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Journal articles on the topic 'Instrumentation RQN'

Author: Grafiati

Published: 12 October 2024

Last updated: 19 July 2025

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1

Shine, Philip, and Michael D. Murphy. "Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study." Sensors 22, no. 1 (2021): 52. http://dx.doi.org/10.3390/s22010052.

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Machine learning applications are becoming more ubiquitous in dairy farming decision support applications in areas such as feeding, animal husbandry, healthcare, animal behavior, milking and resource management. Thus, the objective of this mapping study was to collate and assess studies published in journals and conference proceedings between 1999 and 2021, which applied machine learning algorithms to dairy farming-related problems to identify trends in the geographical origins of data, as well as the algorithms, features and evaluation metrics and methods used. This mapping study was carried

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López, Óscar, Clara Murillo, and Alfonso González. "Systematic Literature Reviews in Kansei Engineering for Product Design—A Comparative Study from 1995 to 2020." Sensors 21, no. 19 (2021): 6532. http://dx.doi.org/10.3390/s21196532.

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Individual products and models on the market must be specifically differentiated from the rest to meet user demand. In terms of consumer purchasing behaviour, consumers increasingly base their decisions on subjective terms or the impression that the product leaves on them, both in terms of functionality, usability, safety, and price adequacy, and regarding the emotions and feelings that it triggers in them. This demand has lead both Asia and Europe to implement new methodologies to develop new products, such as “emotional design” or Kansei engineering. This paper presents a systematic literatu

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Poslad, Stefan, Tayyaba Irum, Patricia Charlton, et al. "How IoT-Driven Citizen Science Coupled with Data Satisficing Can Promote Deep Citizen Science." Sensors 22, no. 9 (2022): 3196. http://dx.doi.org/10.3390/s22093196.

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To study and understand the importance of Internet of Things-driven citizen science (IoT-CS) combined with data satisficing, we set up and undertook a citizen science experiment for air quality (AQ) in four Pakistan cities using twenty-one volunteers. We used quantitative methods to analyse the AQ data. Three research questions (RQ) were posed as follows: Which factors affect CS IoT-CS AQ data quality (RQ1)? How can we make science more inclusive by dealing with the lack of scientists, training and high-quality equipment (RQ2)? Can a lack of calibrated data readings be overcome to yield otherw

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Devalma, Anzhar, Jufrizel Jufrizel, Aulia Ullah, and Ahmad Faizal. "Reliability Analysis of Steam Turbine Instrumentation Using the Failure Mode and Effect Analysis (FMEA) Method at PT. PLN Nusantara Power UP Tenayan." Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) 11, no. 2 (2024): 185–92. http://dx.doi.org/10.33019/jurnalecotipe.v11i2.4504.

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PT. PLN Nusantara Power Unit Generation Tenayan is a company operating in the Steam Power Plant sector in Pekanbaru, Indonesia. One of the main components of a steam power plant (PLTU) is a steam turbine. A steam turbine is a machine that functions to convert kinetic energy into electrical current. Operational failures are often caused by less than optimal instrumentation in the steam turbine. This research uses the failure mode and effect analysis (FMEA) method with the aim of identifying the type of failure, the cause of the failure, the effect of the failure, and determining the RPN value.

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Hidayatulloh, Nurma M., and Tedjo Sukmono. "Determination of Production Instrumentation Equipment Maintenance Intervals In the Paper Industry." PROZIMA (Productivity, Optimization and Manufacturing System Engineering) 4, no. 1 (2021): 23–31. http://dx.doi.org/10.21070/prozima.v4i1.1275.

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PT. XYZ is a manufacturing industry engaged in paper processing with afval raw materials. The problem faced is machine failure that occurs suddenly without predictability, this is because there is no scheduled maintenance (preventive main-tenance). The object of this research is focused on production instrumentation equipment. This study uses the Failure Mode and Effect Analyzer (FMEA) method to identify the causes of failure and the effects of these failures by determining the critical value of the component, namely the Risk Priority Number (RPN) which is the largest, then the Reliability Cen

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Vaezi-Nejad, SM, M. Cox, and N. Cooper. "Novel instrumentation for measurement of relative intensity noise." Transactions of the Institute of Measurement and Control 34, no. 4 (2011): 477–86. http://dx.doi.org/10.1177/0142331211399330.

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Laser diode relative intensity noise (RIN) metrology capabilities have been developed and demonstrated, providing significantly improved sensitivity and accuracy compared with existing methods. The novel use of the demonstrated reference noise source has shown significant advantages, achieving improved sensitivity, reducing measurement accuracy as low as ±1 dB and simplifying the system calibration methodology, thus improving flexibility. Laser RINs of between 10 and 14 dB below the shot RIN have been shown (typically −170 dBm/Hz), which is a direct result of the improved system sensitivity. A

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Rahmadana, Aulia, Jufrizel Jufrizel, Hilman Zarory, and Putut Son Maria. "Reliability Analysis of Coal Feeder Instrumentation Using Failure Mode and Effect Analysis (FMEA) at PT. PLN Nusantara Power UP Tenayan." Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) 11, no. 2 (2024): 170–76. http://dx.doi.org/10.33019/jurnalecotipe.v11i2.4505.

