Documents shared by Anónimo

Soggetti – Soggettività dell’individuo nel diritto internaz.
1. Definizione dell’istituto richiesto
Nel dir. int. classico (XVIII–XIX sec.) solo lo Stato era sogg. di dir. int.
L’individuo era oggetto, non titolare di diritti/obblighi.
Nel tempo ha acquisito crescente soggettività: oggi riconosciuto titolare di diritti e responsabile di violaz. gravi.

2. Evoluzione della soggettività dell’individuo
a) Come titolare di diritti
• Dir. int. dei dir. umani: da Carta ONU e Patti 1966 (civili/

AdaBoost (Adaptive Boosting)

AdaBoost is one of the simplest and earliest boosting algorithms. The main idea behind AdaBoost is to combine many weak learners (models that do slightly better than random guessing) into one strong learner.

It works by training multiple models one after another. After each model, the algorithm checks which data points were predicted wrong. It then gives more importance (weight) to those wrongly predicted samples so that the next model focuses more on correcting those

Predadores: organismos ativos - Carnívoros. Defesa química - Veneno/peçonha(besouro bombaerdeiro) Defesa comportamental - Mimetismo - Camuflagem. 1- Batesiana: animais palatáveis que imitam o padrão de cores de impalatáveis/venenosos. 2- Mulleriana: quando tanto o “original” quanto o mimico são impalatáveis. 3- Agressiva: espécie imita o comportamento ou a coloração de outra afim de predar.

Tanatose: comportamento de “fingir de morto”. Aposematismo: coloração de aviso de partes

Cloud Storage Management (7–8 Marks)

Introduction: Cloud Storage Management refers to the process of storing, organizing, securing, and maintaining data in cloud storage systems. It allows users and businesses to save large amounts of data on remote servers instead of local devices. ✅ Key Concepts of Cloud Storage Management:1. Data Storage in the Cloud: Data is stored on virtualized pools of storage located in data centers.Accessible anytime via internet. 2. Storage Types: Object Storage: Stores

🌩️ Basic Concepts of Cloud Computing (7–8 Marks)

Introduction: Cloud computing is a technology that allows users to access and store data, applications, and services over the Internet instead of a local computer or server. It provides computing resources like servers, storage, databases, networking, software, etc., on demand.

✅ Key Concepts: 1. On-Demand Service: Resources like storage, processing power, and software are available whenever needed. 2. Internet-Based Access:All cloud services

Unit-I

Basic a Concept of technolo cloud Computing Cloud Computing is that allows asers to accerz Jand atam, applications, and services over the internet store instead computing of local Computer resources like netwerking, software. or server. It provides servers, storage, databases, demand. a

Key Concepts ⅰ) On-demand Service Resources like storage, processing whenever needed. power and software are available internet-Based Access All cloud services through the internet using devices. laptops

Virtualization in enterprise solutions allows organizations to consolidate workloads, reduce hardware costs, and improve resource utilization by creating multiple virtual machines on a single physical server. This technology enables efficient management, enhanced flexibility, and better scalability, making it a cornerstone of modern IT infrastructure. 

Key Benefits of Virtualization for Enterprises:

Reduced Costs:Virtualization minimizes the number of physical servers required, leading to lower

Cloud infrastructure refers to the physical and virtual components that support cloud computing services. This includes servers, storage, networking equipment, virtualization software, and other underlying resources managed by a cloud service provider (CSP).

Pros of Cloud Infrastructure

 * Cost Efficiency (Shift from CAPEX to OPEX):

   * Reduced Capital Expenditure: You don't need to purchase expensive hardware, build data centers, or invest in extensive IT infrastructure upfront.

   * Pay-

AdaBoost (Adaptive Boosting)

AdaBoost is a classic and widely used boosting algorithm that focuses on correcting the errors of preceding weak learners (typically decision trees). It works by iteratively adjusting the weights of the training data points. 
How it Works:
Initial Weights: AdaBoost starts by assigning equal weights to all the training data points.
Train a Weak Learner: A "weak" learner (a model that performs slightly better than random chance, like a decision stump) is trained on the