Готові списки джерел за темами / Regression Coefficient And Quality Control Tool

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Добірка наукової літератури з теми "Regression Coefficient And Quality Control Tool"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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Статті в журналах з теми "Regression Coefficient And Quality Control Tool"

Xu, Xin-fang, Li-xing Nie, Li-li Pan, et al. "Quantitative Analysis ofPanax ginsengby FT-NIR Spectroscopy." Journal of Analytical Methods in Chemistry 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/741571.

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Near-infrared spectroscopy (NIRS), a rapid and efficient tool, was used to determine the total amount of nine ginsenosides inPanax ginseng. In the study, the regression models were established using multivariate regression methods with the results from conventional chemical analytical methods as reference values. The multivariate regression methods, partial least squares regression (PLSR) and principal component regression (PCR), were discussed and the PLSR was more suitable. Multiplicative scatter correction (MSC), second derivative, and Savitzky-Golay smoothing were utilized together for the

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Yaswanth, Allamneni*1 T.E.G.K Murthy2 Mandava Venkata Basaveswara Rao3 Y. Udaya Bhaskara Rao4 M. Sivanath5. "VALIDATION OF RP-HPLC ANALYTICAL METHOD FOR ESTIMATION OF CARMUSTINE IN BULK AND LYOPHILIZED VIALS." INDO AMERICAN JOURNAL OF PHARMACEUTICAL RESEARCH 07, no. 09 (2017): 416–23. https://doi.org/10.5281/zenodo.1036370.

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Carmustine is an anti-neoplastic agent. A reverse phase high-performance liquid chromatographic (RP-HPLC) assay method was developed by slightly modifying the USP method and validated for quantitative determination of carmustine in bulk drug and in lyophilized vials. The column utilized for the estimation of assay was 4.6 mm X 15-cm, 5-μm Packing L1 (C18) and the mobile phase employed was a mixture of acetonitrile and water in the ratio of 3:7. The detection was carried out at a wavelength of 200 nm with PDA detector. The flow rate is 1.5 mL per minute at a set temperature of 4-6°C with a tota

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Pezzei, Cornelia, Stefan Schönbichler, Shah Hussain, et al. "Near-infrared and Mid-infrared Spectroscopic Techniques for a Fast and Nondestructive Quality Control of Thymi herba." Planta Medica 84, no. 06/07 (2017): 420–27. http://dx.doi.org/10.1055/s-0043-121038.

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AbstractIn this study, novel near-infrared and attenuated total reflectance mid-infrared spectroscopic methods coupled with multivariate data analysis were established enabling the determination of thymol, rosmarinic acid, and the antioxidant capacity of Thymi herba. A new high-performance liquid chromatography method and UV-Vis spectroscopy were applied as reference methods. Partial least squares regressions were carried out as cross and test set validations. To reduce systematic errors, different data pretreatments, such as multiplicative scatter correction, 1st derivative, or 2nd derivative

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Park, Jong-Rak, Hyun-Hee Kang, Jong-Ku Cho, Kwang-Deog Moon, and Young-Jun Kim. "Application of Non-Destructive Rapid Determination of Piperine in Piper nigrum L. (Black Pepper) Using NIR and Multivariate Statistical Analysis: A Promising Quality Control Tool." Foods 9, no. 10 (2020): 1437. http://dx.doi.org/10.3390/foods9101437.

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Piperine is a bioactive alkaloid compound which provides a unique spicy flavor derived from plants of the Piper nigrum L. Black pepper (n = 160) collected from Vietnam was studied using non-destructive near infrared spectroscopy (NIRS). The spectral acquisition ranged from 1100 to 2500 nm, and a chemometrics analysis program was performed to quantify the piperine contents. High performance liquid chromatography (HPLC) analysis was carried out to develop a chemometric model based on reference values. The black pepper samples were divided into two groups used for calibration (n = 120) and predic

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Kodu, Anselmus Rufus, Kuncu Saragi, Frangky Sitorus, and Ktut Silvanita. "The Influence of Internal Control, User Capability and Information Technology on the Quality of the Accounting Information System at PT VK." International Journal of Research and Innovation in Social Science VII, no. XII (2023): 175–82. http://dx.doi.org/10.47772/ijriss.2023.7012015.

