Extending the UML Statecharts Notation to Model Security ...

ACM is one of the high reputed international journal. Its in one of the largest scientific research journal in world. Computer science, electronics, networking, communication, image processing, data mining, cloud computing and all important research domain journal papers we access through ...

CiteSeerX — Search Results — Foundations of Data ...

The eyes have it: A task by data type taxonomy for information visualizations by Ben Shneiderman - IN IEEE SYMPOSIUM ON VISUAL LANGUAGES , 1996 A useful starting point for designing advanced graphical user interjaces is the Visual lnformation-Seeking Mantra: overview first, zoom and filter, then details on demand.

Data mining - Wikipedia

Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for ...

Data mining | computer science | Britannica

Data mining, also called knowledge discovery in databases, in computer science, the process of discovering interesting and useful patterns and relationships in large volumes of data.The field combines tools from statistics and artificial intelligence (such as neural networks and machine learning) with database management to analyze large digital collections, known as data sets.

Data Mining Tutorial: Process, Techniques, Tools, EXAMPLES

Data mining technique helps companies to get knowledge-based information. Data mining helps organizations to make the profitable adjustments in operation and production. The data mining is a cost-effective and efficient solution compared to other statistical data applications. Data mining helps with the decision-making process.

The 7 Most Important Data Mining Techniques - Data Science

Dec 22, 2017· Data mining is the process of looking at large banks of information to generate new information. Intuitively, you might think that data “mining” refers to the extraction of new data, but this isn’t the case; instead, data mining is about extrapolating patterns and new knowledge from the data you’ve already collected.

Top 15 Best Free Data Mining Tools: The Most …

Aug 19, 2020· Weka supports major data mining tasks including data mining, processing, visualization, regression etc. It works on the assumption that data is available in the form of a flat file. Weka can provide access to SQL Databases through database connectivity and can further process the data/results returned by the query. Click WEKA official website.

Data Mining: Purpose, Characteristics, Benefits ...

Data mining technology is something that helps one person in their decision making and that decision making is a process wherein which all the factors of mining is involved precisely. And while the involvement of these mining systems, one can come across several disadvantages of data mining and they are as follows. 1. It violates user privacy:

Requirements for Statistical Analytics and Data Mining

Data Mining Dissemination Level Public Due Date of Deliverable Month 12, 30.04.2016 Actual Submission Date 01.06.2016 Work Package WP 2, Data Collection and Mining Task T 2.3 Type Report Approval Status Final Version 1.0 Number of Pages 32 Filename D2.3 - Requirements for Statistical ...

Process Mining in the Large: A Tutorial

diagrams, Statecharts, C-nets, and heuristic nets. The incredible growth of event data is also posing new challenges [85]. As event logs grow, process mining techniques need to become more e cient and highly scalable. Dozens of process discovery [2, 19, 21, 26, 50, 28, 32, 33, 34, 52,

UML Statecharts' PTL Formal Semantics

An approach for transforming UML statecharts into Projection Temporal Logic(PTL) formal models for system's simulation and verification is presented in this paper. UML Statechart is a graphic tool used to describe systems' behaviors, but it lacks formal semantics. PTL is a kind of temporal logic interpreted over discrete state sequences (intervals).

A Review on Software Process Mining Using Petri Nets

Since method used in this study is also pertinent to the area of mining the activity logs, in the future, we should also compare it to the existing approaches in this area. This study aims at making the first step from the well-developed theory of Petri Net synthesis to the practically relevant research domain of process mining.

Publications by Prof. David Harel

D. Harel, "Statecharts in the Making: A Personal Account", Proc. 3rd ACM SIGPLAN History of Programming Languages Conference (HOPL III), June 2007. 150. B. Sobolev, D. Harel, C. Vasilakis, and A. Levy, "Using the Statecharts paradigm for simulation of patient flow in surgical care", Health Care Management Science 11 (2008), 79-86.

Process Discovery and Conformance Checking Using …

Process mining problems tend to be very challenging. There are obvious challenges that also apply to many other data mining and machine learning problems, e.g., dealing with noise, concept drift, and the need to explore a large and complex search space. For example, event logs may contain millions of …

Emergent Dynamics of Thymocyte Development and Lineage ...

Experiments have generated a plethora of data about the genes, molecules, and cells involved in thymocyte development. Here, we use a computer-driven simulation that uses data about thymocyte development to generate an integrated dynamic representation—a novel technology we have termed reactive animation (RA). RA reveals emergent properties in complex dynamic biological systems.

Process Cubes: Slicing, Dicing, Rolling Up and Drilling ...

BPEL speci cations, UML activity diagrams, Statecharts, C-nets, or heuristic nets. MXML or XES (www.xes-standard.org) are two typical formats for stor-ing event logs ready for process mining. The incredible growth of event data poses new challenges [53]. As event logs grow, process mining techniques need to become more e cient and highly scalable.

