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SEO
SEO represents Search Engine Optimization. It is a method of strategies and techniques used to increase the amount of visitors to a website. There is a need to obtain a high-ranking placement in the search result pages of a search engine like Google, Bing, Yahoo and other search engines.
Internet users are not at all interested to click through pages and pages of search results, so the ranking of a site in a search result page is essential for driving more traffic towards that website.
Tt 2ndbatx lesson4
This document provides teaching tips and materials for a lesson on starting arguments "for and against" a topic. It discusses whether teenage criminals should be sent to adult prisons or juvenile prisons instead. Arguments presented include that juvenile prisons are better equipped to handle teenagers, who may have acted impulsively and regret their actions, and that adult prisons could be a bad influence. However, some argue that serious teenage criminals may influence other juveniles negatively or that teenagers understand the consequences of their actions. The document also covers grammar topics like using "to" and "for" to express reason, the passive voice, the causative form, and phrasal verbs.
History of poppy A Presentation By Mr Allah Dad khan Former Director General ...
History of poppy A Presentation By Mr Allah Dad khan Former Director General Agriculture Extension KPK Province and Visiting Professor the University of Agriculture Peshawar Pakistan
Evaluation 2 how effective is the combination
The combination of the main product (digipack) and ancillary texts (music video, magazine advert) is highly effective. [1] Images, fonts, and themes are consistent across products to create a cohesive brand identity. [2] Related images and content from the music video are featured on the digipack, directly linking the two. [3] The magazine advert promotes the album using the artist's image, album cover, and conventions like ratings to engage viewers.
Recommended
SEO
SEO represents Search Engine Optimization. It is a method of strategies and techniques used to increase the amount of visitors to a website. There is a need to obtain a high-ranking placement in the search result pages of a search engine like Google, Bing, Yahoo and other search engines.
Internet users are not at all interested to click through pages and pages of search results, so the ranking of a site in a search result page is essential for driving more traffic towards that website.
Tt 2ndbatx lesson4
This document provides teaching tips and materials for a lesson on starting arguments "for and against" a topic. It discusses whether teenage criminals should be sent to adult prisons or juvenile prisons instead. Arguments presented include that juvenile prisons are better equipped to handle teenagers, who may have acted impulsively and regret their actions, and that adult prisons could be a bad influence. However, some argue that serious teenage criminals may influence other juveniles negatively or that teenagers understand the consequences of their actions. The document also covers grammar topics like using "to" and "for" to express reason, the passive voice, the causative form, and phrasal verbs.
History of poppy A Presentation By Mr Allah Dad khan Former Director General ...
History of poppy A Presentation By Mr Allah Dad khan Former Director General Agriculture Extension KPK Province and Visiting Professor the University of Agriculture Peshawar Pakistan
Evaluation 2 how effective is the combination
The combination of the main product (digipack) and ancillary texts (music video, magazine advert) is highly effective. [1] Images, fonts, and themes are consistent across products to create a cohesive brand identity. [2] Related images and content from the music video are featured on the digipack, directly linking the two. [3] The magazine advert promotes the album using the artist's image, album cover, and conventions like ratings to engage viewers.
Software Development for Market Surveillance systems
Основные вопросы лекции:
- London Stock Exchange Group и компания Exactpro;
- представительство в Костроме и возможности трудоустройства;
- характеристики биржевой платформы и обязанности по поддержанию упорядоченного рынка;
- виды финансовых преступлений;
- анализ данных - профессия будущего;
- программное обеспечение систем отслеживания финансовых манипуляций.
Non-Functional Testing at London Stock Exchange
29 November 2016
Harvard Club, New York, QA-Financial Forum
Exactpro is the specialist testing subsidiary of the London Stock Exchange Group. In this presentation,
Iosif Itkin will cover the wide range of testing requirements faced by broker-dealers, banks and
exchanges beyond the requirements of functional testing. Plus: In Conversation with Yann L’Huillier,
CIO, Tradition and Iosif Itkin, CEO, Exactpro
- Iosif Itkin: Exactpro CEO – The London Stock Exchance Group
- Yann L’Huillier: Group Chief Information Officer – Tradition
Exactpro: Non-functional testing approach
This document discusses non-functional testing approaches for financial markets software. It describes the structure of non-functional testing teams, how to prepare tests by configuring load injectors and defining load shapes, and the types of non-functional tests performed, including latency measurements, capacity tests, DLC testing, failover testing, and other approaches to evaluate system performance under stress conditions.
