{"results":[{"id":"ss_d1462a2068b527981538d21f88c2c6d5acf2c6fe","title":"Smart Antennas for Wireless Communications: Is-95 and Third Generation Cdma Applications","authors":[{"name":"J. Liberti"},{"name":"T. Rappaport"}],"abstract":"","source":"Semantic Scholar","year":1999,"language":"en","subjects":["Engineering"],"url":"https://www.semanticscholar.org/paper/d1462a2068b527981538d21f88c2c6d5acf2c6fe","is_open_access":true,"citations":1192,"published_at":"","score":80},{"id":"ss_d1da19c63c0deb0d40af3395347597fa01f1d86e","title":"Wireless networks","authors":[{"name":"K. Pahlavan"}],"abstract":"Segments of Wireless Information Networks Voice Driven Networks: well defined applications Low power, high quality, local services (PCS, wireless PBX, telepoint) - Result of success in cordless telephone industry High power, low quality, wide area (Digital Cellular) - Result of demand for higher capacity in cellular phones","source":"Semantic Scholar","year":1994,"language":"en","subjects":["Engineering","Computer Science"],"doi":"10.1117/12.192184","url":"https://www.semanticscholar.org/paper/d1da19c63c0deb0d40af3395347597fa01f1d86e","pdf_url":"https://doi.org/10.1007/11276.1572-8196","is_open_access":true,"citations":663,"published_at":"","score":69.89},{"id":"arxiv_2511.08108","title":"Improving Industrial Injection Molding Processes with Explainable AI for Quality Classification","authors":[{"name":"Georg Rottenwalter"},{"name":"Marcel Tilly"},{"name":"Victor Owolabi"}],"abstract":"Machine learning is an essential tool for optimizing industrial quality control processes. However, the complexity of machine learning models often limits their practical applicability due to a lack of interpretability. Additionally, many industrial machines lack comprehensive sensor technology, making data acquisition incomplete and challenging. Explainable Artificial Intelligence offers a solution by providing insights into model decision-making and identifying the most relevant features for classification. In this paper, we investigate the impact of feature reduction using XAI techniques on the quality classification of injection-molded parts. We apply SHAP, Grad-CAM, and LIME to analyze feature importance in a Long Short-Term Memory model trained on real production data. By reducing the original 19 input features to 9 and 6, we evaluate the trade-off between model accuracy, inference speed, and interpretability. Our results show that reducing features can improve generalization while maintaining high classification performance, with an small increase in inference speed. This approach enhances the feasibility of AI-driven quality control, particularly for industrial settings with limited sensor capabilities, and paves the way for more efficient and interpretable machine learning applications in manufacturing.","source":"arXiv","year":2025,"language":"en","subjects":["cs.AI"],"doi":"10.1109/RTSI64020.2025.11212395","url":"https://arxiv.org/abs/2511.08108","pdf_url":"https://arxiv.org/pdf/2511.08108","is_open_access":true,"published_at":"2025-11-11T11:07:21Z","score":69},{"id":"arxiv_2503.21240","title":"The Promise and Pitfalls of WebAssembly: Perspectives from the Industry","authors":[{"name":"Ningyu He"},{"name":"Shangtong Cao"},{"name":"Haoyu Wang"},{"name":"Yao Guo"},{"name":"Xiapu Luo"}],"abstract":"As JavaScript has been criticized for performance and security issues in web applications, WebAssembly (Wasm) was proposed in 2017 and is regarded as the complementation for JavaScript. Due to its advantages like compact-size, native-like speed, and portability, Wasm binaries are gradually used as the compilation target for industrial projects in other high-level programming languages and are responsible for computation-intensive tasks in browsers, e.g., 3D graphic rendering and video decoding. Intuitively, characterizing in-the-wild adopted Wasm binaries from different perspectives, like their metadata, relation with source programming language, existence of security threats, and practical purpose, is the prerequisite before delving deeper into the Wasm ecosystem and beneficial to its roadmap selection. However, currently, there is no work that conducts a large-scale measurement study on in-the-wild adopted Wasm binaries. To fill this gap, we collect the largest-ever dataset to the best of our knowledge, and characterize the status quo of them from industry perspectives. According to the different roles of people engaging in the community, i.e., web developers, Wasm maintainers, and researchers, we reorganized our findings to suggestions and best practices for them accordingly. We believe this work can shed light