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PLN Nusantara Power UP Tenayan is a coal-fired power plant supplying electricity to the Riau region with a capacity of 2 x 110 MW. Operating 24/7, the plant faces frequent failures, particularly in the instrumentation components of the coal feeder. This research employs the Failure Mode and Effect Analysis (FMEA) method to identify and analyze these failures. The Risk Priority Number (RPN), calculated by multiplying severity, occurrence, and detection ratings, helps determine the failure level. Research stages include a preliminary study, problem identification, observations and interviews, da

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S, Raehan Adillah, Jufrizel Jufrizel, Putut Son Maria, and Hilman Zarory. "Analisa Keandalan Instrumentasi Boiler Feed Pump Menggunakan Metode Failure Mode and Effect Analysis (FMEA) di PT.PLN Nusantara Power UP Tenayan." JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI 9, no. 3 (2024): 276. http://dx.doi.org/10.36722/sst.v9i3.2882.

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<p><em> </em><strong>PT. PLN Nusantara Power UP Tenayan is a company operating in the power generation sector and focuses on operating PLTUs Tenayan, Indonesia. One part of the machine that influences the operation of the generator is the boiler feed pump. Lack of optimal boiler feed pump instrumentation often results in failure in operating activities. This research uses the Failure Mode and Effect Analysis (FMEA) method with the research objective of finding out the causes of failures that occur, identifying the type of failure, and determining the RPN value and the i

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M.Padol Padilla, Jufrizel, Putut Son Maria, and Ahmad Faizal. "A Reliability Analysis of Steam Condenser Instrumentation Using Failure Mode and Effect Analysis (FMEA)." Jurnal Sistem Cerdas 7, no. 2 (2024): 155–62. http://dx.doi.org/10.37396/jsc.v7i2.426.

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Abstract—PT PLN Nusantara Power UP Tenayan is a steam power plant (PLTU) with a capacity of 2 x 110 MW which is a buffer for the electricity system in the Central Sumatra section. In the production process of PT PLN Nusantara Power UP Tenayan it does not always go well,. So that it will have an impact on the production stages of the power plant. One of the production machines that often fails and disrupts the production stage is the steam condenser. This research uses the Failure Mode And Effect Analysis Method which aims to identify the type of failure, cause of failure, effect of failure, an

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Andriyan, Septa, Jufrizel Jufrizel, Aulia Ulah, and Ahmad Faizal. "Analisa Keandalan Instrumentasi Pada Lime Kiln Unit Menggunakan Metode Reliability Centered Maintenance (RCM) di PT. Indah Kiat Pulp and Paper Perawang." JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI 9, no. 2 (2024): 205. http://dx.doi.org/10.36722/sst.v9i2.2785.

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<p><strong>PT. Indah Kiat Pulp and Paper Perawang is a company that prioritizes paper production. There is a crucial unit known as the lime kiln within the company. Issues occurring within this unit often disrupt the overall production process. Therefore, conducting reliability analysis on the instrumentation of this unit is highly important. This research utilizes the Reliability Centered Maintenance (RCM) method. The objective of this study is to determine which devices within the lime kiln are most vulnerable to problems by calculating the Risk Priority Number (RPN) for each com

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Torres Cedillo, Sergio G., and Philip Bonello. "Empirical identification of the inverse model of a squeeze-film damper bearing using neural networks and its application to a nonlinear inverse problem." Journal of Vibration and Control 24, no. 2 (2016): 357–78. http://dx.doi.org/10.1177/1077546316640985.

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The identification of nonlinear squeeze-film damper (SFD) bearings, typically used in aero-engines, has so far focused on their forward model (i.e. displacement input/force output). The contributions of this paper are the non-parametric identification of the inverse model of the SFD bearing (force input/displacement output) from empirical data, and its application to a nonlinear inverse rotor-bearing problem. This work is motivated by the need for a reliable substitute for internal instrumentation, to enable the identification of rotor unbalance using vibration data from externally mounted sen

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K.H.K. Prasad, B.T. Krishna. "RNN Based Deep Learning Approach for ECG Beat Classification." Tuijin Jishu/Journal of Propulsion Technology 44, no. 5 (2023): 200–210. http://dx.doi.org/10.52783/tjjpt.v44.i5.2451.

