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Bài giảng Quản trị Dự Án Project management lecture slide for MBA

Bài giảng Quản trị Dự Án Project management lecture slide for MBA

Tư liệu khác

... What is their bottom line?  When they need the project completed? Why?  What are the priorities for quality, schedule and cost?  How would they know the project is completed? Conflict among ... for you Outcome may not be exactly what you want Relationship enables you to proactively plan aware of, understand and value the production of an outcome over which you have neither control nor ... power status of each group – your team, your co- workers or others ▪ Using above – work out your strategy for each Types of Power Role produce the outcome you want with people who report to you...
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Vocabulary for MBA

Vocabulary for MBA

TOEFL - IELTS - TOEIC

... paths Core corporate value - A core belief or concept that the corporation believes holds equal weight with profit seeking "Good corporate citizenship is a core corporate value for us." Corporate ... “attaboy” to someone can sound condescending, and can indicate a superior talking to a subordinate I would tend not to say it to a member of my study group, Second, the word “boy” in the South could ... “attaboy” is quick praise In a Dilbert comic strip, visible at , under "Comic Archive" for 12/27/02, a boss tells a worker the worker can t have a raise; the boss continues...
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Some studies on a probabilistic framework for finding object-oriented information in unstructured data

Some studies on a probabilistic framework for finding object-oriented information in unstructured data

Công nghệ thông tin

... user object query X 14 contains both discrete values, such as whether there is a term ‘xyz’, and continuous values, such as normalized TF score Y is a Boolean variable corresponding to whether ... information about real estate becomes very necessarily Additionally, there are more and more websites about real estate such as www.metvuong.com, www.batdongsan.com, www.nhadat24h.com, etc…as shown above ... Pml(s|xi) where xi=xi1,xi2…xik is the relevance features between constraint ci and the document P (ci) = P (ci | correct) x P (correct) + P (ci | incorrect) x P (incorrect) = Pml (s | xi) x (1-ε) + 0.5...
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FOOD AND BEVERAGE INDUSTRY MARKETING PRACTICES AIMED AT CHILDREN: DEVELOPING STRATEGIES FOR PREVENTING OBESITY AND DIABETES pdf

FOOD AND BEVERAGE INDUSTRY MARKETING PRACTICES AIMED AT CHILDREN: DEVELOPING STRATEGIES FOR PREVENTING OBESITY AND DIABETES pdf

Tiếp thị - Bán hàng

... advertising: Ads in schools and on buses, scoreboards, billboards, and book covers; free samples ß Indirect advertising: Corporate-sponsored curricula, promotion programs, corporate gifts, incentive programs ... directly into program content, thereby confounding viewers’ attempts to avoid commercials Coke takes center stage: Judges drink from Coca-Cola glasses prominently placed on American Idol sets Target ... African-American audiences compared to those for general audiences found that far more food commercials appear on shows with large African-American audiences and a larger percentage of these commercials...
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Anti-corruption guidelines (“Toolkit”) for MBA curriculum change 2012 pdf

Anti-corruption guidelines (“Toolkit”) for MBA curriculum change 2012 pdf

Cao đẳng - Đại học

... concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts ... www.hbsp.harvard.edu  308106-PDF-ENG Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts ... Anti-corruption An applied philosophical approach Pearson Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts Core concepts...
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lecture 8 for student

lecture 8 for student

Kỹ năng viết tiếng Anh

... Relatively simple; can be done in 1–1.5 h Disadvantages: Color varies with different proteins to a greater extent than the biuret method Color is not strictly proportional to protein concentration ... proteins Disadvantages: Measures total organic nitrogen, not just protein nitrogen Time consuming (at least h to complete) Poorer precision than the biuret method Corrosive reagent SPECTROSCOPY Dye ... Total protein content Content of a particular protein in a mixture Protein content during isolation and purification of a protein Nonprotein nitrogen Amino acid composition Nutritive value of a...
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Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining ppt

Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining ppt

Cơ sở dữ liệu

... Natl-Semiconduct-DOWN,Oracl-DOWN,SGI-DOW N, Sun-DOW N Apple -Co mp-DOW N,Autodesk-DOWN,DEC-DOWN, ADV-M icro-Device-DOWN,Andrew-Corp-DOWN, Co mputer-Assoc-DOWN,Circuit-City-DOWN, Co mpaq-DOWN, EM C-Corp-DOWN, ... Tan,Steinbach, Kumar Introduction to Data Mining 26 Regression Predict a value of a given continuous valued variable based on the values of other variables, assuming a linear or nonlinear model of dependency ... Data? Commercial Viewpoint Lots of data is being collected and warehoused – Web data, e-commerce – purchases at department/ grocery stores – Bank/Credit Card transactions Computers have become...
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Data Mining: Data Lecture Notes for Chapter 2 Introduction to Data Mining potx

