Tabla de Contenidos: “…. -- Step 2 - exploring the data -- Step 3 - preparing variables to build datasets -- Step 4 - building the model -- Step 5 - creating data for a new, improved model -- Step 6 - improving the model -- Random forest - currency trading strategy -- Getting ready -- Step 1 - collecting and describing the data -- How to do it... -- Step 2 - exploring the data -- Step 3 - preparing variables to build datasets -- Step 4 - building the model -- Support vector machine - currency trading strategy -- Getting ready -- Step 1 - collecting and describing the data -- How to do it... -- Step 2 - exploring the data -- Step 3 - calculating the indicators -- Step 4 - preparing variables to build datasets -- Step 5 - building the model -- Stochastic gradient descent - adult income -- Getting ready -- Step 1 - collecting and describing the data -- How to do it... -- Step 2 - exploring the data -- Step 3 - preparing the data -- Step 4 - building the model -- Step 5 - plotting the model -- Chapter 7: Unsupervised Learning -- Introduction -- Self-organizing map - visualizing of heatmaps -- How to do it... -- Step 1 - exploring data -- Step 2 - training the model -- Step 3 - plotting the model…”

Tabla de Contenidos: “…Current Procedural Terminology (CPT) -- Logical Observation Identifiers Names and Codes (LOINC) -- National Drug Code (NDC) -- Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) -- Breaking down healthcare analytics -- Population -- Medical task -- Screening -- Diagnosis -- Outcome/Prognosis -- Response to treatment -- Data format -- Structured -- Unstructured -- Imaging -- Other data format -- Disease -- Acute versus chronic diseases -- Cancer -- Other diseases -- Putting it all together - specifying a use case -- Summary -- References and further reading -- Chapter 3: Machine Learning Foundations -- Model frameworks for medical decision making -- Tree-like reasoning -- Categorical reasoning with algorithms and trees -- Corresponding machine learning algorithms - decision tree and random forest -- Probabilistic reasoning and Bayes theorem -- Using Bayes theorem for calculating clinical probabilities -- Calculating the baseline MI probability -- 2 x 2 contingency table for chest pain and myocardial infarction -- Interpreting the contingency table and calculating sensitivity and specificity -- Calculating likelihood ratios for chest pain (+ and -) -- Calculating the post-test probability of MI given the presence of chest pain -- Corresponding machine learning algorithm - the Naive Bayes Classifier -- Criterion tables and the weighted sum approach -- Criterion tables -- Corresponding machine learning algorithms - linear and logistic regression -- Pattern association and neural networks -- Complex clinical reasoning -- Corresponding machine learning algorithm - neural networks and deep learning -- Machine learning pipeline -- Loading the data -- Cleaning and preprocessing the data -- Aggregating data -- Parsing data -- Converting types -- Dealing with missing data -- Exploring and visualizing the data -- Selecting features…”

Tabla de Contenidos: “…Advanced driver assistance systems (ADAS) -- Summary -- Chapter 3: Exploring ML Algorithms -- Technical requirements -- How machines learn -- Overview of ML algorithms -- Consideration for choosing ML algorithms -- Algorithms for classification and regression problems -- Linear regression algorithms -- Logistic regression algorithms -- Decision tree algorithms -- Random forest algorithm -- Gradient boosting machine and XGBoost algorithms -- K-nearest neighbor algorithm -- Multi-layer perceptron (MLP) networks -- Algorithms for clustering -- Algorithms for time series analysis -- ARIMA algorithm -- DeepAR algorithm -- Algorithms for recommendation -- Collaborative filtering algorithm -- Multi-armed bandit/contextual bandit algorithm -- Algorithms for computer vision problems -- Convolutional neural networks -- ResNet -- Algorithms for natural language processing (NLP) problems -- Word2Vec -- BERT -- Generative AI algorithms -- Generative adversarial network -- Generative pre-trained transformer (GPT) -- Large Language Model -- Diffusion model -- Hands-on exercise -- Problem statement -- Dataset description -- Setting up a Jupyter Notebook environment -- Running the exercise -- Summary -- Chapter 4: Data Management for ML -- Technical requirements -- Data management considerations for ML -- Data management architecture for ML -- Data storage and management -- AWS Lake Formation -- Data ingestion -- Kinesis Firehose -- AWS Glue -- AWS Lambda -- Data cataloging -- AWS Glue Data Catalog -- Custom data catalog solution -- Data processing -- ML data versioning -- S3 partitions -- Versioned S3 buckets -- Purpose-built data version tools -- ML feature stores -- Data serving for client consumption -- Consumption via API -- Consumption via data copy -- Special databases for ML -- Vector databases -- Graph databases -- Data pipelines…”