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The electrical patterns of the heart, captured through an electrocardiogram (ECG/EKG), serve as a diagnostic tool to identify potential issues such as heart attacks, irregular heart rhythms, heart failure, and arrhythmia, which manifests as irregularities in the heartbeat's rhythm. Deep Learning (DL) architectures have been successfully employed for arrhythmia detection and classification and offered superior performance to traditional shallow Machine Learning (ML) approaches. This paper introduces a novel approach utilizing deep learning techniques, specifically a Bidirectional Gated Recurren

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Zaluzec, Nestor J. "Innovative Instrumentation for Analysis of Nanoparticles: The π Steradian Detector". Microscopy Today 17, № 4 (2009): 56–59. http://dx.doi.org/10.1017/s1551929509000224.

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The analysis was finally completed, the data graphed, and I had to admit to myself, it was looking like an auspicious moment. Only a few weeks earlier, Charlie Lyman and I had been discussing a project that I had been working on for some time, one in which I was admittedly being deliberately vague concerning the details. However, I had promised to keep him updated when it succeeded. Given the date (April 1st) and the data in hand, I couldn't resist sharing with him (and a few colleagues) the first results from that experiment—and my thinly veiled attempt at a quasi-April Fools Day joke. After

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Ellwood, Stephen. "A Retrospective Review of Spinal Radiofrequency Neurotomy Procedures in Patients with Metallic Posterior Spinal Instrumentation – Is it Safe?" January 2018 1, no. 21;1 (2018): E477—E482. http://dx.doi.org/10.36076/ppj.2018.5.e477.

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Background: Recent studies have shown that medial branch radiofrequency neurotomy (RFN) procedures done at the level of a pedicle screw can increase pedicle screw temperature, and it has been speculated that pedicle screw heating may cause thermal injury. There has been a limited amount of investigation into the real-world safety profile of RFN procedures in patients with pedicle screws. Objectives: We aim to demonstrate that the occurrence of serious adverse events is rare for a medial branch RFN procedure completed at a level with metallic spinal hardware when performed according to the Spin

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Kriech, Matthew A., and John C. Conboy. "Using the Intrinsic Chirality of a Molecule as a Label-Free Probe to Detect Molecular Adsorption to a Surface by Second Harmonic Generation." Applied Spectroscopy 59, no. 6 (2005): 746–53. http://dx.doi.org/10.1366/0003702054280711.

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Chiral second harmonic generation (C-SHG) has been used for the label-free detection of (R)-(+)-1,1′-bi-2-naphthol (RBN) and (S)-(+)-1,1′-bi-2-naphthol (SBN) binding to planar-supported lipid bilayers of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphotidylcholine (POPC) based on the intrinsic chirality of the molecules. C-SHG adsorption isotherms of RBN and SBN reveal Langmuir adsorption behavior with binding constants of 2.7 ± 0.2 × 105 M−1 and 3.0 ± 0.1 × 105 M−1, respectively. The kinetics of RBN binding to a POPC bilayer was also measured. It was determined that the adsorption rate for RBN was 5

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Peña, Carlos, David Romero, and Julieta Noguez. "Workforce Learning Curves for Human-Based Assembly Operations: A State-of-the-Art Review." Applied Sciences 12, no. 19 (2022): 9608. http://dx.doi.org/10.3390/app12199608.

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In this state-of-the-art review, the authors explore the recent advancements in the topics of learning curve models and their estimation methods for manual operations and processes as well as the data collection and monitoring technologies used for supporting these. This objective is achieved by answering the following three research questions: (RQ1) What calculation methods for estimating the learning curve of a worker exist in the recent scientific literature? (RQ2) What other usages are manufacturing enterprises giving to the modern learning curve prediction models according to the recent s

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Sun, Shiming, Xin Shan, Xueyun Wei, Chunliang Tai, and Chao Liu. "Learning-based Similarity Join for Power Data." Journal of Physics: Conference Series 2425, no. 1 (2023): 012002. http://dx.doi.org/10.1088/1742-6596/2425/1/012002.

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Abstract The increasing instrumentation of physical and computing processes has given us unprecedented capabilities to collect massive volumes of time series. Power data is a typical kind of time series. Considering that the original time series data has ineluctable limitations such as uneven distribution, non-uniform length, poor sampling rate and noisy, we propose a learning=based similarity join for power data consisting of RNN encoder and matrix model. In addition, we develop the partition techniques by grouping process nodes following the matrix join model, ensuring the accuracy and effic

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Elbadawi, I., M. A. Ashmawy, W. A. Yusmawiza, I. A. Chaudhry, N. B. Ali, and A. Ahmad. "Application of Failure Mode Effect and Criticality Analysis (FMECA) to a Computer Integrated Manufacturing (CIM) Conveyor Belt." Engineering, Technology & Applied Science Research 8, no. 3 (2018): 3023–27. http://dx.doi.org/10.48084/etasr.2043.