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L7 er2
The document discusses various concepts in entity-relationship (E-R) modeling including: weak entity sets and how their primary keys are formed; reducing E-R diagrams to relational schemas; extended E-R features like specialization, generalization, and aggregation; and differences between E-R diagrams and UML class diagrams. Key symbols used in E-R notation are also summarized.
L8 design1
This document provides an overview of relational database design and normalization. It discusses the goals of database design as generating schemas without unnecessary redundancy and allowing easy data retrieval. Normalization aims to design schemas in a desirable normal form, such as Boyce-Codd normal form (BCNF) or third normal form (3NF). The document introduces key concepts like functional dependencies, normal forms, decomposition, and closure of functional dependencies, which are used to determine if a schema is properly normalized and how to decompose schemas if necessary.
L9 design2
This document provides an overview of relational database design concepts including normal forms and decomposition. It begins with an outline of topics to be covered such as algorithms for functional dependencies, decomposition using multi-valued dependencies, normal forms, and modeling temporal data. The document then reviews Boyce-Codd normal form and provides examples of testing for and decomposing relations into BCNF. It also introduces third normal form and covers testing for and decomposing relations into 3NF. Finally, it briefly discusses multi-valued dependencies and compares BCNF and 3NF.
14 pro resolution
This document provides an overview of resolution in propositional logic. It introduces resolution as a new rule of inference that allows inferring a resolvent clause from two clauses. It describes how to convert arbitrary well-formed formulas into conjunctions of clauses to use with resolution. Resolution refutations are discussed as a way to decide logical entailments by attempting to derive the empty clause. Various strategies for conducting resolution refutation searches more efficiently are also covered, including ordering strategies and refinement strategies. Finally, the document defines Horn clauses and their special properties that allow for linear-time deduction algorithms.
13 propositional calculus
This document provides an overview of the Propositional Calculus. It discusses:
- The language of propositional calculus using atoms, connectives, and well-formed formulas
- Rules of inference like modus ponens, conjunction introduction, and disjunction introduction
- Defining proofs and theorems based on applying rules of inference
- Semantics by associating logical elements with truth values under interpretations
- Important concepts like validity, equivalence, entailment, and the soundness and completeness of rules of inference.
- The propositional satisfiability (PSAT) problem and solving techniques like exhaustive search and GSAT.
12 adversal search
This document discusses adversarial search techniques for two-agent games with perfect information. It introduces the minimax procedure and how it recursively assigns values to nodes in a game tree by maximizing the value for the maximizing agent and minimizing for the minimizing agent. The alpha-beta pruning technique is described which improves search efficiency by pruning subtrees that cannot alter the minimax value of the root. Examples of applying minimax and alpha-beta to tic-tac-toe are provided. The document also discusses handling games of chance using expectimax search and learning effective evaluation functions from self-play.
11 alternative search
This document discusses different approaches to solving constraint satisfaction problems including assignment problems. It provides examples of the eight queens problem and constraint propagation techniques. Constructive methods start with no assignments and add values satisfying constraints, while heuristic repair starts with a proposed solution and changes it to violate fewer constraints. Function optimization techniques like hill climbing and simulated annealing are also discussed.
10 2 sum
The document discusses different methods for reinforcement learning, including learning heuristic functions from experiences, learning in explicit and implicit graphs, using rewards instead of goals for tasks, and different algorithms like temporal difference learning and value iteration that help agents learn optimal policies by assigning credit to relevant state-action pairs.
22 planning
The document describes planning techniques in artificial intelligence, including STRIPS planning systems, forward and backward search methods, and partial-order planning. It discusses how STRIPS uses operators to describe state changes and searches for a sequence of actions to reach a goal state. Backward search methods work by regressing goals through operators to produce subgoals. Partial-order planning searches a plan space by transforming incomplete plans into more articulated plans until finding an executable plan.
21 situation calculus
This document provides an overview of the Situation Calculus, a formal logic framework for representing states, actions, and how actions transform states. It describes key components of the Situation Calculus including: (1) representing states as constants and using predicates to describe state properties, (2) representing actions and how they change state properties using effect axioms, (3) using frame axioms to represent properties that don't change with actions, and (4) generating plans by proving the existence of goal states and extracting the actions. Challenges with the approach include dealing with ramifications of actions and specifying all relevant preconditions and qualifications.
