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  • machine learning  (588)
  • T1-995  (346)
  • Chemical Engineering
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  • MDPI - Multidisciplinary Digital Publishing Institute  (897)
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  • 1
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    Advances in Computer-Aided Technology (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2024-03-24
    Description: This book reprints articles from the Special Issue "Advances in Computer-Aided Technology" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of thirteen published articles. This Special Issue belongs to the "Mechatronic and Intelligent Machines" section. Industry 4.0 is characterized by the integration of advanced technologies, such as artificial intelligence, the Internet of Things, and cloud computing, into traditional manufacturing and production processes. CAx (Computer-Aided Systems) systems are a set of computer software tools used in engineering and product design, covering various stages of the product development cycle. Advanced CAx tools combine many different aspects of product lifecycle management (PLM), including design, finite element analysis (FEA), manufacturing, production planning and product. In connection with the transition to Industry 4.0 concepts, the concept of the digital twin comes to the fore, and existing CAx systems must adapt to this trend. The Special Issue deals with a number of research areas, such as: - New trends in CAx systems; Digital manufacturing; Internet of Things in manufacturing; Simulation of production systems and processes; Systems for advanced finite element analysis; Material engineering; Digitization and 3D scanning.
    Keywords: tensor glyph ; golden section ; vector space ; sandwich ; springback ; Vegter yield criterion ; numerical simulation ; PAM-STAMP 2G ; isotropic hardening law ; kinematic hardening law ; bending ; Bauschinger effect ; machine learning ; artificial neural network ; additive manufacturing ; high precision metrology ; CAD ; predictive model ; ship hull structure ; computer-aided design of structure ; database ; function soft block ; gun drill tool ; deep-drilling technology ; optimization ; tool life ; angle ; digital implant impression ; interimplant distance ; intraoral scanner ; trueness ; sewing machine ; needle bar ; floating needle ; electromagnet ; electromagnetic simulation ; noise reduction ; cycloidal gearbox ; friction ; actuator ; servomotor ; permanent magnet synchronous machine ; fixture design ; machining ; sustainable manufacturing ; process innovation ; complex-shape part ; signal processing ; monitoring system ; laser profiler ; surface roughness ; quality assessment ; non-contact method ; vision-based method ; frequency analysis ; abrasive water jet ; wood plastic composite ; natural reinforcement ; knitting machine ; stroke ; drive ; simulation ; cylinder ; dynamic modeling ; load spectrum reconstruction ; fatigue test ; hydraulic excavator ; n/a ; thema EDItEUR::C Language and Linguistics
    Language: English
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  • 2
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    Recent Advances in Mechanics of Non-Newtonian Fluids (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2024-04-11
    Description: Non-Newtonian (non-linear) fluids are common in nature, for example, in mud and honey, but also in many chemical, biological, food, pharmaceutical, and personal care processing industries. This Special Issue of Fluids is dedicated to the recent advances in the mathematical and physical modeling of non-linear fluids with industrial applications, especially those concerned with CFD studies. These fluids include traditional non-Newtonian fluid models, electro- or magneto-rheological fluids, granular materials, slurries, drilling fluids, polymers, blood and other biofluids, mixtures of fluids and particles, etc.
