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Journal articles on the topic 'Real operating conditions (ROC)'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Onumanyi, A. J., E. N. Onwuka, A. M. Aibinu, O. C. Ugweje, and M. J. E. Salami. "A Real Valued Neural Network Based Autoregressive Energy Detector for Cognitive Radio Application." International Scholarly Research Notices 2014 (October 29, 2014): 1–11. http://dx.doi.org/10.1155/2014/579125.

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A real valued neural network (RVNN) based energy detector (ED) is proposed and analyzed for cognitive radio (CR) application. This was developed using a known two-layered RVNN model to estimate the model coefficients of an autoregressive (AR) system. By using appropriate modules and a well-designed detector, the power spectral density (PSD) of the AR system transfer function was estimated and subsequent receiver operating characteristic (ROC) curves of the detector generated and analyzed. A high detection performance with low false alarm rate was observed for varying signal to noise ratio (SNR

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Ghanbarirad, Maryam, Mehrdad Hashemi, Seyed Mehdi Saberi, and Ahmad Majd. "Nrf2 Dysregulation in Major Depressive and Bipolar Disorders." Galen Medical Journal 10 (December 31, 2021): e2074. http://dx.doi.org/10.31661/gmj.v10i0.2074.

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Background: Major depressive disorder (MDD) and bipolar disorder (BPD) are two of the most important mental disorders that greatly impact different aspects of life. These conditions imply heavy health and economic burden and are heterogeneous in nature. Inflammation is reported as the etiology of mental disorders. Nrf2 transcription factor plays a key role in the defense mechanisms against inflammation and oxidative stress. So, this study aimed to evaluate the expression level of Nrf2 in MDD and BPD patients and compared it with healthy control subjects. Materials and Methods: In this study, r

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Grant, Drew, Ian McLane, Valerie Rennoll, and James West. "Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System." Sensors 22, no. 23 (2022): 9530. http://dx.doi.org/10.3390/s22239530.

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Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable, and prompt method to screen for COVID-19 using easily acquirable physiological sounds. These systems have been demonstrated previously and have shown promise but lack robust analysis of their deployment in real-world settings when faced with diverse recording equipment, noise environments, and test subjects. The primary aim of this work is to begin to understand the impacts of these real-world deployment challenge

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Greuell, Wouter, Wietse H. P. Franssen, Hester Biemans, and Ronald W. A. Hutjes. "Seasonal streamflow forecasts for Europe – Part I: Hindcast verification with pseudo- and real observations." Hydrology and Earth System Sciences 22, no. 6 (2018): 3453–72. http://dx.doi.org/10.5194/hess-22-3453-2018.

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Abstract. Seasonal predictions of river flow can be exploited among others to optimise hydropower energy generation, navigability of rivers and irrigation management to decrease crop yield losses. This paper is the first of two papers dealing with a physical model-based system built to produce probabilistic seasonal hydrological forecasts, applied here to Europe. This paper presents the development of the system and the evaluation of its skill. The variable infiltration capacity (VIC) hydrological model is forced with bias-corrected output of ECMWF's seasonal forecast system 4. For the assessm

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Yates, North, Fernando Ponta, and Alayna Farrell. "Towards Universal Non-Dimensional Characterization of the Oscillatory Dynamics of Wind Turbine Rotors of Multiple Sizes." Dynamics 5, no. 2 (2025): 12. https://doi.org/10.3390/dynamics5020012.

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One concern in the field of Horizontal Axis Wind Turbines (HAWTs) is what control strategies are needed to handle gust pulses in the wind to prevent extreme oscillations of the blades to reduce fatigue stress, prevent blade rupture, and extend the turbine’s operational life. In order to design innovative control strategies to modify the blade’s oscillatory response, it is crucial to establish the fundamental vibrational behavior of the blades when excited by gust pulses of different frequencies and amplitudes present in the fluctuating wind inflow. In a series of previous works, the authors pr

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Ashutosh, Yadav, and Archana. "Reinforcement Learning with Variable Fractional Order Approach for MPPT Control of PV Systems for the Real Operating Climatic Condition." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 1 (2021): 44–53. https://doi.org/10.35940/ijrte.A5631.0510121.

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The designing of maximum power point tracking (MPPT) controller is an integral part of the PV array system to ensure a continuous supply of energy in dynamic environmental conditions. The most challenging part here is to design a model that can track the maximum point irrespective of variations in environmental conditions and its parametric variations. The model designed in this article combats both the challenges as it is based on reinforcement learning with fractional-order. The application of Deep Q-learning makes the model parametric free and once the model trained can be implanted in a di

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Shamala N., Srinivas S. ,. "Classification of Solar Cell Cracks Using Deep Learning." Journal of Electrical Systems 20, no. 4s (2024): 105–10. http://dx.doi.org/10.52783/jes.1859.

