Model for Techno-Economic Assessment of Access Technologies. Doctoral Dissertation for PhD, Telecommunications Engineering (EECS)

• URL: http://arxiv.org/abs/2008.07286v4
• Date: Wed, 21 Apr 2021 21:23:52 GMT
• Title: Model for Techno-Economic Assessment of Access Technologies. Doctoral Dissertation for PhD, Telecommunications Engineering (EECS)
• Authors: Carlos Bendicho
• Abstract summary: This dissertation shows State of the Art of techno-economic modeling for access network technologies. The author defines and develops a Universal Techno-Economic Model called UTEM.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This doctoral dissertation shows State of the Art of techno-economic modeling for access network technologies, presents the characteristics a universal techno-economic model should have, and shows a classification and analysis of techno-economic models in the literature based on such characteristics. In order to reduce the gap detected in the literature, the author defines and develops a Universal Techno-Economic Model called UTEM and the corresponding methodology to industrialize techno-economic assessment in multiple domains considering all market players perspectives, also suitable for technological consulting and currently available for all industry stakeholders under specific license of use.

Related papers

• Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents [63.03252293761656]
  This paper systematically reviews the technologies, applications, and evaluation methods of industry agents based on large language models (LLMs)<n>We examine the three key technological pillars that support the advancement of agent capabilities: Memory, Planning, and Tool Use.<n>We provide an overview of the application of industry agents in real-world domains such as digital engineering, scientific discovery, embodied intelligence, collaborative business execution, and complex system simulation.
  arXiv  Detail & Related papers  (2025-10-20T12:46:55Z)
• A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives [65.3369988566853]
  Recent studies have demonstrated that adversaries can replicate a target model's functionality.<n>Model Extraction Attacks pose threats to intellectual property, privacy, and system security.<n>We propose a novel taxonomy that classifies MEAs according to attack mechanisms, defense approaches, and computing environments.
  arXiv  Detail & Related papers  (2025-08-20T19:49:59Z)
• Exploring the Technical Knowledge Interaction of Global Digital Humanities: Three-decade Evidence from Bibliometric-based perspectives [6.4731966382810215]
  This study introduces a new concept of Topic-Method Composition (TMC)<n>TMC refers to a hybrid knowledge structure generated by the co-occurrence of specific research topics and the corresponding method.<n>This study develops a workflow combining bibliometric analysis, topic modeling, and network analysis to analyze the development characteristics and patterns of research disciplines.
  arXiv  Detail & Related papers  (2025-08-11T12:27:39Z)
• Exploring the Future Metaverse: Research Models for User Experience, Business Readiness, and National Competitiveness [0.0]
  The study examines the metaverse as a sociotechnical imaginary, enabled collectively by virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies. We develop three research models, which can guide researchers in examining the metaverse as a sociotechnical future of information technology.
  arXiv  Detail & Related papers  (2024-11-15T18:27:09Z)
• Model-Guided Fieldwork: A Practical, Methodological and Philosophical Investigation in the use of Ethnomethodology for Engineering Software Requirements [0.0]
  This thesis focuses on the use of ethnomethodological fieldwork for the engineering of software requirements. It proposes an approach, dubbed "Model Guided Fieldwork," to support a fieldworker in making observations that may contribute to a technological development process.
  arXiv  Detail & Related papers  (2024-11-14T09:24:56Z)
• Ontology Embedding: A Survey of Methods, Applications and Resources [54.3453925775069]
  Ontologies are widely used for representing domain knowledge and meta data. One straightforward solution is to integrate statistical analysis and machine learning. Numerous papers have been published on embedding, but a lack of systematic reviews hinders researchers from gaining a comprehensive understanding of this field.
  arXiv  Detail & Related papers  (2024-06-16T14:49:19Z)
• The application of Augmented Reality (AR) in Remote Work and Education [9.275489976839754]
  Augmented Reality (AR) technology is gradually transforming traditional work modes and teaching methods. This paper delves into the application potential and actual effects of AR technology in remote work and education.
  arXiv  Detail & Related papers  (2024-04-16T14:04:46Z)
• Measuring Technological Convergence in Encryption Technologies with Proximity Indices: A Text Mining and Bibliometric Analysis using OpenAlex [46.3643544723237]
  This study identifies technological convergence among emerging technologies in cybersecurity. The proposed method integrates text mining and bibliometric analyses to formulate and predict technological proximity indices. Our case study findings highlight a significant convergence between blockchain and public-key cryptography, evidenced by the increasing proximity indices.
  arXiv  Detail & Related papers  (2024-03-03T20:03:03Z)
• The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence [67.70415658080121]
  Recent advances in machine learning and AI are disrupting technological innovation, product development, and society as a whole. AI has contributed less to fundamental science in part because large data sets of high-quality data for scientific practice and model discovery are more difficult to access. Here we explore and investigate aspects of an AI-driven, automated, closed-loop approach to scientific discovery.
  arXiv  Detail & Related papers  (2023-07-09T21:16:56Z)
• Rethinking Model Evaluation as Narrowing the Socio-Technical Gap [47.632123167141245]
  We argue that model evaluation practices must take on a critical task to cope with the challenges and responsibilities brought by this homogenization. We urge the community to develop evaluation methods based on real-world contexts and human requirements.
  arXiv  Detail & Related papers  (2023-06-01T00:01:43Z)
• Socio-Technical Security Modelling: Analysis of State-of-the-Art, Application, and Maturity in Critical Industrial Infrastructure Environments/Domains [0.0]
  This study explores the state-of-the-art, application, and maturity of socio-technical security models for industries and sectors dependent on CI.
  arXiv  Detail & Related papers  (2023-05-09T00:34:12Z)
• Towards a Taxonomy of Industrial Challenges and Enabling Technologies in Industry 4.0 [0.0]
  This article proposes a mixed approach of humanistic and engineering techniques applied to the technological and enterprise fields. The study's results are represented by a taxonomy in which industrial challenges and I4.0-focused technologies are categorized and connected. This taxonomy also formed the basis for creating a public web platform where industrial practitioners can identify candidate solutions for an industrial challenge.
  arXiv  Detail & Related papers  (2022-11-29T19:52:36Z)
• Intelligent interactive technologies for mental health and well-being [70.1586005070678]
  The paper critically analyzes existing solutions with the outlooks for their future. In particular, we:. give an overview of the technology for mental health,. critically analyze the technology against the proposed criteria, and. provide the design outlooks for these technologies.
  arXiv  Detail & Related papers  (2021-05-11T19:04:21Z)
• An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
  This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
  arXiv  Detail & Related papers  (2021-05-07T12:01:31Z)
• A Diagnostic Study of Explainability Techniques for Text Classification [52.879658637466605]
  We develop a list of diagnostic properties for evaluating existing explainability techniques. We compare the saliency scores assigned by the explainability techniques with human annotations of salient input regions to find relations between a model's performance and the agreement of its rationales with human ones.
  arXiv  Detail & Related papers  (2020-09-25T12:01:53Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.