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Fault finding and failure predicting techniques in manufacturing and production systems often involve forecasting failures, their effects, and occurrences. The majority of these techniques predict failures that may appear during the regular system production time. However, they do not estimate the failure modes and they require extensive source code instrumentation. In this study, we suggest an approach for predicting failure occurrences and modes during system production time intervals at the University of Hail (UoH). The aim of this project is to implement failure mode effect and criticality

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Elbadawi, Isam A.Q., Mohamed Arafat Ashmawy, Wan Ahmad Yusmawiza, Imran Ali Chaudhry, Naim Ben Ali, and Ayyaz Ahmad. "Application of Failure Mode Effect and Criticality Analysis (FMECA) to a Computer Integrated Manufacturing (CIM) Conveyor Belt." Engineering, Technology & Applied Science Research 8, no. 3 (2018): 3023–27. https://doi.org/10.5281/zenodo.1400610.

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Fault finding and failure predicting techniques in manufacturing and production systems often involve forecasting failures, their effects, and occurrences. The majority of these techniques predict failures that may appear during the regular system production time. However, they do not estimate the failure modes and they require extensive source code instrumentation. In this study, we suggest an approach for predicting failure occurrences and modes during system production time intervals at the University of Hail (UoH). The aim of this project is to implement failure mode effect and criticality

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Jellish, W. Scott, Randy L. Jensen, Douglas E. Anderson, and John F. Shea. "Intraoperative electromyographic assessment of recurrent laryngeal nerve stress and pharyngeal injury during anterior cervical spine surgery with Caspar instrumentation." Journal of Neurosurgery: Spine 91, no. 2 (1999): 170–74. http://dx.doi.org/10.3171/spi.1999.91.2.0170.

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Object. Recurrent laryngeal nerve (RLN) injury occurs after anterior cervical spine procedures. In this study the authors used intraoperative electromyographic (EMG) monitoring of the posterior pharynx as a surrogate for RLN function and monitored endotracheal tube (ET) cuff pressure to determine if there was an association between these variables and clinical outcome. Methods. Sixty patients in whom anterior cervical spine procedures were to be performed comprised the study population. After intubation, the ET cuff was adjusted to a just-seal volume and attached to a pressure monitor. A laryn

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Shen, Shun, Yunfei Sha, Chunhui Deng, Daxi Fu, Jiakuan Chen, and Xiangmin Zhang. "Comparison of Solid-Phase Microextraction, Supercritical Fluid Extraction, Steam Distillation, and Solvent Extraction Techniques for Analysis of Volatile Consituents in Fructus Amomi." Journal of AOAC INTERNATIONAL 88, no. 2 (2005): 418–23. http://dx.doi.org/10.1093/jaoac/88.2.418.

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Abstract Four sampling techniques, solid-phase microextraction (SPME), supercritical fluid extraction (SFE), steam distillation (SD), and solvent extraction (SE), were compared for the analysis of volatile constituents from a traditional Chinese medicine (TCM) of the dried ripe fruit of Fructus Amomi (Sha Ren). A total of 38 compounds were identified by gas chromatography/mass spectrometry. Different SFE and SPME parameters (modifier content, extraction pressure, and temperature for SFE and fibers, extraction temperature, and time for SPME) were studied. The results by SFE and SPME were compar

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Wang, Junyi, Qinggang Meng, Peng Shang, and Mohamad Saada. "Road surface real-time detection based on Raspberry Pi and recurrent neural networks." Transactions of the Institute of Measurement and Control 43, no. 11 (2021): 2540–50. http://dx.doi.org/10.1177/01423312211003372.

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This paper focuses on road surface real-time detection by using tripod dolly equipped with Raspberry Pi 3 B+, MPU 9250, which is convenient to collect road surface data and realize real-time road surface detection. Firstly, six kinds of road surfaces data are collected by utilizing Raspberry Pi 3 B+ and MPU 9250. Secondly, the classifiers can be obtained by adopting several machine learning algorithms, recurrent neural networks (RNN) and long short-term memory (LSTM) neural networks. Among the machine learning classifiers, gradient boosting decision tree has the highest accuracy rate of 97.92%

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Fatemimoghadam, Armita, Hamid Toshani, and Mohammad Manthouri. "Control of magnetic levitation system using recurrent neural network-based adaptive optimal backstepping strategy." Transactions of the Institute of Measurement and Control 42, no. 13 (2020): 2382–95. http://dx.doi.org/10.1177/0142331220911821.

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In this paper, a novel approach is proposed for adjusting the position of a magnetic levitation system using projection recurrent neural network-based adaptive backstepping control (PRNN-ABC). The principles of designing magnetic levitation systems have widespread applications in the industry, including in the production of magnetic bearings and in maglev trains. Levitating a ball in space is carried out via the surrounding attracting or repelling magnetic forces. In such systems, the permissible range of the actuator is significant, especially in practical applications. In the proposed scheme

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de Bakker, Christopher J., and Peter M. Fredericks. "Determination of Petroleum Properties by Fiber-Optic Fourier Transform Raman Spectrometry and Partial Least-Squares Analysis." Applied Spectroscopy 49, no. 12 (1995): 1766–71. http://dx.doi.org/10.1366/0003702953965975.

