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  • thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology  (1.174)
  • machine learning  (603)
  • bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences  (481)
  • Environmental Sciences.
  • MDPI - Multidisciplinary Digital Publishing Institute  (2.060)
  • Cham :Springer International Publishing :  (347)
  • Frontiers Media SA  (40)
  • Palgrave Macmillan  (5)
  • Dordrecht :Springer Netherlands :
  • Englisch  (2.454)
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  • Englisch  (2.454)
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  • 1
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-14
    Beschreibung: Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.
    Schlagwort(e): cluster analysis ; equity index networks ; machine learning ; copulas ; dependence structures ; quotient of random variables ; density functions ; distribution functions ; multi-factor model ; risk factors ; OLS and ridge regression model ; python ; chi-square test ; quantile ; VaR ; quadrangle ; CVaR ; conditional value-at-risk ; expected shortfall ; ES ; superquantile ; deviation ; risk ; error ; regret ; minimization ; CVaR estimation ; regression ; linear regression ; linear programming ; portfolio safeguard ; PSG ; equity option pricing ; factor models ; stochastic volatility ; jumps ; mathematics ; probability ; statistics ; finance ; applications ; investment home bias (IHB) ; bivariate first-degree stochastic dominance (BFSD) ; keeping up with the Joneses (KUJ) ; correlation loving (CL) ; return spillover ; volatility spillover ; optimal weights ; hedge ratios ; US financial crisis ; Chinese stock market crash ; stock price prediction ; auto-regressive integrated moving average ; artificial neural network ; stochastic process-geometric Brownian motion ; financial models ; firm performance ; causality tests ; leverage ; long-term debt ; capital structure ; shock spillover ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
    Sprache: Englisch
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-14
    Beschreibung: Commodity markets have evolved substantially since the early 2000s and have become more financialized. The recent cold war between the U.S.A. and China, the outbreak of COVID-19, and Russia's invasion of Ukraine have caused resource prices to soar, leading to greater volatility in the commodity markets. The volatility of the commodity markets has increased, and at the same time, financial markets such as the stock market, bond market, and foreign exchange market have become unstable. This has increased the linkage between the commodity and financial markets and has led to a great deal of attention being paid to the commodity markets by governments, companies, and investors.This reprint delves into recent developments in the commodity markets and elucidates the multifaceted factors that have shaped their trajectory. It examines how the interwoven dynamics of supply and demand, geopolitics, technology, and financialization have brought about a new era in commodity trading. By providing a comprehensive survey of these developments, we aim to provide insights that will help stakeholders successfully navigate the challenges and opportunities presented by this evolving landscape.
    Schlagwort(e): Russia and Ukraine conflict ; commodities ; G7 and BRIC markets ; TVP-VAR ; connectedness ; oil price uncertainty shocks ; international equity markets ; global vector autoregressive model ; arbitrage ; efficiency ; futures ; liquidity ; market integration ; platinum ; COVID-19 ; pandemic ; agriculture ; commodity ; MF-DFA ; high frequency ; asymmetric volatility spillover ; bitcoin ; altcoin ; cryptocurrency ; frequency connectedness ; Bitcoin ; machine learning ; random forest regression ; LSTM ; energy market volatility ; oil price dynamics ; fear index ; Markov-regime switching models ; volatility risk premium (VRP) ; implied and realized volatility ; oil and stock returns ; financialization ; Bermudan commodity options ; multi-layer perceptron ; multi-asset stochastic volatility model ; hybrid forecasting approaches ; two-step forecasting approaches ; gold ; euro ; sentiment analysis ; ARIMA ; wavelet transformation ; seasonal decomposition ; long short-term memory ; random forest ; eXtreme gradient boosting ; stock ; markets ; cycles ; investing ; risk ; returns ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
    Sprache: Englisch
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  • 3
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-14
    Beschreibung: Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.