on the future direction of the web and Wasm.","source":"arXiv","year":2025,"language":"en","subjects":["cs.SE"],"url":"https://arxiv.org/abs/2503.21240","pdf_url":"https://arxiv.org/pdf/2503.21240","is_open_access":true,"published_at":"2025-03-27T08:01:22Z","score":69},{"id":"arxiv_2505.15179","title":"RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry","authors":[{"name":"Chaozheng Wang"},{"name":"Zezhou Yang"},{"name":"Shuzheng Gao"},{"name":"Cuiyun Gao"},{"name":"Ting Peng"},{"name":"Hailiang Huang"},{"name":"Yuetang Deng"},{"name":"Michael Lyu"}],"abstract":"Code completion, a crucial practice in industrial settings, helps developers improve programming efficiency by automatically suggesting code snippets during development. With the emergence of Large Code Models (LCMs), this field has witnessed significant advancements. Due to the natural differences between open-source and industrial codebases, such as coding patterns and unique internal dependencies, it is a common practice for developers to conduct domain adaptation when adopting LCMs in industry. There exist multiple adaptation approaches, among which retrieval-augmented generation (RAG) and fine-tuning are the two most popular paradigms. However, no prior research has explored the trade-off of the two approaches in industrial scenarios.   To mitigate the gap, we comprehensively compare the two paradigms including Retrieval-Augmented Generation (RAG) and Fine-tuning (FT), for industrial code completion in this paper. In collaboration with Tencent's WXG department, we collect over 160,000 internal C++ files as our codebase. We then compare the two types of adaptation approaches from three dimensions that are concerned by industrial practitioners, including effectiveness, efficiency, and parameter sensitivity, using six LCMs. Our findings reveal that RAG, when implemented with appropriate embedding models that map code snippets into dense vector representations, can achieve higher accuracy than fine-tuning alone. Specifically, BM25 presents superior retrieval effectiveness and efficiency among studied RAG methods. Moreover, RAG and fine-tuning are orthogonal and their combination leads to further improvement. We also observe that RAG demonstrates better scalability than FT, showing more sustained performance gains with larger scales of codebase.","source":"arXiv","year":2025,"language":"en","subjects":["cs.SE"],"url":"https://arxiv.org/abs/2505.15179","pdf_url":"https://arxiv.org/pdf/2505.15179","is_open_access":true,"published_at":"2025-05-21T06:51:25Z","score":69},{"id":"arxiv_2510.04631","title":"Contrastive Learning Using Graph Embeddings for Domain Adaptation of Language Models in the Process Industry","authors":[{"name":"Anastasia Zhukova"},{"name":"Jonas Lührs"},{"name":"Christian E. Lobmüller"},{"name":"Bela Gipp"}],"abstract":"Recent trends in NLP utilize knowledge graphs (KGs) to enhance pretrained language models by incorporating additional knowledge from the graph structures to learn domain-specific terminology or relationships between documents that might otherwise be overlooked. This paper explores how SciNCL, a graph-aware neighborhood contrastive learning methodology originally designed for scientific publications, can be applied to the process industry domain, where text logs contain crucial information about daily operations and are often structured as sparse KGs. Our experiments demonstrate that language models fine-tuned with triplets derived from graph embeddings (GE) outperform a state-of-the-art mE5-large text encoder by 9.8-14.3% (5.45-7.96p) on the proprietary process industry text embedding benchmark (PITEB) while having 3 times fewer parameters.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CL","cs.IR"],"url":"https://arxiv.org/abs/2510.04631","pdf_url":"https://arxiv.org/pdf/2510.04631","is_open_access":true,"published_at":"2025-10-06T09:36:20Z","score":69},{"id":"arxiv_2506.04980","title":"Agentic AI for Intent-Based Industrial Automation","authors":[{"name":"Marcos Lima Romero"},{"name":"Ricardo Suyama"}],"abstract":"The recent development of Agentic AI systems, empowered by autonomous large language models (LLMs) agents with planning and tool-usage capabilities, enables new possibilities for the evolution of industrial automation and reduces the complexity introduced by Industry 4.0. This work proposes a conceptual framework that integrates Agentic AI with the intent-based paradigm, originally developed in network research, to simplify human-machine interaction (HMI) and better align automation systems with the human-centric, sustainable, and resilient principles of Industry 5.0. Based on