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2023 China Automation Congress, CAC 2023

作者： Qiu, Junxiang Li, Changhe Yang, Shengxiang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo- Exploration Ministry of Education Wuhan430074 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350303759

Aiming at the truck scheduling problem in the open-pit mine scenario, a truck scheduling model based on real-time ore blending is established, and an adaptive evolution algorithm for truck scheduling based on DCNSGA-III is proposed. In the established scheduling model, the real-time grade variance of the crushing plant is minimized as one of the optimization objectives, and the Q-learning algorithm is introduced to adaptively select one of the most effective operators during the search process. Experiments show that the proposed method can effectively control the grade fluctuation of the ore flow and better scheduling schemes are obtained in comparison with algorithms equipped with the traditional search operator selection methods. © 2023 IEEE.

关键词： Evolutionary algorithms

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ON THE MAXIMUM SIZE OF VARIABLE-LENGTH NON-OVERLAPPING CODES

arXiv

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arXiv 2024年

作者： Wang, Geyang Wang, Qi Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland College ParkMD20742 United States Department of Computer Science and Engineering National Center for Applied Mathematics Shenzhen Southern University of Science and Technology Nanshan District Guangdong Shenzhen518055 China

Non-overlapping codes are a set of codewords such that the prefix of each codeword is not a suffix of any codeword in the set, including itself. If the lengths of the codewords are variable, it is additionally required that every codeword is not contained in any other codeword as a subword. Let C(n, q) be the maximum size of q-ary fixed-length non-overlapping codes of length n. The upper bound on C(n, q) has been well studied. However, the nontrivial upper bound on the maximum size of variable-length non-overlapping codes of length at most n remains open. In this paper, by establishing a link between variable-length non-overlapping codes and fixed-length ones, we are able to show that the size of a q-ary variable-length non-overlapping code is upper bounded by C(n, q). Furthermore, we prove that the average length of the codewords in a q-ary variable-length non-overlapping codes is lower bounded by ⌈logq C˜⌉, and is asymptotically no shorter than n−2 as q approaches ∞, where C˜ denotes the cardinality of q-ary variable-length non-overlapping codes of length up to *** Codes 94A45, 94B25 © 2024, CC BY.

关键词： C (programming language)

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Access Control Based on Self-Sovereign Identity 16

Access Control Based on Self-Sovereign Identity

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Nita, Stefania Loredana Mihailescu, Marius Iulian Marascu, Valentina Rogobete, Marius Faculty of Information Systems and Cyber Security Military Technical Academy 'Ferdinand i' Department of Computers and Cybersecurity Bucharest Romania 'Spiru Haret' University Scientific Research Center in Mathematics and Informatics Faculty of Engineering and Computer Science Bucharest Romania National Institute for Laser Plasma and Radiation Physics Low Temperature Plasma Department Bucharest Romania Telematics Harman International Bucharest Romania

ISBN: (纸本)9798350371154

In the rapidly growing interest in digital identity management, there is an important shift toward adopting verifiable credentials, often based on blockchain technology. This transition highlights a growing interest in the concept of Self-Sovereign Identity (SSI), a paradigm that empowers individuals with control over their own digital identities through the use of verifiable credentials. This paper introduces a novel access control framework that leverages the principles of SelfSovereign Identity to significantly enhance the security of system access based on the users' credentials. By integrating the decentralized and user-centric nature of SSI, our proposed framework aims to address existing vulnerabilities in traditional access control systems. It provides a robust, scalable, and controlled mechanism that ensures higher levels of trust and security in digital interactions. This approach aligns with the broader digital identity trends favoring transparency, user autonomy, and trust. © 2024 IEEE.