    Schlagwort(e): fintech ; financial technology ; blockchain ; deep learning ; regtech ; environment ; social sciences ; machine learning ; learning analytics ; student field forecasting ; imbalanced datasets ; explainable machine learning ; intelligent tutoring system ; adversarial machine learning ; transfer learning ; cognitive bias ; stock market ; behavioural finance ; investor’s profile ; Teheran Stock Exchange ; unsupervised learning ; clustering ; big data frameworks ; fault tolerance ; stream processing systems ; distributed frameworks ; Spark ; Hadoop ; Storm ; Samza ; Flink ; comparative analysis ; a survey ; data science ; educational data mining ; supervised learning ; secondary education ; academic performance ; text-to-SQL ; natural language processing ; database ; machine translation ; medical image segmentation ; convolutional neural networks ; SE block ; U-net ; DeepLabV3plus ; cyber-security ; medical services ; cyber-attacks ; data communication ; distributed ledger ; identity management ; RAFT ; HL7 ; electronic health record ; Hyperledger Composer ; cybersecurity ; password security ; browser security ; social media ; ANOVA ; SPSS ; internet of things ; cloud computing ; computational models ; metaheuristics ; phishing detection ; website phishing ; thema EDItEUR::U Computing and Information Technology
    Sprache: Englisch
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  • 4
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-14
    Beschreibung: Sports Medicine and Physical Fitness has been a successful Special Issue, which addressed novel topics in any subject related to sports medicine, physical fitness, and human movement. The article collection was able to positively evaluate three systematic reviews, nineteen original articles, and one brief report. These encompassed a broad range of topics ranging from accident kinematics, soccer monitoring, children’s physical evaluation, adapted physical activity, physical evaluation for people with intellectual disabilities, performance analysis in rowers, ultramarathon racers, karateka’s, rugby players, volleyball and basketball players, and cross-fit athletes, and also aspects related to biomechanics, fatigue and injury prevention in racing motorcycle riders, gymnasts, and cyclists.These scientific contributions within the field of Sports Medicine and Physical Fitness broaden the understanding of specific aspects of each analyzed discipline.It has been a pleasure for the Editorial Team to have served the International Journal Of Environmental Research and Public Health.
    Schlagwort(e): MotoGP ; video analysis ; collision ; accident ; safety ; disability ; tool ; health ; life span ; physical fitness ; reference values ; muscular strength profile ; quadriceps ; hamstring ; H/Q ratio ; total work ; sprint ; postactivation potentiation ; fixed seat rowing ; performance ; psychology ; odontology ; nutrition ; training ; stress ; running ; type 1 diabetes ; high-intensity interval training ; exercise ; VO2max ; anti-inflammatory ; machine learning ; PCA ; intensive training ; proprioception ; postural sway ; testing ; pacing ; cycling ; time trial ; RPE ; cognitive functions ; aging ; partnered dances ; fall prevention ; physical activity ; water polo ; biomechanics ; force-velocity relationship ; power-velocity relationship ; soccer ; match ; internal load ; external load ; fatigue ; young athletes ; cycling performance ; sport nutrition ; hydration ; PA ; MVPA ; accelerometer ; questionnaire ; children ; athlete ; high-intensity functional training ; cross-training ; functional fitness ; vitamin D ; explosive strength ; overload training ; wrist pain ; injury prevention ; overuse ; sitting position ; modified 505 test ; kinetic variables ; completion time ; foot contact ; predictors ; squat ; bench press ; strength ; speed ; interval training ; continuous training ; heart failure ; meta-analysis ; handgrip ; carpi radialis ; flexor digitorum superficialis ; neuromuscular fatigue ; motorcycle ; recovery ; spike jump ; block jump ; critical threshold ; specialization ; anaerobic power ; peak power ; HIFT, high-intensity functional training ; crossfit ; athletes ; field test ; hypertrophy ; katsu ; low-intensity training ; occlusive exercise ; sarcopenia ; diabetes type 1 ; HIIT ; sleep quality ; exercise motivation ; quality of life ; hypoxia ; hyperoxia ; hyperbaric breathing ; nitric oxide ; vascular reactions ; breathing ; extreme environments ; thema EDItEUR::W Lifestyle, Hobbies and Leisure
    Sprache: Englisch
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  • 5
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-14
    Beschreibung: With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