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This study aims to determine the effect of internal control, user capabilities, and information technology utilization on the quality of accounting information systems at PT VKP. This study uses a quantitative method. The data were obtained by distributing questionnaires to the company’s employees and then analyzed using multiple linear regression as a statistical analysis tool. The sample was 50 employees of PT VKP, those working in the Bureau of Finance, Bureau of Human Resources, General Affairs and Information Technology, Bureau of Internal Control System, Bureau of Marketing, Bureau of Op

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Kshirsagar, Mugdha P., and Kanchan C. Khare. "Support Vector Regression Models of Stormwater Quality for a Mixed Urban Land Use." Hydrology 10, no. 3 (2023): 66. http://dx.doi.org/10.3390/hydrology10030066.

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The present study is an attempt to model the stormwater quality of a stream located in Pune, India. The city is split up into twenty-three basins (named A to W) by the Pune Municipal Corporation. The selected stream lies in the haphazardly expanded peri-urban G basin. The G basin has constructed stormwater drains which open up in this selected open stream. The runoff over the regions picks up the non-point source pollutants which are also added to the selected stream. The study becomes more complex as the stream is misused to dump trash materials, garbage and roadside litter, which adds to the

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Franca, Rita D. G., Virgínia C. F. Carvalho, Joana C. Fradinho, Maria A. M. Reis, and Nídia D. Lourenço. "Raman Spectrometry as a Tool for an Online Control of a Phototrophic Biological Nutrient Removal Process." Applied Sciences 11, no. 14 (2021): 6600. http://dx.doi.org/10.3390/app11146600.

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Real-time bioprocess monitoring is crucial for efficient operation and effective bioprocess control. Aiming to develop an online monitoring strategy for facilitating optimization, fault detection and decision-making during wastewater treatment in a photo-biological nutrient removal (photo-BNR) process, this study investigated the application of Raman spectroscopy for the quantification of total organic content (TOC), volatile fatty acids (VFAs), carbon dioxide (CO2), ammonia (NH3), nitrate (NO3), phosphate (PO4), total phosphorus (total P), polyhydroxyalkanoates (PHAs), total carbohydrates, to

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Rahman, M. A., A. B. Baharudin, S. Adi, et al. "Dimensional Deviation Affected by Cutting Parameters and Machine Tool Rigidity in Dry Turning of S45C Steel." Applied Mechanics and Materials 315 (April 2013): 749–54. http://dx.doi.org/10.4028/www.scientific.net/amm.315.749.

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Performance of machining processes is assessed by dimensional and geometrical accuracy which is mentioned in this paper as dimensional deviation. A part quality does not depend solely on the depth of cut, feed rate and cutting speed. Other variable such as excessive machine tool vibration due to insufficient dynamic rigidity can be deleterious to the desired results. The focus of the present study is to find a correlation between dimensional deviation against cutting parameters and machine tool vibration in dry turning. Hence cutting parameters and vibration-based regression model can be estab

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Wang, Zhenjie, Changzhou Zuo, Min Chen, et al. "A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh Gastrodia elata Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics." Foods 12, no. 24 (2023): 4435. http://dx.doi.org/10.3390/foods12244435.

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Gastrodin is one of the most important biologically active components of Gastrodia elata, which has many health benefits as a dietary and health food supplement. However, gastrodin measurement traditionally relies on laboratory and sophisticated instruments. This research was aimed at developing a rapid and non-destructive method based on Fourier transform near infrared (FT-NIR) to predict gastrodin content in fresh Gastrodia elata. Auto-ordered predictors selection (autoOPS) and successive projections algorithm (SPA) were applied to select the most informative variables related to gastrodin c

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Anggraini, Leriza Desitama, and Andini Utari Putri. "THE IMPLEMENTATION OF GOOD CORPORATE GOVERNANCE AND THE GOVERNMENT’S INTERNAL CONTROL SYSTEM IN EFFORT TO IMPROVE THE QUALITY OF REGIONAL FINANCIAL REPORTS IN PALEMBANG CITY." FINANCIAL: JURNAL AKUNTANSI 9, no. 1 (2023): 90–96. http://dx.doi.org/10.37403/financial.v9i1.512.