关键词： Electronic document identification systems

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Imaging atomic-scale chemistry from fused multi-modal electron microscopy

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npj Computational Materials 2022年第1期8卷 164-171页

作者： Jonathan Schwartz Zichao Wendy Di Yi Jiang Alyssa J.Fielitz Don-Hyung Ha Sanjaya D.Perera Ismail El Baggari Richard D.Robinson Jeffrey A.Fessler Colin Ophus Steve Rozeveld Robert Hovden Department of Materials Science and Engineering University of MichiganAnn ArborMIUSA Mathematics and Computer Science Division Argonne National LaboratoryLemontILUSA Advanced Photon Source Facility Argonne National LaboratoryLemontILUSA Dow Chemical Co. MidlandMIUSA Department of Material Science and Engineering Cornell UniversityIthacaNew YorkUSA School of Integrative Engineering Chung-Ang UniversitySeoulRepublic of Korea Department of Physics Cornell UniversityIthacaNYUSA The Rowland Institute at Harvard CambridgeMAUSA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMIUSA National Center for Electron Microscopy Lawrence Berkeley National LaboratoryMolecular FoundryBerkeleyCAUSA Applied Physics Program University of MIchiganAnn ArborMIUnited States

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic ***,fused multi-modal electron microscopy offers high signal-to-noise ratio(SNR)recovery of material chemistry at nano-and atomic-resolution by coupling correlated information encoded within both elastic scattering(high-angle annular dark-field(HAADF))and inelastic spectroscopic signals(electron energy loss(EELS)or energy-dispersive x-ray(EDX)).By linking these simultaneously acquired signals,or modalities,the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector *** many cases,the dose requirements can be reduced by over one order of *** high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

关键词： materials chemistry fused

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Industry 4.0: Architecture and Equipment Revolution

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computers, Materials & Continua 2021年第2期66卷 1175-1194页

作者： Ahmed Bashar Fakhri Saleem Latteef Mohammed Imran Khan Ali Safaa Sadiq Basem Alkazemi Prashant Pillai Bong Jun Choi Department of Medical Instrumentation Techniques Engineering Electrical Engineering Technical CollegeMiddle Technical UniversityBaghdadIraq Department of Electrical Engineering University of Engineering and Technology PeshawarPeshawarPakistan School of Mathematics and Computer Science University of WolverhemptonWulfruna StreetWolverhemptonUK Center of Artificial Intelligence Research and Optimization Torrens UniversityBrisbaneAustralia Department of Computer Science College of Computer&Information SystemsUmm Al-Qura UniversityMeccaSaudi Arabia School of Computer Science and Engineering Soongsil UniversitySeoulSouth Korea

The development of science and technology has led to the era of Industry *** core concept is the combination of“material and informationization”.In the supply chain and manufacturing process,the“material”of the physical entity world is realized by data,identity,intelligence,and *** 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional *** goal is“maximizing production efficiency,minimizing production costs,and maximizing the individual needs of human beings for products and services.”Achieving this goal will surely bring about a major leap in the history of the industry,which will lead to the“Fourth Industrial Revolution.”This paper presents a detailed discussion of industrial big data,strategic roles,architectures,characteristics,and four types of innovative business models that can generate profits for *** key revolutionary aspect of Industry 4.0 is explained,which is the equipment *** important attributes of equipment are explained under the Industry 4.0 perspective.

关键词： Industry 4.0 big data smart manufacturing business model equipment revolution

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Digital Shadow Sensor Framework for Smart Agriculture: Time Series Prediction Through Data Segmentation and Clustering

Digital Shadow Sensor Framework for Smart Agriculture: Time ...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Luca Sciullo Angelo Trotta Sara Bosi Luciano Bononi Marco Di Felice Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center on Electronic Systems “Ercole De Castro” University of Bologna Italy Department of Agricultural and Food Sciences University of Bologna Italy