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The petroleum products unleaded gasoline and reformate have been analyzed by Fourier transform (FT) Raman spectrometry with the use of a fiber optic cable that allows a measurement to be carried out remotely from the spectrometer. Samples were contained in glass cuvettes, and collection of high-quality spectra was simple. Fuel properties such as research octane number (RON), motor octane number (MON), density, benzene content, and flexible volatility index (FVI) were determined by application of the partial least-squares multivariate statistical approach. Analytically useful calibrations ( R2

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Keller, L. M., K. A. Baker, M. A. Lazzara, and J. Gallagher. "A Comparison of Meteorological Observations from South Pole Station before and after Installation of a New Instrument Suite." Journal of Atmospheric and Oceanic Technology 26, no. 8 (2009): 1605–13. http://dx.doi.org/10.1175/2009jtecha1220.1.

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Abstract The Amundsen–Scott South Pole surface meteorological instrument suite was upgraded in 2004. To ensure that the new and old instruments were recording similar information, the two suites of instruments ran simultaneously for a year. Statistical analysis of the time series of temperature, pressure, and wind was performed to determine if there were any significant differences in the observations. Significant differences were found in some of the winter months for temperature and wind speed. No differences were found for the wind direction distribution. There are also noticeable differenc

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Napoli, Christian, Francesco Bonanno, and Giacomo Capizzi. "An hybrid neuro-wavelet approach for long-term prediction of solar wind." Proceedings of the International Astronomical Union 6, S274 (2010): 153–55. http://dx.doi.org/10.1017/s174392131100679x.

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AbstractNowadays the interest for space weather and solar wind forecasting is increasing to become a main relevance problem especially for telecommunication industry, military, and for scientific research. At present the goal for weather forecasting reach the ultimate high ground of the cosmos where the environment can affect the technological instrumentation. Some interests then rise about the correct prediction of space events, like ionized turbulence in the ionosphere or impacts from the energetic particles in the Van Allen belts, then of the intensity and features of the solar wind and mag

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Bai, Siqi, Mingjiang Yan, Qun Wan, Long He, Xinrui Wang, and Junlin Li. "DL-RNN: An Accurate Indoor Localization Method via Double RNNs." IEEE Sensors Journal 20, no. 1 (2020): 286–95. http://dx.doi.org/10.1109/jsen.2019.2936412.

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Jijin, Jofina, Boon-Chong Seet, and Peter Han Joo Chong. "Smart-Contract-Based Automation for OF-RAN Processes: A Federated Learning Use-Case." Journal of Sensor and Actuator Networks 11, no. 3 (2022): 53. http://dx.doi.org/10.3390/jsan11030053.

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The opportunistic fog radio access network (OF-RAN) expands its offloading computation capacity on-demand by establishing virtual fog access points (v-FAPs), comprising user devices with idle resources recruited opportunistically to execute the offloaded tasks in a distributed manner. OF-RAN is attractive for providing computation offloading services to resource-limited Internet-of-Things (IoT) devices from vertical industrial applications such as smart transportation, tourism, mobile healthcare, and public safety. However, the current OF-RAN design is lacking a trusted and distributed mechani

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Azariah, Wilfrid, Fransiscus Asisi Bimo, Chih-Wei Lin, Ray-Guang Cheng, Navid Nikaein, and Rittwik Jana. "A Survey on Open Radio Access Networks: Challenges, Research Directions, and Open Source Approaches." Sensors 24, no. 3 (2024): 1038. http://dx.doi.org/10.3390/s24031038.

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The open radio access network (RAN) aims to bring openness and intelligence to the traditional closed and proprietary RAN technology and offer flexibility, performance improvement, and cost-efficiency in the RAN’s deployment and operation. This paper provides a comprehensive survey of the Open RAN development. We briefly summarize the RAN evolution history and the state-of-the-art technologies applied to Open RAN. The Open RAN-related projects, activities, and standardization is then discussed. We then summarize the challenges and future research directions required to support the Open RAN. Fi

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Tang, Mincheng, Rezki Becheker, Pierre-Henry Hanzard, et al. "Low Noise High-Energy Dissipative Soliton Erbium Fiber Laser for Fiber Optical Parametric Oscillator Pumping." Applied Sciences 8, no. 11 (2018): 2161. http://dx.doi.org/10.3390/app8112161.

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We report on a mode-locked erbium-doped fiber laser delivering highly-chirped pulses with several tens of nanojoules of energy around 1560 nm and its exploitation to efficiently pump a fiber optical parametric oscillator (FOPO), thus enabling picosecond pulse generation around 1700 nm. The laser cavity features a high normal dispersion and mode-locking is sustained using tailored spectral filtering combined with nonlinear polarization evolution and a semiconductor saturable absorber. Numerical simulations show that the laser dynamics is governed by a strong mode-locking mechanism compensating

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Abhold, Mark E., and Michael C. Baker. "MCNP–REN: a Monte Carlo tool for neutron detector design." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 485, no. 3 (2002): 576–84. http://dx.doi.org/10.1016/s0168-9002(01)02106-4.