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The implementation of good corporate governance should be supervised and controlled both internally and externally so that the quality of LKPD can be guaranteed. SPIP also has a role in controlling which has the impact of the presentation of quality financial reports. This study aims to find out how much the implementation of good corporate governance and the government's internal control system is to improve the quality of regional financial reports in Palembang City. This study used a sample of 58 respondents in the Regional Financial and Asset Management Agency (BPKAD) Palembang City. The r

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Книги з теми "Regression Coefficient And Quality Control Tool"

Burns, Tom, and Mike Firn. Research and development. Edited by Tom Burns and Mike Firn. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198754237.003.0029.

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This chapter covers the spectrum of routine monitoring, audit, service evaluation, and formal research. Routine monitoring is an essential task for all mental health professionals, and techniques to make it more palatable are explored, including using routine data for clinical supervision and monitoring team targets. Regular audit is described as an essential tool for logical service development and quality improvement. In the discussion of research, the importance of choosing the correct methodology and of paying attention to detail are stressed. In community psychiatry, sampling bias, regres

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Частини книг з теми "Regression Coefficient And Quality Control Tool"

Schott, Moritz, Adina Zell, Sven Lautenbach, et al. "Analyzing and Improving the Quality and Fitness for Purpose of OpenStreetMap as Labels in Remote Sensing Applications." In Volunteered Geographic Information. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35374-1_2.

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AbstractOpenStreetMap (OSM) is a well-known example of volunteered geographic information. It has evolved to one of the most used geographic databases. As data quality of OSM is heterogeneous both in space and across different thematic domains, data quality assessment is of high importance for potential users of OSM data. As use cases differ with respect to their requirements, it is not data quality per se that is of interest for the user but fitness for purpose. We investigate the fitness for purpose of OSM to derive land-use and land-cover labels for remote sensing-based classification model

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Kalaiselvi, B. "Machine Learning-Driven AI System for Automated Flow Control." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-0330-7.ch004.

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This chapter proposes a new concept of Designing an automatic flow controller that is based on AI and using selected machine learning algorithms. The optimum smart controller uses machine learning concept by learning the knowledge often convectional flow controller. The acquired data set is used to train the built model using ML algorithm using a software tool called Weka 3.8.5 is an open-source software suite developed at the University of Waikato in New Zealand. A model with optimum performance is built, the performance criteria analysis like mean square error, root means square error. The W

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Griffin James M. and Abdelaziz Hala. "Investigating the Sensitivities of Tool Wear When Applied to Monitoring Various Technologies for Micro Milling and Drilling." In Advances in Transdisciplinary Engineering. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-668-2-19.

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By using acoustic emission (AE) it is possible to control deviations and surface quality during micro milling operations. The controlling of such deviations are based on large amounts of associated wear especially in rapid micro machining environments With an increase in AE it is possible to see when tool wear is approaching critical levels and requires swap out. AE is very sensitive to tool wear especially in some micro environments where other measurements can be prone to errors and difficulties. In addition, in the case of drilling both force and power are considered sensitive to tool wear.

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Kadam, Ganesh S., and Raju Shrihari Pawade. "Parametric Evaluation in Context to the Functional Role of Eco-Friendly Water Vapour Cutting Fluid Through Chip Deformation Analysis in HSM Of Inconel 718." In Manufacturing and Processing of Advanced Materials. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815136715123010013.