    Keywords: TA1-2040 ; T1-995 ; Poiseuille–Couette flow ; membrane ; viscous fluid ; channel flow ; existence theorem ; yield stress ; hemoglobe capacitor ; creeping flows ; viscoplastic fluids ; projection method ; power-law fluid ; first- and second-order slip ; Mittag–Leffler ; lubrication ; viscoplastic fluid ; rupture ; convection ; Re numbers ; enhanced oil recovery (EOR) ; SPH-FEM ; Gamma densitometer ; oil recovery ; non-newtonian fluids ; marginal function ; particle interaction ; computational fluid dynamics ; non-isothermal flows ; suspensions ; Brinkman equation ; lubrication approximation (76A05 ; lid-driven cavity ; smoothed particle hydrodynamics (SPH) ; 76D08 ; Phan-Thien–Tanner (PTT) model ; bubble suspension ; porous media ; non-equilibrium thermodynamics ; porous medium ; suspension viscosity ; hemoglobin ; convection-diffusion ; slug translational velocity ; closure relationship ; non-linear fluids ; wormlike micellar solutions (WMS) ; high viscosity oil ; viscoelastic surfactants (VES) ; 76A20) ; meshless ; Bingham fluid ; Reynolds equation ; generalised simplified PTT ; dense suspension ; chemical EOR (cEOR) ; buoyancy force ; viscosity ratio ; aspect ratio ; rheology ; lubrication approximation ; fluid-solid interaction (FSI) ; optimal control ; natural convection ; biofluids ; shear-dependent viscosity ; thermodynamic capacitor ; shear-thinning ; stokesian dynamics ; weak solution ; biological capacitor ; cement ; variable viscosity ; Couette flow ; pressure boundary conditions ; inhomogeneous fluids ; boundary control ; similarity transformation ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 3
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    Nanostructure Based Sensors for Gas Sensing: from Devices to Systems (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2024-04-11
    Description: The development of solid state gas sensors based on microtransducers and nanostructured sensing materials is the key point in the design of portable measurement systems able to reach sensing and identification performance comparable with analytical ones. In such a context several efforts must be spent of course in the development of the sensing material, but also in the choice of the transducer mechanism and its structure, in the electrical characterization of the performance and in the design of suitable measurement setups. This call for papers invites researchers worldwide to report about their novel results on the most recent advances and overview in design and measurements for applications in gas sensors, along with their relevant features and technological aspects. Original research papers are welcome (but not limited) on all aspects that focus on the most recent advances in: (i) basic principles and modeling of gas and VOCs sensors; (ii) new gas sensor principles and technologies; (iii) Characterization and measurements methodologies; (iv) transduction and sampling systems; (vi) package optimization; (vi) gas sensor based systems and applications.
    Keywords: TA1-2040 ; T1-995 ; indium oxide ; n/a ; environmental monitoring ; semiconductor ; gas sensor ; packed gas chromatographic column ; ultrathin carbon layer ; metal-oxide-semiconductor array sensor ; halitosis ; laser ablation ; capacitive micromachined ultrasonic transducers (CMUT) ; LTCC side via ; MEMS ; indirect packaging ; gas sensing ; efficiency ; bad breath ; electrospray ; array optimization ; low temperature co-fired ceramic (LTCC) ; electronic nose ; UV irradiation ; core/shell nanostructure ; combinatorial and high-throughput technique ; sensitive material ; hydrogen sulfide ; CO detection ; ZnO ; amperometric ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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  • 4
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    Machine Learning and Data Mining Applications in Power Systems (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2024-04-11
    Description: This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
    Keywords: virtual power plant (VPP) ; power quality (PQ) ; global index ; distributed energy resources (DER) ; energy storage systems (ESS) ; power systems ; long-term assessment ; battery energy storage systems (BESS) ; smart grids ; conducted disturbances ; power quality ; supraharmonics ; 2–150 kHz ; Power Line Communications (PLC) ; intentional emission ; non-intentional emission ; mains signalling ; virtual power plant ; data mining ; clustering ; distributed energy resources ; energy storage systems ; short term conditions ; cluster analysis (CA) ; nonlinear loads ; harmonics, cancellation, and attenuation of harmonics ; waveform distortion ; THDi ; low-voltage networks ; optimization techniques ; different batteries ; off-grid microgrid ; integrated renewable energy system ; cluster analysis ; K-means ; agglomerative ; ANFIS ; fuzzy logic ; induction generator ; MPPT ; neural network ; renewable energy ; variable speed WECS ; wind energy conversion system ; wind energy ; frequency estimation ; spectrum interpolation ; power network disturbances ; COVID-19 ; time-varying reproduction number ; social distancing ; load profile ; demographic characteristic ; household energy consumption ; demand-side management ; energy management ; time series ; Hidden Markov Model ; short-term forecast ; sparse signal decomposition ; supervised dictionary learning ; dictionary impulsion ; singular value decomposition ; discrete cosine transform ; discrete Haar transform ; discrete wavelet transform ; transient stability assessment ; home energy management ; binary-coded genetic algorithms ; optimal power scheduling ; demand response ; Data Injection Attack ; machine learning ; critical infrastructure ; smart grid ; water treatment plant ; power system ; 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::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
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  • 5
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    Artificial Intelligence Techniques in Hydrology and Water Resources Management (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    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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    Advances in Computational Intelligence Applications in the Mining Industry (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2022-03-21
    Description: This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners.
