ppxscal/embedding_network huggingface dataset:
Gregg College Keyboarding Document Processing (GDP), Word 2007 Update, Kit 3, Lessons 1-120 w/Home Software 2.0, 10 edition
Authors: Scot Ober, Jack Johnson, Arlene Zimmerly
Venue:  (2007)

Gregg College Keyboarding and Document Processing (GDP), Word 2007 Update, 10e by Ober, Johnson, and Zimmerly provides a highly flexible, complete learning system designed to integrate flawlessly with Vista, process and score Office 2007 documents. Building from a strong foundation, this version of GDP focuses on adding flexibility for the instructor, along with updating the program to be compatible with the new Microsoft Word 2007 software. Multiple software enhancements and flexible Instructor Management, both LAN and Web-based, support the program's strong content. Instructors will appreciate the flexibility of Instructor Management that can be successfully implemented in a variety of classroom environments and that can be accessed from any Internet-connected computer—regardless of where the program was installed. Table of contentsAbout KeyboardingPrefaceIntroduction to the StudentBefore You BeginAbout Your BookReference ManualPart One: The Alphabet, Number, and Symbol KeysUnit 1 - Keyboarding: The AlphabetUnit 2 - Keyboarding: The AlphabetUnit 3 - Keyboarding: The NumbersUnit 4 - Keyboarding: The SymbolsPart Two: Basic Business DocumentsUnit 5 - E-Mail and Word ProcessingUnit 6 - ReportsUnit 7 - CorrespondenceUnit 8 - TablesTest 2 - Skills Assessment on Part 2Part Three: Reports, Correspondence, and Employment DocumentsUnit 9 - ReportsUnit 10 - CorrespondenceUnit 11 - Employment DocumentsUnit 12 - Skillbuilding and In-Basket ReviewTest 3 - Skills Assessment on Part 3Part Four: Advanced FormattingUnit 13 - Skill RefinementUnit 14 - ReportsUnit 15 - CorrespondenceUnit 16 - TablesTest 4 - Skills Assessment on Part 4Part Five: Specialized ApplicationsUnit 17 - Formal Report ProjectUnit 18 - International FormattingUnit 19 - Medical Office DocumentsUnit 20 - Legal Office DocumentsTest 5 - Skills Assessment on Part 5Part Six: Using and Designing Business DocumentsUnit 21 - Using and Designing Office FormsUnit 22 - Designing Office PublicationsUnit 23 - Designing Web PagesUnit 24 - Skillbuilding and In-Basket ReviewTest 6 - Skills Assessment on Part 6SkillbuildingAppendixIndex
Comparative analysis of regression and machine learning methods for predicting fault proneness models
Authors: Yogesh Singh, Arvinder Kaur, Ruchika Malhotra
Venue: International Journal of Computer Applications in Technology (2009)

Demand for quality software has undergone rapid growth during the last few years. This is leading to increase in development of machine learning techniques for exploring datasets which can be used in constructing models for predicting quality attributes such as Decision Tree (DT), Support Vector Machine (SVM) and Artificial Neural Network (ANN). This paper examines and compares Logistic Regression (LR), ANN (model predicted in an analogous study using the same dataset), SVM and DT methods. These two methods are explored empirically to find the effect of object-oriented metrics given by Chidamber and Kemerer on the fault proneness of object-oriented system classes. Data collected from Java applications is used in the study. The performance of the methods was compared by Receiver Operating Characteristic (ROC) analysis. DT modelling showed 84.7&#37; of correct classifications of faulty classes and is a better model than the model predicted using LR, SVM and ANN method. The area under the ROC curve of LR, ANN, SVM and DT model is 0.826, 0.85, 0.85 and 0.87, respectively. The paper shows that machine learning methods are useful in constructing software quality models.
A unified statistical model to support local sequence order independent similarity searching for ligand-binding sites and its application to genome-based drug discovery
Authors: Lei Xie, Li Xie, Philip E. Bourne
Venue: Bioinformatics (2009)