Data Mining: Data Lecture Notes for Chapter 2 Introduction to Data Mining potx

Cơ sở dữ liệu

... preserving change of values, i.e., new_value = f(old_value) where f is a monotonic function Interval new_value =a * old_value + b where a and b are constants An attribute encompassing the notion ... new_value = a * old_value Length can be measured in meters or feet Discrete and Continuous Attributes Discrete Attribute – Has only a finite or countably infinite set of values – Examples: zip codes, ... presence counts – Resolution • Patterns depend on the scale © Tan,Steinbach, Kumar Introduction to Data Mining 11 Record Data Data that consists of a collection of records, each of which consists...
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Data Mining: Exploring Data Lecture Notes for Chapter 3 Introduction to Data Mining potx

Data Mining: Exploring Data Lecture Notes for Chapter 3 Introduction to Data Mining potx

Cơ sở dữ liệu

... dimensions must have discrete values • The target value is typically a count or continuous value, e.g., the cost of an item • Can have no target variable at all except the count of objects that have ... contour lines that form the boundaries of these regions connect points with equal values – The most common example is contour maps of elevation – Can also display temperature, rainfall, air pressure, ... Techniques: Contour Plots Contour plots – Useful when a continuous attribute is measured on a spatial grid – They partition the plane into regions of similar values – The contour lines that form the boundaries...
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Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining pptx

Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining pptx

Cơ sở dữ liệu

... 0.419 35 Continuous Attributes: Computing Gini Index Use Binary Decisions based on one value Several Choices for the splitting value – Number of possible splitting values = Number of distinct values ... Attributes: Computing Gini Index For each distinct value, gather counts for each class in the dataset Use the count matrix to make decisions Two-way split (find best partition of values) Multi-way ... Definition Given a collection of records (training set ) – Each record contains a set of attributes, one of the attributes is the class Find a model for class attribute as a function of the values of...
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Data Mining Classification: Alternative Techniques - Lecture Notes for Chapter 5 Introduction to Data Mining pdf

Data Mining Classification: Alternative Techniques - Lecture Notes for Chapter 5 Introduction to Data Mining pdf

Cơ sở dữ liệu

... Type warm cold cold warm cold cold warm warm warm cold cold warm warm cold cold cold warm warm warm warm Give Birth yes no no yes no no yes no yes yes no no yes no no no no no yes no Can Fly no ... Classify records by using a collection of “if…then…” rules Rule: (Condition) → y – where • Condition is a conjunctions of attributes • y is the class label – LHS: rule antecedent or condition ... “nearest” records Introduction to Data Mining 37 Nearest-Neighbor Classifiers Requires three things – The set of stored records – Distance Metric to compute distance between records – The value of...
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Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf

Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf

Cơ sở dữ liệu

... Reducing Number of Comparisons Candidate counting: – Scan the database of transactions to determine the support of each candidate itemset – To reduce the number of comparisons, store the candidates in ... frequent itemsets • Prune candidate itemsets containing subsets of length k that are infrequent • Count the support of each candidate by scanning the DB • Eliminate candidates that are infrequent, ... longer anti-monotone • Suppose: Support(Milk, Coke) = 1.5% and Support(Milk, Coke, Broccoli) = 0.5% • {Milk,Coke} is infrequent but {Milk,Coke,Broccoli} is frequent © Tan,Steinbach, Kumar Introduction...
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Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx

Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx

Cơ sở dữ liệu

... each frequent itemset, compute the descriptive statistics for the corresponding target variable • Frequent itemset becomes a rule by introducing the target variable as rule consequent – Apply statistical ... the discretized intervals affect support & confidence {Refund = No, (Income = $51,250)} → {Cheat = No} {Refund = No, (60K ≤ Income ≤ 80K)} → {Cheat = No} {Refund = No, (0K ≤ Income ≤ 1B)} → {Cheat ... Execution time – If intervals contain n values, there are on average O(n 2) possible ranges Too many rules {Refund = No, (Income = $51,250)} → {Cheat = No} {Refund = No, (51K ≤ Income ≤ 52K)} → {Cheat...
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Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot

Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot

Cơ sở dữ liệu

... correlation, etc K-means will converge for common similarity measures mentioned above Most of the convergence happens in the first few iterations – Often the stopping condition is changed to ‘Until ... Mining 14 Types of Clusters: Conceptual Clusters Shared Property or Conceptual Clusters – Finds clusters that share some common property or represent a particular concept Overlapping Circles ... weighted edges represent the proximities between points – Clustering is equivalent to breaking the graph into connected components, one for each cluster – Want to minimize the edge weight between...
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Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot

Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot

Cơ sở dữ liệu

... Graph – Given a set of points, construct the k-nearest-neighbor (k-NN) graph to capture the relationship between a point and its k nearest neighbors – Concept of neighborhood is captured dynamically ... data set Compute the link value for each set of points, i.e., transform the original similarities (computed by Jaccard coefficient) into similarities that reflect the number of shared neighbors between ... neighbors This corresponds to only keeping the k strongest links of the similarity graph Construct the shared nearest neighbor graph from the sparsified similarity matrix At this point, we could...
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LECTURE NOTES-For Environmental Health Science Students: Air Pollution ppt

LECTURE NOTES-For Environmental Health Science Students: Air Pollution ppt

Điện - Điện tử

... asking about fuel, cooking and ventilation Indoor air sampling procedure Composition of clean dry Atmospheric air vii List of Tables Examples of common conditions to which air exposure may contribute ... Annex-1 Thus, a particular substance can be considered as an air pollutant only when its concentration is relatively high compared with the back ground value and causes adverse effects Air pollution ... widely available, air pollution is a serious problem because of inefficient and smoky fuels used to heat buildings and cook This causes air pollution both out door and indoors The result can be...
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Responsibility of Applicants for Promoting Objectivity in Research for which Public Health Service Funding is Sought and Responsible Prospective Contractors pot

Responsibility of Applicants for Promoting Objectivity in Research for which Public Health Service Funding is Sought and Responsible Prospective Contractors pot

Tài chính doanh nghiệp

... that could be considered FCOIs Because conflicts of interest can vary according to the specific context and Institutional policy, we are concerned that providing examples could create public confusion, ... monitoring their compliance with the policy We disagree with this comment All Federal contractors are required to have an effective means of complying with the terms and conditions of their contract, ... current cost principles may limit an Institution’s ability to recover costs under the Facilities and Administrative cost mechanism However, this does not render those costs ineligible for recovery...
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Praise for Learning Objective-C 2.0 potx

Praise for Learning Objective-C 2.0 potx

Hệ điều hành

... www.it-ebooks.info Download from www.wowebook.com Contents xiii static 45 register 46 const 46 volatile 47 Scope 47 The Scope of Automatic Variables 47 Compound Statements and Scope 48 The Scope ... www.wowebook.com 10 Chapter C, The Foundation of Objective-C You will rarely see either _Bool or bool in Objective-C code, because Objective-C defines its own Boolean type, BOOL BOOL is covered ... isn’t relevant to the example; all you need to consider is that it has a value www.it-ebooks.info Download from www.wowebook.com Preface xxix About the Code Listings The examples in this book are...
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Manual for MBA Internship Programme doc

Manual for MBA Internship Programme doc

Cao đẳng - Đại học

... the quality of recommendations Recommendations should not be vague, abstract, idealistic or ambitious Recommendations should be specific, concrete, to the point, practical, relevant to that organization ... Minnesota Coconut Growers Association (2008) Growing coconuts for fun and profit [Brochure] Crookston, MN: Author Dissertation Olsen, G W (1985) Campus child care within the public supported post-secondary ... people to get their viewpoint on recommendations and their ideas about practicability of recommendations iii) Taking down all notes with a view to write concrete recommendations, alternate plan,...
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Essential Texts for MBA Students 2012 pptx

Essential Texts for MBA Students 2012 pptx

Cao đẳng - Đại học

... committed to minimising them Find out more: 1000 eBooks are now available from SAGE Look out for the eBooks symbol when browsing www.sagepub .co. uk/ebooks ht tp://w w w.uk.sagepub.com/ aboutCommunity.nav ... students Contents PART ONE: INTRODUCTION TO CORPORATE COMMUNICATION \ Defining Corporate Communication: Introduction Scope and Definitions Chapter Summary \ Corporate Communication in Contemporary ... www.sagepub .co. uk Accounting Research Methods in Accounting Second Edition Malcolm Smith Edith Cowan University Updated and expanded, the Second Edition of Research Methods in Accounting, continues...
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