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Demand for increased production rates, better quality, and incorporation of green manufacturing practices has been continually challenging the manufacturers. This could be feasible by adopting high-speed machining (HSM) using eco-friendly cutting fluids but with careful process control. On these lines, the current paper explores process characteristics of the exotic superalloy Inconel 718 being turned at high speeds with tooling as coated carbide inserts and eco-friendly cutting fluid as water vapour. The experiments were carried out by varying three process parameters, viz. cutting speed, fee

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Reineke, Lukas, Ursula Hübner, Saskia Kröner, and Jan-David Liebe. "Should App Self-Management Mean Self-Control? A Quantiative Study on App Supported Diabetes Self-Management." In MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation. IOS Press, 2022. http://dx.doi.org/10.3233/shti220133.

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Apps have been attested to empower patients regarding disease self-management through numerous studies. However, it is still unclear what factors determine the perception of patients whether an app is a useful tool for this purpose. A multiple regression model that was informed by the Technology Acceptance Model (TAM 2) was tested based on the answers of 235 app users with Diabetes type 1 or 2. The model accounted for 59.2% of the variance of the perceived degree of self-management. Factors belonging to the relevance-usefulness-quality complex as well as factors reflecting the patient’s self-c

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Khoulqi, Ichrak, Najlae Idrissi, and Muhammad Sarfraz. "Segmentation of Pectoral Muscle in Mammogram Images Using Gaussian Mixture Model-Expectation Maximization." In Research Anthology on Medical Informatics in Breast and Cervical Cancer. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7136-4.ch038.

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Breast cancer is one of the significant issues in medical sciences today. Specifically, women are suffering most worldwide. Early diagnosis can result to control the growth of the tumor. However, there is a need of high precision of diagnosis for right treatment. This chapter contributes toward an achievement of a computer-aided diagnosis (CAD) system. It deals with mammographic images and enhances their quality. Then, the enhanced images are segmented for pectoral muscle (PM) in the Medio-Lateral-Oblique (MLO) view of the mammographic images. The segmentation approach uses the tool of Gaussia

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Khoulqi, Ichrak, Najlae Idrissi, and Muhammad Sarfraz. "Segmentation of Pectoral Muscle in Mammogram Images Using Gaussian Mixture Model-Expectation Maximization." In Advancements in Computer Vision Applications in Intelligent Systems and Multimedia Technologies. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-4444-0.ch009.

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Gao, Biao, and Yi Hu. "Research on Factors Influencing User Experience in H5 Interactive Advertising Based on Flow Theory." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia231446.

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With the advancement of HTML5 technology, mobile web interactive advertisements based on HTML5 have offered users a superior experience. Drawing from Flow Theory, we constructed a research framework to elucidate how ‘flow’ influences user acceptance and sharing intentions towards H5 interactive advertisements. Furthermore, we aimed to identify factors influencing the flow experience of users. Given the Person-Artifact-Task (PAT) model, which frames the precursors to flow around three dimensions: person, tool, and task, this paper employs a model centered around the person, tool, and task. We c

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Yano, Inacio Henrique, Nelson Felipe Oliveros Mesa, Barbara Teruel, and Jose Ricardo Alves. "MAPPING OF WEEDS IN CROPS OF SUGARCANE BY IMAGES OBTAINED FROM AN UNMANNED AERIAL VEHICLE (UAV)." In Open Science Research XIX. Editora Científica Digital, 2025. https://doi.org/10.37885/250319077.

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Brazil is a global leader in sugarcane production, a crop that provides numerous jobs, generates income, and drives economic development, making it one of the most vital sectors of the Brazilian economy. Weeds in sugarcane fields negatively impact both the productivity of the crop and the quality of the harvested product. Therefore, effective weed control is crucial, with post-emergent herbicides currently being the primary method. However, the extensive use of herbicides can lead to various problems, including high costs and negative effects on the soil’s physical, chemical, and biological pr

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Ramezani, Zahra, Fatemeh Sedaghati, and Roghayeh Heiran. "Quantum Dots for Toxin Detection in Foods and Beverages." In Quantum Dots in Bioanalytical Chemistry and Medicine. Royal Society of Chemistry, 2023. http://dx.doi.org/10.1039/9781839169564-00221.