the intent-based processing, the framework allows human operators to express high-level business or operational goals in natural language, which are decomposed into actionable components. These intents are broken into expectations, conditions, targets, context, and information that guide sub-agents equipped with specialized tools to execute domain-specific tasks. A proof of concept was implemented using the CMAPSS dataset and Google Agent Developer Kit (ADK), demonstrating the feasibility of intent decomposition, agent orchestration, and autonomous decision-making in predictive maintenance scenarios. The results confirm the potential of this approach to reduce technical barriers and enable scalable, intent-driven automation, despite data quality and explainability concerns.","source":"arXiv","year":2025,"language":"en","subjects":["cs.LG","eess.SY"],"doi":"10.1109/INDUSCON66435.2025.11241317","url":"https://arxiv.org/abs/2506.04980","pdf_url":"https://arxiv.org/pdf/2506.04980","is_open_access":true,"published_at":"2025-06-05T12:50:54Z","score":69},{"id":"arxiv_2501.15636","title":"Investigating Circularity in India's Textile Industry: Overcoming Challenges and Leveraging Digitization for Growth","authors":[{"name":"Suman Kumar Das"}],"abstract":"India's growing population and economy have significantly increased the demand and consumption of natural resources. As a result, the potential benefits of transitioning to a circular economic model have been extensively discussed and debated among various Indian stakeholders, including policymakers, industry leaders, and environmental advocates. Despite the numerous initiatives, policies, and transnational strategic partnerships of the Indian government, most small and medium enterprises in India face significant challenges in implementing circular economy practices. This is due to the lack of a clear pathway to measure the current state of the circular economy in Indian industries and the absence of a framework to address these challenges. This paper examines the circularity of the 93-textile industry in India using the C-Readiness Tool. The analysis comprehensively identified 9 categories with 34 barriers to adopting circular economy principles in the textile sector through a narrative literature review. The identified barriers were further compared against the findings from a C-readiness tool assessment, which revealed prominent challenges related to supply chain coordination, consumer engagement, and regulatory compliance within the industry's circularity efforts. In response to these challenges, the article proposes a strategic roadmap that leverages digital technologies to drive the textile industry towards a more sustainable and resilient industrial model.","source":"arXiv","year":2025,"language":"en","subjects":["econ.GN"],"url":"https://arxiv.org/abs/2501.15636","pdf_url":"https://arxiv.org/pdf/2501.15636","is_open_access":true,"published_at":"2025-01-26T18:46:15Z","score":69},{"id":"arxiv_2508.03329","title":"Industrial LLM-based Code Optimization under Regulation: A Mixture-of-Agents Approach","authors":[{"name":"Mari Ashiga"},{"name":"Vardan Voskanyan"},{"name":"Fateme Dinmohammadi"},{"name":"Jingzhi Gong"},{"name":"Paul Brookes"},{"name":"Matthew Truscott"},{"name":"Rafail Giavrimis"},{"name":"Mike Basios"},{"name":"Leslie Kanthan"},{"name":"Wei Jie"}],"abstract":"Recent advancements in Large Language Models (LLMs) for code optimization have enabled industrial platforms to automate software performance engineering at unprecedented scale and speed. Yet, organizations in regulated industries face strict constraints on which LLMs they can use - many cannot utilize commercial models due to data privacy regulations and compliance requirements, creating a significant challenge for achieving high-quality code optimization while maintaining cost-effectiveness. We address this by implementing a Mixture-of-Agents (MoA) approach that directly synthesizes code from multiple specialized LLMs, comparing it against TurinTech AI's vanilla Genetic Algorithm (GA)-based ensemble system and individual LLM optimizers using real-world industrial codebases. Our key contributions include: (1) First MoA application to industrial code optimization using real-world codebases; (2) Empirical evidence that MoA excels with open-source models, achieving 14.3% to 22.2% cost savings and 28.6% to 32.2% faster optimization times for regulated environments; (3) Deployment guidelines demonstrating GA's advantage with commercial models while both ensembles outperform individual LLMs; and (4) Real-world validation across 50 code snippets and seven LLM combinations, generating