20 bayes learning
The document provides an overview of learning Bayes networks from data. It discusses learning the structure and conditional probability tables (CPTs) of a Bayes network given training data. When the network structure is known, the CPTs can be directly estimated from sample statistics in the training data, handling both cases of complete and missing data using techniques like expectation-maximization. When the structure is unknown, scoring metrics like minimum description length are used to search the space of possible structures to find the best fitting network. Dynamic decision networks extend this framework to model sequential decision making problems.
19 uncertain evidence
This document outlines probabilistic inference in Bayes networks. It begins with a review of probability theory concepts like joint probability, marginal probability, conditional probability, and Bayes' rule. It then discusses probabilistic inference in Bayes networks, including causal/top-down inference using evidence to determine probabilities, diagnostic/bottom-up inference using effects to determine causes, and "explaining away" where additional evidence makes other probabilities less certain. The document also covers uncertain evidence, D-separation to determine conditional independence, and inference techniques in polytrees.
18 common knowledge
This document discusses representing commonsense knowledge. It describes commonsense knowledge as everyday facts that most people understand, like objects falling when dropped or fish needing water. Representing all commonsense knowledge is difficult as there are no defined boundaries and some concepts cannot be described with sentences alone. The document outlines research areas in representing objects, materials, space, time, and physical processes. It also discusses knowledge representation using semantic networks and frames to organize taxonomic hierarchies and relationships between objects, properties, and categories in a graph structure. Nonmonotonic reasoning is also discussed for handling exceptions to default inferences.
17 2 expert systems
Rule-based expert systems use facts and rules to achieve expert-level competence in solving problems. They consist of a knowledge base containing facts and rules, an inference engine that manipulates the knowledge base to deduce information, and an explanation subsystem. Rule-based systems apply logical rules to the known facts to determine unknown information. Inductive logic programming learns rules by generalizing from examples to cover positive instances while avoiding negative ones.
17 1 knowledge-based system
The document discusses knowledge-based systems and their ability to reason over extensive knowledge bases. It addresses the theoretical problems of soundness, completeness, and tractability when using logical reasoning systems. Horn clauses and PROLOG are introduced as more efficient ways to perform inference compared to full predicate calculus. Different methods for reasoning including forward chaining and truth and assumption-based maintenance are also summarized.
16 2 predicate resolution
This document discusses resolution in predicate calculus. It covers topics like unification, predicate calculus resolution, converting well-formed formulas to clause form, using resolution to prove theorems, and answer extraction. It also discusses the equality predicate and paramodulation inference rule. The document provides examples to illustrate various concepts and techniques in resolution-based automated theorem proving in first-order logic.
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Software Development for Market Surveillance systems
Основные вопросы лекции:
- London Stock Exchange Group и компания Exactpro;
- представительство в Костроме и возможности трудоустройства;
- характеристики биржевой платформы и обязанности по поддержанию упорядоченного рынка;
- виды финансовых преступлений;
- анализ данных - профессия будущего;
- программное обеспечение систем отслеживания финансовых манипуляций.
Non-Functional Testing at London Stock Exchange
29 November 2016
Harvard Club, New York, QA-Financial Forum
Exactpro is the specialist testing subsidiary of the London Stock Exchange Group. In this presentation,
Iosif Itkin will cover the wide range of testing requirements faced by broker-dealers, banks and
exchanges beyond the requirements of functional testing. Plus: In Conversation with Yann L’Huillier,
CIO, Tradition and Iosif Itkin, CEO, Exactpro
- Iosif Itkin: Exactpro CEO – The London Stock Exchance Group
- Yann L’Huillier: Group Chief Information Officer – Tradition
Exactpro: Non-functional testing approach
This document discusses non-functional testing approaches for financial markets software. It describes the structure of non-functional testing teams, how to prepare tests by configuring load injectors and defining load shapes, and the types of non-functional tests performed, including latency measurements, capacity tests, DLC testing, failover testing, and other approaches to evaluate system performance under stress conditions.
Χριστουγεννιάτικα συννεφόλεξα Ε1 τμήμα
Τα παιδιά του τμήματος Ε1 του 4ου Δημοτικού Σχολείου
Αθήνας φτιάχνουν χριστουγεννιάτικα συννεφόλεξα.
