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Smart lecture room for smart campus building automation system

BÁO CÁO THỰC TẬP-BUILDING AUTOMATION SYSTEM

BÁO CÁO THỰC TẬP-BUILDING AUTOMATION SYSTEM

... thông số Enthalpy Báo động máy bơm cho chiller Báo động chiller Báo động nhiệt độ cao ống nước cung cấp Báo động nhiệt độ thấp ống nước cung cấp Báo động nhiệt độ cao ống nước hồi Báo động nhiệt ... Chế độ báo động Chiller Bất kỳ chiller báo động bị ngưng lại thay chiller dự phòng Chiller không cho phép hoạt động chế độ báo động ghi nhận sửa chữa Chiller xem chế độ báo động phận báo động ... khảo bảng điểm điều khiển) C.4    Báo động cố tải mô tơ quạt FCU Báo động nhiệt độ phòng giới hạn cao/thấp Báo động có báo cháy (nếu kết nối với hệ thống báo cháy) FCU cho phòng giám đốc phòng...
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báo cáo hóa học:

báo cáo hóa học:" Research Article Ontology-Based Device Descriptions and Device Repository for Building Automation Devices Henrik Dibowski and Klaus Kabitzsch" potx

... (i.e., thousands of devices) and perform efficient data access and queries, for example, for accessing device properties, for querying for devices that match certain requirements, or for estimating ... Technologies and Factory Automation (ETFA ’09), Mallorca, Spain, September 2009 [2] H Dibowski and K Kabitzsch, Ontology-based device descriptions and triple store based device repository for automation ... Figures and 8) and the concept ba :Device for example, the datatype properties ba:deviceName, ba :device- IngressProtection, ba:deviceMounting-Form, ba:deviceManufacturerName (virtual property), and...
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Development of DMC controllers for temperature control of a room deploying the displacement ventilation HVAC system

Development of DMC controllers for temperature control of a room deploying the displacement ventilation HVAC system

... develop a controller for temperature control inside a room within a desired band of temperatures for comfort The details of the geometry of the room and the HVAC system based on displacement ventilation ... disadvantages of the DMC controller First, the DMC controller is a local controller which can only guarantee the stability of the system in a local area Second, the DMC controller is a model-based controller ... controlling the temperature in a room deploying a displacement ventilation HVAC system without heater It is a nonlinear system with large disturbance, which has delay in the control variable and in the...
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Tài liệu Training document for the company-wide automation solution Totally Integrated Automation (T I A) doc

Tài liệu Training document for the company-wide automation solution Totally Integrated Automation (T I A) doc

... Module Guide for the training document Automation- and Drive Technology- SCE T I A Training document Last revision: 02/2002 Page of 54 Module Guide for the training document Automation- and Drive ... Guide for the training document Automation- and Drive Technology- SCE T I A Training document Last revision: 02/2002 Page 43 of 54 Module Guide for the training document Automation- and Drive ... – Totally Integrated Automation (T I A) Learning goal: The reader is introduced to the philosophy of Totally Integrated Automation (T I A) Therefore the reader should receive an overview of the...
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lecture 8 for student

lecture 8 for student

... reactions Conversion Factors from Nitrogen to Protein for Foods Sample preparation Digestion Neutralization and Distillation 6.25 Corns [2] 6. 38 5 .83 Nuts Oats Rye Beans 5.30 Barley Meat Calculations ... after cooling and incubated at room temperature for 10 CuSO4-K Na Tartrate-NaOH solution is added after cooling and incubated at room temperature for 10min Freshly prepared Folin reagent is added ... then the reaction mixture is mixed and incubated at 50◦C for 10 Absorbance is read at 650 nm A standard curve of BSA is carefully constructed for estimating protein concentration of the unknown Application...
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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

... better, customized services for an edge (e.g in Customer Relationship Management) © Tan,Steinbach, Kumar Introduction to Data Mining Why Mine Data? Scientific Viewpoint Data collected and stored at ... the data is never analyzed at all 4,000,000 3,500,000 The Data Gap 3,000,000 2,500,000 2,000,000 1, 500,000 Total new disk (TB) since 19 95 1, 000,000 Number of analysts 500,000 19 95 19 96 19 97 19 98 ... 19 96 19 97 19 98 19 99 © Tan,Steinbach, KumarKamath, V Kumar, Data Mining for Mining and Engineering Applications” From: R Grossman, C Introduction to Data Scientific What is Data Mining? Many Definitions...
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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

... p2 p3 p4 p1 p3 p4 p2 0 y 1 p1 p1 p2 p3 p4 x 2. 828 3.1 62 5.099 p2 2. 828 1.414 3.1 62 p3 3.1 62 1.414 p4 5.099 3.1 62 Distance Matrix © Tan,Steinbach, Kumar Introduction to Data Mining 50 Minkowski ... Tan,Steinbach, Kumar Introduction to Data Mining 42 Mapping Data to a New Space Fourier transform Wavelet transform Two Sine Waves © Tan,Steinbach, Kumar Two Sine Waves + Noise Introduction to Data Mining ... Tan,Steinbach, Kumar Introduction to Data Mining 19 Ordered Data Spatio-Temporal Data Average Monthly Temperature of land and ocean © Tan,Steinbach, Kumar Introduction to Data Mining 20 Data Quality...
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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