Execution Engine - an overview | ScienceDirect Topics

The original motivation for Dryad was to execute data mining operations efficiently, which has also lead to technologies such as MapReduce or Hadoop. Dryad is a general-purpose execution engine and can also be used to implement a wide range of other application types, including time series analysis, image processing, and a variety of scientific ...

LIMBAJUL JAVA PDF

Jan 30, 2020· Using Kolb’s Experiential Learning Cycle to improve student learning in virtual computer laboratories. User Username Password Remember me. A comparison of Java and Objective-C. Object Oriented Analysis and Design. Alan Cooper, About Face: The article discusses some aspects of the design of Data Mining algorithms in Java. Java Language Binding

Design of modern elevator group control systems | Semantic ...

To provide good transportation services for passengers in modern buildings, a good elevator group control system (EGCS) is inevitably necessary. The viewpoint of designing the EGCS is very important. The passenger-based viewpoint proposed provides a new way to think about this system. The capacity constraint following consideration for the passengers is utilized to make the performance better.

Classification and prediction of academic talent using ...

Sep 08, 2010· Nowadays, data mining (DM) classification and prediction techniques are widely used in various fields. However, this approach has not attracted much interest from people in human resource. In this article, we attempt to determine the potential classification techniques for academic talent forecasting in higher education institutions.

Embry-Riddle Aeronautical University - Faculty Directory

Currently, Liu is working on educational data mining to improve computer-supported collaborative learning environment and enhance the problem-solving competence of adult learners. ... H. Liu, D. P. Gluch, Query Generation Guidelines and Consideration to Statecharts of Object-Oriented Designs, Proceeding of the Conference of Advances in Computer ...

Process Mining: Multi Dimensional Cubes

processes based on event data. The growth of event data provides many opportunities but also imposes new challenges. Process mining is typically done for an isolated well-defined process in steady-state. Process mining tools have in common is that installation …

UML Statecharts' PTL Formal Semantics

An approach for transforming UML statecharts into Projection Temporal Logic(PTL) formal models for system's simulation and verification is presented in this paper. UML Statechart is a graphic tool used to describe systems' behaviors, but it lacks formal semantics. PTL is a kind of temporal logic interpreted over discrete state sequences (intervals).

Spreadsheets for business process management: Using ...

Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do ...

LIMBAJUL JAVA PDF

Jan 30, 2020· Using Kolb’s Experiential Learning Cycle to improve student learning in virtual computer laboratories. User Username Password Remember me. A comparison of Java and Objective-C. Object Oriented Analysis and Design. Alan Cooper, About Face: The article discusses some aspects of the design of Data Mining algorithms in Java. Java Language Binding

What is ADV (Abstract Data View) | IGI Global

What is ADV (Abstract Data View)? Definition of ADV (Abstract Data View): A model which allows specifying the structure of interface objects and their relationships with other software components. The behavioural aspects of the interface are specified using ADV-charts, which are a variant of StateCharts

jianfeiwu000dm - Google Sites

Mining Multiple Information Sources Workshop in conjunction with the 2009 IEEE International Conference on Data Mining, Miami, Dec 6, 2009. [13] Anne M Denton, Jianfei Wu. “Data Mining of Vector-Item Patterns Using Neighborhood Histograms”[J]. Knowledge and Information Systems (KIAS). 3,2009 (Impact Factor 2.211).

Ultra High Alkali Fep Hoses Eaton - Mining

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Decomposing Petri Nets for Process Mining {A Generic …

mining. data-oriented analysis (data mining, machine learning, business intelligence) process model analysis ... Statecharts, C-nets, and heuristic nets. In fact, also di erent types of Petri nets can be employed, e.g., safe Petri nets, labeled Petri nets, free-choice

Operational techniques for implementing traceability in ...

The statecharts are developed for frozen mackerel production and corn wet milling processes. All states and events for these processes as well as the information that needs to be captured for each transition are indentified that includes the product, process and quality information. The data capture points were

Complex Data Type - an overview | ScienceDirect Topics

Jiawei Han, ... Jian Pei, in Data Mining (Third Edition), 2012. 10.1.2 Requirements for Cluster Analysis. Clustering is a challenging research field. In this section, you will learn about the requirements for clustering as a data mining tool, as well as aspects that can be used for comparing clustering methods.

Process Discovery and Conformance Checking Using …

Process mining problems tend to be very challenging. There are obvious challenges that also apply to many other data mining and machine learning problems, e.g., dealing with noise, concept drift, and the need to explore a large and complex search space. For example, event logs may contain millions of …

Eventn | Node.js HTTP Microservices for ETL, Analytics ...

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Publications by Prof. David Harel

D. Harel, "Statecharts in the Making: A Personal Account", Proc. 3rd ACM SIGPLAN History of Programming Languages Conference (HOPL III), June 2007. 150. B. Sobolev, D. Harel, C. Vasilakis, and A. Levy, "Using the Statecharts paradigm for simulation of patient flow in surgical care", Health Care Management Science 11 (2008), 79-86.