over 8,700 variants, addresses gaps in industrial LLM ensemble evaluation. This provides actionable guidance for organizations balancing regulatory compliance with optimization performance in production environments.","source":"arXiv","year":2025,"language":"en","subjects":["cs.SE","cs.AI"],"url":"https://arxiv.org/abs/2508.03329","pdf_url":"https://arxiv.org/pdf/2508.03329","is_open_access":true,"published_at":"2025-08-05T11:15:06Z","score":69},{"id":"arxiv_2404.00783","title":"Potentials of the Metaverse for Robotized Applications in Industry 4.0 and Industry 5.0","authors":[{"name":"Eric Guiffo Kaigom"}],"abstract":"As a digital environment of interconnected virtual ecosystems driven by measured and synthesized data, the Metaverse has so far been mostly considered from its gaming perspective that closely aligns with online edutainment. Although it is still in its infancy and more research as well as standardization efforts remain to be done, the Metaverse could provide considerable advantages for smart robotized applications in the industry.Workflow efficiency, collective decision enrichment even for executives, as well as a natural, resilient, and sustainable robotized assistance for the workforce are potential advantages. Hence, the Metaverse could consolidate the connection between Industry 4.0 and Industry 5.0. This paper identifies and puts forward potential advantages of the Metaverse for robotized applications and highlights how these advantages support goals pursued by the Industry 4.0 and Industry 5.0 visions.   Keywords: Robotics, Metaverse, Digital Twin, VR/AR, AI/ML, Foundation Model;","source":"arXiv","year":2024,"language":"en","subjects":["cs.RO","eess.SY"],"doi":"10.1016/j.procs.2024.02.005","url":"https://arxiv.org/abs/2404.00783","pdf_url":"https://arxiv.org/pdf/2404.00783","is_open_access":true,"published_at":"2024-03-31T20:05:23Z","score":68},{"id":"arxiv_2405.01158","title":"Towards Transparent and Efficient Anomaly Detection in Industrial Processes through ExIFFI","authors":[{"name":"Davide Frizzo"},{"name":"Francesco Borsatti"},{"name":"Alessio Arcudi"},{"name":"Antonio De Moliner"},{"name":"Roberto Oboe"},{"name":"Gian Antonio Susto"}],"abstract":"Anomaly Detection (AD) is crucial in industrial settings to streamline operations by detecting underlying issues. Conventional methods merely label observations as normal or anomalous, lacking crucial insights. In Industry 5.0, interpretable outcomes become desirable to enable users to understand the rational under model decisions. This paper presents the first industrial application of ExIFFI, a recent approach for fast, efficient explanations for the Extended Isolation Forest (EIF) AD method. ExIFFI is tested on four industrial datasets, demonstrating superior explanation effectiveness, computational efficiency and improved raw anomaly detection performances. ExIFFI reaches over then 90\\% of average precision on all the benchmarks considered in the study and overperforms state-of-the-art Explainable Artificial Intelligence (XAI) approaches in terms of the feature selection proxy task metric which was specifically introduced to quantitatively evaluate model explanations.","source":"arXiv","year":2024,"language":"en","subjects":["cs.LG","cs.AI"],"url":"https://arxiv.org/abs/2405.01158","pdf_url":"https://arxiv.org/pdf/2405.01158","is_open_access":true,"published_at":"2024-05-02T10:23:17Z","score":68},{"id":"arxiv_2408.10788","title":"Understanding the Skills Gap between Higher Education and Industry in the UK in Artificial Intelligence Sector","authors":[{"name":"Khushi Jaiswal"},{"name":"Ievgeniia Kuzminykh"},{"name":"Sanjay Modgil"}],"abstract":"As Artificial Intelligence (AI) changes how businesses work, there is a growing need for people who can work in this sector. This paper investigates how well universities in United Kingdom offering courses in AI, prepare students for jobs in the real world. To gain insight into the differences between university curricula and industry demands we review the contents of taught courses and job advertisement portals. By using custom data scraping tools to gather information from job advertisements and university curricula, and frequency and Naive Bayes classifier analysis, this study will show exactly what skills industry is looking for. In this study we identified 12 skill categories that were used for mapping. The study showed that the university curriculum in the AI domain is well balanced in most technical skills, including Programming and Machine learning subjects, but have a gap in Data Science and Maths and Statistics skill