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The article focuses on simplifying oil and gas predictive modeling using chemometrics, specifically employing Raman spectroscopy, to predict and optimize refined fuel properties. Topics include the advantages of using chemometrics to convert data into actionable insights, the challenges associated with adopting new instruments, and the benefits of pre-developed Raman spectroscopy models to streamline testing processes in labs.

Raman spectroscopy can characterize size-related properties of semiconductor nanomaterials according to the change of Raman shift. When limited to physical mechanisms, it is often difficult to predict the size dependent Raman shift of semiconductor nanomaterials. To predict the size-dependent Raman shift more accurately and efficiently, a simple and effective method was created, demonstrated, and achieved via the deep learning model. The deep learning model is implemented by multilayer perceptron. For size-dependent Raman shifts of three common semiconductor nanomaterials (InP, Si, CeO2), the prediction error was 1,47%, 1,18%, and 0.58%, respectively. The research has practical value in material characterization and related engineering applications, where physical mechanisms are not the focus and building predictive models quickly is key. [ABSTRACT FROM AUTHOR]

When evaluating fruit, such as the Nanguo pear, ensuring high quality of the product is a top priority. The quality of a Nanguo pear will directly affect its appearance, taste, and commodity value. Currently, most of the quality detection methods of Nanguo pears are destructive. In this work, nondestructive testing methods for the internal and external quality of the Nanguo pear were studied. First, the spectral curves of the Nanguo pear were collected to establish the internal comprehensive quality indicators. Second, the successive projection algorithm was used to extract the spectral characteristics of samples. Based on the gray level co-occurrence matrix, texture features of the sample image were extracted. Finally, the model was established by fusing spectral and image features together, and good modeling results were achieved. The internal and external quality of the Nanguo pear were detected simultaneously. The accuracy of the external quality assessment was 97.14%. For the internal quality prediction model, the correction set R2 c and RMSEC are 0.959 and 0.483, respectively, and the prediction set R2 P and RMSEP are 0.920 and 0.615, respectively. It provides a theoretical basis for the development of an online nondestructive testing system for fruit. [ABSTRACT FROM AUTHOR]

The nature theory of Chinese medicine (CM) is a core basic theory of traditional Chinese medicine (TCM), and CM chemical fingerprint technology has been widely used in identification and research of CM. Following the previous study results, the UV spectrum data of 61 CMs with clear cold-hot nature, in which 30 CMs are "cold" medicines and 31 CMs are "hot" medicines, were analyzed. Based on the constructed CM fingerprint database, a retrieval scheme is studied to build a predictive identification model used to classify the cold-hot nature of CMs. According to the experimental results, this prediction model is best for the identification of the UV spectrum of petroleum ether solvents; compared with existing classical models, the constructed model has better predictive stability and extrapolation. The proposed prediction model is proven to be effective. [ABSTRACT FROM AUTHOR]

The article offers information related to the optimization of a soil particle content prediction model based on a combined spectral index and successive projections algorithm using vis-NIR spectroscopy. It explores the problem of fast estimation of soil particle content by visible–near-infrared spectroscopy.

The article presents simple examples to understand the features of decision trees or classification trees that offer a simple visual representation to understand and interpret data or to build automated predictive models. The consideration of decision trees as an example of supervised methods with little data preparation required is tackled. A similar strategy applied to chromatographic experiments to unravel the enantioselective mechanisms contributing to chiral separations is explored.

The article offers information on the Training an Agent Manually via Evaluative Reinforcement (TAMER) algorithm developed by the Peter Stone at the University of Texas at Austin, which allows humans to provide real-time feedback to robots. Topics discussed include the use of deep machine learning in the algorithm by Stone, the learning of predictive model of human reward in TAMER, and the current method of artificial intelligence (AI) training of robots.

The article offers multiple news briefs. Topics discussed include 2022 will be the year when humans and AI work together to drive enterprise performance; Organizations will focus on AI initiatives that augment human performance, not replace humans with machines; and Businesses will expect vendors to deliver comprehensive AI-enabled solutions for line of business teams instead of focusing on developer tools and technologies for IT.

The article mentions the calculation of cetane indexes and smoke points for bitumen-based middle distillates and focuses on a set of correlations that estimate cetane numbers and smoke points, which are needed for oil-sand projects in Canada. Two procedures for the calculated cetane index in ASTM D4737 are explained.

The article discusses several studies on how near-infrared (NIR) spectroscopy calibration models, like calibration transfer and universal calibration, interacts with the predictive data. Two set of results were derived using two models, the first was from real reference value while the second was from random reference value. The experiment's results showed an agreement between the two instruments .

The article discusses the use of field-solver software to predict the behavior of circuits operating at speed and densities beyond the capabilities of Spice, a common circuit simulator. Under such condition, engineers could use field-solver software, also known as electromagnetic field solver, in order to calculate Maxwell's equations for a physical representation of circuits. A representation of the physical configuration of the circuit should be provided to field-solver software. The limitations of field-solver software are discussed.

The article focuses on a conditional generative adversarial network (GAN) that can assist with the postoperative prediction of optical coherence tomography (OCT) in macular surgery featured at the 2021 Canadian Ophthalmological Society Annual Meeting. Topics covered include the potential use of a GAN in macular surgery, and the results of a project which evaluated the predictive accuracy of GAN algorithms for predicting postoperative OCT imaging.

