Determination of sensitivity of drainage morphometry towards hydrological response interactions for various datasets

This book examines current trends and developments in the methods and applications of geospatial analysis and highlights future development prospects. It provides a comprehensive discussion of remote sensing- and geographical information system (GIS)-based data processing techniques, current practices, theories, models, and applications of geospatial analysis. Data acquisition and processing techniques such as remote sensing image selections, classifications, accuracy assessments, models of GIS data, and spatial modeling processes are the focus of the first part of the book. In the second part, theories and methods related to fuzzy sets, spatial weights and prominence, geographically weighted regression, weight of evidence, Markov-cellular automata, artificial neural network, agent-based simulation, multi-criteria evaluation, analytic hierarchy process, and a GIS network model are included. Part three presents selected best practices in geospatial analysis. The chapters, all by expert authors, are arranged so that readers who are new to the field will gain an overview and important insights. Those readers who are already practitioners will gain from the advanced and updated materials and state-of-the-art developments in geospatial analysis.

Drug testing in the era of new psychoactive substances.

In recent years, the growing interest in new techniques for spatial data acquisition, processing and analysis has also found applications in surveying and geological departments, where it is used in the process of developing documentation. In the conditions of mining operations, surveying measurements must be carried out quickly, safely and with sufficient accuracy. The use of laser scanning allows the collection of a significant amount of data, which requires time-consuming processing, but is necessary for accurate modelling of objects in 3D. The legal basis for the use of laser scanning in mining is the acts that regulate activities in the field of surveying, geological survey documentation and technical standards for surveying. The process of implementing laser scanning in underground mining requires compliance with occupational safety regulations and technical standards, as well as proper training of personnel. The laser scanners used in practice are equipped with the SLAM algorithm, enabling precise measurement and point cloud generation. Appropriate software is crucial for processing and analysing the collected data. The use of laser scanning makes it possible to efficiently perform non-standard measurements, which contributes to streamlining work at mining facilities. However, to realize its full potential, it is necessary to train personnel and raise the level of use of this technology.

This conference series, founded at the University of Bologna in 1990 and now at the 13th edition, is devoted to the progress in Magnetic Resonance in Porous Media and in our understanding of Porous Media themselves, and to stimulate the contact among people from various parts of Academia and Industry. Researchers in Physics, Chemistry, Engineering, Life Sciences, Mathematics, Computer Sciences, and in Industrial Applications will benefit from exchange of ideas, experiences, and new approaches. Topics will include innovative techniques to study structure, behavior of fluids, and their interactions in every kind of natural and artificial porous materials, including rocks, cements, biological tissues, foodstuffs, wood, particle packs, sediments, pharmaceuticals, zeolites, and bioconstructs. New data acquisition and processing techniques are also expected to be strong features.

The harsh environment and limited resources available in the Arctic region make collection of most scientifically relevant data in the area difficult and/or expensive. The Monterey Bay Aquarium Research Institute (MBARI), along with other partners, has developed an autonomous underwater vehicle (AUV) specifically designed to withstand the difficult environment in the Arctic and capable of collecting a variety of scientific data. This tool has the potential to replace capabilities previously supported by the US Navy SCICEX cruises which used submarines for measuring and monitoring Arctic oceanographic properties. Scientific access to Navy submarines has been severely restricted over the last several years, with the future prospects for continued support uncertain. Ice draft data was one important piece of data historically collected by the submarines that MBARI's AUV now has the potential to provide. This ice draft data has particular value to climatologists and Arctic scientists who are striving to evaluate the impact of global climate on the thickness and extent of the Arctic ice sheet. This paper examines the ice draft data collected by the ALTEX AUV during its engineering test cruise in the Arctic in October 2001. A description of the experiments and the general performance of the vehicle are presented along with the scientific instrumentation layout of the AUV. Further, the modifications made to the ASL Environmental Sciences Ice Profiler/spl trade/ instrument to support vehicle operations in real-time are described. The use of this real-time data to drive vehicle decision making during missions is addressed as well. The data acquisition and processing techniques used to determine ice draft are then outlined, followed by samples of the ice draft data itself and estimates of its accuracy and repeatability. The conclusion include lessons learned and future plans for the ice profiling science payload.