categories.","source":"arXiv","year":2024,"language":"en","subjects":["cs.AI"],"doi":"10.1177/09504222241280441","url":"https://arxiv.org/abs/2408.10788","pdf_url":"https://arxiv.org/pdf/2408.10788","is_open_access":true,"published_at":"2024-08-20T12:28:58Z","score":68},{"id":"arxiv_2407.04503","title":"When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings","authors":[{"name":"Jérémy Perez"},{"name":"Grgur Kovač"},{"name":"Corentin Léger"},{"name":"Cédric Colas"},{"name":"Gaia Molinaro"},{"name":"Maxime Derex"},{"name":"Pierre-Yves Oudeyer"},{"name":"Clément Moulin-Frier"}],"abstract":"As large language models (LLMs) start interacting with each other and generating an increasing amount of text online, it becomes crucial to better understand how information is transformed as it passes from one LLM to the next. While significant research has examined individual LLM behaviors, existing studies have largely overlooked the collective behaviors and information distortions arising from iterated LLM interactions. Small biases, negligible at the single output level, risk being amplified in iterated interactions, potentially leading the content to evolve towards attractor states. In a series of telephone game experiments, we apply a transmission chain design borrowed from the human cultural evolution literature: LLM agents iteratively receive, produce, and transmit texts from the previous to the next agent in the chain. By tracking the evolution of text toxicity, positivity, difficulty, and length across transmission chains, we uncover the existence of biases and attractors, and study their dependence on the initial text, the instructions, language model, and model size. For instance, we find that more open-ended instructions lead to stronger attraction effects compared to more constrained tasks. We also find that different text properties display different sensitivity to attraction effects, with toxicity leading to stronger attractors than length. These findings highlight the importance of accounting for multi-step transmission dynamics and represent a first step towards a more comprehensive understanding of LLM cultural dynamics.","source":"arXiv","year":2024,"language":"en","subjects":["physics.soc-ph","cs.AI","cs.MA"],"url":"https://arxiv.org/abs/2407.04503","pdf_url":"https://arxiv.org/pdf/2407.04503","is_open_access":true,"published_at":"2024-07-05T13:44:09Z","score":68},{"id":"arxiv_2405.02435","title":"Bridging the Gap: A Study of AI-based Vulnerability Management between Industry and Academia","authors":[{"name":"Shengye Wan"},{"name":"Joshua Saxe"},{"name":"Craig Gomes"},{"name":"Sahana Chennabasappa"},{"name":"Avilash Rath"},{"name":"Kun Sun"},{"name":"Xinda Wang"}],"abstract":"Recent research advances in Artificial Intelligence (AI) have yielded promising results for automated software vulnerability management. AI-based models are reported to greatly outperform traditional static analysis tools, indicating a substantial workload relief for security engineers. However, the industry remains very cautious and selective about integrating AI-based techniques into their security vulnerability management workflow. To understand the reasons, we conducted a discussion-based study, anchored in the authors' extensive industrial experience and keen observations, to uncover the gap between research and practice in this field. We empirically identified three main barriers preventing the industry from adopting academic models, namely, complicated requirements of scalability and prioritization, limited customization flexibility, and unclear financial implications. Meanwhile, research works are significantly impacted by the lack of extensive real-world security data and expertise. We proposed a set of future directions to help better understand industry expectations, improve the practical usability of AI-based security vulnerability research, and drive a synergistic relationship between industry and academia.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CR","cs.SE"],"url":"https://arxiv.org/abs/2405.02435","pdf_url":"https://arxiv.org/pdf/2405.02435","is_open_access":true,"published_at":"2024-05-03T19:00:50Z","score":68},{"id":"doaj_10.1155/2022/1554190","title":"A Novel Method to Broaden the Single-Mode Bandwidth of the Rectangular Waveguide","authors":[{"name":"Tingting Xie"},{"name":"Xiaohe Cheng"},{"name":"Yuan Yao"},{"name":"Yaohui Yang"},{"name":"Ting Zhang"},{"name":"Junsheng Yu"},{"name":"Xiaodong Chen"}],"abstract":"In this paper, a new class of broadband and low-loss transmission line called slotted rectangular waveguide (SRW) is proposed and analyzed. The proposed SRW consists of the rectangular waveguide and the