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11th world conference "Intelligent System for Industrial Automation" (WCIS-2020) / / Rafik Aziz Aliev [and four others] editors
| 11th world conference "Intelligent System for Industrial Automation" (WCIS-2020) / / Rafik Aziz Aliev [and four others] editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (xvii, 615 pages) : illustrations |
| Disciplina | 670.28563 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Intel·ligència artificial
Aplicacions industrials Artificial intelligence - Industrial applications |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-68004-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- 11th International Conference on Intelligent Systems for Industrial Automation, WCIS-2020, Tashkent, Uzbekistan, November 26-28 -- Organization -- Co-chairmen and Editors -- International Program Committee -- Organizing Committee -- Chairmen -- Co-chairmen -- Members -- Conference Organizing Secretariats -- Contents -- Prediction Intervals for the Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) via the LUBE Method -- 1 Introduction -- 2 Methods -- 2.1 Study Area and Data Sets -- 2.2 Artificial Neural Network (ANN) -- 2.3 Adaptive Neuro-Fuzzy Inference System (ANFIS) -- 2.4 PIs Construction by LUBE Method -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Analysis and Modeling of Information Security Systems in Industry 4.0 -- 1 Introduction -- 2 Analysis and Modeling -- 3 Conclusion -- References -- Using Non-linear Integral Models in Automatic Control and Measurement Systems for Sensors' Input Signals' Recovery -- 1 Introduction -- 2 Methods for Solving Polynomial Integral Equations -- 2.1 Model Regularization -- 2.2 Algorithms for Solving Polynomial Integral Equations -- 2.3 Solving Polynomial Integral Equations with Tabular-Type Kernels in an Infinite Period -- 3 Results and Practical Application of the Offered Methods -- 4 Conclusions -- References -- Neural Network Method and Algorithm for Document Detection Based on Signaling Analysis -- 1 Introduction -- 2 The Main Part -- 3 Conclusion -- References -- Using Fuzzy Probabilistic Implication in Z-set Based Inference -- 1 Introduction -- 2 Preliminaries -- 3 Statement of the Problem -- 4 Solution Method -- 5 Numerical Example -- 6 Conclusion -- References -- Accounting Experience Between Fuzzy Integral and Z-numbers -- 1 Introduction -- 2 Calculation of Fuzzy Integral by the Fuzzy Measure.
3 Calculation on the Basis of the Combination of Z-numbers -- 4 To Carry Out Computational Experiments on the Basis of Z-numbers -- 5 Conclusion -- References -- A Recurrent Method for Structural-Parametric Identification of Fuzzy Neural Networks -- 1 Introduction -- 2 Weighed Mamdani FNNs and Its Learning Problem -- 2.1 Weighed Mamdani Model -- 2.2 Statement of the Problem -- 3 New Approach for the Identification of Weighed Mamdani FNN -- 4 Structure and Parameter Initialization of the Proposed Method -- 5 Parameter Learning Using a Gradient Descent Method -- 6 Numerical Experiments -- 7 Conclusion -- References -- Voltage Control System for Electrical Networks Based on Fuzzy Sets -- 1 Introduction -- 2 Problem Statement and Main Results -- 3 Practical Results -- 4 Conclusion -- References -- Algorithms for the Synthesis of Optimal Linear-Quadratic Stationary Controllers -- 1 Introduction -- 2 Problem Definition -- 3 Control Law -- 4 Solution -- 5 Conclusion -- References -- Toward Ordering of n-Tuples of Z-Numbers -- 1 Introduction -- 2 State of the Art -- 3 Preliminaries -- 4 Statement of the Problem and Method of Solution -- 5 Conclusion -- References -- Determining the Activity of Fullerene Nanoparticles Using QSAR Models -- 1 Introduction -- 2 Methods -- 2.1 Data -- 2.2 Data Pre-processing -- 2.3 Feature Selection -- 2.4 QSAR Model Development -- 3 Results -- 3.1 Outliers Treatment -- 3.2 Processing Null Values -- 3.3 Bivariate Analysis -- 3.4 Multicollinearity -- 3.5 Feature Selection Using Wrapper Methods -- 3.6 Model Building -- 3.7 Evaluating and Optimizing Models -- 3.8 Predictions -- 4 Discussion -- 5 Conclusion -- Appendices -- References -- Selection of the Optimal Class of Features for Recognition of the Azerbaijani Handprinted Characters -- 1 Introduction -- 2 Thinning -- 3 Extraction of Soft Features for Hand-Printed Recognition. 4 Results of Experiments -- 5 Conclusion -- References -- About One Feature Selection Algorithm in Pattern Recognition -- 1 Introduction -- 2 Methodology -- 2.1 Mathematical Formulation of the Problem -- 2.2 Algorithm -- 2.3 Example of Comparison -- 3 Conclusion -- References -- The Neural Network Based Decision Support System Using Aggregated Opinions of Public Observers -- 1 Introduction -- 2 Problem Definition -- 3 Fuzzy Utility Function -- 4 NN Model for Aggregation of Recipient Assessments -- 5 Conclusion -- References -- Multi-model Virtual Analysers of Parameters of Technological Processes -- 1 Introduction -- 2 Machine Learning -- 3 Conclusion -- References -- Fuzzy Assessment of Technological Risks in the Main Oil Pipeline -- 1 Introduction -- 2 Solution and Discussion of the Problem -- 3 Conclusion -- References -- The Efficiency of the FSV Model