Functional relationships between proteins that do not share global structure similarity can be established by detecting their ligand-binding-site similarity. For a large-scale comparison, it is critical to accurately and efficiently assess the statistical significance of this similarity. Here, we report an efficient statistical model that supports local sequence order independent ligand–binding-site similarity searching. Most existing statistical models only take into account the matching vertices between two sites that are defined by a fixed number of points. In reality, the boundary of the binding site is not known or is dependent on the bound ligand making these approaches limited. To address these shortcomings and to perform binding-site mapping on a genome-wide scale, we developed a sequence-order independent profile–profile alignment (SOIPPA) algorithm that is able to detect local similarity between unknown binding sites a priori. The SOIPPA scoring integrates geometric, evolutionary and physical information into a unified framework. However, this imposes a significant challenge in assessing the statistical significance of the similarity because the conventional probability model that is based on fixed-point matching cannot be applied. Here we find that scores for binding-site matching by SOIPPA follow an extreme value distribution (EVD). Benchmark studies show that the EVD model performs at least two-orders faster and is more accurate than the non-parametric statistical method in the previous SOIPPA version. Efficient statistical analysis makes it possible to apply SOIPPA to genome-based drug discovery. Consequently, we have applied the approach to the structural genome of Mycobacterium tuberculosis to construct a protein–ligand interaction network. The network reveals highly connected proteins, which represent suitable targets for promiscuous drugs. Contact: lxie@sdsc.edu
An Experimental Study of a Cognitive Tool for Classroom Use: A Knowledge of Fraction Equivalence
Authors: Siu Cheung Kong
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

A cognitive tool (CT) that helps learners to generate a knowledge of fraction equivalence, which comprises conceptual and procedural knowledge, has been built. The aim of this research is to study the effectiveness of the CT in generating a knowledge of fraction equivalence for classroom use. Two groups of learners were randomly selected to learn the subject knowledge. One group, the CTWSGp, initially started to learn with the CT and then worked with drilling-orientated worksheets (WS), and the other group, the WSCTGp, learned in the reverse order. The results of pre-test-post-test experimental studies show that both groups had gained competency in the knowledge of fraction equivalence by the end of the learning period. An analysis of the results indicates that learners in the CTWSGp group learnt the subject matter better than the WSCTGp group, and that the CT is a more effective tool than drilling-orientated worksheets.
Simple equations on binary factorial languages
Authors: A. E. Frid
Venue: Theoretical Computer Science (2009)

We consider equations on the monoid of factorial languages on the binary alphabet. We use the notion of a canonical decomposition of a factorial language and previous results by Avgustinovich and the author to solve several simple equations on binary factorial languages including X^n=Y^n, the commutation equation XY=YX and the conjugacy equation XZ=ZY. At the end of the paper, we discuss the difficulties hindering the reduction of equations on factorial languages to equations on words and the extension of the alphabet considered.
Media Literacy and Universal Access in Europe
Authors: Maria Sourbati
Venue: The Information Society (2009)

The promotion of media literacy as way of increasing access to the range of services available via today's media and communication technologies is currently an emphasis in Europe's information society policy debates. The notion of media literacy heralds a shift in the communications policy arena, especially with regard to media access as a policy goal. Taking into account the situated origins of the inherited regulatory concepts of access, this article argues that the way in which we operationalize media access must reflect how individuals engage with convergent electronic media services. It proposes a context-and user-sensitive approach, where the situation of media (non)users is assessed in terms of the technological and social infrastructure needed to support their access to particular media services.
Freedom of choice as motivational factor for active learning
Authors: Atanas Radenski
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

Freedom to choose what, when, and how to contribute in a learning process can motivate students to actively engage and achieve more in their studies. However, freedom of choice complicates course management and may deter instructors from allowing such freedom. Our approach is to utilize existing functionality of course management systems such as Moodle to automatically facilitate and coordinate free student choices and provide much needed relief for instructors at the same time. Using Moodle we have developed novel digital study packs that blend freedom of choice with guidance and control. Our survey shows that assisted freedom of choice is ranked highest in 51% of student responses -- in contrast to unlimited choice at 28% or no choice at all at 21%. Experience reported in this paper may be beneficial for instructors who would like to expand their courses with new motivational learning techniques.
A coordinate SPC model for assuring designated fit quality via quality-oriented statistical tolerancing
Authors: Yu Zhang, Musheng Yang
Venue: Computers and Industrial Engineering (2009)