inverted low-loss slotline, which can selectively suppress the higher-order mode (TE20 mode) and broaden the single dominant mode (TE10 mode) bandwidth in a rectangular waveguide (RW). The design principle and transmission characteristics of the SRW are illustrated and analyzed in this work. The transmission dominant mode bandwidth of the proposed SRW is analyzed and compared with the classic rectangular waveguide (RW), in which the dominant mode bandwidth of 60–155 GHz (88.4% bandwidth) is broader than the RW bandwidth of 60–116 GHz (63%). Two feed structures that can excite the two operating bandwidths (W and D band) of them separately are also designed. The SRW and transition exhibit broadband and low-loss characteristics from 75 GHz to 155 GHz, in which the transmission loss is lower than 0.68 dB and the return loss is over 18 dB.","source":"DOAJ","year":2022,"language":"","subjects":["Electrical engineering. Electronics. Nuclear engineering","Cellular telephone services industry. Wireless telephone industry"],"doi":"10.1155/2022/1554190","url":"http://dx.doi.org/10.1155/2022/1554190","is_open_access":true,"published_at":"","score":66},{"id":"arxiv_2209.14812","title":"Named Entity Recognition in Industrial Tables using Tabular Language Models","authors":[{"name":"Aneta Koleva"},{"name":"Martin Ringsquandl"},{"name":"Mark Buckley"},{"name":"Rakebul Hasan"},{"name":"Volker Tresp"}],"abstract":"Specialized transformer-based models for encoding tabular data have gained interest in academia. Although tabular data is omnipresent in industry, applications of table transformers are still missing. In this paper, we study how these models can be applied to an industrial Named Entity Recognition (NER) problem where the entities are mentioned in tabular-structured spreadsheets. The highly technical nature of spreadsheets as well as the lack of labeled data present major challenges for fine-tuning transformer-based models. Therefore, we develop a dedicated table data augmentation strategy based on available domain-specific knowledge graphs. We show that this boosts performance in our low-resource scenario considerably. Further, we investigate the benefits of tabular structure as inductive bias compared to tables as linearized sequences. Our experiments confirm that a table transformer outperforms other baselines and that its tabular inductive bias is vital for convergence of transformer-based models.","source":"arXiv","year":2022,"language":"en","subjects":["cs.AI","cs.CL"],"url":"https://arxiv.org/abs/2209.14812","pdf_url":"https://arxiv.org/pdf/2209.14812","is_open_access":true,"published_at":"2022-09-29T14:25:44Z","score":66},{"id":"arxiv_2111.13854","title":"A novel knowledge graph development for industry design: A case study on indirect coal liquefaction process","authors":[{"name":"Zhenhua Wang"},{"name":"Beike Zhang"},{"name":"Dong Gao"}],"abstract":"Hazard and operability analysis (HAZOP) is a remarkable representative in industrial safety engineering. However, a great storehouse of industrial safety knowledge (ISK) in HAZOP reports has not been thoroughly exploited. In order to reuse and unlock the value of ISK and optimize HAZOP, we have developed a novel knowledge graph for industrial safety (ISKG) with HAZOP as the carrier through bridging data science and engineering design. Specifically, firstly, considering that the knowledge contained in HAZOP reports of different processes in industry is not the same, we creatively develope a general ISK standardization framework, it provides a practical scheme for integrating HAZOP reports from various processes and uniformly representing the ISK with diverse expressions. Secondly, we conceive a novel and reliable information extraction model based on deep learning combined with data science, it can effectively mine ISK from HAZOP reports, which alleviates the obstacle of ISK extraction caused by the particularity of HAZOP text. Finally, we build ISK triples and store them in the Neo4j graph database. We take indirect coal liquefaction process as a case study to develop ISKG, and its oriented applications can optimize HAZOP and mine the potential of ISK, which is of great significance to improve the security of the system and enhance prevention awareness for people. ISKG containing the ISK standardization framework and the information extraction model sets an example of the interaction between data science and engineering design, which can enlighten other researchers and extend the perspectives of industrial