in an Intelligent Search Engine -- 1 Introduction -- 2 Main Chapter -- 3 Conclusion Remarks -- References -- Neural-Network Based Approach to Mechanism of Liquid Extraction -- 1 Introduction -- 2 Experimental Part -- 3 Conclusions and Disscussion -- References -- Predicting the Performance of Marital Gas Pipelines with Different Coatings -- 1 Introduction -- 2 Construction of a Dynamic Model for a Time Series -- 3 Choosing the Dimension of the Embedding Space -- 4 Direct and Iterative Forecasting Methods Based on Dynamic Model Mapping -- 5 Numerical Implementation of the Method and Discussion of Results -- References -- Enhancing Teaching Approach with 3D Primitives in Virtual and Augmented Reality -- 1 Introduction -- 2 Augmented and Virtual Reality (AR/VR) in E-Learning -- 2.1 Using AR in Education -- 2.2 Virtual Reality (VR) for Education -- 2.3 The Need for Virtual Reality in Education -- 3 How to Implement Graphics Field -- 4 Implication of 3D Modeling by Software -- 5 Conclusion -- References. Modelling of Gas Lift Dynamic Processes Using ANFIS and ANN -- 1 Introduction -- 2 Method -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Recognition and Classification of Pollen Grains Based on the Use of Statistical, Dynamic Image Characteristics, and Unique Properties of Neural Networks -- 1 Introduction -- 2 Main Part -- 2.1 Main Features, Principles, and Characteristics of the Technology for Identifying Images of Pollen Grains -- 2.2 Generalized Algorithms for Identification, Recognition, and Classification of Images of Micro-objects -- 3 Conclusion -- References -- Fuzzy Type-2 Decision Making Method on Project Selection -- 1 Introduction -- 2 Preliminaries -- 3 Statement of the Problem -- 4 Solution of the Problem -- 5 Conclusion -- References -- IoT and Intelligent Wireless Sensor Network for Remote Monitoring Systems of Solar Power Stations -- 1 Introduction -- 2 Configuration of Intelligent WSN -- 3 The Principle of Construction of Intelligent Wireless Sensor Networks -- 4 Construction Concept of SPS Remote Monitoring System -- 5 Simulation and Results -- 6 Conclusion -- References -- Path Planning Collision Free for Warehouse Mobile Robot -- 1 Introduction -- 2 Method -- 2.1 Current Situation and Warehouse Mobile Robot -- 3 Results and Discussions -- 4 Conclusion -- References -- Simulation Model of the Multi-position Mechatronic Module Functioning of an Intelligent Robot -- 1 Introduction -- 2 Research Methodology -- 3 Analysis and Results -- 4 Conclusion -- References -- Decision-Making in the Production of Hard-To-Recover Oil Reserves Under Uncertainty -- 1 Introduction -- 2 A Brief Overview of Optimization Methods for Gas-Lift Production -- 3 Problem Statement -- 4 Results of Research -- 5 Conclusion -- References -- Automatic Recognition of Uzbek Speech Based on Integrated Neural Networks -- 1 Introduction. 2 End-to-End Speech Recognition Systems -- 3 Experiments -- 4 Conclusion -- References -- Software Selection Problem by Using Single Valued Neutrosophic (SVN)-Based TOPSIS Method -- 1 Introduction -- 2 Preliminaries -- 3 Statement of the Problem -- 4 Solution of the Problem -- 5 Conclusion -- References -- Neural Network Model for Adaptive Control of Nonlinear Dynamic Object -- 1 Introduction -- 2 Main Part -- 3 Conclusion -- References -- Identification and Ranking of Key Factors for Pattern of Consumer Buying Decisions in Digital Marketing -- 1 Introduction -- 2 Preliminaries -- 3 Statement of the Problem -- 4 Solution of the Problem -- 5 Conclusion -- References -- The Possibilities of Using Cloud Computing for Applications of Industrial Automation -- 1 Introduction -- 2 Methodical Aspects of Using Cloud Computing in Industry -- 3 Generalized Scenario of Virtualization in the Cloud Infrastructure -- 4 Conclusion -- References -- Application of Fuzzy AHP Method to Material Selection Problem -- 1 Introduction -- 2 Preliminaries -- 3 Fuzzy AHP -- 4 Application -- 4.1 Calculations for Criteria -- 4.2 Calculations for Impact Strength Criterion -- 4.3 Calculations for "Brinell Hardness" Criterion -- 4.4 Calculations for Machinability Index Criterion -- 4.5 Calculations for Estimated Cost Per Lbs Criterion -- 5 Global and Local Weights Calculations -- 6 Decision Matrix -- 7 Ranking the Alternatives -- 8 Discussion and Conclusion -- References -- Problems of Visualization and 3d Modeling in Chemistry: Analysis of Electronodonor Properties and Spatial Complex-Forming Structure of the Obtained Sulfocationite -- 1 Introduction -- 2 Method of Calculation -- 3 DFT Analysis -- 4 Research of Including Complex-Forming -- 5 Conclusion -- References. Application of Modern Technologies for Planning Improvement and Saving on Costs in the Enterprise of the Industry 4.0. |
| Record Nr. | UNINA-9910483846803321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
AI on the job : guide to successful human-machine collaboration / / Andreas Moring
| AI on the job : guide to successful human-machine collaboration / / Andreas Moring |
| Autore | Moring Andreas |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer-Verlag, , [2022] |
| Descrizione fisica | 1 online resource (140 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