    Keywords: truck dispatching ; mining equipment uncertainties ; orebody uncertainty ; discrete event simulation ; Q-learning ; grinding circuits ; minerals processing ; random forest ; decision trees ; machine learning ; knowledge discovery ; variable importance ; mineral prospectivity mapping ; random forest algorithm ; epithermal gold ; unstructured data ; blast impact ; empirical model ; mining ; fragmentation ; mine worker fatigue ; random forest model ; health and safety management ; stockpiles ; operational data ; mine-to-mill ; geostatistics ; ore control ; mine optimization ; digital twin ; modes of operation ; geological uncertainty ; multivariate statistics ; partial least squares regression ; oil sands ; bitumen extraction ; bitumen processability ; mine safety and health ; accidents ; narratives ; natural language processing ; random forest classification ; hyperspectral imaging ; multispectral imaging ; dimensionality reduction ; neighbourhood component analysis ; artificial intelligence ; mining exploitation ; masonry buildings ; damage risk analysis ; Bayesian network ; Naive Bayes ; Bayesian Network Structure Learning (BNSL) ; rock type ; mining geology ; bluetooth beacon ; classification and regression tree ; gaussian naïve bayes ; k-nearest neighbors ; support vector machine ; transport route ; transport time ; underground mine ; tactical geometallurgy ; data analytics in mining ; ball mill throughput ; measurement while drilling ; non-additivity ; coal ; petrographic analysis ; macerals ; image analysis ; semantic segmentation ; convolutional neural networks ; point cloud scaling ; fragmentation size analysis ; structure from motion ; 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
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  • 7
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    Empowering Materials Processing and Performance from Data and AI (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2024-04-09
    Description: Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new materials and products. Additionally, this gives rise to new paradigms in bridging raw material data and processing to the induced properties and performance. This present topical issue is a compilation of contributions on novel ideas and concepts, addressing several key challenges using data and artificial intelligence, such as:- proposing new techniques for data generation and data mining;- proposing new techniques for visualizing, classifying, modeling, extracting knowledge, explaining and certifying data and data-driven models;- processing data to create data-driven models from scratch when other models are absent, too complex or too poor for making valuable predictions;- processing data to enhance existing physic-based models to improve the quality of the prediction capabilities and, at the same time, to enable data to be smarter; and- processing data to create data-driven enrichment of existing models when physics-based models exhibit limits within a hybrid paradigm.
    Keywords: plasticity ; machine learning ; constitutive modeling ; manifold learning ; topological data analysis ; GENERIC ; soft living tissues ; hyperelasticity ; computational modeling ; data-driven mechanics ; TDA ; Code2Vect ; nonlinear regression ; effective properties ; microstructures ; model calibration ; sensitivity analysis ; elasto-visco-plasticity ; Gaussian process ; high-throughput experimentation ; additive manufacturing ; Ti–Mn alloys ; spherical indentation ; statistical analysis ; Gaussian process regression ; nanoporous metals ; open-pore foams ; FE-beam model ; data mining ; mechanical properties ; hardness ; principal component analysis ; structure–property relationship ; microcompression ; nanoindentation ; analytical model ; finite element model ; artificial neural networks ; model correction ; feature engineering ; physics based ; data driven ; laser shock peening ; residual stresses ; data-driven ; multiscale ; nonlinear ; stochastics ; neural networks ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
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  • 8
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    Insecticides for Mosquito Control: Strengthening the Evidence Base (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2023-04-05
    Description: The eradication of vector-borne diseases is threatened by the limited range of available insecticides, leading, inevitably, to the development of resistance. This is particularly concerning for malaria control, which relies heavily on insecticide-treated nets (ITNs) and indoor residual sprays (IRS). New chemistries are being developed, and innovative deployment of insecticides may play a role in overcoming resistance, either through new types of tools or new means of distribution. A variety of novel product types and vector control strategies are under development and evaluation, which is to be celebrated, but a strong evidence base is needed to guide effective operational deployment decisions. Novel approaches should be supported by robust data collected using appropriate and validated methods to monitor efficacy, durability, and any emerging resistance. This reprint presents original research into developing and characterizing new vector control products, as well as understanding and monitoring insecticide resistance. Review articles explore the impact of insecticide resistance and offer guidance on insecticide choice in the face of pyrethroid resistance. Consensus methodologies are presented, in the form of standard operating procedures (SOPs) designed to be adopted and used to generate reproducible data that can be compared and interpreted across and between studies. It is hoped that this collection of articles offers inspiration and guidance on how consistent data can be generated to inform more effective development, evaluation, and use of new and existing vector control tools.