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Zhao, Qiulong, Chunxue Wang, Jiaxin Cheng, et al. "Pharmacokinetic Study of Coadministration with Cefuroxime Sodium for Injection Influencing ReDuNing Injection-Derived Seven Phytochemicals and Nine Metabolites in Rats." Journal of Analytical Methods in Chemistry 2022 (July 2, 2022): 1–17. http://dx.doi.org/10.1155/2022/2565494.

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According to the sixth edition of China’s “New Coronavirus Diagnosis and Treatment Plan (NCDTP),” ReDuNing injection (RDN) was firstly introduced to treat severe and critical COVID-19, whereas its combination with broad-spectrum antibiotics was suggested to take with extreme caution and full reasons. Therefore, we aim to describe the pharmacokinetics of seven active phytochemicals and semiquantification of nine relevant metabolites in ReDuNing injection (RDN) after combining with cefuroxime sodium (CNa) for injection in rat plasma. Male Sprague–Dawley rats were randomly assigned to six groups,

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Iturria-Rivera, Pedro Enrique, Han Zhang, Hao Zhou, Shahram Mollahasani, and Melike Erol-Kantarci. "Multi-Agent Team Learning in Virtualized Open Radio Access Networks (O-RAN)." Sensors 22, no. 14 (2022): 5375. http://dx.doi.org/10.3390/s22145375.

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Starting from the concept of the Cloud Radio Access Network (C-RAN), continuing with the virtual Radio Access Network (vRAN) and most recently with the Open RAN (O-RAN) initiative, Radio Access Network (RAN) architectures have significantly evolved in the past decade. In the last few years, the wireless industry has witnessed a strong trend towards disaggregated, virtualized and open RANs, with numerous tests and deployments worldwide. One unique aspect that motivates this paper is the availability of new opportunities that arise from using machine learning, more specifically multi-agent team

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Hamdan, Mutasem Q., Haeyoung Lee, Dionysia Triantafyllopoulou, et al. "Recent Advances in Machine Learning for Network Automation in the O-RAN." Sensors 23, no. 21 (2023): 8792. http://dx.doi.org/10.3390/s23218792.

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The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as a promising solution. O-RAN introduces disaggregation and virtualization, enabling network operators to deploy multi-vendor and interoperable solutions. However, managing and automating the complex O-RAN ecosystem presents numerous challenges. To address this, machine learning (ML) techniques have gained considerable attention in recent years, offering promising avenues for network automation in O-RAN. This paper presents

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Sepúlveda, Samuel, and Ania Cravero. "Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study." Applied Sciences 12, no. 11 (2022): 5563. http://dx.doi.org/10.3390/app12115563.

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Context: Software product lines (SPLs) have reached a considerable level of adoption in the software industry. The most commonly used models for managing the variability of SPLs are feature models (FMs). The analysis of FMs is an error-prone, tedious task, and it is not feasible to accomplish this task manually with large-scale FMs. In recent years, much effort has been devoted to developing reasoning algorithms for FMs. Aim: To synthesize the evidence on the use of reasoning algorithms for feature modeling. Method: We conducted a systematic mapping study, including six research questions. Thi

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Zhang, Jingjing, Yuanyuan Li, Teng Li, Lina Xun, and Caifeng Shan. "License Plate Localization in Unconstrained Scenes Using a Two-Stage CNN-RNN." IEEE Sensors Journal 19, no. 13 (2019): 5256–65. http://dx.doi.org/10.1109/jsen.2019.2900257.

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Firouzi, Ramin, and Rahim Rahmani. "5G-Enabled Distributed Intelligence Based on O-RAN for Distributed IoT Systems." Sensors 23, no. 1 (2022): 133. http://dx.doi.org/10.3390/s23010133.

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Edge-based distributed intelligence techniques, such as federated learning (FL), have recently been used in many research fields thanks, in part, to their decentralized model training process and privacy-preserving features. However, because of the absence of effective deployment models for the radio access network (RAN), only a tiny number of FL apps have been created for the latest generation of public mobile networks (e.g., 5G and 6G). There is an attempt, in new RAN paradigms, to move toward disaggregation, hierarchical, and distributed network function processing designs. Open RAN (O-RAN)

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Nguyen, Anh-Hang, and Hyuk-Kee Sung. "Improving the Performance of Optical Phased Array by Reducing Relative Intensity Noise of Optically Injection-Locked Laser Array." Photonics 9, no. 11 (2022): 868. http://dx.doi.org/10.3390/photonics9110868.