Artificial intelligence - Industrial applications
Artificial intelligence - Social aspects Human-computer interaction Intel·ligència artificial Aplicacions industrials Interacció persona-ordinador |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783662640050
9783662640043 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910523759103321 |
Moring Andreas
|
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| Berlin, Germany ; ; New York, New York : , : Springer-Verlag, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Biocatalysis for green chemistry and chemical process development [[electronic resource] /] / edited by Junhua (Alex) Tao, Romas Kazlauskas
| Biocatalysis for green chemistry and chemical process development [[electronic resource] /] / edited by Junhua (Alex) Tao, Romas Kazlauskas |
| Pubbl/distr/stampa | Hoboken, N.J., : John Wiley & Sons, c2011 |
| Descrizione fisica | 1 online resource (493 p.) |
| Disciplina | 660.6/3 |
| Altri autori (Persone) |
TaoJunhua
KazlauskasR. J <1956-> (Romas J.) |
| Soggetto topico |
Environmental chemistry - Industrial applications
Enzymes - Biotechnology Green technology Química verda Enzims Biocatàlisi Aplicacions industrials Ecotecnologia |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
1-283-17573-8
9786613175731 1-118-02829-5 1-118-02828-7 1-118-02830-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Overview of biotechnology tools for green synthesis: enzymes, cells and their tunability by engineering -- How green can the industry become with biotechnology -- Emerging enzymes and their synthetic applications -- Reaction efficiencies and green chemistry metrics of biotransformations -- Application and case studies - pharmaceuticals and fine chemicals -- Biocatalytic routes to chiral intermediates for development of drugs -- Transglutaminase for protein drug modification: pegylation and beyond -- Microbial production of plant-derived pharmaceutical natural products through metabolic engineering: artemisinin and beyond -- Toward greener therapeutic proteins -- Application and case studies ? flavor & fragrance, agrochemicals and fine chemicals -- Opportunities for biocatalysis in the flavor, fragrance and cosmetic industry -- Application of biocatalysis in the agrochemical industry -- Green production of fine chemicals by isolated enzymes -- Whole cell production of fine chemicals and intermediates -- Application and case studies ? polymers and renewable chemicals -- Green chemistry for the production of biodegradable, biorenewable, biocompatible polymers -- Enzymatic degradation of lignocellulosic biomass -- Bioconversion of renewables-plant oils -- Microbial bioprocesses for industrial scale chemical production. |
| Record Nr. | UNINA-9910130871103321 |
| Hoboken, N.J., : John Wiley & Sons, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Cannabis/hemp for sustainable agriculture and materials / / edited by Dinesh Chandra Agrawal, Rajiv Kumar, Muralikrishnan Dhanasekaran
| Cannabis/hemp for sustainable agriculture and materials / / edited by Dinesh Chandra Agrawal, Rajiv Kumar, Muralikrishnan Dhanasekaran |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (335 pages) |
| Disciplina | 905 |
| Soggetto topico |
Cannabis
Cànem Cànnabis Aplicacions industrials |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
981-16-8778-1
981-16-8777-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743254703321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Frontiers in industrial and applied mathematics : FIAM-2021, Punjab, India, December 21-22 / / Rajesh Kumar Sharma [and four others] editors
| Frontiers in industrial and applied mathematics : FIAM-2021, Punjab, India, December 21-22 / / Rajesh Kumar Sharma [and four others] editors |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (659 pages) |
| Disciplina | 620.00151 |
| Collana | Springer proceedings in mathematics & statistics |
| Soggetto topico |
Engineering mathematics
Matemàtica per a enginyers Aplicacions industrials |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 981-19-7272-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | C. Özman, T. Saner, F. Gül, M. Diederich, A. C. Benim, and U. Janoske, Computational and Experimental Investigation of Flow and Convective Heat Transfer along Rough Surfaces -- M. Kumar, Neelesh S. Upadhye, and A. K. B. Chand, Distribution of Noise in Linear Recurrent Fractal Interpolation Functions for Data Sets with α-Stable Noise -- Maggie E. Habeeb, Oblivious Transfer using Non-abelian Groups -- P. Kushwah and J. Saha, Solution of Population Balance Equation using Homotopy Analysis Method -- V. Singh, Waseem A. Khan, and A. Sharma, Certain Properties and their Volterra Integral Equation Associated with the Second-Kind Chebyshev Matrix Polynomials in Two Variables -- R. Saranya, N. Annapoorani, and J. Saha, Blow-up Analysis and Global Existence of Solutions for a Fractional Reaction-Diffusion Equation -- N. Rani and V. Mishra, Ways of Constructing Multiplicative Magic Cubes -- S. Singh Rawat and Komal, Novel q-Rung Orthopair Fuzzy Hamacher Dual Muirhead Mean Operator for Multi-Attribute Decision Making -- A. Srivastava and B. S. Bhadauria, Convective