Tabla de Contenidos: “…Crest-climbing insight No. 4: Your flawed fear needs a free ride home -- Crest-climbing insight No. 5: You can't climb all the hills today -- Great social impact communicators build a resilient mindset to keep going in the face of adversity -- Act with integrity -- Lead with humility -- Be scientific in your approach -- Stay skeptical -- Communicate with transparency and openness -- After your hike past the crest, learn to navigate the cloud forest beyond -- Wait -- Analyze -- Take Gratitude -- Evaluate Options -- Run Again -- The watchout and the opportunity -- Key Questions -- Chapter 6: Secret #6: Highly effective social impact communicators ... cede perfection to the messy reality of change-making -- How messy looks for social impact communicators -- Paint the vision, not Van Gogh -- Why you should embrace satisfied persistence rather than perfection -- Stop trying to tie up all the loose ends -- Move ahead instead of around in circles -- When the dust flies, remember it will settle -- Capture attention and direct focus rather than sowing chaos -- Turn panic into peaceful action -- Guard the silent moments -- Engage in regular conversation that sparks ideas and opportunities -- Trade predictability for adaptability -- Key Questions -- Chapter 7: Secret #7: Highly effective social impact communicators ... build personal and professional legacies that outlive them and their careers -- First principles of legacy building for social impact communicators -- Principle No. 1: Legacy is the ripple effect of our actions -- Principle No. 2: Legacy is shiftable, not set in stone -- Principle No. 3: Legacy exists beyond our lifetime -- Principle No. 4: Legacy can be a blessing or a byword -- Principle No. 5: Legacy persists in the background -- How you can create a legacy that outlives you -- Legacy Builder 1: Give away your grace and mercy liberally…”

Tabla de Contenidos: “…7.7 Python中用于优化的包 -- 7.8 Octave中用于优化的包 -- 7.9 Julia中用于优化的包 -- 7.10 总结 -- 7.11 回 及练习 -- 第8章 Anaconda中的无监督学习 -- 8.1 无监督学习简介 -- 8.2 层次 类 -- 8.3 k-均值 类 -- 8.4 Python包scipy简介 -- 8.5 Python包contrastive简介 -- 8.6 Python包sklearn scikit-learn 简介 -- 8.7 R包rattle简介 -- 8.8 R包randomUniformForest简介 -- 8.9 R包Rmixmod简介 -- 8.10 Julia实现 -- 8.11 类分析的任务 图 -- 8.12 总结 -- 8.13 回 及练习 -- 第9章 Anaconda中的监督学习 -- 9.1 监督学习概 -- 9.2 分类 -- 9.2.1 k-最 算法 -- 9.2.2 叶斯分类器 -- 9.2.3 强化学习 -- 9.3 监督学习的R实现 -- RtextTools简介 -- 9.4 Python实现 -- 使用scikit-learn sklearn 模块 -- 9.5 Octave实现 -- 9.6 Julia实现 -- R中机器学习的任务 图 -- 9.7 总结 -- 9.8 回 及练习 -- 第10章 数据 测分析 建模和 -- 10.1 理 数据 测分析 -- 10.2 有用的数据 -- 10.2.1 R包AppliedPredictiveModeling -- 10.2.2 时 序列分析 -- 10.3 测未来事件 -- 10.3.1 季 性 -- 10.3.2 可 化组件 -- 10.3.3 R包LiblineaR -- 10.3.4 R包datarobot -- 10.3.5 R包eclust -- 10.4 模型 择 -- 10.4.1 Python包model-catwalk -- 10.4.2 Python包sklearn -- 10.4.3 Julia包QuantEcon -- 10.4.4 Octave包ltfat -- 10.5 Granger因果关系检 -- 10.6 总结 -- 10.7 回 及练习 -- 第11章 Anaconda云 -- 11.1 Anaconda云简介 -- 11.2 深入学习Jupyter Notebook -- 11.2.1 Jupyter Notebook格式 -- 11.2.2 Notebooks分享 -- 11.2.3 目分享 -- 11.2.4 环境分享 -- 11.3 复制他人的环境到本地 -- 从Anaconda下 包 -- 11.4 总结 -- 11.5 回 及练习 -- 第12章 分布式 算、并 算和HPCC -- 12.1 分布式和并 算简介 -- 12.1.1 并 处理的任务 图 -- 12.1.2 Python示例程序 -- 12.2 理 MPI -- 12.2.1 R包Rmpi -- 12.2.2 R包plyr -- 12.2.3 R包parallel -- 12.2.4 R包snow -- 12.3 Python并 处理 -- 12.3.1 单 率的并 处理 -- 12.3.2 Monte-Carlo期权定价并 处理 -- 12.4 算 点 -- 12.5 Anaconda 加组件 -- 12.6 HPCC简介 -- 12.7 总结 -- 12.8 回 及练习…”

