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13th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2023

作者： Wandy, Wandy Adi, Kusworo Ayu, Media Anugerah Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science South Jakarta Indonesia

ISBN: (纸本)9798350347319

Sports Science is an interdisciplinary and multidisciplinary science that strives to increase athletic performance and endurance. Sport Science recognizes and prevents injuries. Sensors and statistics formalize Sports Science. Runners need coaches and teams to support them before, during, and after the run race. Coaches generate running training plans to boost performance. Running race performances may be impacted by air pollution exposure while training, so coaches should consider limiting air pollution exposure when training. One of the external factors is Particulate Matter (PM2.5 and PM10). Sensors connecting to the Internet can record external factors and produce csv data. The foundation of supervised machine learning is the labeling process. Labeling a set of data is one of the laborious and time-consuming phases in every machine-learning application because it requires verifying the accuracy of the labels and making any necessary revisions. This research aimed to find a solution to automatically label numerous air particulate matter raw data using a rule based on parameters to reduce manual work, human errors and faster processes. This labeled data will later be used for supervised machine learning classification to support the coach in generating training programs for the runners in a Sports Information System. Based on Indonesia Air Quality index rule-based approach, labeled text data in csv has been generated and tested with PM2.5 and PM10 parameters in three scenarios with a 100% success rate. It was possible to automate the labeling process, and it explained how automation results in fast and accurate results. © 2023 IEEE.

关键词： Classification (of information)

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Low Complexity Broadband Array Processing in Dynamic Scenarios with Jamming

Low Complexity Broadband Array Processing in Dynamic Scenari...

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IEEE Conference on Vehicular Technology (VTC)

作者： Daniel V. De Lima João Paulo J. Da Costa Ricardo K. Miranda Antonio Arlis S. Da Silva Giovanni A. Santos José Alfredo R. Vargas Auzuir R. De Alexandria Postgraduate Program in Telecommunications Engineering (PPGET) IFCE Fortaleza Brazil Hamm-Lippstadt University of Applied Sciences (HSHL) Lippstadt Germany Graduate School for Applied Research in North Rhine-Westphalia (PKNRW) Bochum Germany Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Graduate Program in Computing (PPGC) UFRGS Porto Alegre Brazil Postgraduate Program in Mechatronics Engineering (PPMEC) UnB Brasilia Brazil

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Vehicle-to-Everything (V2X) networks require low-latency communications utilizing a broad spectrum while operating under jamming. In this sense, low complexity antenna array-based broadband jamming mitigation schemes are crucial in order to allow low latency communication and low-cost hardware. In this paper we propose low-complexity algorithms for signal recovery in broadband processing scenario applied to V2X. Numerical simulation of a jamming scenario demonstrate the proposed algorithm achieving the same performance in terms of signal-to-interference plus noise ratio (SINR) as the state-of-the-art while taking signiflcantly less time to compute.

关键词： Heuristic algorithms Prevention and mitigation Interference Numerical simulation Broadband communication Broadband antennas Jamming

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Mitigation potential of sulfate-resistant Portland cement for internal sulfate attack

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Journal of Building Pathology and Rehabilitation 2022年第1期7卷 1-10页

作者： Camanducaia, Laura P. M. Santos, Nathalia C. S. Medeiros-Junior, Ronaldo A. Federal University of Parana UFPR Curitiba Brazil Civil Engineering Studies Center (CESEC) Postgraduate Program in Civil Engineering (PPGEC) Federal University of Parana UFPR Curitiba Brazil Centro Politecnico Jardim das Americas Curitiba 81531-970 Parana Brazil

Concrete structures can have their durability affected due to internal sulfate attack (ISA). This attack can occur by the use of aggregates contaminated with sulfides, such as pyrite. The oxidation of pyrite releases sulfate ions into the cement matrix and favors the formation of expansive phases, such as gypsum and secondary ettringite. These expansions cause cracks and progressive degradation of concrete structures. Therefore, this study aimed to evaluate the effect of sulfate-resistant Portland cement in the likely mitigation of ISA. Mortar specimens with two types of cement (CEM I and CEM I SR) were cast with and without pyrite. These mortars naturally aged for 406 days and later were subjected to wetting and drying cycles at 40 °C to stimulate the ISA. The following properties of mortars were evaluated over time: length change and mass variation, tensile and compressive strengths, capillary and immersion water absorption, and electrical resistivity. The results showed that sulfate-resistant Portland cement only managed to reduce the length change in the first ages. The results of water absorption tests showed that the attack by sulfates due to pyrite oxidation is in the early stages. However, water absorption was reduced by 60% during the 56 wetting and drying cycles with water only. The electrical resistivity of the pyrite mortars was greatly affected (about 550%) over the 18 weeks of exposure. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Expansion Internal sulfate attack Mortar Sulfate resistant Portland cement