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Relative intensity noise (RIN) is an important factor that determines the performance of optical phased arrays (OPA) that are configured using semiconductor lasers as light emission sources. This study proposes a method of improving the optical signal-to-noise ratio (OSNR) of an OPA by reducing the RIN and using high coherence of optically injection-locked (OIL) laser arrays. We numerically demonstrated a laser RIN reduction of 22.7 dB by the OIL laser compared to a free-running laser. We achieved an OPA RIN reduction of 13.2 dB by combining the coherent outputs with the uncorrelated noise of

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Linden, Gabriel S., Semhal Ghessese, Danielle Cook, and Daniel J. Hedequist. "Pedicle Screw Placement in Adolescent Idiopathic Scoliosis: A Comparison between Robotics Coupled with Navigation versus the Freehand Technique." Sensors 22, no. 14 (2022): 5204. http://dx.doi.org/10.3390/s22145204.

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(1) Background: Robotics coupled with navigation (RAN) is a modern surgical platform shown to increase screw placement accuracy during pediatric scoliosis surgery. Our institution uses a technique which combines the RAN platform for apical pedicle screw placement and the freehand (FH) technique for terminal pedicle screw placement during scoliosis surgery (termed hybrid technique). We question if the complementary use of the RAN technology affects intraoperative outcomes, relative to the FH-only approach. (2) Methods: 60 adolescent idiopathic scoliosis (AIS) patients, ages 11–19 at surgery, wh

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Xiaoli, Chu, Yuan Hongfu, and Lu Wanzhen. "In-Line Monitoring of Several Pilot Scale Catalytic Reforming Units Using a Short-Wavelength near Infrared Analyser." Journal of Near Infrared Spectroscopy 13, no. 1 (2005): 37–45. http://dx.doi.org/10.1255/jnirs.455.

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This paper reports a novel application of in-line, short wavelength, near infrared (SW-NIR) spectroscopy to monitor eight pilot scale reforming units, for real-time determination of research octane number (RON) and aromatic compositions (benzene, toluene, xylene and total aromatics) of reforming gasoline, by an on-line SW-NIR system constructed by ourselves. Robust partial least squares calibration models for sample composition and measurement conditions were built using a global calibration set including off-line and in-line samples. Prediction results of the global models, over a six month p

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Thornton, John, Benedicta D. Arhatari, Mitchell Sesso, et al. "Failure Evaluation of a SiC/SiC Ceramic Matrix Composite During In-Situ Loading Using Micro X-ray Computed Tomography." Microscopy and Microanalysis 25, no. 3 (2019): 583–91. http://dx.doi.org/10.1017/s1431927619000187.

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AbstractIn this study, we have examined ceramic matrix composites with silicon carbide fibers in a melt-infiltrated silicon carbide matrix (SiC/SiC). We subjected samples to tensile loads while collecting micro X-ray computed tomography images. The results showed the expected crack slowing mechanisms and lower resistance to crack propagation where the fibers ran parallel and perpendicular to the applied load respectively. Cracking was shown to initiate not only from the surface but also from silicon inclusions. Post heat-treated samples showed longer fiber pull-out than the pristine samples, w

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Dryjański, Marcin, Łukasz Kułacz, and Adrian Kliks. "Toward Modular and Flexible Open RAN Implementations in 6G Networks: Traffic Steering Use Case and O-RAN xApps." Sensors 21, no. 24 (2021): 8173. http://dx.doi.org/10.3390/s21248173.

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The development of cellular wireless systems has entered the phase when 5G networks are being deployed and the foundations of 6G solutions are being identified. However, in parallel to this, another technological breakthrough is observed, as the concept of open radio access networks is coming into play. Together with advancing network virtualization and programmability, this may reshape the way the functionalities and services related to radio access are designed, leading to modular and flexible implementations. This paper overviews the idea of open radio access networks and presents ongoing O

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Hull, R. "Direct Transmission Electron Microscope Observations of Doping Variations in InP-Based Semiconductor Laser Diodes." Microscopy and Microanalysis 4, S2 (1998): 648–49. http://dx.doi.org/10.1017/s1431927600023369.

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The ability to map semiconductor doping distributions with high spatial resolution (∽10 nm) and high compositional sensitivity (of order 1 ppm) is of enormous importance to the microelectronics and optoelectronics industry. Although several methods (e.g. scanning capacitance microscopy, masked secondary ion mass spectroscopy, secondary electron microscopy, electron holography) are under development, no technique currently offers the combination of sufficient resolution, sensitivity and reproducibility to fully address characterization requirements. In this paper, we describe development of a t

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Pniov, Alexey, Andrey Zhirnov, Dmitriy Shelestov, et al. "Yb,Er:glass Microlaser at 1.5 µm for optical fiber sensing: development, characterization and noise reduction." ACTA IMEKO 5, no. 4 (2016): 24. http://dx.doi.org/10.21014/acta_imeko.v5i4.423.

