-critical coming from the e-Health remote monitoring of patient by their physician but also the management of the patient in case of vital emergency situation. By tuning the system configuration and parameters of the proposed applicative scenario, we evaluate, by simulation, the KPIs of a one M2M-based IoT solution by exploiting (1) the different features of the standard, (2) the capabilities of the underlying infrastructure, and (3) the performance of the oneM2M stacks used in the solution. The simulation and performance evaluation are based on two tools developed by the authors. One is a specific profiler for oneM2M open-source stack, whereas the simulation and performance evaluation is build on top of the OMNeT++ discrete event simulator.

关键词： ETSI oneM2M Consortium IoT Use Cases Performance Evaluation Meta-Modeling

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An Analytical Model for Sustainable Product Ideation Based on Main Parameter Values and Social Network Data 24th

An Analytical Model for Sustainable Product Ideation Based o...

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24th International TRIZ Future Conference

作者： Ghane, Mostafa Cavallucci, Denis Univ Kebangsaan Malaysia Bangi Malaysia M5 Solutions AI Selangor Malaysia INSA Strasbourg 24 Blvd Victoire F-67084 Strasbourg France

ISBN: (纸本)9783031759253;9783031759239;9783031759222

The Main Parameter of Value (MPV) is a vital factor in TRIZ' Trend of Engineering System Evolution (TESE), helping to understand what customers like in specific products. The Trend of S-Curve Evolution in TESE shows how the MPV changes over time, guiding decisions for innovating products. In the current industrial landscape, the surge in industrial revolution is reshaping consumer choices towards sustainable products. Manufacturers vie for market dominance, continually seeking insights into customers' preferences regarding MPVs for design forecasts and sustainable innovations. However, existing MPV analyses are primarily manual, lacking a computational model for predicting future MPVs. This study addresses this gap by proposing an AI-driven computational model for identifying potential MPVs. Utilizing the Python programming, the methodology incorporates Natural Language Processing (NLP) for feature extraction and Machine Learning algorithms, including Naive Bayes and Linear Regression Classifier to achieve accurate means of predicting and understanding MPVs. The anticipated outcome is an automated S-Curve analysis derived from AI-analyzed MPV data. This visual representation of evolving MPVs over time is expected to empower manufacturers with insights for strategic decision-making and innovation in sustainable product development, fostering a competitive edge in the market.

关键词： TRIZ Artificial Intelligence Main Parameter of Value

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Digital Twin-Based Security Orchestration, Automation and Response for IoT and CPS 7th

Digital Twin-Based Security Orchestration, Automation and Re...

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7th ifip WG 5.5 International Cross-Domain Conference on Internet of Things

作者： Nguyen, Phu H. Rauniyar, Ashish Niemi, Toni Valtteri SINTEF Trondheim Norway Univ Oslo Oslo Norway

ISBN: (纸本)9783031819025;9783031819001;9783031818998

The digitisation leveraging technologies in the Internet of Things (IoT) and Cyber-Physical Systems (CPS) has been largely adopted together with the Digital Twin (DT) paradigm. However, the distributed and heterogeneous nature of IoT or CPS poses significant challenges in safeguarding against diverse attack surfaces, including physical devices, network infrastructures, and third-party integration. Furthermore, the evolving security threats and potential cascading effects from cyber attacks add another layer of complexity to the security landscape. Therefore, in this paper, we propose a digital twin-based security orchestration automation and response framework, striving for the business continuity (SOAR4BC). Leveraging system contexts from the DT in combination with security intelligence from the security tools gives us a holistic context for SOAR, which has not been seen in the existing approaches. By subjecting tampered data and distributed denial of service (DDoS) detection to rigorous experimental evaluation, we substantiate the efficacy and reliability of the SOAR4BC framework in detecting and responding to security policy violations within simulated digital twin environments. This validation serves as a compelling proof of concept, highlighting the SOAR4BC framework's robustness in addressing cyber threats. Our work offers novel insights into the convergence of digital twin technology and cybersecurity, illuminating the unique challenges and opportunities inherent in DT-based IoT and CPS systems.

关键词： IoT CPS Security Digital Twin Security Orchestration SOAR Critical Infrastructures Machine Learning

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Development of a TRIZ-Based Design Methodology for Digital Transformation 24th

Development of a TRIZ-Based Design Methodology for Digital T...

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24th International TRIZ Future Conference

作者： Otsuka, Yuki Hasegawa, Hiroshi Shibaura Inst Technol 307 FukasakuMinuma Ku Saitama Japan

ISBN: (纸本)9783031759253;9783031759239;9783031759222

Since 2010s at business, digital transformation (DX) initiatives and digitalizing businesses have increased. The design of digital information systems is influenced by business and technological aspects and can have a considerable impact on the attractiveness of services. However, research on design science for DX or digitalizing business remains inadequate and not established. Meanwhile, the effectiveness of many methods established in the engineering field, including TRIZ that supports design and conceptual design, has been tested. The authors proposed "Creative and inventive Design Support System (CDSS)" in 2009 to support conceptual design in the engineering field based on TRIZ and suggested new methods "CDSSforDX" for applications in digital business and digital transformation (DX) in 2023. CDSSforDX is based on CDSS and has two additional processes, "strategic response" and "digital business strategy and DX strategy process," as the strategy. In this paper, we present CDSSforDX methods and show the evaluation results and examples of using this methodology.