Instability in a Composite Nanofluid Layer under Local Thermal Non-equilibrium -- N. Madaan and S. Sharma, Investigation of Traffic Dynamics Considering Driver’s Characteristics and Downstream Traffic Conditions -- R. Pasupathi, M. A. Navascués, and A. K. B. Chand, Fractal Convolution Bessel Sequences on Rectangle -- S. Devaiya and S. K. Srivastava, Uniform Approximation of Functions Belonging to L[0,∞)-space Using Cγ.T Means of Fourier-Laguerre Series -- M. Diederich, F. Gül, C. Özman, A. C. Benim, L. Ihringer, and D. Möller, Numerical Modelling and Experimental Validation of Mechanical Separation of Helminth Eggs for Wastewater Purification -- H. A. Kumara Swamy, Sankar Mani, N. Keerthi Reddy, and S. R. Sudheendra, Heat Transfer and Second Law Analysis of Ag-water Nanoliquid in a Non-Uniformly Heated Porous Annulus -- Anjali and M. K. Singh, Qualitative Analysis of Peer Influence Effects on Testing of Infectious Disease Model -- R. Goel, R. C. Mittal, and N. Ahlawat, B-Splines Collocation Approach to Simulate Secondary Dengue Virus (DENV) Infection Model with Diffusion -- A. Kumar, B.S Bhadauria, and A. Srivastava, Study of Heat and Mass Transfer in a Composite Nanofluid Layer -- Bhagwat R. Yewale and Deepak B. Pachpatte, On the Existence and Stability Analysis for Ψ-Caputo Fractional Boundary-value Problem -- R. Rath and K. Sharma, Alternative Crack-tip Enrichment Functions for XFEM in Arbitrary Polarized Piezoelectric Media -- S. C. Sekhara Rao and A. K. Chaturvedi, Convergence Analysis of a Layer Resolving Numerical Technique for a Class of Coupled System of Singularly Perturbed Parabolic Convection-Diffusion Equations having an Interface -- P. Megha and G. Chandhini, Filtering in Time-dependent Problems -- N. Gupta and N. Kanth, Heat Transfer Model for Silk Finishing Calendar -- H. D. Arora, A. Naithani, and Aakanksha, A Multi-attribute Decision Making Approach for Fuzzy Divergence Measure in Selection of Covid-19 Vaccine -- N. Singh and Manish K. Khandelwal, Magnetohydrodynamic Mixed Convection Flow in a Vertical Channel Filled with Porous Media -- A. Ali, R. P. Sharma, and A. Zishan, Group Action on Fuzzy Ideals of Near-Rings -- R. Revathi, D. Narsimhulu, and A. Ramu, Effect of Viscosity on the Spherical Shock Wave Propagation in a Dusty Gas with Radiation Heat Flux and Exponentially Varying Density -- M. Arora and R. Bajaj, On the Stability of a Heated Inclined Fluid Layer with Gravity Modulation -- S. C. Srivastava, N. K. Thakur, and A. Pramanayagam, Dynamical Study of an Epidemiological Model with Harvesting and Infection in Prey Population -- G. Raiya and M. Mittal, Joint Decisions on Imperfect Production Process and Carbon Emission Reduction Under Carbon Regulations -- S. Naskar, N. Islam, R. Gayen, and R. Datta, Propagation of Water Waves in the Presence of a Horizontal Plate Submerged in a Two-layer Fluid -- P. Saini, Transversely Isotropic Homogeneous Medium with Absorbing Boundary Conditions: Elastic Wave Propagation using Spectral Element Method -- K. B. Devi, Reingachan N., and T. B. Singh, Growth of Polynomials having No-zero Inside a Circle -- V. Siwach, Manju S. Tonk, and H. Poonia, Simulation of Queues in Sugar Mills using Monte-Carlo Technique -- R. Singla, G. Singh, and V. Kanwar, An Adaptive Step-size Optimized Seventh-order Hybrid Block Method for Integrating Differential Systems Efficiently -- M. Diederich, L. Di Bartolo, and A. C. Benim, Comparison of Prediction Accuracy between Interpolation and Artificial Intelligence Application of CFD Data for 3D Cavity Flow -- J. Tushar, A. Kumar, and S. Kumar, Virtual Element Methods for Optimal Control Problems Governed by Elliptic Interface Problems -- Vijay and A.K.B. Chand, Positivity Preserving Rational Quartic Spline Zipper Fractal Interpolation Functions -- Z. Mkhize, N. Parumasurand, and P. Singh, Heptic Hermite Collocation on Finite Elements -- J. Raj Sharma and H. Singh, A Computationally Efficient Sixth-order Method for Nonlinear Models -- S. Panday, W. H. Chanu, and Y. N. Devi, New Higher Order Iterative Method for Multiple Roots of Nonlinear Equations -- M. Singh and A. Gupta, Separation Axioms in Bipolar Fuzzy Topological Spaces -- V. Singh and B. Singh, A Study of Ciric Type Generalized Contraction via B-contraction with Application -- D. Amin and D. B. Singh, Evolution of Weak Discontinuities in a Perfectly Conducting Mixture of Gas and Dust Particles -- S. Chawla and S. C. Sekhara Rao, Numerical Treatment for a Coupled System of Singularly Perturbed Reaction Diffusion Equations with Robin Boundary Conditions and having Boundary and Interior Layers -- M. Arora, M. Danesh, and A. Rana, Double-Diffusive Convection with the Effect of Rotation in Magnetic Nanofluids -- R. Sasikumar and P. Arriyamuthu, Modeling for Implications of Covid-19 Pandemic on Healthcare System in India. |
| Record Nr. | UNINA-9910647776403321 |
| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
IEEE open journal of nanotechnology
| IEEE open journal of nanotechnology |
| Pubbl/distr/stampa | New York, NY : , : IEEE, , 2020- |
| Disciplina | 620.5 |
| Soggetto topico |
Nanotechnology
Nanotecnologia Aplicacions industrials |
| Soggetto genere / forma |
Periodicals.