    Schlagwort(e): QA75.5-76.95 ; T58.5-58.64 ; metadata ; image classification ; sensitivity analysis ; ROI detection ; residual learning ; image alignment ; adaptive convolutional kernels ; Hough transform ; class imbalance ; land surface temperature ; inundation mapping ; multiscale representation ; object-based ; convolutional neural networks ; scene classification ; morphological profiles ; hyperedge weight estimation ; hyperparameter sparse representation ; semantic segmentation ; vehicle classification ; flood ; Landsat imagery ; target detection ; multi-sensor ; building damage detection ; optimized kernel minimum noise fraction (OKMNF) ; sea-land segmentation ; nonlinear classification ; land use ; SAR imagery ; anti-noise transfer network ; sub-pixel change detection ; Radon transform ; segmentation ; remote sensing image retrieval ; TensorFlow ; convolutional neural network ; particle swarm optimization ; optical sensors ; machine learning ; mixed pixel ; optical remotely sensed images ; object-based image analysis ; very high resolution images ; single stream optimization ; ship detection ; ice concentration ; online learning ; manifold ranking ; dictionary learning ; urban surface water extraction ; saliency detection ; spatial attraction model (SAM) ; quality assessment ; Fuzzy-GA decision making system ; land cover change ; multi-view canonical correlation analysis ensemble ; land cover ; semantic labeling ; sparse representation ; dimensionality expansion ; speckle filters ; hyperspectral imagery ; fully convolutional network ; infrared image ; Siamese neural network ; Random Forests (RF) ; feature matching ; color matching ; geostationary satellite remote sensing image ; change feature analysis ; road detection ; deep learning ; aerial images ; image segmentation ; aerial image ; multi-sensor image matching ; HJ-1A/B CCD ; endmember extraction ; high resolution ; multi-scale clustering ; heterogeneous domain adaptation ; hard classification ; regional land cover ; hypergraph learning ; automatic cluster number determination ; dilated convolution ; MSER ; semi-supervised learning ; gate ; Synthetic Aperture Radar (SAR) ; downscaling ; conditional random fields ; urban heat island ; hyperspectral image ; remote sensing image correction ; skip connection ; ISPRS ; spatial distribution ; geo-referencing ; Support Vector Machine (SVM) ; very high resolution (VHR) satellite image ; classification ; ensemble learning ; synthetic aperture radar ; conservation ; convolutional neural network (CNN) ; THEOS ; visible light and infrared integrated camera ; vehicle localization ; structured sparsity ; texture analysis ; DSFATN ; CNN ; image registration ; UAV ; unsupervised classification ; SVMs ; SAR image ; fuzzy neural network ; dimensionality reduction ; GeoEye-1 ; feature extraction ; sub-pixel ; energy distribution optimizing ; saliency analysis ; deep convolutional neural networks ; sparse and low-rank graph ; hyperspectral remote sensing ; tensor low-rank approximation ; optimal transport ; SELF ; spatiotemporal context learning ; Modest AdaBoost ; topic modelling ; multi-seasonal ; Segment-Tree Filtering ; locality information ; GF-4 PMS ; image fusion ; wavelet transform ; hashing ; machine learning techniques ; satellite images ; climate change ; road segmentation ; remote sensing ; tensor sparse decomposition ; Convolutional Neural Network (CNN) ; multi-task learning ; deep salient feature ; speckle ; canonical correlation weighted voting ; fully convolutional network (FCN) ; despeckling ; multispectral imagery ; ratio images ; linear spectral unmixing ; hyperspectral image classification ; multispectral images ; high resolution image ; multi-objective ; convolution neural network ; transfer learning ; 1-dimensional (1-D) ; threshold stability ; Landsat ; kernel method ; phase congruency ; subpixel mapping (SPM) ; tensor ; MODIS ; GSHHG database ; compressive sensing ; thema EDItEUR::U Computing and Information Technology::UY Computer science
    Sprache: Englisch
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-14
    Beschreibung: Despite being one of the most popular sports worldwide, basketball has received limited research attention compared to other team sports. Establishing a strong evidence base with high-quality and impactful research is essential in enhancing decision-making processes to optimize player performance for basketball professionals. Consequently, the book entitled Improving Performance and Practice in Basketball provides a collection of novel research studies to increase the available evidence on various topics with strong translation to practice in basketball. The book includes work by 40 researchers from 16 institutions or professional organizations from 9 countries. In keeping with notable topics in basketball research, the book contains 2 reviews focused on monitoring strategies to detect player fatigue and considerations for travel in National Basketball Association players. In addition, 8 applied studies are also included in the book, focused on workload monitoring, game-related statistics, and the measurement of physical and skill attributes in basketball players. This book also has a strong focus on increasing the evidence available for female basketball players, who have traditionally been under-represented in the literature. The outcomes generated from this book should provide new insights to inform practice in many areas for professionals working in various roles with basketball teams.