关键词： Problem solving Digital transformation Digital business Conceptual design Storytelling

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Assessing Backdoor Risk in Deepfake Detection 20th

Assessing Backdoor Risk in Deepfake Detection

引用

20th ifip WG 11.9 International Conference on Digital Forensics

作者： Wang, Jiawen Li, Boquan Yu, Min Chow, Kam-Pui Jiang, Jianguo Du, Fuqiang Meng, Xiang Huang, Weiqing Chinese Acad Sci Beijing Peoples R China Harbin Engn Univ Harbin Peoples R China Singapore Management Univ Singapore Singapore Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9783031710278;9783031710254;9783031710247

Deepfake images and videos are spreading in cyberspace, threatening individuals and society. Although well-designed deep learning models have achieved satisfactory performance in detecting deepfakes, they face security risks. Compared with deep learning attacks on artificial intelligence systems, backdoor attacks on deepfake detectors have received limited attention. This chapter describes a backdoor risk assessment method for deepfake detectors. It highlights the vulnerabilities of deepfake detectors against backdoor attacks introduced by poisoning training data. Furthermore, it assesses the risk posed by these attacks on five benchmark deepfake detectors. The risk assessment results demonstrate that deepfake detectors are exposed to common but very harmful backdoor risks that must be mitigated.

关键词： Multimedia Forensics Deepfake Detection Backdoor Attack Risk Assessment

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The Evolving Landscape of TRIZ: A Generative AI-Powered Perspective 24th

The Evolving Landscape of TRIZ: A Generative AI-Powered Pers...

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24th International TRIZ Future Conference

作者： Pheunghua, Tanasak TRIZ Specialist (Level 4) Bangkok Thailand

ISBN: (纸本)9783031759215;9783031759192;9783031759185

The surge of Generative AI has revolutionized problem-solving, giving rise to innovative tools that unlock unprecedented solutions and cross-industry breakthroughs within the TRIZ methodology. This paper unveils five ground-breaking Generative AI- integrated tools designed to enhance innovation and problem-solving across diverse domains. 1. Mechanism Oriented Search (MOS): Identifies and analyzes specific problem mechanisms, abstracting them for cross-industry comparison, facilitating the discovery of innovative solutions by applying insights from one field to challenges in another. 2. Resource Innovator for Non-Engineering: Extends TRIZ to non-engineering fields, focusing on identifying and leveraging unique resources within domains like nursing, education, and communication, empowering users to uncover hidden potential. 3. TRIZ FOS-Market Explorer: Facilitates the discovery and analysis of adjacent market opportunities by abstracting the primary function of a product or service and identifying similar functions across various industries, revealing potential new markets. 4. Systematic Idea Generation: Employs detailed resource analysis and TRIZ principles to facilitate innovation within existing systems, categorizing resources and suggesting strategic modifications to components or processes. 5. Function Redirector: Fosters innovation by redirecting functions and resources towards achieving goals in novel ways, deconstructing primary functions into auxiliary functions to stimulate creative problem-solving. These tools collectively harness the power of Generative AI to revolutionize problem-solving and innovation across various sectors, offering structured analysis, imaginative recombination, and cross-disciplinary insights.

关键词： TRIZ GPT Generative AI Problem-solving Innovation Cross-industry Resource analysis

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Evaluating Cyber Security Risks and Mitigation Strategies for Smart Grids Based on Business Case Scenarios 18th

Evaluating Cyber Security Risks and Mitigation Strategies fo...

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18th International Conference on Critical Infrastructure Protection

作者： Abraham, Doney Yayilgan, Sule Abomhara, Mohamed Norwegian Univ Sci & Technol Gjovik Norway

ISBN: (纸本)9783031818905;9783031818882;9783031818875

The integration of smart grid technologies in energy infrastructures is a significant shift towards efficient, sustainable and reliable electricity management, but it also brings cyber security challenges to the forefront. This study delves into the cyber security vulnerabilities of key smart grid assets such as smart meters, advanced metering infrastructure systems and distributed energy resources such photovoltaic systems, virtual power plants and battery parks. A comprehensive threestep methodology is employed to identify attack vectors, analyze attack tactics and specify the appropriate mitigation strategies. The confidentiality, integrity and availability model and MITRE ATT&CK framework are employed to identify the four main attack vectors and specify the appropriate mitigation strategies based on established security principles. The results highlight the need to implement robust security measures to safeguard smart grid assets and offer strategic guidance for addressing the cyber security challenges. The study enriches the discourse on smart grid security by providing actionable insights for improving energy system reliability and resilience.

关键词： Smart Grids Business Cases Cyber Security Attack Vectors Risk Identification Attack Mitigation

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Detecting Control Injection Attacks Using Energy Data Anomalies in Computer Numerical Control Machining 18th

Detecting Control Injection Attacks Using Energy Data Anomal...

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18th International Conference on Critical Infrastructure Protection

作者： Kimmell, Jeffrey Orlyanchik, Vladimir Sturm, Logan Dawson, Joel Taylor, Curtis Oak Ridge Natl Lab Oak Ridge TN 37831 USA Cybersecur Mfg Innovat Inst San Antonio TX 78249 USA

ISBN: (纸本)9783031818905;9783031818882;9783031818875

The widespread adoption of networked devices, sophisticated automation and data-driven processes in industry - also known as Industry 4.0 - has boosted the quantity and quality of manufacturing products. However, the benefits come with substantial increases in the attack surfaces of manufacturing processes and systems. In addition to affecting the quality and readiness of critical products, attacks against manufacturing processes and systems can have severe physical consequences, including human injury and death. This chapter presents the results of remote network-based control injection attacks on a computer numerical control mill. The focus is on the impacts of attacks during computer numerical control mill operation. A machine-agnostic, affordable and scalable solution for attack monitoring is developed by considering the physical effects of the attacks on wax workpieces. A simple threshold-based method for detecting attacks is demonstrated and its effectiveness is evaluated.

关键词： Manufacturing Cyber Security Attack Detection Power Analysis Attack Quantification

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