“…In the Languedoc region, the early balance between the mediterranean oak forest and human activities leads us to review the history of deforestation. …”

Tabla de Contenidos: “…-- 2.2 The Untapped Green Potential of the Subsides Agreement -- 2.3 Three Ways to Protect the Environment -- 2.4 Trade Sanctions and Forests Protection -- 2.5 A New Kind of Environmental Bargain -- 2.6 The EU's Sustainable Commercial Policy -- 2.7 From Exception to Promotion -- i -- ii -- iii -- 3 The Power of Ideas -- 3.1 From Weak to Strong Integration -- 3.2 Watching the Seeds Grow -- 3.3 The Development Factor -- 3.4 It's Not All About the Environment -- 3.5 Two Birds with One Stone -- 3.6 Missed Opportunities -- 6 Conclusions -- 1 Ideational Change -- 2 Historical Contingency -- 2.1 The gatt and Embedded Liberalism -- 2.2 The wto and the Resurgence of Neoliberalism -- 2.3 The 2030 Agenda and the Instrumental Role of Trade -- 3 A New Trade Story -- 3.1 One. …”

Tabla de Contenidos: “…Cryptic Eucoleus [Capillaria] sp. in the respiratory tract of a cat from Australia -- Comparison of quantitative polymerase chain reaction, Kato-Katz and circulating cathodic antigen rapid test for the diagnosis of Schistosoma mansoni infection: A cross-sectional study in Kirinyaga County, Kenya -- Field evaluation of Veeralin, an alpha-cypermethrin + PBO long-lasting insecticidal net, against natural populations of Anopheles funestus in experimental huts in Muheza, Tanzania -- In vitro anti-Trypanosoma cruzi activity enhancement of curcumin by its monoketone tetramethoxy analog diveratralacetone -- Complexity of malaria transmission dynamics in the Brazilian Atlantic Forest -- Using cerebrospinal fluid to confirm Angiostrongylus cantonensis as the cause of canine neuroangiostrongyliasis in Australia where A. cantonensis and Angiostrongylus mackerrasae co-exist -- Molecular screening for tick-borne bacteria and hematozoa in Ixodes cf. boliviensis and Ixodes tapirus (Ixodida: Ixodidae) from western highlands of Panama -- Illuminating the bacterial microbiome of Australian ticks with 16S and Rickettsia-specific next-generation sequencing -- Biolarviciding for malaria vector control: Acceptance and associated factors in southern Tanzania -- Unexpected failure of Ixodes scapularis nymphs to transmit a North American Borrelia bissettiae strain -- Promastigotes of Leishmania donovani exhibited sensitivity towards the high altitudinal plant Cicer microphyllum -- Towards understanding transfluthrin efficacy in a pyrethroid-resistant strain of the malaria vector Anopheles funestus with special reference to cytochrome P450-mediated detoxification -- Insecticide-impregnated netting: A surface treatment for killing Lutzomyia longipalpis (Diptera: Psychodidae), the vector of Leishmania infantum -- Cat fleas (Ctenocephalides felis clade 'Sydney') are dominant fleas on dogs and cats in New South Wales, Australia: Presence of flea-borne Rickettsia felis, Bartonella spp. but absence of Coxiella burnetii DNA -- Babesia gibsoni emerging with high prevalence and co-infections in "fighting dogs" in Hungary -- Morphological and molecular characterization of a new species of Isospora Schneider, 1881 (Apicomplexa: Eimeriidae) from the western wattlebird Anthochaera lunulata Gould in Western Australia -- Unravelling the diversity of the Crassiphialinae (Digenea: Diplostomidae) with molecular phylogeny and descriptions of five new species -- Haemoprotozoan surveillance in peri-urban native and introduced wildlife from Australia -- VectorMap-GR: A local scale operational management tool for entomological monitoring, to support vector control activities in Greece and the Mediterranean Basin -- Neospora caninum and Toxoplasma gondii as causes of reproductive losses in commercial sheep flocks from Argentina -- Molecular detection of Borrelia burgdorferi (sensu lato) and Rickettsia spp. in hard ticks distributed in Tokachi District, eastern Hokkaido, Japan -- Considerations for anthelmintic resistance emergence in hookworm at a single locus -- Wild deer in the United Kingdom are a potential reservoir for the livestock parasite Babesia divergens -- First description of sarcoptic mange in an Iberian hare (Lepus granatensis) -- Evaluation of buffered Trypanosoma evansi antigen and rapid serum agglutination test (BA/Te) for the detection of anti-T. evansi antibodies in horses in Brazil -- Cryptosporidium of birds in pet markets in Wuhan city, Hubei, China -- Global analysis of cytochrome c oxidase subunit 1 (cox1) gene variation in Dibothriocephalus nihonkaiensis (Cestoda: Diphyllobothriidae) -- Insecticidal efficacy of afoxolaner against Stomoxys calcitrans (Diptera: Muscidae) in dogs -- The detection of Schistosoma bovis in livestock on Pemba Island, Zanzibar: A preliminary study -- Sarcoptic mange in the wild boar, Sus scrofa, in Sweden -- Dengue outbreaks in Bangladesh: Historic epidemic patterns suggest earlier mosquito control intervention in the transmission season could reduce the monthly growth factor and extent of epidemics -- Predicting eastern equine encephalitis spread in North America: An ecological study -- Vapor phase repellency and insecticidal activity of pyridinyl amides against anopheline mosquitoes -- Editorial: First anniversary of Current Research in Parasitology &Vector-BorneDiseases…”