safety.","source":"arXiv","year":2021,"language":"en","subjects":["cs.CL"],"url":"https://arxiv.org/abs/2111.13854","pdf_url":"https://arxiv.org/pdf/2111.13854","is_open_access":true,"published_at":"2021-11-27T09:37:56Z","score":65},{"id":"doaj_10.52638/rfpt.2019.440","title":"Pré-localisation des données pour la modélisation 3D de tunnels : développements et évaluations","authors":[{"name":"Christophe Heinkelé"},{"name":"Pierre Charbonnier"},{"name":"Philippe Foucher"},{"name":"Emmanuel Moisan"}],"abstract":"Le présent article décrit l'implémentation d'une méthode de pré-location décimétrique d'images au sein de grands volumes de données dans des tunnels navigables et routiers. Elle repose sur une technique d'odométrie visuelle simplifiée, ce qui la rend rapide et facile à mettre en oeuvre. Cette méthode permet de structurer les données afin d'améliorer les traitements postérieurs, comme par exemple la reconstruction 3D par photogrammétrie. La méthode est évaluée sur la précision de la localisation par comparaison avec des techniques de localisation plus conventionnelles. La structuration des données qui découle de cette localisation des images au sein de l'ouvrage constitue l'aspect le plus important du travail présenté ici.","source":"DOAJ","year":2020,"language":"","subjects":["Instruments and machines","Applied optics. Photonics","Cellular telephone services industry. Wireless telephone industry"],"doi":"10.52638/rfpt.2019.440","url":"https://rfpt.sfpt.fr/index.php/RFPT/article/view/440","is_open_access":true,"published_at":"","score":64},{"id":"doaj_10.1155/2020/8707182","title":"Elliptical Ring Antenna Excited by Circular Disc Monopole for UWB Communications","authors":[{"name":"Krittaya Nakprasit"},{"name":"Arnon Sakonkanapong"},{"name":"Chuwong Phongcharoenpanich"}],"abstract":"This research proposes a compact elliptical ring antenna excited by a circular disc monopole (CDM) for ultra-wideband (UWB) communications. In the study, time- and frequency-domain pulse distortions of the antenna in the transmission mode were characterized by magnitude and phase of the antenna transfer function (Hrad). The results showed that the gain and magnitude of Hrad in the boresight direction are sufficiently flat with linear phase response. The average antenna gain is 3.9 dBi over the UWB spectrum. The antenna also exhibits low pulse distortion with the correlation factors (ρ) of 0.98 and 0.93 for the fifth-order derivative Gaussian pulse and modulated Gaussian pulse with 6 GHz band rejection. The CDM-excited elliptical ring antenna possesses several attractive features, including wide bandwidth, flat gain, compactness, low cost, and low distortion.","source":"DOAJ","year":2020,"language":"","subjects":["Electrical engineering. Electronics. Nuclear engineering","Cellular telephone services industry. Wireless telephone industry"],"doi":"10.1155/2020/8707182","url":"http://dx.doi.org/10.1155/2020/8707182","is_open_access":true,"published_at":"","score":64},{"id":"arxiv_2002.12878","title":"Blockchain in Space Industry: Challenges and Solutions","authors":[{"name":"Mohamed Torky"},{"name":"Tarek Gaber"},{"name":"Aboul Ella Hassanien"}],"abstract":"Blockchain technology can play a vital role in the space industry and exploration. This magic technology can provide decentralized and secure techniques for processing and manipulating space resources as space digital tokens. Tokenizing space resources such as orbits, satellites, spacecraft, orbital debris, asteroids, and other space objects in the form of blockchain-based digital tokens will reflect plenty of various applications in the space mining industry. Moreover, Blockchain algorithms based on smart contracts can be utilized for tracking all space transactions and communications in a transparent, verifiable, and secure manner. This paper is one of the first attempts towards conceptually investigating adopting blockchain theory in the space industry based on space digital token concept. A new conceptual blockchain in space industry framework is proposed, and new models are created for introducing proposed solutions for some major challenges in the space industry and exploration. Finally, the paper is ended with discussing SpaceChain, the first open-source blockchain-based satellite network in the world as a case study of applying blockchain theory in designing and implementing satellite systems.","source":"arXiv","year":2020,"language":"en","subjects":["eess.SP"],"url":"https://arxiv.org/abs/2002.12878","pdf_url":"https://arxiv.org/pdf/2002.12878","is_open_access":true,"published_at":"2020-02-27T16:44:16Z","score":64}],"total":2577573,"page":1,"page_size":20,"sources":["DOAJ","arXiv","CrossRef","Semantic Scholar"],"query":"Cellular telephone services industry. Wireless telephone industry"}