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Food safety is a complex issue that significantly affects human health and industry. Bacteria are everywhere and can contaminate food and beverages, and some bacteria and fungi can produce toxins; in such cases, the identification of pathogens alone is not sufficient to prevent harm. Therefore, rapid, sensitive, and easy detection methods for these microorganisms’ toxins are urgently necessary. More specifically, the development of new methods for toxin detection is of vital importance to national organizations responsible for overseeing food and beverage quality control (such as the Food and

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Тези доповідей конференцій з теми "Regression Coefficient And Quality Control Tool"

Pirnstill, Logan M., Yue Qiu, and Chirag Kharangate. "Investigation of Universal Consolidated Database for Heat Transfer Coefficient in Flow Condensation and Machine Learning Modelling." In ASME 2023 Heat Transfer Summer Conference collocated with the ASME 2023 17th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/ht2023-107311.

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Abstract Miniature condensers have been recognized as an effective tool for developing compact heat rejection devices. However, due to complex physical behaviors resulting from phase change, predicting necessary quantities like heat transfer coefficient has proven to be a difficult task. This study will use a database of 37 flow condensation studies for development of machine learning tools to predict two-phase heat transfer coefficient. In comparison to previous work performed by Zhou et. al. [1], this study will utilize thermodynamic data, dimensionless flow data, channel type, channel geome

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Pasupuleti, Thejasree, Manikandan Natarajan, Dhanasekar Raju, PC Krishnamachary, and R. Silambarasan. "Optimization of Wire Electrical Discharge Machining Parameters for Invar 36 Material Using Regression Modeling." In Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility (ADMMS’25). SAE International, 2025. https://doi.org/10.4271/2025-28-0122.

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<div class="section abstract"><div class="htmlview paragraph">Wire Electrical Discharge Machining (WEDM) is a sophisticated machining technique that offers significant advantages for processing materials with elevated hardness and complex geometries. Invar 36, a nickel-iron alloy characterized by a reduced coefficient of thermal expansion, is extensively used in the aerospace, automotive, and electronic sectors due to its superior dimensional stability across a wide temperature range. The primary goals are to improve machining settings and develop regression models that can precise

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Natarajan, Manikandan, Thejasree Pasupuleti, Jothi Kiruthika, PC Krishnamachary, and R. Silambarasan. "Optimization of Wire Electrical Discharge Machining Parameters for Invar 36 Material Using Regression Modeling." In 11th SAEINDIA International Mobility Conference (SIIMC 2024). SAE International, 2024. https://doi.org/10.4271/2024-28-0246.

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<div class="section abstract"><div class="htmlview paragraph">Wire Electrical Discharge Machining (WEDM) is an advanced method of machining that provides distinct benefits in machining materials with high hardness and intricate geometries. Invar 36, a nickel-iron alloy with a lower coefficient of thermal expansion, is widely used in the aerospace, automotive, and electronic industries because of its excellent dimensional stability across a broad range of temperatures. The main objectives are to optimize the machining parameters and create regression models that can accurately predi

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S S, Safeer, Anwar Sadique, and Navaneeth D. "A Machine Learning Approach for the Prediction of Surface Roughness Using the Tool Vibration Data in Turning Operation." In Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility (ADMMS’25). SAE International, 2025. https://doi.org/10.4271/2025-28-0152.

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<div class="section abstract"><div class="htmlview paragraph">Surface roughness is a key factor in different machining processes and plays an important role in ergonomics, assembly process, wear and fatigue life of components. Other factors like functionality, performance and durability of parts are also affected by surface roughness. Although maintaining an optimum surface roughness is a major challenge in many manufacturing industries. Surface roughness during machining depends upon machining parameters such as tool geometry, feed rate, depth of cut, rotational speed, lubrication

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Alghazal, M. A., and D. Krinis. "Data-Driven Modeling of Oil Saturation from Dielectric Logs Using Ensemble Regression, Dimensionality Reduction and Anomaly Detection Machine Learning Algorithms." In ADIPEC. SPE, 2023. http://dx.doi.org/10.2118/216430-ms.

