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  • Organic Chemistry  (68,964)
  • Chemical Engineering  (17,982)
  • deep learning
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  • 1
    Keywords: Biomass conversion ; Biotechnology ; Chemical Engineering ; Chemistry industry ; Industrial Chemistry ; Kent ; Riegel ; biochemical engineering
    Description / Table of Contents: Substantially revising and updating the classic reference in the field, this handbook offers a valuable overview and myriad details on current chemical processes, products, and practices. No other source offers as much data on the chemistry, engineering, economics, and infrastructure of the industry. The Handbook serves a spectrum of individuals, from those who are directly involved in the chemical industry to others in related industries and activities. It provides not only the underlying science and technology for important industry sectors, but also broad coverage of critical supporting topics. Industrial processes and products can be much enhanced through observing the tenets and applying the methodologies found in chapters on Green Engineering and Chemistry (specifically, biomass conversion), Practical Catalysis, and Environmental Measurements; as well as expanded treatment of Safety, chemistry plant security, and Emergency Preparedness. Understanding these factors allows them to be part of the total process and helps achieve optimum results in, for example, process development, review, and modification. Important topics in the energy field, namely nuclear, coal, natural gas, and petroleum, are covered in individual chapters. Other new chapters include energy conversion, energy storage, emerging nanoscience and technology. Updated sections include more material on biomass conversion, as well as three chapters covering biotechnology topics, namely, Industrial Biotechnology, Industrial Enzymes, and Industrial Production of Therapeutic Proteins.
    Pages: Online-Ressource (XIV, 1562 pages)
    ISBN: 9780387278438
    Language: English
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: Nondestructive testing and evaluation (NDT&E) is one of the most important techniques for determining the quality and safety of materials, components, devices, and structures. NDT&E technologies include ultrasonic testing (UT), magnetic particle testing (MT), magnetic flux leakage testing (MFLT), eddy current testing (ECT), radiation testing (RT), penetrant testing (PT), and visual testing (VT), and these are widely used throughout the modern industry. However, some NDT processes, such as those for cleaning specimens and removing paint, cause environmental pollution and must only be considered in limited environments (time, space, and sensor selection). Thus, NDT&E is classified as a typical 3D (dirty, dangerous, and difficult) job. In addition, NDT operators judge the presence of damage based on experience and subjective judgment, so in some cases, a flaw may not be detected during the test. Therefore, to obtain clearer test results, a means for the operator to determine flaws more easily should be provided. In addition, the test results should be organized systemically in order to identify the cause of the abnormality in the test specimen and to identify the progress of the damage quantitatively.
    Keywords: composites ; multi-scale ; embedded damage ; non-destructive testing ; photoacoustic ; ultrasonic representation ; terahertz ; coded-aperture imaging ; convolution neural network (CNN) ; fast image reconstruction ; nondestructive evaluation ; acoustic nonlinearity parameter ; indirect method ; laser ultrasound ; fully non-contact ; surface acoustic wave ; UWB-PPM ; UWB-OOK ; buried objects ; nondestructive environment ; Levenberg–Marquardt method ; textured surface anomaly detection ; computer vision ; deep learning ; attention mechanism ; adaptive fusion ; power quality disturbances ; long short term memory ; convolutional neural network ; short time Fourier transform ; leaky Lamb wave ; semi-analytical finite element (SAFE) ; waveguide sensor ; finite-width plate ; waveguide plate ; width modes ; spatial beating ; Rayleigh–Sommerfeld integral (RSI) ; weld cracks ; eddy current nondestructive testing ; gradiently relative magnetic permeability ; heat affected zone ; austenitic stainless steel ; circulating fluidized bed combustion boiler ; water-cooled wall tube ; magnetic sensor array ; magnetic flux density ; flexible ultrasonic probe ; neutron irradiation embrittlement ; reactor pressure vessel ; magnetic nondestructive evaluation ; micromagnetic multiparameter microstructure and stress analysis 3MA ; magnetic adaptive testing ; 3D imaging of metal grains ; non-destructive testing methods ; stacking images ; SA106 carbon steel ; terahertz waves ; refractive index ; thickness measurement ; Shim stock films ; composite materials ; reflection mode ; neutron radiography ; Bragg-edge imaging ; gas tungsten arc welding (GTAW) ; low transformation temperature (LTT) steel ; austenite-to-martensite transformation ; Debye–Waller factor ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Language: English
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  • 3
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    Springer Nature | Springer Nature Switzerland
    Publication Date: 2024-04-14
    Description: This open access book constitutes revised selected papers from the International Workshops held at the 4th International Conference on Process Mining, ICPM 2022, which took place in Bozen-Bolzano, Italy, during October 23–28, 2022. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 42 papers included in this volume were carefully reviewed and selected from 89 submissions. They stem from the following workshops: – 3rd International Workshop on Event Data and Behavioral Analytics (EDBA) – 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 3rd International Workshop on Responsible Process Mining (RPM) (previously known as Trust, Privacy and Security Aspects in Process Analytics) – 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) – 3rd International Workshop on Streaming Analytics for Process Mining (SA4PM) – 7th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) – 1st International Workshop on Education meets Process Mining (EduPM) – 1st International Workshop on Data Quality and Transformation in Process Mining (DQT-PM)