... object Introduction to Data Mining separate face becomes a Star Plots for Iris Data Setosa Versicolour Virginica © Tan,Steinbach, Kumar Introduction to Data Mining 29 Chernoff Faces for Iris Data ... Tan,Steinbach, Kumar Introduction to Data Mining 35 OLAP Operations: Data Cube The key operation of a OLAP is the formation of a data cube A data cube is a multidimensional representation of data, together ... Kumar Introduction to Data Mining 11 Representation Is the mapping of information to a visual format Data objects, their attributes, and the relationships among data objects are translated into...
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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

... same data! 10 © Tan,Steinbach, Kumar Introduction to Data Mining Decision Tree Classification Task Decision Tree © Tan,Steinbach, Kumar Introduction to Data Mining Apply Model to Test Data Test Data ... P(C2) = 4/ 6 Error = – max (2/6, 4/ 6) = – 4/ 6 = 1/3 Introduction to Data Mining 43 Comparison among Splitting Criteria For a 2-class problem: © Tan,Steinbach, Kumar Introduction to Data Mining 44 Misclassification ... > Yes 3 3 2 3 3 No 4 4 Gini © Tan,Steinbach, Kumar 0 .42 0 0 .40 0 0.375 0. 343 0 .41 7 Introduction to Data Mining 0 .40 0 0.300 0. 343 0.375 0 .40 0 0 .42 0 37 Alternative Splitting Criteria...
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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

... (3) until stopping criterion is met © Tan,Steinbach, Kumar Introduction to Data Mining 14 Example of Sequential Covering (ii) Step © Tan,Steinbach, Kumar Introduction to Data Mining 15 Example ... Tan,Steinbach, Kumar Introduction to Data Mining 27 Indirect Methods © Tan,Steinbach, Kumar Introduction to Data Mining 28 Indirect Method: C4.5rules Extract rules from an unpruned decision tree For each ... have the k smallest distance to x © Tan,Steinbach, Kumar Introduction to Data Mining 39 nearest-neighbor Voronoi Diagram © Tan,Steinbach, Kumar Introduction to Data Mining 40 Nearest Neighbor Classification...
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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

... 159 3 56 357 68 9 Introduction to Data Mining 367 368 22 Subset Operation Using Hash Tree Hash Function transaction 1+ 23 56 2+ 3 56 12+ 3 56 1,4,7 3+ 56 3 ,6, 9 2,5,8 13+ 56 234 567 15+ 145 1 36 345 ... 159 Introduction to Data Mining 3 56 357 68 9 367 368 23 Subset Operation Using Hash Tree Hash Function transaction 1+ 23 56 2+ 3 56 12+ 3 56 1,4,7 3+ 56 3 ,6, 9 2,5,8 13+ 56 234 567 15+ 145 1 36 345 ... 3 ,6, 9 1,4,7 234 567 345 1 36 145 2,5,8 124 457 © Tan,Steinbach, Kumar 125 458 Introduction to Data Mining 159 3 56 357 68 9 367 368 17 Association Rule Discovery: Hash tree Hash Function 1,4,7 Candidate...
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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

... viable candidate, then it can be obtained by merging w with < {1} {2 6} {5}> © Tan,Steinbach, Kumar Introduction to Data Mining 37 GSP Example © Tan,Steinbach, Kumar Introduction to Data Mining ... 0. 17 = 0.9 Sup(W1, W2, W3) = + + + + 0. 17 = 0. 17 © Tan,Steinbach, Kumar Introduction to Data Mining 20 Multi-level Association Rules Food Electronics Bread Computers Milk Wheat Skim White Foremost ... 7, 8, 1, 1, 1, 8, Introduction to Data Mining 26 Examples of Sequence Data Sequence Database Sequence Element (Transaction) Event (Item) Customer Purchase history of a given customer A set of items...
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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

... Tan,Steinbach, Kumar Introduction to Data Mining Partitional Clustering Original Points © Tan,Steinbach, Kumar A Partitional Clustering Introduction to Data Mining Hierarchical Clustering p1 p2 Traditional ... e.g., autocorrelation Dimensionality Noise and Outliers Type of Distribution © Tan,Steinbach, Kumar Introduction to Data Mining 18 Clustering Algorithms K-means and its variants Hierarchical clustering ... Kumar K-means Clusters Introduction to Data Mining 44 Overcoming K-means Limitations Original Points © Tan,Steinbach, Kumar K-means Clusters Introduction to Data Mining 45 Hierarchical Clustering...
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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

... Density Introduction to Data Mining 33 SNN Clustering Can Handle Differing Densities Original Points © Tan,Steinbach, Kumar SNN Clustering Introduction to Data Mining 34 SNN Clustering Can Handle ... merge (c) and (d) Introduction to Data Mining 13 Chameleon: Clustering Using Dynamic Modeling Adapt to the characteristics of the data set to find the natural clusters Use a dynamic model to measure ... Data Mining 18 Experimental Results: CHAMELEON © Tan,Steinbach, Kumar Introduction to Data Mining 19 Experimental Results: CURE (10 clusters) © Tan,Steinbach, Kumar Introduction to Data Mining...
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