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Abstract Dielectric is a specialized logging tool employed to measure the oil saturation independently of water salinity, enabled by the convoluted multi-frequency measurements of the formation's dielectric properties. Conventional resistivity and salinity-dependent tools are more commonly used but with high measurement uncertainty in variable salinity environments. In this paper, we developed a unique data-driven model encapsulating several supervised and unsupervised machine learning algorithms to predict the dielectric-based saturation using readily available reservoir and well data. More t

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Kuo, Chi-Wei, and C. Steve Suh. "Wavelet Based Nonlinear Time-Frequency Control Theory With Local Adaptability." In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-115011.

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Abstract A novel nonlinear control concept featuring simultaneous control of vibration amplitude in the time domain and spectral response in the frequency domain is developed and subsequently incorporated to maintain dynamic stability in these nonlinear dynamics by denying bifurcation and route-to-chaos from coming to pass. This study mathematically examines the time-frequency control theory and derives the ranges of the regression step sizes that ensure fast convergence and solution stability of the controller design. The local adaptability is novel, intelligent, self-adjusting, and universal

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Ferguson, Max, Kincho H. Law, Raunak Bhinge, and Yung-Tsun Tina Lee. "A Generalized Method for Featurization of Manufacturing Signals, With Application to Tool Condition Monitoring." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67987.

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The application of machine learning techniques in the manufacturing sector provides opportunities for increased production efficiency and product quality. In this paper, we describe how audio and vibration data from a sensor unit can be combined with machine controller data to predict the condition of a milling tool. Emphasis is placed on the generalizability of the method to a range of prediction tasks in a manufacturing setting. Time series, audio, and acceleration signals are collected from a Computer Numeric Control (CNC) milling machine and discretized into blocks. Fourier transformation

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Hoang, Danny, Nasir Mannan, Ruby ElKharboutly, Ruimin Chen, and Farhad Imani. "Edge Cognitive Data Fusion: From In-Situ Sensing to Quality Characterization in Hybrid Manufacturing Process." In ASME 2023 18th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/msec2023-105170.

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Abstract While hybrid additive manufacturing offers improved material properties, increased design flexibility, and reduced production time, the presence of variation in the process (e.g., torque, current, power, and tool speed), together with the impact of tool degradation (e.g., spindles, holders, and cutters) alters the surface roughness and dimensional accuracy of fabricated parts. Recently, edge sensors are coupled with machine learning techniques (e.g., feature-based support vector machines and end-to-end deep neural networks) to connect process parameters with build quality. However, th

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Natarajan, Manikandan, Thejasree Pasupuleti, Navya C, Jothi Kiruthika, and R. Silambarasan. "Optimization and Regression Modeling of Fused Deposition Modeling for PLA Material for Vehicle Interior Applications." In Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility (ADMMS’25). SAE International, 2025. https://doi.org/10.4271/2025-28-0159.

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<div class="section abstract"><div class="htmlview paragraph">Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has revolutionized the manufacturing sector by enabling the production of complex geometries using various materials. Polylactic Acid (PLA) is a biodegradable thermoplastic often used in additive manufacturing (AM) because to its eco-friendliness, cost-effectiveness, and processing simplicity. This research seeks to enhance the parameters of Fused Deposition Modeling (FDM) for PLA material with the Technique for Order Preference by Similarity to I

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Vianna, Armando. "Applying Machine Learning in Highly Laminated Formation to Differentiate Pay and Non-Pay Zones and Resolve Rt for Fit for Purpose Azimuthal Resistivity Tool Selection." In GOTECH. SPE, 2025. https://doi.org/10.2118/224566-ms.

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Abstract In this work, firstly, we present a systematic workflow combining linear regression, polynomial regression to generate Rt profiles based on the Vshale model and CART - Classification And Regression Tree method to differentiate between pay and non-pay zones. This machine learning method is a decision tree, a classifier that does not require any knowledge or parameter setting. This approach is known as supervised learning, thus given training data; the ML algorithm induces a decision tree. From a decision tree, it can create rules about the data to predict the classification of unseen r

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