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A fiber-pumped single-frequency microchip erbium laser was developed and characterized with the aim of using it in coherent Optical Time Domain Reflectometry (OTDR) measurements and sensing. The laser is pumped by a fiber-coupled 976 nm laser diode and provides 8 mW TEM00 single frequency output power at 1.54 µm wavelength, suitable for efficient coupling to optical fibers. The amplitude and phase noise of this 200 THz oscillator were experimentally investigated and a Relative Intensity Noise (RIN) control loop was developed providing 27 dB RIN peak reduction at the relaxation oscillation freq

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Shen, Wei, Weida Ni, Rui Yong, et al. "Estimating RQD for Rock Masses Based on a Comprehensive Approach." Applied Sciences 13, no. 23 (2023): 12855. http://dx.doi.org/10.3390/app132312855.

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Rock Quality Designation (RQD) is among the widely used measures of the quality of rock masses and can be derived through Monte Carlo stochastic process-based fracture network simulations. However, repeated simulations can yield variable RQD results. Here, we introduce a four-step approach that incorporates class ratio analysis to estimate the representative RQD, which includes (1) extracting the mean and confidence interval of the RQD sample, in terms of the Confidence Neutrosophic Number Cubic Value (CNNCV), (2) employing class ratio analysis to determine the thresholds of the number of virt

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Winey, Karen I., Jonathan H. Laurer, and Brian P. Kirkmeyer. "Ionic Nano-Aggregates in Polyethylene-Based Ionomers: Comparison of Stem and Saxs Results." Microscopy and Microanalysis 6, S2 (2000): 1110–11. http://dx.doi.org/10.1017/s1431927600038046.

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Semicrystalline ionomers are industrially important materials in adhesives, packaging, engineering thermoplastics, coatings, and more. The most common of these are based on poly(ethylene-ran-methacrylic acid), E/MAA random copolymers partially neutralized with various cations and produced by DuPont under the tradename Surlyn®. In 1990, Register and Cooper described the morphology of semicrystalline ionomers as crystalline lamellae separated by an amorphous polymeric matrix that contains isolated cation-rich domains. Their anomalous small angle X-ray scattering experiments are consistent with t

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O’Reilly, Jamie A., Jordan Wehrman, and Paul F. Sowman. "A Guided Tutorial on Modelling Human Event-Related Potentials with Recurrent Neural Networks." Sensors 22, no. 23 (2022): 9243. http://dx.doi.org/10.3390/s22239243.

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In cognitive neuroscience research, computational models of event-related potentials (ERP) can provide a means of developing explanatory hypotheses for the observed waveforms. However, researchers trained in cognitive neurosciences may face technical challenges in implementing these models. This paper provides a tutorial on developing recurrent neural network (RNN) models of ERP waveforms in order to facilitate broader use of computational models in ERP research. To exemplify the RNN model usage, the P3 component evoked by target and non-target visual events, measured at channel Pz, is examine

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Vilà, Irene, Oriol Sallent, and Jordi Pérez-Romero. "On the Design of a Network Digital Twin for the Radio Access Network in 5G and Beyond." Sensors 23, no. 3 (2023): 1197. http://dx.doi.org/10.3390/s23031197.

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A Network Digital Twin (NDT) is a high-fidelity digital mirror of a real network. Given the increasing complexity of 5G and beyond networks, the use of an NDT becomes useful as a platform for testing configurations and algorithms prior to their application in the real network, as well as for predicting the performance of such algorithms under different conditions. While an NDT can be defined for the different subsystems of the network, this paper proposes an NDT architecture focusing on the Radio Access Network (RAN), describing the components to represent and model the operation of the differ

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Xiong, Yongcheng, Wenhong Jia, Limin Zhang, Ying Zhao, and Lifang Zheng. "Feedforward Control of Piezoelectric Ceramic Actuators Based on PEA-RNN." Sensors 22, no. 14 (2022): 5387. http://dx.doi.org/10.3390/s22145387.

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Multilayer perceptron (MLP) has been demonstrated to implement feedforward control of the piezoelectric actuator (PEA). To further improve the control accuracy of the neural network, reduce the training time, and explore the possibility of online model updating, a novel recurrent neural network named PEA-RNN is established in this paper. PEA-RNN is a three-input, one-output neural network, including one gated recurrent unit (GRU) layer, seven linear layers, and one residual connection in the linear layers. The experimental results show that the displacement linearity error of piezoelectric cer

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Shin, Moonsun, Seonmin Hwang, Byungcheol Kim, Sungbo Seo, and Junghwan Kim. "IoT-Based Intelligent Monitoring System Applying RNN." Applied Sciences 12, no. 20 (2022): 10421. http://dx.doi.org/10.3390/app122010421.

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In this paper, we propose an intelligent monitoring framework based on the Internet of Things (IoT) by applying a Recurrent Neural Network (RNN) for the predictive maintenance of a biobanking system. RNN, which is one of the deep learning models, is used for time series data. It is called a sequence model because it processes inputs and outputs in sequence units. The proposed framework measures the internal temperature of the cryogenic freezer and the temperature of each component simultaneously, monitors the internal temperatures of internal and middle layers in real time, sends the sensing t

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