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This study evaluates the efficacy of a Deep Learning model in classifying solar cell images with and without cracks, crucial for early detection and maintenance of photovoltaic systems. The model demonstrates high overall accuracy (94%) and sensitivity (91%), indicating its proficiency in recognizing images with cracks while minimizing false positives. Receiver Operating Characteristic (ROC) analysis supports the model's robust discrimination between positive and negative cases, with an Area Under the Curve (AUC) of 0.93. Despite promising results, opportunities for improvement include dataset

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Liu, Chang, Jacob Dobson, and Peter Cawley. "Efficient generation of receiver operating characteristics for the evaluation of damage detection in practical structural health monitoring applications." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 473, no. 2199 (2017): 20160736. http://dx.doi.org/10.1098/rspa.2016.0736.

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Permanently installed guided wave monitoring systems are attractive for monitoring large structures. By frequently interrogating the test structure over a long period of time, such systems have the potential to detect defects much earlier than with conventional one-off inspection, and reduce the time and labour cost involved. However, for the systems to be accepted under real operational conditions, their damage detection performance needs to be evaluated in these practical settings. The receiver operating characteristic (ROC) is an established performance metric for one-off inspections, but t

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PIELECHA, Ireneusz, Wojciech CIEŚLIK, and Kinga FLUDER. "Analysis of energy management strategies for hybrid electric vehicles in urban driving conditions." Combustion Engines 173, no. 2 (2018): 14–18. http://dx.doi.org/10.19206/ce-2018-203.

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The pursuit of fuel consumption reduction by vehicles leads to a sudden increase in the share of hybrid and electric drives in the vehicle market. Replacing hybrid vehicles with electric vehicles requires long-term technological solutions, both for the infrastructure and the vehicles themselves. Therefore, one of the leading types of passenger car drives is currently the hybrid drive. The generated work share of electric drives used to power hybrid vehicles is a determinant of the viability of using electric drives. The article estimates the operating time share of electric and hybrid modes op

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Turechek, W. W., J. S. Hartung, and J. McCallister. "Development and Optimization of a Real-Time Detection Assay for Xanthomonas fragariae in Strawberry Crown Tissue with Receiver Operating Characteristic Curve Analysis." Phytopathology® 98, no. 3 (2008): 359–68. http://dx.doi.org/10.1094/phyto-98-3-0359.

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Angular leaf spot of strawberry is caused by the bacterium Xanthomonas fragariae. The disease is transmitted primarily through systemically infected nursery stock. This creates problems for nurseries wishing to export plants to Europe because of quarantine restrictions. Currently, field inspections for symptoms are used to certify plants free of X. fragariae, but visual inspection is not useful for detecting plants infected systemically. To detect systemic infections, polymerase chain reaction (PCR) is the desired tool because of its sensitivity, specificity, and ease of use. In this study, we

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Jesupriya J. "Hybrid Deep Learning for Air Quality Prediction: A Multi-Output, Attention-Based Approach for Pollutant and AQI Classification." Journal of Information Systems Engineering and Management 10, no. 22s (2025): 278–93. https://doi.org/10.52783/jisem.v10i22s.3510.

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Air pollution is a critical worldwide issue requiring precise forecasting for the deployment of efficient proactive interventions. The current study proposes a hybrid deep learning model based on multi-head attention mechanisms, bidirectional LSTMs, and dense layers to forecast the overall Air Quality Index (AQI) and identify specific thresholds of pollutant severity. The model utilizes deep learning algorithms for predictive accuracy to process primary air pollutants such as PM2.5, PM10, NO₂, CO, and O₃. Robustness tests were conducted by using different performance measures such as the F1-sc

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Convertino, Victor A., Robert W. Techentin, Ruth J. Poole, et al. "AI-Enabled Advanced Development for Assessing Low Circulating Blood Volume for Emergency Medical Care: Comparison of Compensatory Reserve Machine-Learning Algorithms." Sensors 22, no. 7 (2022): 2642. http://dx.doi.org/10.3390/s22072642.

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The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to compare for the first time the discriminative ability of two machine learning (ML) algorithms based on real-time feature analysis of arterial waveforms obtained from a non-invasive continuous blood pressure system (Finometer®) signal to predict the onset of decompensated shock: the compensatory reserve index (CRI) and the compensatory reserve metric (

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Kaliyannan, Devarajan, Mohanraj Thangamuthu, Pavan Pradeep, Sakthivel Gnansekaran, Jegadeeshwaran Rakkiyannan, and Alokesh Pramanik. "Tool Condition Monitoring in the Milling Process Using Deep Learning and Reinforcement Learning." Journal of Sensor and Actuator Networks 13, no. 4 (2024): 42. http://dx.doi.org/10.3390/jsan13040042.