Revistes electròniques |
| ISSN | 2644-1292 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
OJN
IOJNAY |
| Record Nr. | UNISA-996404435703316 |
| New York, NY : , : IEEE, , 2020- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
IEEE open journal of nanotechnology
| IEEE open journal of nanotechnology |
| Pubbl/distr/stampa | New York, NY : , : IEEE, , 2020- |
| Disciplina | 620.5 |
| Soggetto topico |
Nanotechnology
Nanotecnologia Aplicacions industrials |
| Soggetto genere / forma |
Periodicals.
Revistes electròniques |
| ISSN | 2644-1292 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
OJN
IOJNAY |
| Record Nr. | UNINA-9910439053103321 |
| New York, NY : , : IEEE, , 2020- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Information and communication technologies for agriculture theme II : data / / edited by Dionysis D. Bochtis [and four others]
| Information and communication technologies for agriculture theme II : data / / edited by Dionysis D. Bochtis [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (296 pages) |
| Disciplina | 630.2085 |
| Collana | Springer Optimization and Its Applications |
| Soggetto topico |
Agricultural informatics
Enginyeria agronòmica Innovacions agrícoles Internet de les coses Aplicacions industrials |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-84148-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Part I: Data Technologies -- You Got Data Now What: Building the Right Solution for the Problem -- 1 Introduction -- 2 Sensors and Their Readings -- 3 Networks of Sensors -- 3.1 In-Field Crop Production -- 3.2 Intensive Crop Production -- 3.3 Intensive Animal Production -- 4 Using Machine Learning -- 5 Remaining Challenges and Opportunities -- References -- Data Fusion and Its Applications in Agriculture -- 1 Introduction -- 2 Data Fusion -- 2.1 Introduction -- 2.2 The ``Whys´´ and ``Wherefores´´ of Information Fusion -- 2.3 Information Fusion: Methods, Techniques, and Algorithms -- 2.4 Models of Data Fusion -- Architectures and Performance Aspects -- Data Alignment and Fusion of Attributes -- 2.5 Applications of Information Fusion in Agriculture -- Remote Sensing Image Preprocessing -- Restoration and Denoising -- Pixel-based Classification -- Spectral Feature Classification -- Classification with Spatial Information -- Target Recognition -- Scene Understanding -- 2.6 Data Mining and Artificial Intelligence in Agriculture -- Yield Prediction -- Disease Detection -- Weed Detection -- Species Recognition -- 3 Conclusions and Future Challenges -- References -- Machine Learning Technology and Its Current Implementation in Agriculture -- 1 Introduction -- 2 Machine Learning Versus Conventional Programming -- 3 Fundamental Features of Machine Learning -- 4 Types of Machine Learning Methods -- 4.1 Supervised Learning -- Regression -- Classification -- 4.2 Unsupervised Learning -- Clustering -- Dimensionality Reduction -- Association -- 4.3 Reinforcement Learning -- Classification -- Control -- 4.4 Recommender Systems (Active Learning) -- Content-based -- Collaborative Filtering -- 5 Families of Machine Learning Algorithms -- 5.1 Regression -- 5.2 Regularization -- 5.3 Bayesian -- 5.4 Instance-based -- 5.5 Decision Tree.