    Schlagwort(e): GV557-1198.995 ; n/a ; talent selection ; classification tree ; Movement Assessment Battery for Children-2 ; NBA ; basketball ; maturation ; body composition ; fatigue ; countermovement jump ; athletic performance ; circadian rhythm ; injury ; basketball tactics ; female ; athlete ; non-linear analysis ; monitoring ; basketball performance ; performance analysis ; training load ; variability ; game-related statistics ; sleep ; youth athletes ; accelerometer ; women athletes ; fat free mass ; collegiate athletes ; workloads ; team sports ; machine learning ; microtechnology ; motor manual sequences ; elite sport ; attention ; visuo-spatial working memory ; playing position ; smallest worthwhile change ; body fat ; thema EDItEUR::V Health, Relationships and Personal development::VX Mind, body, spirit::VXH Complementary therapies, healing and health::VXHT Traditional medicine and herbal remedies
    Sprache: Englisch
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  • 7
    Publikationsdatum: 2024-04-11
    Beschreibung: It has become more evident that many microalgae respond very differently than land plants to diverse stimuli. Therefore, we cannot reduce microalgae biology to what we have learned from land plants biology. However, we are still at the beginning of a comprehensive understanding of microalgae biology. Microalgae have been posited several times as prime candidates for the development of sustainable energy platforms, making thus the in-depth understanding of their biological features an important objective. Thus, the knowledge related to the basics of microalgae biology must be acquired and shared rapidly, fostering the development of potential applications. Microalgae biology has been studied for more than forty years now and more intensely since the 1970’s, when genetics and molecular biology approaches were integrated into the research programs. Recently, studies on the molecular physiology of microalgae have provided evidences on the particularities of these organisms, mainly in model species, such as Chlamydomonas reinhardtii. Of note, cellular responses in microalgae produce very interesting phenotypes, such as high lipid content in nitrogen deprived cells, increased protein content in cells under high CO2 concentrations, the modification of flagella structure and motility in basal body mutant strains, the different ancient proteins that microalgae uses to dissipate the harmful excess of light energy, the hydrogen production in cells under sulfur deprivation, to mention just a few. Moreover, several research groups are using high-throughput and data-driven technologies, including “omics” approaches to investigate microalgae cellular responses at a system-wide level, revealing new features of microalgae biology, highlighting differences between microalgae and land plants. It has been amazing to observe the efforts towards the development and optimization of new technologies required for the proper study of microalgae, including methods that opened new paths to the investigation of important processes such as regulatory mechanisms, signaling crosstalk, chemotactic mechanisms, light responses, chloroplast controlled mechanisms, among others. This is an exciting moment in microalgae research when novel data are been produced and applied by research groups from different areas, such as bioprocesses and biotechnology. Moreover, there has been an increased amount of research groups focused in the study of microalgae as a sustainable source for bioremediation, synthesis of bioproducts and development of bioenergy. Innovative strategies are combining the knowledge of basic sciences on microalgae into their applied processes, resulting in the progression of many applications that hopefully, will achieve the necessary degree of optimization for economically feasible large-scale applications. Advances on the areas of basic microalgae biology and novelties on the essential cellular processes were revealed. Progress in the applied science showed the use of the basic science knowledge into fostering translational research, proposing novel strategies for a sustainable world scenario. In this present e-book, articles presented by research groups from different scientific areas showed, successfully, the increased development of the microalgae research. Herewith, you will find articles ranging from bioprospecting regional microalgae species, through advances in microalgae molecular physiology to the development of techniques for characterization of biomass and the use of biomass into agriculture and bioenergy production. This e-book is an excellent source of knowledge for those working with microalgae basic and applied sciences, and a great opportunity for researchers from both areas to have an overview of the amazing possibilities we have for building an environmentally sustainable future once the knowledge is translated into novel applications.
    Schlagwort(e): TA1-2040 ; TP248.13-248.65 ; QK1-989 ; Q1-390 ; Biotechnology ; biomass ; Hydrogen ; bioenergy ; Nutrients ; Lipids ; Microalgae ; Biofuels ; sustainability ; Carbon Dioxide ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Sprache: Englisch
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  • 8
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: In recent years, the fascination with shape memory alloys (SMAs) has grown across industries such as aerospace, automotive, naval, civil, and biology. SMAs possess unique properties, including the ability to recover from deformation when heated, exhibit pseudoelastic stress-strain behavior for large deformations, and exceptional biocompatibility for bioengineering applications. However, a comprehensive understanding of critical characteristics like transformation temperature and stress values is necessary to fully utilize SMAs. The shape memory effect, where SMAs regain their original shape after deformation under specific thermal conditions, has driven innovative applications in various sectors. In aerospace, SMAs are used in wing structures and actuation systems, enabling morphing and improving aerodynamics. In healthcare, they are integrated into orthopedic devices, simplifying surgical procedures and providing necessary support. The automotive industry also benefits from SMAs, using them in seatbelts and vibration damping systems for enhanced safety and comfort. Accurate knowledge of critical characteristics is essential for effective utilization of SMAs, unlocking their potential in different fields. The remarkable versatility of SMAs, with their deformation recovery, pseudoelasticity, and biocompatibility, positions them as a material of immense interest. As research and development continue, SMAs are poised to drive future innovations, shaping various industries.