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More from Tianlu Wang
L7 er2
The document discusses various concepts in entity-relationship (E-R) modeling including: weak entity sets and how their primary keys are formed; reducing E-R diagrams to relational schemas; extended E-R features like specialization, generalization, and aggregation; and differences between E-R diagrams and UML class diagrams. Key symbols used in E-R notation are also summarized.
L8 design1
This document provides an overview of relational database design and normalization. It discusses the goals of database design as generating schemas without unnecessary redundancy and allowing easy data retrieval. Normalization aims to design schemas in a desirable normal form, such as Boyce-Codd normal form (BCNF) or third normal form (3NF). The document introduces key concepts like functional dependencies, normal forms, decomposition, and closure of functional dependencies, which are used to determine if a schema is properly normalized and how to decompose schemas if necessary.
L9 design2
This document provides an overview of relational database design concepts including normal forms and decomposition. It begins with an outline of topics to be covered such as algorithms for functional dependencies, decomposition using multi-valued dependencies, normal forms, and modeling temporal data. The document then reviews Boyce-Codd normal form and provides examples of testing for and decomposing relations into BCNF. It also introduces third normal form and covers testing for and decomposing relations into 3NF. Finally, it briefly discusses multi-valued dependencies and compares BCNF and 3NF.
14 pro resolution
This document provides an overview of resolution in propositional logic. It introduces resolution as a new rule of inference that allows inferring a resolvent clause from two clauses. It describes how to convert arbitrary well-formed formulas into conjunctions of clauses to use with resolution. Resolution refutations are discussed as a way to decide logical entailments by attempting to derive the empty clause. Various strategies for conducting resolution refutation searches more efficiently are also covered, including ordering strategies and refinement strategies. Finally, the document defines Horn clauses and their special properties that allow for linear-time deduction algorithms.
13 propositional calculus
This document provides an overview of the Propositional Calculus. It discusses:
- The language of propositional calculus using atoms, connectives, and well-formed formulas
- Rules of inference like modus ponens, conjunction introduction, and disjunction introduction
- Defining proofs and theorems based on applying rules of inference
- Semantics by associating logical elements with truth values under interpretations
- Important concepts like validity, equivalence, entailment, and the soundness and completeness of rules of inference.
- The propositional satisfiability (PSAT) problem and solving techniques like exhaustive search and GSAT.
12 adversal search
This document discusses adversarial search techniques for two-agent games with perfect information. It introduces the minimax procedure and how it recursively assigns values to nodes in a game tree by maximizing the value for the maximizing agent and minimizing for the minimizing agent. The alpha-beta pruning technique is described which improves search efficiency by pruning subtrees that cannot alter the minimax value of the root. Examples of applying minimax and alpha-beta to tic-tac-toe are provided. The document also discusses handling games of chance using expectimax search and learning effective evaluation functions from self-play.
11 alternative search
This document discusses different approaches to solving constraint satisfaction problems including assignment problems. It provides examples of the eight queens problem and constraint propagation techniques. Constructive methods start with no assignments and add values satisfying constraints, while heuristic repair starts with a proposed solution and changes it to violate fewer constraints. Function optimization techniques like hill climbing and simulated annealing are also discussed.
10 2 sum
The document discusses different methods for reinforcement learning, including learning heuristic functions from experiences, learning in explicit and implicit graphs, using rewards instead of goals for tasks, and different algorithms like temporal difference learning and value iteration that help agents learn optimal policies by assigning credit to relevant state-action pairs.
22 planning
The document describes planning techniques in artificial intelligence, including STRIPS planning systems, forward and backward search methods, and partial-order planning. It discusses how STRIPS uses operators to describe state changes and searches for a sequence of actions to reach a goal state. Backward search methods work by regressing goals through operators to produce subgoals. Partial-order planning searches a plan space by transforming incomplete plans into more articulated plans until finding an executable plan.
21 situation calculus
This document provides an overview of the Situation Calculus, a formal logic framework for representing states, actions, and how actions transform states. It describes key components of the Situation Calculus including: (1) representing states as constants and using predicates to describe state properties, (2) representing actions and how they change state properties using effect axioms, (3) using frame axioms to represent properties that don't change with actions, and (4) generating plans by proving the existence of goal states and extracting the actions. Challenges with the approach include dealing with ramifications of actions and specifying all relevant preconditions and qualifications.