    Keywords: prallethrin ; insecticide ; spatial treatment ; mosquito fitness ; protection ; pyrethroids ; Aedes albopictus ; Culex pipiens ; life tables ; mosquito ; bite-proof garment ; model ; textile ; non-insecticidal ; physical barrier ; insecticide selection ; out-crossing ; strain authentication ; laboratory screening ; pyrethroid ; pyrethroid resistance ; insecticide resistance ; insecticide resistance management ; vector control ; malaria ; malaria control ; Anopheles ; host-seeking behavior ; insecticide exposure ; pathogen transmission ; Aedes aegypti ; Anopheles gambiae ; ATSB ; Culex quinquefasciatus ; Iroquois ; RNAi ; Saccharomyces cerevisiae ; yeast ; Anopheles mosquito ; fertility ; ovary development ; pyriproxyfen (PPF) ; side-effects ; machine learning ; image classification ; automated identification ; convolutional neural network ; insecticide-treated net (ITN) ; PBO ITN ; synergist ITN ; dual-AI ITN ; insecticide resistance management (IRM) ; method validation ; durability monitoring ; bioinsecticide ; disease transmission ; insecticide-resistance ; mosquito-borne disease ; mosquito control ; natural compounds ; phytochemical ; malaria vector ; insecticide treated nets ; cytochrome P450s ; kdr ; cuticular resistance ; deltamethrin ; imidacloprid ; bifenthrin ; β-cyfluthrin ; etofenprox ; α-cypermethrin ; λ-cyhalothrin ; thiacloprid ; mosquitoes ; Attractive Toxic Sugar Bait (ATSB) ; Attractive Targeted Sugar Bait (ATSB) ; diagnostic bioassay ; resistance monitoring ; insecticide-treated nets (ITN) ; strain characterisation ; method development ; product evaluation ; quality control (QC) ; dual active ingredients (dual-AI) ; bioefficacy ; IRS ; application technology ; broflanilide ; clothianidin ; pirimiphos-methyl ; WHO tube ; WHO tunnel test ; ITNs ; interceptor ; interceptor G2 ; membrane ; human arm ; rabbit ; bioassay ; bio-efficacy ; 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::P Mathematics & science::PS Biology, life sciences::PSB Biochemistry
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  • 9
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    Fit-for-Purpose Land Administration Fit-for-Purpose Land Administration- Providing Secure Land Rights at Scale. Volume 1: Conceptual Innovations (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2024-03-27
    Description: This Special Issue provides an insight, collated from 26 articles, focusing on various aspects of the Fit-For-Purpose Land Administration (FFPLA) concept and its application. It presents some influential and innovative trends and recommendations for designing, implementing, maintaining and further developing Fit-For-Purpose solutions for providing secure land rights at scale. The first group of 14 articles is published in Volume One and discusses various conceptual innovations related to spatial, legal and institutional aspects and its wider applications within land use management. The second group of 12 articles is published in Volume Two and focuses on case studies from various countries throughout the world, providing evidence and lessons learned from the FFPLA implementation process.