Tabla de Contenidos: “…Reconstruction of Subsurface Salinity Structure in the South China Sea Using Satellite Observations: A LightGBM-Based Deep Forest Method -- L ́ea Schamberger, Audrey Minghelli, Malik Chami and Fran ̧cois Steinmetz Improvement of Atmospheric Correction of Satellite Sentinel-3/OLCI Data for Oceanic Waters in Presence of Sargassum -- Mingjun He, Shuangyan He, Xiaodong Zhang, Feng Zhou and Peiliang Li AssessmentofNormalizedWater-LeavingRadianceDerivedfromGOCIUsingAERONET-OC Data -- Shiming Lu, Mingjun He, Shuangyan He, Shuo He, Yunhe Pan, Wenbin Yin and Peiliang Li An Improved Cloud Masking Method for GOCI Data over Turbid Coastal Waters -- Hongwei Zhang, Yuanshuai Zhang, Ziwang Li, Bingyi Liu, Bin Yin and Songhua Wu Small Angle Scattering Intensity Measurement by an Improved Ocean Scheimpflug Lidar System -- Junyi Li, Huiyuan Zheng, Lingling Xie, Quanan Zheng, Zheng Ling and Min Li Response of Total Suspended Sediment and Chlorophyll-a Concentration to Late Autumn Typhoon Events in The Northwestern South China Sea -- Khalid A. …”

Tabla de Contenidos: “…Infinitiv Perfekt Vorgangspassiv -- 5.3. Random Forests und Trees -- 5.3.1. Epistemisches dürfte -- 5.3.2. …”

Tabla de Contenidos: “…Colombia has steadily strengthened its economy over the last two decades -- Yet, regional inequality remains high, with room for improvement -- The population in Colombia has concentrated at a faster pace than its economy -- The post-COVID19 period has been used as an opportunity to bridge the territorial divide -- In a nutshell: Assets and challenges of rural regions in Colombia -- Economic patterns shaping Colombian rural regions -- Colombia and its rural regions are diversifying the economic structure -- Economic diversity enhances the resilience of regions -- Rural economies face high labour informality and low education attainment -- Unemployment in rural areas is lower than in urban, despite labour informality -- Demographic patterns in Colombian rural regions -- Colombia's population continues to grow regardless of region, with particular strength in several rural areas -- The Colombian population is young, particularly in rural areas -- Yet, the share of young people in rural places depicts a decreasing trend -- Women's inclusion leads to improved social cohesion and economic prosperity -- Well-being enablers -- Snapshot of quality of life in Colombia -- Civil infrastructure has proved crucial for Colombia and still has significant room for improvement -- Road infrastructure -- Rural communities significantly lag in broadband connectivity and speeds -- Education in rural regions is progressing well in Colombia, though efforts must continue -- Environment: Biodiversity as an opportunity and deforestation as a threat -- Security and land access -- References -- Notes -- Annex 2.A. …”