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Tool condition monitoring (TCM) is crucial in the machining process to confirm product quality as well as process efficiency and minimize downtime. Traditional methods for TCM, while effective to a degree, often fall short in real-time adaptability and predictive accuracy. This research work aims to advance the state-of-the-art methods in predictive maintenance for TCM and improve tool performance and reliability during the milling process. The present work investigates the application of Deep Learning (DL) and Reinforcement Learning (RL) techniques to monitor tool conditions in milling operat

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Mikić, Danilo, Eleonora Desnica, Imre Kiss, and Vladimir Mikić. "RELIABILITY ANALYSIS OF ROLLING BALL BEARINGS CONSIDERING THE BEARING RADIAL CLEARANCE AND OPERATING TEMPERATURE." Advanced Engineering Letters 1, no. 1 (2022): 16–22. http://dx.doi.org/10.46793/adeletters.2022.1.1.3.

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The aim of the research conducted in this particular paper was related to a comprehensive reliability analysis of SKF 626 Open Deep Groove ball bearings, conducted under controlled laboratory conditions. The experimental research consisted of: measurements of radial internal clearance (RIC) in ball bearings, measurement methods for the detection of bearing operating temperature and rolling element bearing wear, complete with the cage deformation of the the damaged bearing, the failure of which was revealed after the examination. The inspected SKF 6206 open deep groove ball bearings operating u

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Cieslik, Wojciech, Filip Szwajca, Jedrzej Zawartowski, et al. "Capabilities of Nearly Zero Energy Building (nZEB) Electricity Generation to Charge Electric Vehicle (EV) Operating in Real Driving Conditions (RDC)." Energies 14, no. 22 (2021): 7591. http://dx.doi.org/10.3390/en14227591.

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The growing number of electric vehicles in recent years is observable in almost all countries. The country’s energy transition should accompany this rise in electromobility if it is currently generated from non-renewable sources. Only electric vehicles powered by renewable energy sources can be considered zero-emission. Therefore, it is essential to conduct interdisciplinary research on the feasibility of combining energy recovery/generation structures and testing the energy consumption of electric vehicles under real driving conditions. This work presents a comprehensive approach for evaluati

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Leśkiewicz, Maciej, Miron Kaliszewski, Maksymilian Włodarski, Jarosław Młyńczak, Zygmunt Mierczyk, and Krzysztof Kopczyński. "Improved real-time bio-aerosol classification using artificial neural networks." Atmospheric Measurement Techniques 11, no. 11 (2018): 6259–70. http://dx.doi.org/10.5194/amt-11-6259-2018.

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Abstract. Air pollution has had an increasingly powerful impact on the everyday life of humans. More and more people are aware of the health problems that may result from inhaling air which contains dust, bacteria, pollens or fungi. There is a need for real-time information about ambient particulate matter. Devices currently available on the market can detect some particles in the air but cannot classify them according to health threats. Fortunately, a new type of technology is emerging as a promising solution. Laser-based bio-detectors are characterizing a new era in aerosol research. They ar

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Jibunor, Jonathan Ebube, Benison Blessing Odigie, and Olamotse Roland Igbape. "A Bayesian Learning Framework Powered by IoT for Enhancing Highway Safety and Reducing Accidents: A Case Study of Benin-Onitsha Express Way." International Journal of Research and Innovation in Applied Science IX, no. X (2024): 334–60. http://dx.doi.org/10.51584/ijrias.2024.910032.

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The problem of frequent accidents on the Benin-Onitsha Express Way in Nigeria expressway necessitated the development of a predictive system that can enhance road safety. To address this issue, the study employed a framework that leverages real-time data collection from vehicles and road conditions to predict accident risks and deliver timely warnings to drivers. The methodology involved analyzing three years of historical accident data to identify high-risk areas and develop a cost-effective IoT model utilizing Bayesian learning techniques. The framework incorporated ESP8266-based client devi

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Jay, Singh, and Prakash Patidar Chandra. "Performance Evaluation of Identity Based Face Recognition Models in IoT Based Smart Home." International Journal of Science, Mathematics and Technology Learning 33, no. 1 (2025): 1112–23. https://doi.org/10.5281/zenodo.15493464.

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In recent years, the field of image recognition has been significantly advanced by deep learning, which offers highly effective techniques for feature extraction and classification. Face detection and recognition is a fundamental computer vision technology that enables systems to automatically identify and locate human faces in digital images or video frames. It supports a wide range of applications, including surveillance, facial recognition, and emotion analysis. OpenCV, a widely used open source computer vision library, provides an extensive suite of tools and pre-trained models that stream

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Moulin, D., B. Drubay, D. Acker та L. Laiarinandrasana. "A Practical Method Based on Stress Evaluation (σd Criterion) to Predict Initiation of Crack Under Creep and Creep-Fatigue Conditions". Journal of Pressure Vessel Technology 117, № 4 (1995): 335–40. http://dx.doi.org/10.1115/1.2842132.