    Keywords: complete cadastre ; legal element ; fixing boundary ; eligible landowner ; agreement ; boundary marker ; fit-for-purpose land administration (FFP LA) ; violent conflict ; United Nations ; extra-legal ; transitional justice ; peace building ; land governance ; power relations ; securing land rights ; land registration ; development impacts ; fit-for-purpose land administration ; land administration ; decentralization ; India ; fit-for-purpose ; institutions ; governance ; politics ; Amazon ; deforestation ; Fit-For-Purpose land administration ; participatory mapping ; indigenous land conflict ; Cumaribo ; Colombia ; community-based land adjudication ; components of adjudication ; land tenure ; land rights ; good practices ; updating land records ; systematic land registration ; unconventional approach ; case study ; Benin ; cadaster ; land administration domain model ; LADM ; cadastre ; FFPLA ; customary tenure ; land inventory ; land management ; mobile-based applications ; pro-poor ; land surveying ; tenure security ; land rights and tenure ; fit-for-purpose approach ; human rights ; design science research ; design thinking ; fit for purpose ; spatial data quality ; spatial data quality assurance ; maintenance ; update ; upgrade ; upkeep ; renewal ; data quality ; spatial framework ; STDM ; technology ; UAV ; feature extraction ; rapid urbanization ; climate change ; pandemic ; urban resilience ; spatial ; legal ; and institutional frameworks ; land tenure security ; pro-poor land recordation ; land governance reform ; cost effectiveness ; innovative technology ; case studies ; Uganda ; customary land tenure ; land recordation tools ; semantic technologies ; land information system ; fit-for-purpose land management ; aerial and street level imagery ; machine learning ; integrated land programs ; land policy ; pilot study ; informal settlements ; urban development ; Brazil ; community-based crowdsourcing ; SiGIT ; Ecuador ; land and resources rights ; public-private partnerships ; corporate social responsibility ; poverty reduction ; business driven solutions ; social enterprises ; n/a ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
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  • 10
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    Solution Models based on Symmetric and Asymmetric Information (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publication Date: 2024-04-11
    Description: This Special Issue covers symmetry and asymmetry phenomena occurring in real-life problems. We invited authors to submit their theoretical or experimental research presenting engineering and economic problem solution models dealing with the symmetry or asymmetry of different types of information. The issue gained interest in the research community and received many submissions. After rigorous scientific evaluation by editors and reviewers, nine papers were accepted and published. The authors proposed different MADM and MODM solution models as integrated tools to find a balance between the components of sustainable global development, to find a symmetry axis concerning goals, risks, and constraints to cope with the complicated problems. Most approaches suggested decision models under uncertainty, combining the usual decision-making methods with interval-valued fuzzy or rough sets theory, also Z numbers. The application fields of the proposed models involved both problems of technological sciences and social sciences. The papers cover three essential areas: engineering, economy, and management. We hope that a summary of the Special Issue as provided here will encourage a detailed analysis of the papers included in the Printed Edition.
    Keywords: TA1-2040 ; T1-995 ; rough sets ; interval type-2 fuzzy set (IT2FS) ; resources distribution ; the criteria of the weights ; public management ; Step-wise Weight Assessment Ratio Analysis (SWARA) ; multi-criteria decision-making (MCDM) ; symmetry of the method ; quadcopter ; transaction cost ; full fuzzy environment ; dual generalized geometric Bonferroni mean (DGGBM) operator ; data logger ; information theory ; control system ; salvage value ; nonlinear dynamics ; pattern formation ; oscillations ; stability ; Pythagorean fuzzy set ; FAHP ; fuzzy sets ; group decision-making ; generalized Bonferroni mean (GBM) operator ; probabilistic systems analysis ; economic decisions ; 2-tuple linguistic neutrosophic numbers set (2TLNNSs) ; evaluating the quality of distant courses ; subjective weights ; Z-numbers ; green supplier selection ; dual generalized Bonferroni mean (DGBM) operator ; normal cloud ; thrust ; sensor ; neutrosophic numbers ; MCDM ; Bayes’ theorem ; optimal dividend ; logistics ; measurement ; hybrid MCDM ; combining the weights ; data envelopment analysis ; criteria weights ; multiple attribute decision making (MADM) ; IDOCRIW ; excess-of-loss reinsurance ; fuzzy efficiency ; multiple-criteria decision-making (MCDM) ; MCGDM ; transport ; backward cloud transformation ; engineering problems ; rough ARAS ; capital injection ; performance ; Bonferroni mean (BM) operator ; green supply chain management ; population sizes ; hybrid problem solution models ; criteria weight assessment ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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