Tabla de Contenidos: “…. -- 7.1 Introduction and literature review -- 7.2 Materials and methods -- 7.2.1 Logistic regression -- 7.2.2 Gaussian naive Bayes -- 7.2.3 K-Nearest neighbors -- 7.2.4 Support vector classification -- 7.2.5 Radial basis function -- 7.2.6 Artificial neural network -- 7.2.7 Cart algorithm -- 7.2.8 Random forest -- 7.2.9 Gradient boosting machines -- 7.2.10 XGBoost -- 7.2.11 LightGBM -- 7.2.12 CatBoost -- 7.3 Experimental results -- 7.4 Conclusion and future work -- References -- 8 Healthcare cybersecurity challenges: a look at current and future trends -- 8.1 Introduction -- 8.2 The amount of prior works -- 8.3 Difficulties -- 8.3.1 Security assurance for remote work -- 8.3.2 Endpoint device administration -- 8.3.3 The role of humans in cybersecurity -- 8.3.4 A disregard for security -- 8.3.5 Ineffective risk assessment communication at the board level -- 8.3.6 Poor business continuity strategies -- 8.3.7 Ineffective incident response coordination -- 8.3.8 A tight budget and the requirement to provide healthcare services uninterrupted -- 8.3.9 Dangerous medical cyber-physical systems -- 8.4 A review of current and future trends in cybersecurity challenges in healthcare -- 8.5 Discussion -- 8.5.1 Cyber-physical medical systems -- 8.5.2 Data privacy, confidentiality, and consent -- 8.5.3 Cloud computing -- 8.5.4 Malware -- 8.5.5 Security of health application (or "app") -- 8.5.6 Insider danger -- 8.6 Cybersecurity tools, defenses, and mitigation techniques -- 8.6.1 Cryptographic systems or other technological advances -- 8.6.2 Governance and risk assessment -- 8.6.3 Laws or other regulations -- 8.6.4 A comprehensive strategy for proactive cybersecurity culture -- 8.6.5 Instruction and simulated settings…”

Tabla de Contenidos: “…-- Creating Materialized Views and understanding how BI Engine works -- Understanding BI Engine -- Summary -- Chapter 8: Building Machine Learning Solutions on GCP -- Technical requirements -- A quick look at ML -- Exercise - practicing ML code using Python -- Preparing the ML dataset by using a table from the BigQuery public dataset -- Training the ML model using Random Forest in Python -- Creating a batch prediction using the training dataset's output -- The MLOps landscape in GCP -- Understanding the basic principles of MLOps -- Introducing GCP services related to MLOps -- Exercise - leveraging pre-built GCP models as a service -- Uploading the image to a GCS bucket -- Creating a detect text function in Python -- Exercise - using GCP in AutoML to train an ML model -- Exercise - deploying a dummy workflow with Vertex AI Pipelines -- Creating a dedicated regional GCS bucket -- Developing the pipeline on Python -- Monitoring the pipeline on the Vertex AI Pipelines console -- Exercise - deploying a scikit-learn model pipeline with Vertex AI -- Creating the first pipeline, which will result in an ML model file in GCS -- Running the first pipeline in Vertex AI Pipelines -- Creating the second pipeline, which will use the model file from the prediction results as a CSV file in GCS -- Running the second pipeline in Vertex AI Pipelines -- Summary…”