    Keywords: process mining ; process discovery ; process analytics ; process querying ; conformance checking ; predictive process monitoring ; data science ; knowledge graphs ; event data ; streaming analytics ; machine learning ; deep learning ; business process management ; health informatics ; thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining ; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBH Digital and information technologies: Health and safety aspects
    Language: English
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-03-23
    Description: This Special Issue includes contributions about occupants’ sustainable living in buildings and communities, highlighting issues surrounding the sustainable development of our environments and lives by emphasizing smart and green design perspectives. This Special Issue specifically focuses on research and case studies that develop promising methods for the sustainable development of our environment and identify factors critical to the application of a sustainable paradigm for quality of life from a user-oriented perspective. After a rigorous review of the submissions by experts, fourteen articles concerning sustainable living and development are published in this Special Issue, written by authors sharing their expertise and approaches to the concept and application of sustainability in their fields. The fourteen contributions to this special issue can be categorized into four groups, depending on the issues that they address. All the proposed methods, models, and applications in these studies contribute to the current understanding of the adoption of the sustainability paradigm and are likely to inspire further research addressing the challenges of constructing sustainable buildings and communities resulting in a sustainable life for all of society.
    Keywords: sustainability ; regionalism ; climate ; unit plan ; apartment ; Singapore ; Korea ; sustainable architecture ; space syntax ; partitioning theory ; total depth ; intelligibility ; movement economies ; architecture ; building performance simulation ; performance-based design ; agent-based model ; Gaussian process ; electroencephalography ; virtual reality ; monument architecture ; stress ; data visualization ; deep learning ; smart building ; interactive experience ; “five senses” interaction ; people-oriented ; embedding ; recommender system ; collaborative filtering ; housing preference ; housing decision ; human behavior simulation ; virtual users ; social sustainability ; performance analysis ; evaluation method ; architectural design education ; eye tracking ; virtual environment ; street robbery ; CPTED ; crime prevention ; fixation count ; people with physical disabilities ; job retention ; path analysis ; perceived workplace safety ; workplace disability facilities ; work satisfaction ; social housing ; social economy actors ; Seoul ; South Korea ; sustainable development ; sustainable design ; energy efficiency ; public rental housing ; building simulation ; elderly ; biophilia ; biophilic experience ; smart home ; smart-home service ; service framework ; water distribution ; water war ; conflict ; ownership ; divided Cyprus ; blue-collar workers ; intervention study ; health promotion ; cardiovascular disease ; n/a ; thema EDItEUR::A The Arts ; thema EDItEUR::A The Arts::AM Architecture
    Language: English
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2023-06-23
    Description: The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices. The thirteen research papers published in this Special Issue make significant contributions to long- and short-term hydrological modeling and water resources management under changing environments using AI techniques coupled with various analytics tools. These contributions, which cover hydrological forecasting, microclimate control, and climate adaptation, can promote hydrology research and direct policy making toward sustainable and integrated water resources management.
    Keywords: ANN ; roadside IoT sensors ; simulations of the gridded rainstorms ; 2D inundation simulation and real-time error correction ; weather types and features ; meteorological feature extraction ; artificial neural network ; self-organizing map (SOM) ; urban agriculture ; resource utilization efficiency ; urban northern Taiwan ; machine learning ; random forest ; regression analysis ; support vector machine ; threshold rainfall ; threshold runoff ; XGBoost ; stochastic rainfall generator ; Huff rainfall curve ; copula ; GeoAI ; artificial intelligence ; hydrological ; hydraulic ; fluvial ; water quality ; geomorphic ; modeling ; anomaly detection ; deep reinforcement learning ; telemetry water level ; time series ; ensemble ; multi-model ensemble ; precipitation ; forecasting ; persian gulf ; deep learning ; dam inflow ; RNN ; LSTM ; GRU ; hyperparameter ; rainfall time series ; artificial neural networks ; Multiple Linear Regression ; Chania ; CNN ; ELM ; temporary rivers ; hydrological extremes ; multivariate stochastic model ; autoregressive model ; Markov model ; daily temperature ; temperature generator ; Bayesian neural network ; forecasting uncertainty ; multi-step ahead forecasting ; probabilistic streamflow forecasting ; variational inference ; smart microclimate-control system (SMCS) ; system dynamics ; water–energy–food nexus ; agricultural resilience ; hydroinformatics ; hydrological modeling ; early warning ; uncertainty ; sustainability
    Language: English
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2022-05-06
    Description: In recent years, new and emerging digital technologies applied to food science have been gaining attention and increased interest from researchers and the food/beverage industries. In particular, those digital technologies that can be used throughout the food value chain are accurate, easy to implement, affordable, and user-friendly. Hence, this Special Issue (SI) is dedicated to novel technology based on sensor technology and machine/deep learning modeling strategies to implement artificial intelligence (AI) into food and beverage production and for consumer assessment. This SI published quality papers from researchers in Australia, New Zealand, the United States, Spain, and Mexico, including food and beverage products, such as grapes and wine, chocolate, honey, whiskey, avocado pulp, and a variety of other food products.