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Aerial multi-spectral AI-based detection system for unexploded ordnance

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Defence Technology（防务技术） 2023年第9期27卷 24-37页

作者： Seungwan Cho Jungmok Ma Oleg A.Yakimenko Republic of Korea Army Republic of Korea/Defense Acquisition Program Administration47Gwanmun-roGwacheon-siGyeonggi-do13809Republic of Korea Department of Defense Science Korea National Defense University1040Republic of Korea Hwangsanbul-ro Yangchon-myeonNonsan-siChungcheongnam-do33021Republic of Korea Department of Systems Engineering Naval Postgraduate SchoolUSA 1 University Circle MontereyCA93943USA

Unexploded ordnance(UXO)poses a threat to soldiers operating in mission areas,but current UXO detection systems do not necessarily provide the required safety and efficiency to protect soldiers from this *** technological advancements in artificial intelligence(AI)and small unmanned aerial systems(sUAS)present an opportunity to explore a novel concept for UXO *** new UXO detection system proposed in this study takes advantage of employing an AI-trained multi-spectral(MS)sensor on *** paper explores feasibility of AI-based UXO detection using sUAS equipped with a single(visible)spectrum(SS)or MS digital electro-optical(EO)***,it describes the design of the Deep Learning Convolutional Neural Network for UXO detection,the development of an AI-based algorithm for reliable UXO detection,and also provides a comparison of performance of the proposed system based on SS and MS sensor imagery.

关键词： Unexploded ordnance(UXO) Multispectral imaging Small unmanned aerial systems(sUAS) Object detection Deep learning convolutional neural network(DLCNN)

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Classification and tracking of items on a moving conveyor belt using convolutional networks and image processing

Classification and tracking of items on a moving conveyor be...

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Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), International Conference on

作者： Angelo Leite Medeiros De Góes Adrião Duarte Dória Neto Matheus Gomes Diniz Andrade Thiago Theiry De Oliveira Electrical and Computer Engineering Postgraduate Program Federal University of Rio Grande do Norte Natal Brazil Computer Engineering Federal University of Rio Grande do Norte Natal Brazil

The prolonged waiting time at supermarket checkout lines poses a significant challenge to the shopping experience, impacting customer satisfaction and operational efficiency. This paper presents a prototype that addresses this issue by utilizing computer vision and deep learning. The model, incorporating convolutional neural networks such as YOLO v4 tiny and YOLO v5 small, along with tools like OpenCV and Roboflow for dataset management, achieves a remarkable 98% mean average precision for two-class detection. It efficiently detects, classifies, tracks, and counts items on a mobile supermarket conveyor belt. Additionally, we introduce a versatile framework designed for seamless integration into real-world applications. It comprises a customizable monitoring application and simulator that facilitates synthetic image data generation. Managing diverse items in a supermarket presents a major challenge for data gathering, labeling, and training. In that sense, the importance of customizable monitoring and simulation tools is highlighted, emphasizing their practical role. Our findings demonstrate the feasibility of maintaining a minimal 0% to 2.85% precision tradeoff while using half of the data as synthetic for two-class detection, indicating potential practicality in supermarkets with proper scaling. In summary, this study brings tangible benefits to both customers and retailers, offering a potential to streamline, speed up, and cut costs in the supermarket checkout process.