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The behavior of defects like cracks in nuclear components operating at high temperature, where creep is significant, must be under control. There exists the need to have a practical method of analysis, which can be used by engineers, to calculate the time of initiation for defects existing at the start of life of nuclear components. This study presents the background, the development, the application, and results concerning validation work made for a simplified method named σd of prediction of initiation for nuclear structures made of 316L austenitic steel and operating at temperature where cr

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Meina, Michał, Ewa Ratajczak, Maria Sadowska, et al. "Heart Rate Variability and Accelerometry as Classification Tools for Monitoring Perceived Stress Levels—A Pilot Study on Firefighters." Sensors 20, no. 10 (2020): 2834. http://dx.doi.org/10.3390/s20102834.

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Chronic stress is the main cause of health problems in high-risk jobs. Wearable sensors can become an ecologically valid method of stress level assessment in real-life applications. We sought to determine a non-invasive technique for objective stress monitoring. Data were collected from firefighters during 24-h shifts using sensor belts equipped with a dry-lead electrocardiograph (ECG) and a three-axial accelerometer. Levels of stress experienced during fire incidents were evaluated via a brief self-assessment questionnaire. Types of physical activity were distinguished basing on accelerometer

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Zhao, Fumeng, Xingmin Meng, Yi Zhang, Guan Chen, Xiaojun Su, and Dongxia Yue. "Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology." Sensors 19, no. 12 (2019): 2685. http://dx.doi.org/10.3390/s19122685.

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Geological conditions along the Karakorum Highway (KKH) promote the occurrence of frequent natural disasters, which pose a serious threat to its normal operation. Landslide susceptibility mapping (LSM) provides a basis for analyzing and evaluating the degree of landslide susceptibility of an area. However, there has been limited analysis of actual landslide activity processes in real-time. The SBAS-InSAR (Small Baseline Subsets-Interferometric Synthetic Aperture Radar) method can fully consider the current landslide susceptibility situation and, thus, it can be used to optimize the results of

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Zhou, Yulong, Zekun Zheng, Han Duan, Chaoyang Zhao, and Zhonghai Wang. "A temperature-adaptive neutron-gamma discrimination algorithm for NaIL detector using a one-dimensional Convolutional Neural Network." Journal of Instrumentation 20, no. 03 (2025): P03032. https://doi.org/10.1088/1748-0221/20/03/p03032.

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Abstract Both the NaIL scintillator and silicon photomultiplier (SiPM) are susceptible to temperature fluctuations, which could change the characteristics of detected neutron and gamma waveforms and result in significant drift in the pulse shape discrimination (PSD) values with fixed PSD algorithm parameters, causing false alarms or missed alarms. This paper investigates a temperature-adaptive neutron-gamma discrimination algorithm using a one-dimensional convolutional neural network (1D-CNN). This algorithm can discriminate mixed neutron-gamma data automatically at various temperatures, rathe

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Blazek, Roman, Pavol Durana, and Katarina Valaskova. "Creative Accounting as an Apparatus for Reporting Profits in Agribusiness." Journal of Risk and Financial Management 13, no. 11 (2020): 261. http://dx.doi.org/10.3390/jrfm13110261.

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The economic results of a company are an important tool for many entities, e.g., for internal entities as well as for external entities. As the economic results of a company are often the only source of information that informs the company’s partners about the managerial activities of their company, it is necessary to present these economic results using real numbers. However, companies prefer to achieve better results by applying the principles of creative accounting, which leads to improved economic values being shown to be achieved during an accounting period. The purpose of this article is

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Haq, Muhammad Abdul, Iwan Kurnianto Wibowo, and Bima Sena Bayu Dewantara. "Improving the speed of ball detection process and obstacle detection process in ERSOW robot using omnidirectional vision based on ROS." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 3 (2021): 1365–71. https://doi.org/10.11591/ijeecs.v22.i3.pp1365-1371.

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This paper presents a novel approach for improving the computation speed of the ball detection and obstacle detection processes in our robot. The conditions of obstacle detection and ball detection in our robot still have a slow processing speed, this condition makes the robot not real-time and the robot's movement is hampered. To build a good world model, things to note are obstacle information and real-time ball detection. The focus of this research is to increase the speed of the process of the ball and obstacle detection around the robot. To increase the speed of the process, it is nec

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Giavarina, Davide, Mariarosa Carta, Alessandro Fabbri, Jacopo Manfredi, Edoardo Gasparotto, and Giuliano Soffiati. "Monitoring high-dose heparin levels by ACT and HMT during extracorporeal circulation: diagnostic accuracy of three compact monitors." Perfusion 17, no. 1 (2002): 23–26. http://dx.doi.org/10.1191/0267659102pf530oa.

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The correct monitoring of heparin therapy and its reversal determines the successful conduct of cardiovascular surgery with extracorporeal circulation (ECC). The activated coagulation time (ACT) and the heparin management test (HMT) are the most frequently used tests in the operating room. Three compact monitors for ACT or HMT are here evaluated. Forty samples were obtained, at 10-min intervals, from eight patients during ECC. The ACT or HMT was immediately performed using: Hemochron Junior™ ACT, CoaguCeck™ Pro (ACT) and Rapid Point Coag (HMT). Data were compared between them and with the hepa

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Uwihirwe, Judith, Markus Hrachowitz, and Thom A. Bogaard. "Landslide precipitation thresholds in Rwanda." Landslides 17, no. 10 (2020): 2469–81. http://dx.doi.org/10.1007/s10346-020-01457-9.