The article reports on a study which showed that machine learning models using electronic health records (EHR) and text data from clinical notes can be useful in treating patients with glaucoma. The study was conducted by Doctor Sophia Y. Wang and Benjamin Tseng of Byers Eye Institute. Other topics include the advances in the use of artificial intelligence (AI) in glaucoma treatment.

The article focuses on a process prediction method to prevent corrosion and damage to a heat exchanger used in the chemical and process industries. It mentions the important features of the new method including the application of rigorous thermodynamics. It presents several steps including simulation of the crude distillation unit (CDU) and connection with the distributed control system (DCS).

The article reports on the increasing number of local governments in the U.S. that include geographic information system (GIS) technology in their predictive modeling processes. City and county law enforcement integrated GIS into predictive modeling to analyze the potential for criminal activities in a specific area. GIS is also used by public works departments to enhance their predictive modeling for asset management and maintenance.

The article reports a map of the Big Bang's cosmic microwave background (CMB) generated by Planck's space observatory reveals anomalies in the standard model of cosmology. The article notes the anomalies relate to predictions about CMB temperatures and the asymmetry of average CMB temperatures across the universe. It also notes a cold spot in the CMB is larger than the standard model's prediction.

The article offers information on the study which indicates the accuracy of intraocular pressure (IOL) power prediction using ray tracing. According to Doctor Arthur B. Cummings, ray tracing could offer a technique that would achieve the desired postoperative refraction. Furthermore, Cummings indicates that the improving performance of the method is being achieved through software refinements.

The article discusses the effectiveness of the predictive diagnostics of IntelliSense platform in reducing scrap rates and downtime associated with pneumatic cylinder. It states that the predictive diagnostics reduce the defect rate by identifying the changes in cylinder performance. It mentions that the platform uses pressure sensors to monitor inlet and exhaust pressure.

The aricle offers information on aspects related to algorithmic and mathematical prediction. It discusses the importance of prediction theory for accuracy of researches related to mathematics and nature law. Also mentioned the Game of Life ,atmodel invented by British mathematician John Horton Conway.

The author examines the evolution of prediction and the future of predictability. According to the author unlike the Egyptians, Hebrews and the Greeks that used cyclical events and elements of super human forces in predicting the future, modern predictions use set of scientific rules to analyze the knowable and the not too knowable. With machines and data, he claims that many variables can now be analyzed coherently to make accurate predictions.

The article discusses the management and maintenance of consistent and appropriate service delivery of a modern contact center, focusing on algorithms for more accurate forecasting, evaluation and optimization of operational strategies across all seasons and years. It mentions advanced strategic planning systems that involves predictive models and prescriptive models. It also discusses strategic planning technologies including data capture and storage, forecasting, and performance prediction.

The author discusses predictive analytics as the next major trends in customer relationship management (CRM), which has been explored at the 15th annual CRM Market Awards. He mentions that organizations are focusing on the use of predictive analytics to determine which customers and prospect customers are most likely to purchase instead of focusing on their historical buying behavior. He mentions CRM companies as Rising Star awards recipients such as Bullhorn, SalesPredict, and Infer.

This article discusses the weaknesses of U.S. computer industry in terms of forecasting technological innovations. This deficit in foresight follows two patterns, namely the Extreme Tendency in which the technologies and the problems they address are given a status more extreme than is warranted, and the Quiescent Tendency, in which innovations and challenges go unnoticed in public discourse. Companies can avoid these tendencies by looking at the information technologies used by researchers and academics, employees, early adopters in their industry segment, and children.

The article discusses Researchers for the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error (CLEERE) study on myopia in children. The study was done by Karla Zadnik, OD, PhD, professor and dean of the College of Optometry at The Ohio State University and the team of researchers. The research developed prediction model for detecting myopia in children at an early stage.

The article discusses the challenge of managing big data and the use of big data in the construction and engineering industries. Topics discussed include the size of big data which exceeds the capabilities of traditional data management technologies and the predictive analytics in BIM (building-information-modeling) models for project management.

The article discusses components of an Enterprise Analytical Quality Performance Platform (EAQP) data model. It notes multiple interface for the Quality Lifecycle Analysis of EAQP which include predictive modeling capabilities to allow proactive quality management. It also highlights the benefits that the interfaces provide such as access to and integration of key data from multiple sources, operational systems, and platforms.

The article focuses on a two-step-prediction model which identified patients who are at high risk for methicillin-resistant Staphylococcus aureus in VA hospitals in the U.S.

The article presents quotes from notable people in the media industry in response to the question, "What magazines will you be reading in 10 years?" The interviewees also project what may happen with print and digital media. They include David Remnick of "The New Yorker," Soledad O'Brien of CNN's "American Morning," and Andrew Swinand of Starcom USA.

This article focuses on a new prediction method devised by Columbus, Ohio-based Battelle Memorial Institute, to reduce the guesswork and increasing the certainty for designers of both structures and heavy equipment. The highly accurate method calculates for previously unaccounted-for low-frequency harmonic stress, such as earthquakes, ocean waves or a car passing over a bridge. Pingsha Dong, technical director for welded structures research at the Institute, found such stress primarily responsible for damage to welded joints. His method, dubbed Verity, easily integrates into computer-aided design programs. Verity now is used primarily in private industry. If included in building codes, it could predict the life expectancy of structures such as bridges with the highest order of accuracy.