    Keywords: sensory ; physicochemical measurements ; artificial neural networks ; near infra-red spectroscopy ; wine quality ; machine learning modeling ; weather ; consumer acceptance prediction ; data fusion ; emotion recognition ; facial expression recognition ; galvanic skin response ; machine learning ; neural networks ; sensory analysis ; avocado ; cultivars ; preference mapping ; sensory evaluation ; sensory descriptive analysis ; consumer science ; unifloral honeys ; botanical origin ; physicochemical parameters ; classification ; natural language processing ; deep learning ; sensory science ; flavor lexicon ; long short-term memory ; n/a ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general ; bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences ; bic Book Industry Communication::T Technology, engineering, agriculture
    Language: English
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: Photoacoustic (or optoacoustic) imaging, including photoacoustic tomography (PAT) and photoacoustic microscopy (PAM), is an emerging imaging modality with great clinical potential. PAI’s deep tissue penetration and fine spatial resolution also hold great promise for visualizing physiology and pathology at the molecular level. PAI combines optical contrast with ultrasonic resolution, and is capable of imaging at depths of up to 7 cm with a real-time scalable spatial resolution of 10 to 500 µm. PAI has demonstrated applications in brain imaging and cancer imaging, such as breast cancer, prostate cancer, ovarian cancer etc. This Special Issue focuses on the novel technological developments and pre-clinical and clinical biomedical applications of PAI. Topics include but are not limited to: brain imaging; cancer imaging; image reconstruction; quantitative imaging; light source and delivery for PAI; photoacoustic detectors; nanoparticles designed for PAI; photoacoustic molecular imaging; photoacoustic spectroscopy.
    Keywords: photoacoustic imaging ; tomography ; thermoacoustic ; radio frequency ; image quality assessment ; image formation theory ; image reconstruction techniques ; sparsity ; signal processing ; deconvolution ; empirical mode decomposition ; signal deconvolution ; photoacoustics ; tissue characterization ; absorption ; Photoacoustic Computed Tomography (PACT) ; ring array ; fast imaging ; low cost ; photoacoustic tomography ; full-field detection ; wave equation ; final time inversion ; uniqueness ; stability ; iterative reconstruction ; 3D photoacoustic tomography ; full-view illumination and ultrasound detection ; photoacoustic coplanar ; quartz bowl ; correlation matrix filter ; time reversal operator ; photo-acoustic tomography ; reflection artifacts ; deep learning ; convolutional neural network ; time reversal ; Landweber algorithm ; U-net ; optoacoustic imaging ; respiratory gating ; motion artifacts ; full-ring illumination ; diffused-beam illumination ; point source illumination ; ultrasound tomography (UST) ; photoacoustic tomography (PAT) ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
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  • 8
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    IntechOpen | IntechOpen
    Publication Date: 2024-04-14
    Description: This book analyzes the application of computer science and artificial intelligence (AI) techniques in the semantics’ analysis for linguistics, classical studies, and philosophy. Similar techniques can be implemented to incorporate the fields of education, psychology, humanities, law, maritime, data science and business intelligence. The book is suitable for the broader audience interested in the emerging scientific field of formal and Natural Language Processing (NLP). The significance of incorporating all aspects of logic design right at the beginning of the creation of a new NLP system is emphasized and analyzed throughout the book. NLP and AI systems offer an unprecedented set of virtues to society. However, the principles of ethical logic design and operation of primitive to deep learning NLP products must be considered in the future, even via the preparation of legislation if needed. As law applications are already taking advantage of the techniques mentioned, the manufacturers should apply the laws and the possible knowledge development of the NLP products could even be monitored after sales. This will minimize the drawbacks of implementing such intelligent technological solutions. NLP systems are a digital representation of ourselves and may even interact with each other in the future. Learning from them is also a way to improve ourselves.