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Abstract Regional empirical-statistical thresholds indicating the precipitation conditions initiating landslides are of crucial importance for landslide early warning system development. The objectives of this research were to use landslide and precipitation data in an empirical-statistical approach to (1) identify precipitation-related variables with the highest explanatory power for landslide occurrence and (2) define both trigger and trigger-cause based thresholds for landslides in Rwanda, Central-East Africa. Receiver operating characteristics (ROC) and area under the curve (AUC) metrics w

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Lee, Chanjoo, Donggu Kim, Sungjung Kim, Un Ji, Jihyun Kim, and Dongwoo Ko. "Flow structure around an actual willow patch under different depth conditions." E3S Web of Conferences 40 (2018): 02049. http://dx.doi.org/10.1051/e3sconf/20184002049.

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Vegetation is one of the key factors in river management where environmental aspects as well as flood protection should be taken into consideration. Because of this, numerous studies have been done including experiments and hydrodynamic modelling. Because most of experimental studies were made in indoor laboratory flumes with artificial trees, there are still limitations in transfer of their result to actual channels. REC (River Experiment Center) of Korea has been operating three real-scale, nature-like outdoor experimental channels. In a straight channel, several 4x2 m actual willow patches

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Chen, Lihua, Yu Zhao, Jingjing Qiu, and Xiaosheng Lin. "Analysis and validation of biomarkers of immune cell-related genes in postmenopausal osteoporosis: An observational study." Medicine 103, no. 19 (2024): e38042. http://dx.doi.org/10.1097/md.0000000000038042.

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Postmenopausal osteoporosis (PMOP) is a common metabolic inflammatory disease. In conditions of estrogen deficiency, chronic activation of the immune system leads to a hypo-inflammatory phenotype and alterations in its cytokine and immune cell profile, although immune cells play an important role in the pathology of osteoporosis, studies on this have been rare. Therefore, it is important to investigate the role of immune cell-related genes in PMOP. PMOP-related datasets were downloaded from the Gene Expression Omnibus database. Immune cells scores between high bone mineral density (BMD) and lo

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Ransom, Joshua F., Aaron Galaznik, Emelly Rusli, Bruno Lempernesse, and Marc Berger. "Real-World Rates and Management of Thrombocytopenia Due to Cancer Treatment in Advanced/Metastatic Female Genitourinary Malignancies." Blood 134, Supplement_1 (2019): 4895. http://dx.doi.org/10.1182/blood-2019-129086.

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OBJECTIVES Thrombocytopenia is a common, potentially treatment-limiting hematologic side effect in cancer treatment (Kuter DJ, 2018). This is particularly true for female genitourinary (fGU) cancers, such as ovarian and endometrial, where treatment involves agents such as platinum-based agents, taxanes, PARP inhibitors, and gemcitabine (Lord R et al., 2018; Berek JS et al., 2018; Cassidy CA et al., 2001; Ten Berg MJ et al., 2001; Mahner S., 2015). Evidence has shown that dose reduction can be an effective way to address thrombocytopenia and avoid discontinuation of treatment (Lord R et al., 20

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Ramljak, Ivana, Dinko Begušić, and Josip Lorincz. "Operational Characteristics of Square-Law Combining Energy Detector in MIMO-OFDM Cognitive Radio Systems." Applied Sciences 12, no. 9 (2022): 4684. http://dx.doi.org/10.3390/app12094684.

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To ensure effective spectrum usage, cognitive radio networks (CRNs) are being investigated extensively. The important function of CRNs is spectrum sensing (SS). This is the process of sensing the unused frequency spectrum and deciding whether the signal transmission of a primary user (PU) exists. In this work, the results of a performance analysis related to detecting PU signals using the energy detection (ED) SS method realized by employing the square-law combining (SLC) technique are presented. The assessment of the effectiveness of the ED method is performed in relation to prominent communi

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Firoozi, Zahra, Elham Mohammadisoleimani, Farzaneh Bagheri, et al. "Evaluation of the Expression of Infection-Related Long Noncoding RNAs among COVID-19 Patients: A Case-Control Study." Genetics Research 2024 (February 15, 2024): 1–9. http://dx.doi.org/10.1155/2024/3391054.

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Background and Aims. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a worldwide pandemic, activates signaling cascades and leads to innate immune responses and secretion of multiple chemokines and cytokines. Long noncoding RNAs (lncRNAs) have a crucial role in inflammatory pathways. Through our search on the PubMed database, we discovered that existing research has primarily focused on examining the regulatory impacts of five lncRNAs in the context of viral infections. However, their role in regulating other conditions, including SARS-CoV-2, has not been explored. Therefore, thi

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Wang, Anyou, Rong Hai, Paul J. Rider, and Qianchuan He. "Noncoding RNAs and Deep Learning Neural Network Discriminate Multi-Cancer Types." Cancers 14, no. 2 (2022): 352. http://dx.doi.org/10.3390/cancers14020352.