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A Multi-Layered Methodology for Driver Behavior Analysis Using TinyML and Edge Computing

A Multi-Layered Methodology for Driver Behavior Analysis Usi...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Morsinaldo Medeiros Thommas Flores Marianne Silva Ivanovitch Silva Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte Natal Brazil Federal University of Alagoas Penedo Brazil

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

The rapid increase in vehicular sensor data and advances in Internet of Things (IoT) technologies pose a dual challenge and opportunity for real-time traffic management and driver behavior analysis in the domain of Intelligent Transportation Systems (ITS). The current gap lies in effectively processing this data at the network edge, which is critical for timely and efficient decision-making in ITS. Our study proposes a novel, multi-layered, stream-oriented data processing methodology specifically designed for edge computing environments to address this challenge. This approach integrates soft sensors, the Typicality and Eccentricity Data Analytics (TEDA) framework, and an incremental clustering algorithm to detect and classify driver behavior patterns. The emphasis on using low-energy hardware and TinyML techniques is crucial, aiming to optimize processing efficiency while minimizing the environmental impact. To substantiate the efficacy of our methodology, we conducted a practical case study in Natal-RN, Brazil, utilizing the Freematics One + OBD-II microcontroller device for real-world application and validation. This involved two participants and focused on real-time data analysis for driver profile detection. The preliminary results demonstrate a significant potential of our approach in accurately classifying driving behaviors and patterns, offering insights for enhancing vehicle efficiency and reducing fuel consumption. This study fills a critical gap in ITS. It sets the stage for future research in sustainable and adaptive transportation systems, leveraging the power of edge computing and incremental algorithms in real-time data stream processing.

关键词： Data analysis Soft sensors Image edge detection Heuristic algorithms Clustering algorithms Real-time systems Classification algorithms

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Thermo-optical properties of erbium-doped germanate-bismuth glasses

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Optical Materials 2025年 166卷

作者： Silva, Adriano Almeida Lima, Lucas Batista Silva da Silva, Isis Lee Garcia, Hans Anderson Bell, Maria José Valenzuela Kassab, Luciana Reyes Pires Santos, Francisco Eroni Paz Postgraduate Program in Physics Federal University of Piauí PI 64049550 Brazil Department of Physics Federal University of Juiz de Fora MG Juiz de Fora36036-900 Brazil Faculdade de Tecnologia São Paulo CEETEPS SP São Paulo01124060 Brazil Postgraduate Program in Engineering and Materials Science Federal University of Teresina PI 64049550 Brazil

In this study, we investigate the thermo-optical properties of GeO2–Bi2O3 glasses doped with different concentrations of rare earth ions by thermal lens technique;UV-VIS and photoluminescence (PL) spectroscopy, as well as measurements of thermal diffusivity, thermal conductivity and quantum efficiency, are presented aiming at potential photonic applications. High infrared fluorescence lifetimes around 4 ms and quantum efficiencies of ∼80 % for 1 % Er3+ concentration, determined via lifetime and thermal lens methods, enabled efficient laser operation. Positive ds/dT values confirmed the self-focusing nature beneficial for high-power systems. While quantum efficiencies decreased exponentially with rising Er3+ due to non-radiative relaxation from erbium-matrix interactions, reasonably high efficiencies above 74 % persisted at 1 % doping. The thermal diffusivity and conductivity exhibited little changes with varying Er3+ concentration and showed to be matrix dependent. © 2025 Elsevier B.V.

关键词： Quantum efficiency

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Analysis of the need for the development of learning media for IOT-Based smart building installation systems 6

Analysis of the need for the development of learning media f...

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6th International Conference on Technology and Vocational Teachers, ICTVT 2020

作者： Salsabila, A. Khairudin, M. Postgraduate Program of Electrical Engineering Education Universitas Negeri Yogyakarta Indonesia Department of Electrical Engineering Educatio Faculty of Engineering Universitas Negeri Yogyakarta Indonesia

Learning media is a means of learning for students that can provide a real picture of real work that has a high risk if it is carried out directly. Learning media has a role in facilitating students to be able to experience it directly with minimal risk from a practicum. Analyzing the need for making learning media is very important for the development of real learning media. This study aims to: (1) Determine the need for the development of learning media for IOT-based smart building installation systems in Vocational High School (VHS);(2) Analyzing the needs used in the development of learning media for IOT-based smart building installation systems in VHS. The results showed that the things needed in developing IOT learning media were seen from the technology used in the form of (1) Software based on media interaction with the internet using a visual studio;(2) Arduino Uno, temperature sensor device, ESP8266, gas sensor and light sensor are needed as hardware to reflect building capabilities;(3) The cloud computing system uses spread sheets to store data;(4) Internet network for uploading and downloading data. In its implementation, a needs analysis for the development of instructional media is needed so that in the later development process the media is developed appropriately and on target. The results of research and development research using the ADDIE method need the development of learning media for IOT-based smart building installation systems in vocational high schools to improve the learning abilities of students. © Published under licence by IOP Publishing Ltd.