5.6 Ensemble -- 5.7 Clustering -- 5.8 Dimensionality Reduction -- 5.9 Association Rule -- 5.10 Artificial Neural Networks -- 5.11 Deep Neural Networks -- 6 Machine Learning in Agriculture -- 6.1 Yield Prediction -- 6.2 Crop Disease Detection -- 6.3 Weed Detection -- 6.4 Quality Assessment -- 7 Summary of the Basic Aspects of the Reviewed Studies -- 8 Conclusions -- References -- Part II: Applications -- Application Possibilities of IoT-based Management Systems in Agriculture -- 1 Introduction -- 1.1 Data Acquisition and Management in Agriculture -- 2 Methodology -- 3 Progression and Evaluation of the System -- 3.1 The Main Characteristics Based on the Literature -- 3.2 Determining the Possibilities from a Practical Standpoint -- Data Acquisition Systems -- Data Management Methods and Applications -- Data Utilization -- 4 Discussion -- 5 Conclusions -- References -- Plant Species Detection Using Image Processing and Deep Learning: A Mobile-Based Application -- 1 Introduction -- 2 Background Research -- 2.1 Deep Learning -- 3 Methodology -- 3.1 Dataset and Data Preparation -- Background Removal -- Data Augmentation -- 4 Software Development and Analysis -- 5 Detailed Design and Software Implementation -- 5.1 Developing Convolutional Neural Network -- 5.2 Online Classification System App -- 6 Testing and Evaluation -- 7 Discussion and Future Work -- 8 Conclusions -- References -- Computer Vision-based Detection and Tracking in the Olive Sorting Pipeline -- 1 Introduction -- 1.1 Industrial Sorters -- 2 Problem Description -- 2.1 Related Work -- 3 The Proposed Olive Separation Approach -- 3.1 Image Binarization -- 3.2 Distance Transform -- 3.3 Watershed Transform -- 3.4 Centroid Extraction -- 3.5 Multiple Object Tracking -- 4 The Unscented Kalman Filter -- 4.1 Prediction Phase of the UKF -- 4.2 Update Phase of the UKF. 5 The Kuhn-Munkres (Hungarian) Algorithm -- 6 Results -- 6.1 Sample Collection -- 6.2 Simulation Design -- 6.3 Results Using Kalman Filtering -- 7 Evaluation of the Results -- 8 Conclusions -- References -- Integrating Spatial with Qualitative Data to Monitor Land Use Intensity: Evidence from Arable Land - Animal Husbandry Systems -- 1 Introduction -- 1.1 Land Use Intensity and Farming Systems -- 1.2 Land Use/Land Cover (LULC) Extraction -- 2 Methodology -- 2.1 Study Area -- 2.2 Materials and Methods -- Timeline of Changes -- Remote Sensing Data -- 2.3 Participatory Workshop -- 3 Results and Discussion -- 3.1 Image Processing -- 3.2 Land Cover Type Extraction and Change Detection -- 3.3 Land Conversions -- 3.4 Results from Qualitative Methods -- 3.5 Comparison and Synthesis of Results -- 3.6 Farming Systems and Land Use Intensity -- 4 Conclusion: Ways Forward in Integrating Qualitative Data in Land Use Intensity -- References -- Air drill Seeder Distributor Head Evaluation: A Comparison between Laboratory Tests and Computational Fluid Dynamics Simulatio... -- 1 Introduction -- 2 Materials and Methods -- 2.1 Tested Model Description -- 2.2 Description of Distributor Head´s Test Bench -- 2.3 Experiment Design -- 2.4 Numerical Simulations -- Air-Seeds Mixture Flow -- Air Flow -- Particles Trajectory -- Discrete Phase Model Setup -- 3 Results -- 3.1 Experimental Results -- 3.2 Numerical Results -- 3.3 Validation of the Numerical Model -- 4 Conclusions and Perspectives -- References -- Part III: Value Chain -- Data-Based Agricultural Business Continuity Management Policies -- 1 Introduction -- 2 Motivation -- 2.1 Business Intelligence Tools as Business Continuity Solutions in the Modern Era -- 2.2 Business Continuity and Big Data Challenges in the Agricultural Domain -- 2.3 Research Steps -- 3 Tools and Methods -- 3.1 Formulation of Datasets. 3.2 Business Intelligence Multidimensional Data Models - Preliminary Concepts -- 3.3 Business Process Modelling Notation (BPMN) for Supporting Business Decisions Based on Multidimensional Data -- 3.4 A Robust Machine Learning Agricultural Business Continuity Classifier -- 4 Results -- 4.1 The Multidimensional Data Models for Supporting Agricultural Business Continuity Management Decisions -- Model 1: The Criticality Levels Multidimensional Model -- Model 2: The Risks/Hazards Multidimensional Model -- 4.2 Machine Learning Predictive Analytics Based on the Proposed Multidimensional Schemas -- Data Preprocessing -- Risk Exposure Classification Based on Decision Tree Induction -- Boosting the Risk Exposure classifier´s Predictive Power with the 10-Fold Cross-Validation and the Random Forest Techniques -- 5 Discussion -- 6 Conclusions -- References -- Soybean Price Trend Forecast Using Deep Learning Techniques Based on Prices and Text Sentiments -- 1 Introduction -- 2 Related Work -- 2.1 Price Prediction of Agricultural Commodities -- 2.2 Deep Learning for Price Trend Prediction -- 2.3 Deep Learning