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Detecting cancers at early stages can dramatically reduce mortality rates. Therefore, practical cancer screening at the population level is needed. To develop a comprehensive detection system to classify multiple cancer types, we integrated an artificial intelligence deep learning neural network and noncoding RNA biomarkers selected from massive data. Our system can accurately detect cancer vs. healthy objects with 96.3% of AUC of ROC (Area Under Curve of a Receiver Operating Characteristic curve), and it surprisingly reaches 78.77% of AUC when validated by real-world raw data from a completel

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Johnson, Nils P., Wenguang Li, Xi Chen, et al. "Diastolic pressure ratio: new approach and validation vs. the instantaneous wave-free ratio." European Heart Journal 40, no. 31 (2019): 2585–94. http://dx.doi.org/10.1093/eurheartj/ehz230.

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Abstract Aims The instantaneous wave-free ratio (iFR) and whole-cycle Pd/Pa investigate coronary physiology during non-hyperaemic conditions. To test for unique physiologic properties of the wave-free period when making resting coronary pressure measurements, we compared post hoc a diastolic pressure ratio (dPR) and Pd/Pa against iFR for numerical similarity and test/retest repeatability. Methods and results Eight hundred and ninety-three lesions from 833 subjects were included from the VERIFY 2 and CONTRAST studies. Diastolic pressure ratio and a linear transform of Pd/Pa were compared agains

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Kuizinienė, Dovilė, and Tomas Krilavičius. "Balancing Techniques for Advanced Financial Distress Detection Using Artificial Intelligence." Electronics 13, no. 8 (2024): 1596. http://dx.doi.org/10.3390/electronics13081596.

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Imbalanced datasets are one of the main issues encountered by artificial intelligence researchers, as machine learning (ML) algorithms can become biased toward the majority class and perform insufficiently on the minority classes. Financial distress (FD) is one of the numerous real-world applications of ML, struggling with this issue. Furthermore, the topic of financial distress holds considerable interest for both academics and practitioners due to the non-determined indicators of condition states. This research focuses on the involvement of balancing techniques according to different FD cond

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Gui, Junhao, Yaping Tian, Xinyu Wen, et al. "Serum microRNA characterization identifies miR-885-5p as a potential marker for detecting liver pathologies." Clinical Science 120, no. 5 (2010): 183–93. http://dx.doi.org/10.1042/cs20100297.

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Circulating miRNAs (microRNAs) are emerging as promising biomarkers for several pathological conditions, and the aim of this study was to investigate the feasibility of using serum miRNAs as biomarkers for liver pathologies. Real-time qPCR (quantitative PCR)-based TaqMan MicroRNA arrays were first employed to profile miRNAs in serum pools from patients with HCC (hepatocellular carcinoma) or LC (liver cirrhosis) and from healthy controls. Five miRNAs (i.e. miR-885-5p, miR-574-3p, miR-224, miR-215 and miR-146a) that were up-regulated in the HCC and LC serum pools were selected and further quanti

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Kostomakhin, Mikhail, Aleksandr Sayapin, Efim Pestryakov, and Nikolay Petrishchev. "IMPROVEMENT OF DIAGNOSTIC TOOLS FOR EQUIPMENT TO INCREASE ROI." Tekhnicheskiy servis mashin 62, no. 4 (2024): 32–39. https://doi.org/10.22314/2618-8287-2024-62-4-32-39.

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An increase in the efficiency of investments of an agricultural enterprise can be achieved through the optimal use of resources, including by increasing the efficiency of the equipment used. (Research purpose) The research purpose is studying the status of the issue in order to improve the efficiency of investments and justify the need to improve the means of diagnosing the technical condition of equipment. (Materials and methods) Carried out an analysis of developments and revealed that in order to be able to increase the investment efficiency indicator, diagnostic tools for agricultural mach

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Chhapariya, Koushikey, Emmett Ientilucci, Krishna Mohan Buddhiraju, and Anil Kumar. "Target Detection and Characterization of Multi-Platform Remote Sensing Data." Remote Sensing 16, no. 24 (2024): 4729. https://doi.org/10.3390/rs16244729.

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Detecting targets in remote sensing imagery, particularly when identifying sparsely distributed materials, is crucial for applications such as defense, mineral exploration, agriculture, and environmental monitoring. The effectiveness of detection and the precision of the results are influenced by several factors, including sensor configurations, platform properties, interactions between targets and their background, and the spectral contrast of the targets. Environmental factors, such as atmospheric conditions, also play a significant role. Conventionally, target detection in remote sensing ha

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Zimbelman, Eloise G., and Robert F. Keefe. "Development and validation of smartwatch-based activity recognition models for rigging crew workers on cable logging operations." PLOS ONE 16, no. 5 (2021): e0250624. http://dx.doi.org/10.1371/journal.pone.0250624.