关键词： Students

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POTENTIAL UTILIZATION OF CRUDE GLYCERIN IN ORGANOSOLV PRETREATMENT OF EUCALYPTUS RESIDUAL BIOMASS 30th

POTENTIAL UTILIZATION OF CRUDE GLYCERIN IN ORGANOSOLV PRETRE...

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30th European Biomass Conference and Exhibition, EUBCE 2022

作者： Lima, Izabela da Silva Soares, Ricardo Reis Rezende, Mylene Cristina Alves Ferreira Rossa, Vinicius Federal University of Uberlândia Chemistry Department Postgraduate Program in Biofuels Uberlândia Brazil FederalUniversity of Uberlândia Department of Chemical Engineering 1K Uberlândia Brazil

With the growing search for alternative and renewable energy sources, lignocellulosic biomass is becoming more and more relevant. In Brazil, due to the abundance and variety of biomass, the forestry sector can be highlighted as an important segment in the construction of a green economy, since they have been investing in the total use of forests, including generated residues. The objective of this work is to perform in the residual biomass of eucalyptus an organosolv pretreatment using as a solvent the crude glycerin resulting from the production of biodiesel, to promote the delignification of biomass, in addition to an efficient fractioning and generation of bioproducts of interest. The experiments were performed in batch reactors varying temperature, crude glycerin/water concentration, and reaction time. At the end of each experiment, the pretreated biomass, and a liquid phase (black liquor) containing the solubilized organosolv lignin were obtained. The biomasses "in nature" and pretreated were chemically characterized to evaluate the pretreatment efficiency, and the lignin was recovered from the black liquor quantified and characterized. As a result, high rates of biomass delignification were obtained after pretreatment, reaching a maximum content of 83.09%. In the recovery of lignin, a maximum of 11.25 g of lignin/100 g of biomass was reached, lignin that presented similar chemical characteristics with commercial lignin. Considering the satisfactory results obtained, the use of by-products (forestry residues and crude glycerin) can help to make the process viable, besides generating interesting bioproducts to the market and being able to be integrated with biorefineries. © 2022, ETA-Florence Renewable Energies., All rights reserved.

关键词： Biomass

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Evaluation of concrete self-healing with different fly ash contents and cracking ages by means of ultrasonic pulse velocity and compressive strength tests

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Journal of Building Pathology and Rehabilitation 2021年第1期6卷 1-12页

作者： Wons, Mayara Camara, Letícia Esteves, Ian Trentin, Priscila O. Medeiros-Junior, Ronaldo A. Federal University of Parana (UFPR) Curitiba Brazil Postgraduate Program in Civil Engineering (PPGEC) Federal University of Parana (UFPR) Curitiba Brazil Civil Engineering Studies Center (CESEC) Postgraduate Program in Civil Engineering (PPGEC) Federal University of Parana (UFPR) Curitiba Brazil Centro Politecnico Jardim das Americas Curitiba 81531-970 Parana Brazil

This study aims to analyze the self-healing of concretes with different fly ash contents. The concrete specimens with different amounts of fly ash in the composition of the cements were subjected to cracking at 7 days and 28 days of age. The cracking was generated by the application of 80% of the rupture load by compression for 2 min. After cracking, twelve wetting and drying cycles were performed to favor the development of self-healing. Each 7-day cycle (168 h) consisted of 78 h of immersion in lime-saturated water and 90 h of exposure to the laboratory environment. The analysis of the phenomenon occurred through the ultrasonic pulse velocity and compressive strength tests at the cracking dates and after the last wetting and drying cycle. In the samples submitted to cracking at 28 days of age, the reductions in ultrasonic pulse velocity after the cracking process was directly proportional to the fly ash content in the concrete. The reduction in ultrasonic pulse velocity due to cracking was 3.7% for cement with higher fly ash content, while cement without the presence of this mineral addition had a reduction of 1.9%. The compressive strength test was not an adequate technique to visualize the effects of concrete self-healing. The main contribution of the study was to prove that a non-destructive test can be applied to monitor the concrete self-healing. Also, the study showed the importance of crack age in the efficiency of self-healing in concretes with different fly ash contents. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG part of Springer Nature.

关键词： Compressive strength Fly ash Self-healing Ultrasonic pulse velocity

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