for Text Sentiment Analysis -- 3 Methodology -- 4 Results -- 4.1 Models Considering Only Prices -- 4.2 Models Considering Only Text Sentiments -- 4.3 Ensemble Model Considering Prices and Text Sentiments -- 5 Discussion -- 5.1 Benefits of Deep Learning for Agricultural Price Prediction -- 5.2 Adaptation and Uses for Other Products -- 6 Conclusions -- References -- Use of Unsupervised Machine Learning for Agricultural Supply Chain Data Labeling -- 1 Introduction -- 2 Unsupervised Machine Learning in Agriculture -- 3 Methodology -- 4 Results -- 5 Discussion -- 5.1 Training Time for Each Model -- 5.2 Implementation Difficulties -- 5.3 Benefits for SC Traceability -- 5.4 Adaptation to Other SCs -- 6 Conclusions -- References. |
| Record Nr. | UNISA-996466419403316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Information and communication technologies for agriculture theme II : data / / edited by Dionysis D. Bochtis [and four others]
| Information and communication technologies for agriculture theme II : data / / edited by Dionysis D. Bochtis [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (296 pages) |
| Disciplina | 630.2085 |
| Collana | Springer Optimization and Its Applications |
| Soggetto topico |
Agricultural informatics
Enginyeria agronòmica Innovacions agrícoles Internet de les coses Aplicacions industrials |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-84148-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Part I: Data Technologies -- You Got Data Now What: Building the Right Solution for the Problem -- 1 Introduction -- 2 Sensors and Their Readings -- 3 Networks of Sensors -- 3.1 In-Field Crop Production -- 3.2 Intensive Crop Production -- 3.3 Intensive Animal Production -- 4 Using Machine Learning -- 5 Remaining Challenges and Opportunities -- References -- Data Fusion and Its Applications in Agriculture -- 1 Introduction -- 2 Data Fusion -- 2.1 Introduction -- 2.2 The ``Whys´´ and ``Wherefores´´ of Information Fusion -- 2.3 Information Fusion: Methods, Techniques, and Algorithms -- 2.4 Models of Data Fusion -- Architectures and Performance Aspects -- Data Alignment and Fusion of Attributes -- 2.5 Applications of Information Fusion in Agriculture -- Remote Sensing Image Preprocessing -- Restoration and Denoising -- Pixel-based Classification -- Spectral Feature Classification -- Classification with Spatial Information -- Target Recognition -- Scene Understanding -- 2.6 Data Mining and Artificial Intelligence in Agriculture -- Yield Prediction -- Disease Detection -- Weed Detection -- Species Recognition -- 3 Conclusions and Future Challenges -- References -- Machine Learning Technology and Its Current Implementation in Agriculture -- 1 Introduction -- 2 Machine Learning Versus Conventional Programming -- 3 Fundamental Features of Machine Learning -- 4 Types of Machine Learning Methods -- 4.1 Supervised Learning -- Regression -- Classification -- 4.2 Unsupervised Learning -- Clustering -- Dimensionality Reduction -- Association -- 4.3 Reinforcement Learning -- Classification -- Control -- 4.4 Recommender Systems (Active Learning) -- Content-based -- Collaborative Filtering -- 5 Families of Machine Learning Algorithms -- 5.1 Regression -- 5.2 Regularization -- 5.3 Bayesian -- 5.4 Instance-based -- 5.5 Decision Tree.
5.6 Ensemble -- 5.7 Clustering -- 5.8 Dimensionality Reduction -- 5.9 Association Rule -- 5.10 Artificial Neural Networks -- 5.11 Deep Neural Networks -- 6 Machine Learning in Agriculture -- 6.1 Yield Prediction -- 6.2 Crop Disease Detection -- 6.3 Weed Detection -- 6.4 Quality Assessment -- 7 Summary of the Basic Aspects of the Reviewed Studies -- 8 Conclusions -- References -- Part II: Applications -- Application Possibilities of IoT-based Management Systems in Agriculture -- 1 Introduction -- 1.1 Data Acquisition and Management in Agriculture -- 2 Methodology -- 3 Progression and Evaluation of the System -- 3.1 The Main Characteristics Based on the Literature -- 3.2 Determining the Possibilities from a Practical Standpoint -- Data Acquisition Systems -- Data Management Methods and Applications -- Data Utilization -- 4 Discussion -- 5 Conclusions -- References -- Plant Species Detection Using Image Processing and Deep Learning: A Mobile-Based Application -- 1 Introduction -- 2 Background Research -- 2.1 Deep Learning -- 3 Methodology -- 3.1 Dataset and Data Preparation -- Background Removal -- Data Augmentation -- 4 Software Development and Analysis -- 5 Detailed Design and Software Implementation -- 5.1 Developing Convolutional Neural Network -- 5.2 Online Classification System App -- 6 Testing and Evaluation -- 7 Discussion and Future Work -- 8 Conclusions -- References -- Computer Vision-based Detection and Tracking in the Olive Sorting Pipeline -- 1 Introduction -- 1.1 Industrial