We have developed and routinely used a reel-to-reel (R2R) scanning Hall-probe microscopy (SHPM) system to characterize REBCO conductors developed at the University of Houston. By mapping the screening-current-induced field of a magnetized REBCO conductor, the SHPM system enables 2-dimensional imaging of critical current density (<i>J</i>_c) distribution in a contact-free, non-destructive approach. Most existing SHPM systems investigate the magnetized REBCO conductors at remnant state without external background field. However, because of the inhomogeneity in the distribution of nanoscale artificial pinning centers in advanced REBCO conductors, there is a demand for reel-to-reel in-field examination over long conductor lengths. We have been developing a new R2R SHPM, capable of measuring the <i>J</i>_c profile of long REBCO conductors at the temperature of 63.5&#x2013;77 K and in an applied field up to 5 T. With optimal data acquisition and processing techniques, we overcame the challenge of measuring weak screening-current-field signals in a strong background field. R2R <i>J</i>_c mapping has been performed on long REBCO conductors with a spatial resolution as low as 0.15 mm² and a longitudinal scanning speed comparable with our existing system. Our previous study revealed a good correlation between the REBCO conductors&#x2019; 65-K in-field <i>J</i>_c and their <i>J</i>_c over a wide span of temperatures and fields. Using this correlation, the in-field R2R SHPM will serve not only as a means of quality control, but also provide insight into high-field performance of advanced REBCO conductors at low temperatures.

Exploration for reef reservoirs in the Deep Basin of Alberta during the mid-1960s resulted in the discovery at Strachan and Ricinus West of 1.9 Tcf of sales gas, 50 million bbl of condensate, and 24.5 million long tons of sulfur in two reefs of Late Devonian age. The reefs were discovered in 1967 and 1969, respectively, by adapting the seismic common-depth point (CDP) techniques of data acquisition and processing that were being developed (particularly in the Rainbow area, in the shallower part of the Western Canada sedimentary basin). The key well for these discoveries was the Gulf-Strachan well in Isd. 12-31-37-9 W5M, which was drilled in 1955. This well encountered a partial buildup of an Upper Devonian reef which yielded some gas and salt water at a depth of 13,900 ft (4,237 m). CDP seismic data were acquired and, after considerable experimentation in processing with orientation to the appropriate geologic model, showed that the key well was on the flank of what is now called the Strachan reef. In 1968, Banff and Aquitaine drilled a full reef buildup of 900 ft (274 m) in Isd. 10-31-37-9 W5M with a pay section of 536 ft (165 m). A separate pool, the Ricinus West reef, was discovered in 1969 by Banff and Aquitaine in Isd. 6-25-36-10 W5M. The well showed a reef buildup of 800 ft (245 m) and a maximum pay of 634 ft 193 m). Remaining reserves of marketable natural gas at Strachan and Ricinus West, after 6 years of production, are about 1 Tcf.

Human–robot interaction (HRI) in human social environments (HSEs) poses unique challenges for robot perception systems, which must combine asynchronous, heterogeneous data streams in real time. Multimodal perception systems are well-suited for HRI in HSEs and can provide more rich, robust interaction for robots operating among humans. In this article, we provide an overview of multimodal perception systems being used in HSEs, which is intended to be an introduction to the topic and summary of relevant trends, techniques, resources, challenges, and terminology. We surveyed 15 peer-reviewed robotics and HRI publications over the past 10+ years, providing details about the data acquisition, processing, and fusion techniques used in 65 multimodal perception systems across various HRI domains. Our survey provides information about hardware, software, datasets, and methods currently available for HRI perception research, as well as how these perception systems are being applied in HSEs. Based on the survey, we summarize trends, challenges, and limitations of multimodal human perception systems for robots, then identify resources for researchers and developers and propose future research areas to advance the field.