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Analysis of high-resolution inertial sensor and global navigation satellite system (GNSS) data collected by mobile and wearable devices is a relatively new methodology in forestry and safety research that provides opportunities for modeling work activities in greater detail than traditional time study analysis. The objective of this study was to evaluate whether smartwatch-based activity recognition models could quantify the activities of rigging crew workers setting and disconnecting log chokers on cable logging operations. Four productive cycle elements (travel to log, set choker, travel awa

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Jiang, Dazuo, Huanqing Zou, Yike Guo, Fuqiang Tian, Hongqi Liu, and Yufeng Yin. "Simulation on Operating Overvoltage of Dropping Pantograph Based on Pantograph–Catenary Arc and Variable Capacitance Model." Applied Sciences 14, no. 16 (2024): 6861. http://dx.doi.org/10.3390/app14166861.

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When the electric locomotive pantograph is dropping, the interruption of pantograph catenary contact causes electromagnetic oscillation and arcing. The frequent arc burning that occurs due to charge accumulation results in the amplitude of overvoltage increasing gradually, posing a threat to locomotive high-voltage equipment. However, the physical mechanisms and characteristics of overvoltage are still unclear. This paper proposes a simulation model of operating overvoltage due to a dropping pantograph based on the pantograph–catenary arc and variable capacitance. Distributed RLC electromagnet

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Major, Vincent J., Neil Jethani, and Yindalon Aphinyanaphongs. "Estimating real-world performance of a predictive model: a case-study in predicting mortality." JAMIA Open 3, no. 2 (2020): 243–51. http://dx.doi.org/10.1093/jamiaopen/ooaa008.

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Abstract Objective One primary consideration when developing predictive models is downstream effects on future model performance. We conduct experiments to quantify the effects of experimental design choices, namely cohort selection and internal validation methods, on (estimated) real-world model performance. Materials and Methods Four years of hospitalizations are used to develop a 1-year mortality prediction model (composite of death or initiation of hospice care). Two common methods to select appropriate patient visits from their encounter history (backwards-from-outcome and forwards-from-a

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Kim, Heejung, Sunkook Kim, Mingoo Lee, et al. "Smart Patch for Skin Temperature: Preliminary Study to Evaluate Psychometrics and Feasibility." Sensors 21, no. 5 (2021): 1855. http://dx.doi.org/10.3390/s21051855.

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There is a need for continuous, non-invasive monitoring of biological data to assess health and wellbeing. Currently, many types of smart patches have been developed to continuously monitor body temperature, but few trials have been completed to evaluate psychometrics and feasibility for human subjects in real-life scenarios. The aim of this feasibility study was to evaluate the reliability, validity and usability of a smart patch measuring body temperature in healthy adults. The smart patch consisted of a fully integrated wearable wireless sensor with a multichannel temperature sensor, signal

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Bochkarev, Igor, Vadim Khramshin, Zhalalidin Galbaev, and Aida Sandybaeva. "Design of electromechanical brake mechanisms with permanent magnets as braking power source." Известия высших учебных заведений. Электромеханика 67, no. 4 (2024): 55–67. http://dx.doi.org/10.17213/0136-3360-2024-3-55-67.

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The aim of this research is to develop new design solutions for frictional brake mechanisms with permanent magnets and propose their structural analysis including heating of their active parts during operation. Standard technical recom-mendations applied for this brake type were used in the design process. To confirm compliance with the obtained rec-ommendations, experimental investigations were carried out using frictional brake mechanisms with the braking torque of 20 Nm with the permanent magnet made from barium ferrite 24BA210. The proposed general layout frictional brake mechanisms with p

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Rajaraman, Sivaramakrishnan, Stefan Jaeger, and Sameer K. Antani. "Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images." PeerJ 7 (May 28, 2019): e6977. http://dx.doi.org/10.7717/peerj.6977.

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Background Malaria is a life-threatening disease caused by Plasmodium parasites that infect the red blood cells (RBCs). Manual identification and counting of parasitized cells in microscopic thick/thin-film blood examination remains the common, but burdensome method for disease diagnosis. Its diagnostic accuracy is adversely impacted by inter/intra-observer variability, particularly in large-scale screening under resource-constrained settings. Introduction State-of-the-art computer-aided diagnostic tools based on data-driven deep learning algorithms like convolutional neural network (CNN) has

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Zhu, Zhongmin, Yifei Jin, Brianna Hajek, Shuming Nie, and Viktor Gruev. "Abstract 2528: Bioinspired multispectral imaging for intraoperative detection of metastatic lymph nodes: enhancing precision through UV and NIR fluorescence." Cancer Research 85, no. 8_Supplement_1 (2025): 2528. https://doi.org/10.1158/1538-7445.am2025-2528.