Sorters -- 2 Problem Description -- 2.1 Related Work -- 3 The Proposed Olive Separation Approach -- 3.1 Image Binarization -- 3.2 Distance Transform -- 3.3 Watershed Transform -- 3.4 Centroid Extraction -- 3.5 Multiple Object Tracking -- 4 The Unscented Kalman Filter -- 4.1 Prediction Phase of the UKF -- 4.2 Update Phase of the UKF. 5 The Kuhn-Munkres (Hungarian) Algorithm -- 6 Results -- 6.1 Sample Collection -- 6.2 Simulation Design -- 6.3 Results Using Kalman Filtering -- 7 Evaluation of the Results -- 8 Conclusions -- References -- Integrating Spatial with Qualitative Data to Monitor Land Use Intensity: Evidence from Arable Land - Animal Husbandry Systems -- 1 Introduction -- 1.1 Land Use Intensity and Farming Systems -- 1.2 Land Use/Land Cover (LULC) Extraction -- 2 Methodology -- 2.1 Study Area -- 2.2 Materials and Methods -- Timeline of Changes -- Remote Sensing Data -- 2.3 Participatory Workshop -- 3 Results and Discussion -- 3.1 Image Processing -- 3.2 Land Cover Type Extraction and Change Detection -- 3.3 Land Conversions -- 3.4 Results from Qualitative Methods -- 3.5 Comparison and Synthesis of Results -- 3.6 Farming Systems and Land Use Intensity -- 4 Conclusion: Ways Forward in Integrating Qualitative Data in Land Use Intensity -- References -- Air drill Seeder Distributor Head Evaluation: A Comparison between Laboratory Tests and Computational Fluid Dynamics Simulatio... -- 1 Introduction -- 2 Materials and Methods -- 2.1 Tested Model Description -- 2.2 Description of Distributor Head´s Test Bench -- 2.3 Experiment Design -- 2.4 Numerical Simulations -- Air-Seeds Mixture Flow -- Air Flow -- Particles Trajectory -- Discrete Phase Model Setup -- 3 Results -- 3.1 Experimental Results -- 3.2 Numerical Results -- 3.3 Validation of the Numerical Model -- 4 Conclusions and Perspectives -- References -- Part III: Value Chain -- Data-Based Agricultural Business Continuity Management Policies -- 1 Introduction -- 2 Motivation -- 2.1 Business Intelligence Tools as Business Continuity Solutions in the Modern Era -- 2.2 Business Continuity and Big Data Challenges in the Agricultural Domain -- 2.3 Research Steps -- 3 Tools and Methods -- 3.1 Formulation of Datasets. 3.2 Business Intelligence Multidimensional Data Models - Preliminary Concepts -- 3.3 Business Process Modelling Notation (BPMN) for Supporting Business Decisions Based on Multidimensional Data -- 3.4 A Robust Machine Learning Agricultural Business Continuity Classifier -- 4 Results -- 4.1 The Multidimensional Data Models for Supporting Agricultural Business Continuity Management Decisions -- Model 1: The Criticality Levels Multidimensional Model -- Model 2: The Risks/Hazards Multidimensional Model -- 4.2 Machine Learning Predictive Analytics Based on the Proposed Multidimensional Schemas -- Data Preprocessing -- Risk Exposure Classification Based on Decision Tree Induction -- Boosting the Risk Exposure classifier´s Predictive Power with the 10-Fold Cross-Validation and the Random Forest Techniques -- 5 Discussion -- 6 Conclusions -- References -- Soybean Price Trend Forecast Using Deep Learning Techniques Based on Prices and Text Sentiments -- 1 Introduction -- 2 Related Work -- 2.1 Price Prediction of Agricultural Commodities -- 2.2 Deep Learning for Price Trend Prediction -- 2.3 Deep Learning for Text Sentiment Analysis -- 3 Methodology -- 4 Results -- 4.1 Models Considering Only Prices -- 4.2 Models Considering Only Text Sentiments -- 4.3 Ensemble Model Considering Prices and Text Sentiments -- 5 Discussion -- 5.1 Benefits of Deep Learning for Agricultural Price Prediction -- 5.2 Adaptation and Uses for Other Products -- 6 Conclusions -- References -- Use of Unsupervised Machine Learning for Agricultural Supply Chain Data Labeling -- 1 Introduction -- 2 Unsupervised Machine Learning in Agriculture -- 3 Methodology -- 4 Results -- 5 Discussion -- 5.1 Training Time for Each Model -- 5.2 Implementation Difficulties -- 5.3 Benefits for SC Traceability -- 5.4 Adaptation to Other SCs -- 6 Conclusions -- References. |
| Record Nr. | UNINA-9910552715003321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Information and communication technologies for agriculture-Theme IV : actions / / edited by Dionysis D. Bochtis [and four others]
| Information and communication technologies for agriculture-Theme IV : actions / / edited by Dionysis D. Bochtis [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (293 pages) |
| Disciplina | 630.2085 |
| Collana | Springer Optimization and Its Applications |
| Soggetto topico |
Agricultural informatics
Innovacions agrícoles Internet de les coses Aplicacions industrials |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-84156-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466555703316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