In IoT-based smart agriculture systems, the acquisition of high-quality sensing data plays a key role in enabling informed decisions by farmers. However, the deployment of wireless sensors in remote agricultural areas often entails facing frequent network disconnections. Furthermore, the necessity for uninterrupted monitoring is in contrast with the energy-saving requirements of battery-operated IoT devices. In this paper, we propose a solution that decouples the connection between IoT sensors and the cloud by introducing an intermediary software stratum acting as an edge data proxy. More specifically, our framework assigns a Digital Shadow to each IoT device, endowed with the capability to predict forthcoming sensor values during devices' low-power modes or network disconnections. Three main contributions are provided in this paper. First, we present the architecture and operations of our framework, enabling the orchestration of phases of sensor readings and data forecasting and the consequential adjustment of the device sampling frequency. Second, we introduce a novel time series forecasting approach that aims at identifying diverse patterns in the sensor time series and at instantiating distinct Machine Learning (ML) models for each individual pattern. Third, we validate our framework through real-world soil moisture datasets. The experimental results showcase the efficacy of our approach in delivering accurate forecasts, outperforming single-model and context-aware methodologies.

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ZION: A Scalable W3C Web of Things Directory

ZION: A Scalable W3C Web of Things Directory

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Cristiano Aguzzi Lorenzo Gigli Ivan Zyrianoff Luca Roffia Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center on Electronic Systems “Ercole De Castro” University of Bologna Italy Department of Electrical Electronic and Information Engineering “Guglielmo Marconi” University of Bologna Italy

The proliferation of non-interoperable smart objects within the Internet of Things (IoT) has led to a fragmented and heterogeneous landscape. The Web of Things (WoT), particularly the W3C WoT, has emerged as a promising solution to this challenge, enabling seamless integration across IoT platforms and domains by extending known web standards. This paper introduces Zion, an open-source scalable W3C Thing Description Directory (TDD) designed to efficiently address the indexing and querying of Thing Descriptions (TDs) and the associated Web Things (WTs). Zion offers a standard API for performing CRUDL operations while supporting metadata querying through JSONPath. We further demonstrate its practical utility through real-world deployments, applying Zion to Structural Health Monitoring (SHM) and integrating it with IoT devices alongside blockchain technology. Comparative analysis with the other TDD implementations complying with the W3C standards – e.g., WoT Hive and TinyIoT – demonstrates that Zion outperforms both. It exhibits response times approximately ten times lower than those observed in the compared TDDs under high workloads.

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Bioinformatics and systems biology approaches to identify molecular targets and pathways shared between Schizophrenia and bipolar disorder

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Informatics in Medicine Unlocked 2024年 49卷

作者： Khatun, Mst Tania Rana, Humayan Kabir Hossain, Md Arju Lakshmanna, Kuruva Rahman, Md Mafizur Parvin, Anzana Rahman, Md Habibur Department of Biotechnology and Genetic Engineering Islamic University Department of Computer Science and Engineering Green University of Bangladesh Department of Microbiology Primeasia University School of Computer Science Engineering and Information Systems VIT Department of Computer Science and Engineering Islamic University Center for Advanced Bioinformatics and Artificial Intelligence Research Islamic University

Schizophrenia is a heterogeneous spectrum disorder of unknown etiology that is going to be a public concern around the world. The molecular association between the pathophysiology of schizophrenia (SP) and bipolar disorder (BD) is still not clear enough. To address this gap, we developed an integrated bioinformatics approach to identify common molecular signatures and possible interactive pathways that are common in the molecular pathogenic process between SP and BD. We employed pluripotent stem cell (iPSC)-derived cortical interneuron transcriptomic data and post-mortem brain transcriptomic data from patients with SP and BD, respectively. Twenty common differentially expressed genes (DEGs) were identified between SP and BD. Positive regulation of cyclic AMP (cAMP)-mediated signaling and regulation of the metabolic process were found to be common biological pathways between these two disorders. Protein-protein interactions and transcriptional regulatory interactions identified with hub-bottleneck proteins (LY6G5B, DLGAP2, DXO, EGR3, BAG6, DL-GAP2, SKIV2L, CSNK2B and RXRB), regulatory transcription factors (FOXC1, GATA2, RELA and ELK4), and regulatory microRNAs (hsa-mir-34a-5p, hsa-mir23b-3p, hsa-mir-146a-5p, hsa-mir-27a-3p, and hsa-mir-1-3p) are as key molecular signatures between SP and BD. Protein-chemical and protein-drug interactions revealed valproic acid, antirheumatic agents, trichostatin A, aarsenic, and 4-(5-benzo (1,3) dioxol-5-yl-4-pyridin-2yl-1H-imidazole-2-yl) benzamide and isopropyl alcohol compounds could be used as a potential therapeutic target molecule against SP and BD. The research findings would be used in wet lab-based research to further clarify potential therapeutic targets for the treatment of SP and BP disorders. © 2024 The Authors