20 bayes learning
The document provides an overview of learning Bayes networks from data. It discusses learning the structure and conditional probability tables (CPTs) of a Bayes network given training data. When the network structure is known, the CPTs can be directly estimated from sample statistics in the training data, handling both cases of complete and missing data using techniques like expectation-maximization. When the structure is unknown, scoring metrics like minimum description length are used to search the space of possible structures to find the best fitting network. Dynamic decision networks extend this framework to model sequential decision making problems.
19 uncertain evidence
This document outlines probabilistic inference in Bayes networks. It begins with a review of probability theory concepts like joint probability, marginal probability, conditional probability, and Bayes' rule. It then discusses probabilistic inference in Bayes networks, including causal/top-down inference using evidence to determine probabilities, diagnostic/bottom-up inference using effects to determine causes, and "explaining away" where additional evidence makes other probabilities less certain. The document also covers uncertain evidence, D-separation to determine conditional independence, and inference techniques in polytrees.
18 common knowledge
This document discusses representing commonsense knowledge. It describes commonsense knowledge as everyday facts that most people understand, like objects falling when dropped or fish needing water. Representing all commonsense knowledge is difficult as there are no defined boundaries and some concepts cannot be described with sentences alone. The document outlines research areas in representing objects, materials, space, time, and physical processes. It also discusses knowledge representation using semantic networks and frames to organize taxonomic hierarchies and relationships between objects, properties, and categories in a graph structure. Nonmonotonic reasoning is also discussed for handling exceptions to default inferences.
17 2 expert systems
Rule-based expert systems use facts and rules to achieve expert-level competence in solving problems. They consist of a knowledge base containing facts and rules, an inference engine that manipulates the knowledge base to deduce information, and an explanation subsystem. Rule-based systems apply logical rules to the known facts to determine unknown information. Inductive logic programming learns rules by generalizing from examples to cover positive instances while avoiding negative ones.
17 1 knowledge-based system
The document discusses knowledge-based systems and their ability to reason over extensive knowledge bases. It addresses the theoretical problems of soundness, completeness, and tractability when using logical reasoning systems. Horn clauses and PROLOG are introduced as more efficient ways to perform inference compared to full predicate calculus. Different methods for reasoning including forward chaining and truth and assumption-based maintenance are also summarized.
16 2 predicate resolution
This document discusses resolution in predicate calculus. It covers topics like unification, predicate calculus resolution, converting well-formed formulas to clause form, using resolution to prove theorems, and answer extraction. It also discusses the equality predicate and paramodulation inference rule. The document provides examples to illustrate various concepts and techniques in resolution-based automated theorem proving in first-order logic.
16 1 predicate resolution
This document provides an outline and overview of key concepts in resolution in predicate calculus, including:
- Unification, which allows resolving clauses that have matching but complementary literals
- Converting formulas to clause form by eliminating quantifiers and connectives
- Using resolution to prove theorems by deriving the empty clause
- The equality predicate and paramodulation, an inference rule used with resolution when equality is present
The document describes these concepts over multiple sections and provides examples to illustrate predicate calculus resolution.
15 predicate
The document discusses the predicate calculus and its use for representing knowledge. It introduces the motivation and basic components of the predicate calculus language, including terms, well-formed formulas, and quantifiers. It explains the semantics of the language including interpretations, models, and the semantics of quantifiers. Finally, it provides examples of how predicate calculus can be used to conceptualize and represent knowledge about the world.
09 heuristic search
This document discusses various heuristic search algorithms including A*, iterative-deepening A*, and recursive best-first search. It begins by introducing the concept of using evaluation functions to guide best-first search and preferentially expand nodes with lower heuristic values. It then presents the general graph search algorithm and describes how A* specifically reorders nodes using an evaluation function that considers path cost and estimated cost to the goal. Consistency conditions for the heuristic function are discussed which guarantee A* finds optimal solutions.
08 uninformed search
This document discusses uninformed search algorithms. It outlines breadth-first search, depth-first search, and iterative deepening search. Breadth-first search finds the shortest path but uses exponential memory. Depth-first search uses linear memory but may explore large parts of the search space without finding the goal. Iterative deepening search combines the benefits of depth-first search and guarantees of finding the shortest solution like breadth-first search.
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