Tabla de Contenidos: “…The efforts to develop Forest Farmer Group (FFG) business through designing visual identity packaging of mangrove coffee products in Indramayu -- 1 Introduction -- 2 Methods -- 3 Analysis And Discussion -- 3.1 SWOT analysis -- 3.2 Segmentation, targeting, positioning (STP) -- 3.3 Concept -- Message concept -- Creative concept -- Visual concept -- Media concept -- 4 Conclusion -- References -- Exploring ideas of sustainable workplace through visual storytelling: A case study of #KomikCeritaIndah -- 1 Introduction -- 2 Research Methods -- 3 Result And Discussions -- 3.1 Collaborate: #KomikCeritaIndah, Comic Series from Women Lead by Magdalene -- 3.2 Communicate: Campaign objectives through visual narratives -- 3.2.1 Communicate: Final visual implementation -- 3.3 Connect: Circulating The #KomikCeritaIndah on Instagram -- 4 Conclusion -- References -- How SME-scaled branding agencies creates a high-quality yet affordable brand identity design for SMEs in Indonesia -- 1 Introduction -- 2 Research Methods -- 3 Result And Discussion -- 4 Conclusions -- References -- Philosophical potential of Ngalokat Cai ritual for Cimahi city branding design based on sustainable development goals -- 1 Introduction -- 2 Methodology -- 2.1 Method of collecting data -- 3 Result and Discussion -- 3.1 Analysis -- 3.2 City identity -- 3.3 City branding through media design concept -- 4 Conclusion -- References -- Zine on sharia investment basics for college students -- 1 Introduction -- 2 Research Methods -- 2.1 Methods of data collecting -- 2.2 Methods of data analysis -- 3 Results and Discussion -- 3.1 Media and content concept -- 4 Conclusion -- References -- Fish consumption culture in Manado as a consideration to a web design -- 1 Introduction -- 2 Research Methods -- 3 Result and Discussion -- 4 Conclusion -- References…”

Tabla de Contenidos: “…12.3.1.5 Spying -- 12.3.2 Active Attacks -- 12.3.2.1 Denial of Service -- 12.3.2.2 Distributed Denial of Service (DDOS) -- 12.3.2.3 Message Modification -- 12.3.2.4 Masquerade -- 12.3.2.5 Trojans -- 12.3.2.6 Replay Attacks -- 12.3.3 Programming Weapons for the Attackers -- 12.3.3.1 Dormant Phase -- 12.3.3.2 Propagation Phase -- 12.3.3.3 Triggering Phase -- 12.3.3.4 Execution Phase -- 12.4 Recent Cyber Attacks -- 12.5 Drawbacks of Traditional Cryptography -- 12.5.1 Cost and Time Delay -- 12.5.2 Disclosure of Mathematical Computation -- 12.5.3 Unsalted Hashing -- 12.5.4 Attacks -- 12.6 Need of Quantum Cryptography -- 12.6.1 Quantum Mechanics -- 12.7 Evolution of Quantum Cryptography -- 12.8 Conclusion and Future Work -- References -- Chapter 13 Identification of Bacterial Diseases in Plants Using Re-Trained Transfer Learning in Quantum Computing Environment -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Proposed Methodology -- 13.3.1 SVM Classifier -- 13.3.2 Random Forest to Classify the Rice Leaf -- 13.3.2.1 Image Pre-Processing -- 13.3.2.2 Feature Extraction -- 13.3.2.3 Classification -- 13.4 Experiment Results -- Conclusion -- References -- Chapter 14 Quantum Cryptography -- 14.1 Fundamentals of Cryptography -- 14.2 Principle of Quantum Cryptography -- 14.2.1 Quantum vs. …”

Tabla de Contenidos: “…Front Cover -- Graph Based Multimedia Analysis -- Copyright -- Contents -- List of figures -- List of tables -- Biography -- Foreword -- Preface -- 1 Introduction -- 1.1 Motivation -- 1.2 Chapter organization -- 1.3 Basics of multimedia -- 1.4 Preliminaries of a video -- 1.5 Multimedia problems -- 1.6 Graph based solutions -- 1.7 Other solution models -- 1.8 Organization of the book -- References -- 2 Theoretical foundations -- 2.1 Motivation -- 2.2 Organization -- 2.3 Graph basics -- 2.4 Delaunay graph -- 2.5 Bipartite graph -- 2.6 Minimum spanning tree -- 2.7 Optimum path forest -- 2.8 Random walks on a graph -- 2.9 Knapsack problems -- 2.10 Elementary game theory -- References -- 3 Exocentric video summarization -- 3.1 Motivation -- 3.2 Chapter organization -- 3.3 Related works -- 3.3.1 Related works for exocentric video summarization -- 3.3.2 Related works for scalable exocentric video summarization -- 3.4 Method I: Delaunay graph based solutions for exocentric video summarization -- 3.4.1 Method IA: Constrained Delaunay graph clustering based summary -- 3.4.1.1 Video frame presampling -- 3.4.1.2 Feature extraction -- 3.4.1.3 Elimination of redundant frames -- 3.4.1.4 Delaunay graph based constrained clustering -- 3.4.1.5 Key frame extraction -- 3.4.2 Method IB: Delaunay graph based summary with user customization -- 3.4.3 Method IC: Delaunay graph based summary in enhanced feature space -- 3.5 Method II: A graph modularity based clustering for exocentric video summarization -- 3.5.1 Compressed domain feature extraction -- 3.5.2 Multi-feature fusion -- 3.5.3 Graph modularity based clustering -- 3.5.4 Key frame extraction -- 3.6 Scalable exocentric video summarization with skeleton graph and random walk -- 3.6.1 Extraction of skeleton graph -- 3.6.2 Clustering of skeleton graph via MST -- 3.6.3 Label propagation with random walks…”