Reservoir characterization is a critical aspect of hydrocarbon exploration and production, providing essential insights into reservoir properties, fluid behavior, and potential production performance. This review presents an overview of the application of integrated petrophysical analysis and geostatistical methods in enhancing reservoir characterization. The integration of petrophysical analysis and geostatistical methods enables a comprehensive understanding of reservoir properties and heterogeneities, leading to more accurate reservoir models and improved reservoir management strategies. Petrophysical analysis involves the interpretation of well log data, core measurements, and laboratory experiments to quantify reservoir properties such as porosity, permeability, fluid saturations, and lithology. Geostatistical methods, including variogram analysis, spatial interpolation, and stochastic simulation, are used to spatially model reservoir properties and uncertainties, integrating available data and capturing spatial variability. Key benefits of integrating petrophysical analysis and geostatistical methods include enhanced reservoir characterization, improved reservoir modeling accuracy, optimized well placement and production strategies, and reduced exploration and development risks. Case studies demonstrate the application of integrated approaches in various reservoir settings, including clastic, carbonate, and unconventional reservoirs, highlighting the effectiveness of these methods in improving reservoir understanding and performance prediction. Challenges and limitations associated with integrated petrophysical analysis and geostatistical methods include data quality and availability, uncertainty quantification, computational complexity, and model validation. Addressing these challenges requires a multidisciplinary approach, involving collaboration between geoscientists, reservoir engineers, petrophysicists, and data scientists, as well as advancements in data acquisition, processing, and modeling techniques. The integration of petrophysical analysis and geostatistical methods offers significant opportunities for enhancing reservoir characterization and improving reservoir management practices. By leveraging available data and integrating multidisciplinary expertise, operators can achieve a better understanding of reservoir behavior, optimize production strategies, and maximize hydrocarbon recovery from subsurface reservoirs. Continued research and innovation in integrated reservoir characterization techniques are essential for addressing challenges and unlocking the full potential of hydrocarbon resources in a sustainable and efficient manner.

Motivation: Motion-insensitive high-resolution quantitative spinal cord imaging is critical for evaluating spinal cord pathologies and monitoring treatment. Goal(s): We aim to implement a stack of star radial acquisition of the spinal cord at 7T and evaluate its potential to generate quantitative T2* maps in the cervical spine. Approach: A multi-echo golden‐angle radial sampling pulse sequence was developed for Siemens 7T Terra. X scanner. The gridding reconstruction method was used for image reconstruction. Results: Our results show the feasibility of high-resolution spine imaging and T2* mapping using radial trajectories. Image quality was improved when compared to the MEDIC sequence. Impact: Imaging small-diameter structures such as the spinal cord at high spatial resolutions demands new data acquisition and processing techniques to mitigate limitations due to motion artifacts. Radial MRI acquisition can help reduce motion artifacts and increase speed.

Traditional plant breeding evaluation methods are time-consuming, labor-intensive, and costly. Accurate and rapid phenotypic trait data acquisition and analysis can improve genomic selection and accelerate cultivar development. In this work, a technique for data acquisition and image processing was developed utilizing small unmanned aerial vehicles (UAVs), multispectral imaging, and deep learning convolutional neural networks to evaluate phenotypic characteristics on citrus crops. This low-cost and automated high-throughput phenotyping technique utilizes artificial intelligence (AI) and machine learning (ML) to: (i) detect, count, and geolocate trees and tree gaps; (ii) categorize trees based on their canopy size; (iii) develop individual tree health indices; and (iv) evaluate citrus varieties and rootstocks. The proposed remote sensing technique was able to detect and count citrus trees in a grove of 4,931 trees, with precision and recall of 99.9% and 99.7%, respectively, estimate their canopy size with overall accuracy of 85.5%, and detect, count, and geolocate tree gaps with a precision and recall of 100% and 94.6%, respectively. This UAV-based technique provides a consistent, more direct, cost-effective, and rapid method to evaluate phenotypic characteristics of citrus varieties and rootstocks.