    Keywords: deep learning ; neural network ; regression ; cryptography ; predictive maintenance ; information security ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation
    Language: English
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  • 9
    Publication Date: 2023-05-10
    Description: Current approaches to Natural Language Processing (NLP) have shown impressive improvements in many important tasks: machine translation, language modeling, text generation, sentiment/emotion analysis, natural language understanding, and question answering, among others. The advent of new methods and techniques, such as graph-based approaches, reinforcement learning, or deep learning, have boosted many NLP tasks to a human-level performance (and even beyond). This has attracted the interest of many companies, so new products and solutions can benefit from advances in this relevant area within the artificial intelligence domain.This Special Issue reprint, focusing on emerging techniques and trendy applications of NLP methods, reports on some of these achievements, establishing a useful reference for industry and researchers on cutting-edge human language technologies.
    Keywords: natural language processing ; distributional semantics ; machine learning ; language model ; word embeddings ; machine translation ; sentiment analysis ; quality estimation ; neural machine translation ; pretrained language model ; multilingual pre-trained language model ; WMT ; neural networks ; recurrent neural networks ; named entity recognition ; multi-modal dataset ; Wikimedia Commons ; multi-modal language model ; concreteness ; curriculum learning ; electronic health records ; clinical text ; relationship extraction ; text classification ; linguistic corpus ; deception ; linguistic cues ; statistical analysis ; discriminant function analysis ; fake news detection ; stance detection ; social media ; abstractive summarization ; monolingual models ; multilingual models ; transformer models ; transfer learning ; discourse analysis ; problem–solution pattern ; automatic classification ; machine learning classifiers ; deep neural networks ; question answering ; machine reading comprehension ; query expansion ; information retrieval ; multinomial naive bayes ; relevance feedback ; cause-effect relation ; transitive closure ; word co-occurrence ; automatic hate speech detection ; multisource feature extraction ; Latin American Spanish language models ; fine-grained named entity recognition ; k-stacked feature fusion ; dual-stacked output ; unbalanced data problem ; document representation ; semantic analysis ; conceptual modeling ; universal representation ; trend analysis ; topic modeling ; Bert ; geospatial data technology and application ; attention model ; dual multi-head attention ; inter-information relationship ; question difficult estimation ; named-entity recognition ; BERT model ; conditional random field ; pre-trained model ; fine-tuning ; feature fusion ; attention mechanism ; task-oriented dialogue systems ; Arabic ; multi-lingual transformer model ; mT5 ; language marker ; mental disorder ; deep learning ; LIWC ; spaCy ; RobBERT ; fastText ; LIME ; conversational AI ; intent detection ; slot filling ; retrieval-based question answering ; query generation ; entity linking ; knowledge graph ; entity embedding ; global model ; DISC model ; personality recognition ; predictive model ; text analysis ; data privacy ; federated learning ; transformer ; n/a ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBX History of engineering & technology
    Language: English
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-09
    Description: This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective.
    Keywords: subject-dependent emotion recognition ; subject-independent emotion recognition ; electrodermal activity (EDA) ; deep learning ; convolutional neural networks ; automatic facial emotion recognition ; intensity of emotion recognition ; behavioral biometrical systems ; machine learning ; artificial intelligence ; driving stress ; electrodermal activity ; road traffic ; road types ; Viola-Jones ; facial emotion recognition ; facial expression recognition ; facial detection ; facial landmarks ; infrared thermal imaging ; homography matrix ; socially assistive robot ; EEG ; arousal detection ; valence detection ; data transformation ; normalization ; mental stress detection ; electrocardiogram ; respiration ; in-ear EEG ; emotion classification ; emotion monitoring ; elderly caring ; outpatient caring ; stress detection ; deep neural network ; convolutional neural network ; wearable sensors ; psychophysiology ; sensor data analysis ; time series analysis ; signal analysis ; similarity measures ; correlation statistics ; quantitative analysis ; benchmarking ; boredom ; emotion ; GSR ; classification ; sensor ; face landmark detection ; fully convolutional DenseNets ; skip-connections ; dilated convolutions ; emotion recognition ; physiological sensing ; multimodal sensing ; flight simulation ; activity recognition ; physiological signals ; thoracic electrical bioimpedance ; smart band ; stress recognition ; physiological signal processing ; long short-term memory recurrent neural networks ; information fusion ; pain recognition ; long-term stress ; electroencephalography ; perceived stress scale ; expert evaluation ; affective corpus ; multimodal sensors ; overload ; underload ; interest ; frustration ; cognitive load ; stress research ; affective computing ; human-computer interaction ; deep convolutional neural network ; transfer learning ; auxiliary loss ; weighted loss ; class center ; stress sensing ; smart insoles ; smart shoes ; unobtrusive sensing ; stress ; center of pressure ; regression ; signal processing ; arousal ; aging adults ; musical genres ; emotion elicitation ; dataset ; emotion representation ; feature selection ; feature extraction ; computer science ; virtual reality ; head-mounted display ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
    Language: English
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