    Schlagwort(e): shape memory alloy (SMAs) ; shape memory effect (SME) ; superelasticity ; smart materials ; constitutive models ; simulation and modeling ; smart devices ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
    Sprache: Englisch
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: Mg alloy is the lightest metallic structural material and possesses the advantages of high specific strength, high specific stiffness, good electromagnetism shield, good damping capacity, good machinability, and easy recycling, etc. Therefore, it has extremely broad application prospects and has drawn considerable interest in the fields of automobile, electronics, electrical appliances, transportation, aerospace, and aviation. In addition, Mg alloys are gradually showing application potential in emerging industries, serving as biodegradable metals in the biomedical field, functional material for hydrogen storage, and so on. This Special Issue (SI), entitled “Research Progress in High-Performance Magnesium Alloy and Its Applications”, presents recent developments and excellent results in the field of Mg alloys, and includes 10 articles and one editorial covering some interesting aspects of the topic.
    Schlagwort(e): grain refinement ; high strength and toughness ; {10–12} twin ; Mg-Gd-Y alloy ; multidirectional impact forging ; Mg-Zn-Mn-Ca ; Ca2Mg6Zn3 phase ; corrosion behaviors ; SKPFM ; boride ; MgB2 ; mechanical alloying ; ignition ; combustion ; flame temperature ; magnesium alloy ; biocompatibility ; surface coating modification ; corrosion resistance ; implantable bio-metal materials ; filler material ; welding ; scandium ; microstructure modification ; mechanical properties ; microstructure ; texture ; stretch formability ; high temperature cross-rolling ; annealing ; wire arc additive manufacturing ; cold metal transfer ; Al-Mg alloys ; orthogonal experiment ; Mg-Bi-Ca alloy ; hot deformation ; constitutive model ; dynamic recrystallization kinetics ; Mg alloy ; twinning ; random orientation ; compression ; room temperature ; backward extrusion ; tensile strength ; failure mechanism ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
    Sprache: Englisch
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publikationsdatum: 2024-04-11
    Beschreibung: Metalliferous minerals play a central role in the global economy. They will continue to provide the raw materials we need for industrial processes. Significant challenges will likely emerge if the climate-driven green and low-carbon development transition of metalliferous mineral exploitation is not managed responsibly and sustainably. Green low-carbon technology is vital to promote the development of metalliferous mineral resources shifting from extensive and destructive mining to clean and energy-saving mining in future decades. Global mining scientists and engineers have conducted a lot of research in related fields, such as green mining, ecological mining, energy-saving mining, and mining solid waste recycling, and have achieved a great deal of innovative progress and achievements. This Special Issue intends to collect the latest developments in the green low-carbon mining field, written by well-known researchers who have contributed to the innovation of new technologies, process optimization methods, or energy-saving techniques in metalliferous minerals development.
    Schlagwort(e): metallurgical slag-based binders ; solidification/stabilisation ; As(III) ; As(V) ; calcium hydroxide ; sublevel caving ; numerical simulation ; physical model ; structural parameter ; green mining ; limestone ; high temperature ; confining pressure ; SHPB ; constitutive model ; open-pit mine ; PLAXIS 3D ; dynamic load ; safety factor ; acceleration ; particle sedimentation ; filling mining ; degree of influence ; pipeline transportation ; solid waste utilization ; tailings ; reclamation risk ; hazard identification ; complex network ; hazard management ; digital mine ; mine short-term production planning ; haulage equipment dispatch plan ; ABCA ; NSGA ; settlement velocity measurement ; K-means ; tailings backfill ; unsupervised learning ; cemented paste backfill ; ESEM ; picture processing ; floc networks ; pumping agent ; fractal dimension ; backfill slurry ; strength of cemented backfill ; inhomogeneity of cemented backfill ; cemented tailings backfill ; copper ; zinc ; recovery ; sulfide concentrate ; artificial microbial community ; granular backfill ; bearing characteristics ; numerical model ; particle size ; surface subsidence ; blasting dust movement ; dust concentration ; particle size distribution ; blasting dust reduction ; backfill ; metal mine ; log-sigmoid ; tailings pond ; regional distribution ; dam break ; accident statistics ; causation analysis ; backfilling ; increasing resistance and reducing pressure ; computational fluid dynamics ; spiral pipe ; stowing gradient ; coal-based solid waste ; orthogonal experiment ; strength development ; regression analysis ; engineering performance ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TT Other technologies and applied sciences::TTU Mining technology and engineering
    Sprache: Englisch
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