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Intraoperative identification of metastatic lymph nodes (LNs) remains a clinical challenge, with current techniques often leading to unnecessary removal of healthy tissue or retention of cancer-positive nodes. To address this issue, we developed a bioinspired multispectral imaging system that integrates ultraviolet (UV) autofluorescence and near-infrared (NIR) fluorescence detection. This platform mimics the mantis shrimp's unique visual system, leveraging vertically stacked photodiodes and pixelated spectral filters to achieve simultaneous imaging across the UV, visible, and NIR spectral rang

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Seo, Iksu, Seongweon Kim, Youngwoo Ryu, Jungyong Park, and Dong Seog Han. "Underwater Moving Target Classification Using Multilayer Processing of Active Sonar System." Applied Sciences 9, no. 21 (2019): 4617. http://dx.doi.org/10.3390/app9214617.

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The task of detecting and classifying highly maneuverable and unidentified underwater targets in complex environments is significant in active sonar systems. Previous studies have applied many detection schemes to this task using signals above a preset threshold to separate targets from clutter; this is because a high signal-to-noise ratio (SNR) target has sufficient feature vector components to be separated out. However, in real environments, the received target return’s SNR is not always above the threshold. Therefore, a target detection algorithm is needed for varied target SNR conditions.

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Huertas-Leyva, Pedro, Giovanni Savino, Niccolò Baldanzini, and Marco Pierini. "Loss of Control Prediction for Motorcycles during Emergency Braking Maneuvers Using a Supervised Learning Algorithm." Applied Sciences 10, no. 5 (2020): 1754. http://dx.doi.org/10.3390/app10051754.

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The most common evasive maneuver among motorcycle riders and one of the most complicated to perform in emergency situations is braking. Because of the inherent instability of motorcycles, motorcycle crashes are frequently caused by loss of control performing braking as an evasive maneuver. Understanding the motion conditions that lead riders to start losing control is essential for defining countermeasures capable of minimizing the risk of this type of crashes. This paper provides predictive models to classify unsafe loss of control braking maneuvers on a straight line before becoming irrevers

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Li, Yanjun. "Mathematical Modeling Methods and Their Application in the Analysis of Complex Signal Systems." Advances in Mathematical Physics 2022 (October 7, 2022): 1–10. http://dx.doi.org/10.1155/2022/1816814.

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Mathematical models are effective means of answers established by humans to solve real-world problems. Complex wireless communication can establish information interaction between vehicles, in order to reduce the delay time of the coordination control optimization timing scheme in coordination delay time. For smart car driving, a complex signal system, this study first establishes a relevant mathematical model. It is used to compare three mathematical models commonly used today. The results obtained under the same conditions show that the mathematical model is better in dealing with the comple

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Umoh, Edidiong Ekpe. "Reliability of AI Algorithms in Safety Applications." International Journal of Engineering and Advanced Technology Studies 12, no. 2 (2024): 74–85. http://dx.doi.org/10.37745/ijeats.13/vol12n27485.

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The integration of Artificial Intelligence (AI) algorithms into safety-critical applications has become increasingly prevalent across various domains, including autonomous vehicles, medical diagnosis, industrial automation, and aerospace systems. These applications rely heavily on AI to make decisions that directly affect human safety, economic stability, and operational efficiency. Given the critical nature of these tasks, it is essential to rigorously assess the reliability of AI algorithms to ensure they perform consistently and accurately under all conditions. Reliability, in this context,

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Pratskova, Svetlana E., Aleksandr V. Kolesnikov, Alena O. Kuvaeva, and Oksana U. Kuznetsova. "The research of the possibility of using industrial effluents for the regeneration of Na-cation exchanger in the water treatment process." Butlerov Communications 61, no. 2 (2020): 139–44. http://dx.doi.org/10.37952/roi-jbc-01/20-61-2-139.

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One of the main tasks of environmental protection enterprises is to reduce industrial effluents. Industrial effluents with a content of sodium chloride 24-25% and sodium sulfate 1.5-3.0% are formed at one of the plants. The high content of sodium chloride in the effluent allowed us to make an assumption about the possibility of their use in the regeneration of Na-cation exchanger in the process of water treatment for vapor-vapor cooling of operating metallurgical units. The aim of the work was to determine the feasibility of using industrial salt effluents in the water treatment process while

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Pielecha, Ireneusz, Andrzej Szałek, and Grzegorz Tchorek. "Two Generations of Hydrogen Powertrain—An Analysis of the Operational Indicators in Real Driving Conditions (RDC)." Energies 15, no. 13 (2022): 4734. http://dx.doi.org/10.3390/en15134734.

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Hydrogen fuel cells are systems that can be successfully used to partially replace internal combustion propulsion systems. For this reason, the article presents an operational analysis of energy flow along with an analysis of individual energy transmission systems. Two generations of the Toyota Mirai vehicle were used for the tests. The operational analyses were carried out on the same route (compliant with RDE test requirements), assessing the system’s operation in three driving sections (urban, rural and motorway). Both generations of the drive system with fuel cells are quite different, whi

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