关键词： Bipolar Differentially expressed genes microRNAs Pathways Schizophrenia Transcription factors

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An IoT-AI Toolchain for Structural Health Monitoring

An IoT-AI Toolchain for Structural Health Monitoring

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IEEE International Workshop on Measurements and Networking Proceedings (M&N)

作者： Mattia Forlesi Alfonso Esposito Leonardo Ciabattini Luca Sciullo Marco Di Felice Soroosh Kamali Emma Ghini Stefano Silvestri Alessandro Marzani Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center on Electronic Systems “Ercole De Castro” - ARCES University of Bologna Italy Department of Civil Chemical Environmental and Materials Engineering University of Bologna Italy

ISBN: (数字)9798350370539

ISBN: (纸本)9798350370546

Next-generation Structural Health Monitoring (SHM) systems can benefit significantly from the integration of Internet of Things (IoT) and Machine Learning (ML) technologies to assess the integrity of civil buildings and infrastructures. However, the deployment of scalable and accurate data analytics techniques for damage detection and classification is often hindered by the processing of voluminous sensor data and by the complexity of generating representative pseudo datasets for actual healthy and damaged conditions. We propose a framework for SHM data management and analytics that draws upon competencies and tools from various domains, including IoT, numerical modeling, and AI. Our methodology spans from data gathering from on-field sensors, data processing upon their physical interpretation, up to an alarming system. It integrates data-driven and model-based approaches to perform anomaly detection and, consequentially, to classify damage characteristics via a set of dedicated algorithms. In this work, we specifically describe the IoT-AI architecture for SHM, highlighting critical points and further developments. In addition, we present an illustrative implementation carried out on a concrete structure by reporting examples of possible outcomes of our framework.

关键词： Data analysis Buildings Machine learning Data models Numerical models Complexity theory Classification algorithms

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Self-Propelled Capsule Endoscope and Tracking Control of Its Wireless Power Supply Coil

Self-Propelled Capsule Endoscope and Tracking Control of Its...

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Robotics, engineering, science, and Technology (RESTCON), International Conference on

作者： Takahiro Ito Kohei Fujita Kenji Miyauchi Sunao Murakami Hiroshi Ohtake Chihiro Katsuta Kaoru Karasawa Akane Tanaka Hiroshi Matsuda Toshihiro Kimura Hiromu Kutsumi Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Division of Animal Life Science Tokyo University of Agriculture and Technology Fuchu-shi Japan Savior Inc Yokohama-Sh Japan Center for Clinical Research and Advanced Medicine Establishment Shiga University of Medical Science Otsu-Shi Japan

We have developed the self-propelled capsule endoscope. Although it is the same size as a conventional capsule endoscope, with a diameter of 11 mm and a length of 31 mm, it can travel inside the gastrointestinal tract. A running mechanism that uses vibrations allows it to run without any protrusions on the outer shell. Therefore, there is no risk of harming the inside of the body. This is a noteworthy feature of this capsule. Experiments have confirmed that this capsule can travel in the intestines of living dogs. Because the power supply to this capsule needs to continue stably for over an hour, we developed a wireless power supply method to the internal capsule. Conventional wireless power supply with a fixed power transmission coil had the problem that power supply would be interrupted if the capsule moved. Therefore, we investigated stabilizing the power supply by moving the power transmission coil in X-Y to follow the capsule in response to increases and decreases in the power supply. We were able to confirm the feasibility through experiments. This technology can be expected to perform endoscopic examinations with less burden on both patients and doctors, and can also be applied to power supply to medical devices inside the body.

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