Recent advancement in digital signal processing and analog-to-digital conversion techniques has driven the use of software radio in radio frequency signal receiving. This paper applies the concept of software radio to GPS signal acquisition and tracking. GPS signal receiver consists of RF front-end, buffer memory, and a digital signal processor. In comparison with traditional approaches, the software radio structure has many advantages such as programmability and flexibility. In this paper, GPS acquisition and tracking algorithms are designed and developed. The simulation results show that this technique can improve the whole performance of GPS receivers and can provide the experiment platform with the design and development of kinds of the new algorithms and ideas for enhancing GPS receiver performance.

Incremental forming is a versatile and cost-effective sheet metal forming technique widely adopted in low-volume manufacturing and prototyping across various industries. Recent advancements in data-driven approaches, including machine vision, neural networks, and 3D reconstruction methods, have significantly enhanced the precision and efficiency of incremental forming processes. This study explores the integration of advanced data acquisition and processing techniques to improve the accuracy, automation, and defect detection capabilities in incremental forming. Key advancements such as robot-assisted forming, computer-controlled toolpath generation from CAD models, and real-time quality monitoring using machine vision are discussed. The potential of single- and multi-view 3D reconstruction methods for optimizing toolpath strategies and enhancing formability is also examined. The findings highlight opportunities for full automation in incremental forming, demonstrating its potential to revolutionize modern manufacturing by reducing costs, increasing customization, and improving product quality. These advancements could benefit industries such as aerospace, automotive, and medical device manufacturing, where precision and flexibility are critical.

Despite the fact that digital techniques for data acquisition and processing were widely used in electrogastrographic (EGG) research during the last decade, inappropriate signal conditioning and digitization are still potential pitfalls threatening the reliability of the experiments. The aim of this paper was to review: (1) the importance of the antialiasing low-pass filtering for reducing recording artifacts and interferences, (2) the advantages brought by the proper choice of filter cutoff frequency and the slope for the decrement of the minimal required sampling frequency, (3) the impact of incorrectly selected sampling frequency on data interpretations, with particular attention to the percent distribution ranges, and (4) the "leakage effect" related to the finite number of samples processed simultaneously in frequency domain representation of the recordings. A model of electrogastrographic (EGG) recording was mixed with a model of electrocardiographic (ECG) artifact. The resulting finite-duration signal was low-pass filtered and then digitized with a sampling frequency of 1 Hz. The cutoff frequency of the first-order low-pass filter was altered from 0.5 to 0.1 Hz. Amplitude frequency spectra of the digitized recordings were investigated. An example with a real human electrogastrogram in which an ECG artifact was present confirmed the simulation results. When a first-order anti-aliasing filter is utilized at least a fivefold difference between the filter cutoff frequency and the sampling frequency is recommended for compliance with the Nyquist theorem of digitization. Leakage effects associated with the finite-time duration of the recordings and the use of the discrete Fourier transform should be considered when frequency domain analysis is performed. Misinterpretation of the "bradygastric" and "tachygastric" ranges in the percent distribution of EGG frequency components is possible if inappropriate signal conditioning and digitization are employed.

The use of imaging technologies has expanded tremendously in medicine over the past two decades. This expansion reflects the evolution of new imaging tools that reveal human anatomy and physiology in ever‐increasing detail, as well as the development of digital data acquisition and processing techniques that extract information from human tissues in ever‐expanding degrees of subtlety. A further factor that is stimulating growth in imaging is the expansion of knowledge about biological systems at the cellular, molecular, and genetic levels. This factor is transforming medical imaging from a “technology‐push” discipline into one where fundamental biological questions, as well as important clinical issues, are the force driving development of new imaging technologies. This transformation demands enhanced knowledge about the interface between biological properties of tissues and the characteristics of imaging systems. Exploration of the existing state of knowledge about the interface, and what is needed for the immediate future, is the subject of this article.