“…In this Special Issue of the journal Forests, we explore the broad range of current research dedicated to our topic: International Short Rotation Woody Crop Production Systems for Ecosystem Services and Phytotechnologies…”

Tabla de Contenidos: “…Correlating individual stocks with the broader market -- Exploring risk and return -- Examining the market with the non-parametric runs test -- Testing for random walks -- Determining market efficiency with autoregressive models -- Creating tables for a stock prices database -- Populating the stock prices database -- Optimizing an equal weights two-asset portfolio -- Chapter 8: Text Mining and Social Network Analysis -- Introduction -- Creating a categorized corpus -- Tokenizing news articles in sentences and words -- Stemming, lemmatizing, filtering, and TF-IDF scores -- Recognizing named entities -- Extracting topics with non-negative matrix factorization -- Implementing a basic terms database -- Computing social network density -- Calculating social network closeness centrality -- Determining the betweenness centrality -- Estimating the average clustering coefficient -- Calculating the assortativity coefficient of a graph -- Getting the clique number of a graph -- Creating a document graph with cosine similarity -- Chapter 9: Ensemble Learning and Dimensionality Reduction -- Introduction -- Recursively eliminating features -- Applying principal component analysis for dimension reduction -- Applying linear discriminant analysis for dimension reduction -- Stacking and majority voting for multiple models -- Learning with random forests -- Fitting noisy data with the RANSAC algorithm -- Bagging to improve results -- Boosting for better learning -- Nesting cross-validation -- Reusing models with joblib -- Hierarchically clustering data -- Taking a Theano tour -- Chapter 10: Evaluating Classifiers, Regressors, and Clusters -- Introduction -- Getting classification straight with the confusion matrix -- Computing precision, recall, and F1-score -- Examining a receiver operating characteristic and the area under a curve…”

Tabla de Contenidos: “…. -- Classifying data points with Random Forest model using MLib -- Getting ready -- How to do it... -- Chapter 8: Learn Deeply from Data -- Introduction -- Creating a Word2vec neural net using Deep Learning for Java (DL4j) -- How to do it... -- How it works... -- There's more -- Creating a Deep Belief neural net using Deep Learning for Java (DL4j) -- How to do it... -- How it works... -- Creating a deep autoencoder using Deep Learning for Java (DL4j) -- How to do it...…”

Tabla de Contenidos: “…. -- Predicting breast cancer outcomes using Random Forests -- Getting ready -- How to do it... -- There's more... -- Chapter 11: Parallel Processing with Dask and Zarr -- Reading genomics data with Zarr -- Getting ready -- How to do it... -- There's more... -- See also -- Parallel processing of data using Python multiprocessing -- Getting ready -- How to do it... -- There's more... -- See also -- Using Dask to process genomic data based on NumPy arrays -- Getting ready -- How to do it... -- There's more... -- See also -- Scheduling tasks with dask.distributed -- Getting ready -- How to do it... -- There's more... -- See also -- Chapter 12: Functional Programming for Bioinformatics -- Understanding pure functions -- Getting ready -- How to do it... -- There's more... -- Understanding immutability -- Getting ready -- How to do it... -- There's more... -- Avoiding mutability as a robust development pattern -- Getting ready -- How to do it... -- There's more... -- Using lazy programming for pipelining -- Getting ready -- How to do it... -- There's more... -- The limits of recursion with Python -- Getting ready -- How to do it... -- There's more... -- A showcase of Python's functools module -- Getting ready -- How to do it... -- There's more... -- See also... -- Index -- Other Books You May Enjoy…”