On the basis of studies to process quality indices and fit quality indices, the quality-oriented statistical tolerancing is introduced, which provides an interface between fit quality and the process parameter design of mating parts. A statistical mating model via the quality-oriented statistical tolerancing under information-based manufacturing condition is discussed. Compared with traditional mating model for a pair of hole/shaft fit, the statistical mating model is developed for equal batches of hole/shaft fit, and it can achieve a designated fit quality and minimum defective ratio by fully utilizing statistical tolerance zone and the known information of manufactured mating parts via a coordinate SPC model and local network and information system. Thus, production cost for mating parts can be reduced obviously. This new approach provides a possibility and guideline to concurrent design of the process quality, statistical tolerances to assure designated process quality and fit quality for hole and shaft parts.
Development of Design Strategy for RBF Neural Network with the Aid of Context-Based FCM
Authors: Ho-Sung Park, Sung-Kwun Oh, Hyun-Ki Kim
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, we develop a new design strategy of Radial Basis Function (RBF) neural network and provide a comprehensive design methodology and algorithmic setup supporting its development. The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of FCM clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space. A series of numeric studies exploiting synthetic data and data from the Machine Learning Repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.
Factor Analysis of Incidence Data via Novel Decomposition of Matrices
Authors: Radim Belohlavek, Vilem Vychodil
Venue: Proceedings of the 7th International Conference on Formal Concept Analysis (2009)

Matrix decomposition methods provide representations of an object-variable data matrix by a product of two different matrices, one describing relationship between objects and hidden variables or factors, and the other describing relationship between the factors and the original variables. We present a novel approach to decomposition and factor analysis of matrices with incidence data. The matrix entries are grades to which objects represented by rows satisfy attributes represented by columns, e.g. grades to which an image is red or a person performs well in a test. We assume that the grades belong to a scale bounded by 0 and 1 which is equipped with certain aggregation operators and forms a complete residuated lattice. We present an approximation algorithm for the problem of decomposition of such matrices with grades into products of two matrices with grades with the number of factors as small as possible. Decomposition of binary matrices into Boolean products of binary matrices is a special case of this problem in which 0 and 1 are the only grades. Our algorithm is based on a geometric insight provided by a theorem identifying particular rectangular-shaped submatrices as optimal factors for the decompositions. These factors correspond to formal concepts of the input data and allow for an easy interpretation of the decomposition. We present the problem formulation, basic geometric insight, algorithm, illustrative example, experimental evaluation.
Building the Internet of Things Using RFID: The RFID Ecosystem Experience
Authors: Evan Welbourne, Leilani Battle, Garret Cole, Kayla Gould, Kyle Rector, Samuel Raymer, Magdalena Balazinska, Gaetano Borriello
Venue: IEEE Internet Computing (2009)

At the University of Washington, the RFID Ecosystem creates a microcosm for the Internet of Things. The authors developed a suite of Web-based, user-level tools and applications designed to empower users by facilitating their understanding, management, and control of personal RFID data and privacy settings. They deployed these applications in the RFID Ecosystem and conducted a four-week user study to measure trends in adoption and utilization of the tools and applications as well as users' qualitative reactions.
Learning to Powerpoint: Creating Effective Presentations
Authors: Angela Bessant
Venue:  (2007)

This text shows how to create, organize and design effective presentations using PowerPoint. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
On a Data-Driven Method for Staffing Large Call Centers
Authors: Achal Bassamboo, Assaf Zeevi
Venue: Operations Research (2009)

We consider a call center model with multiple customer classes and multiple server pools. Calls arrive randomly over time, and the instantaneous arrival rates are allowed to vary both temporally and stochastically in an arbitrary manner. The objective is to minimize the sum of personnel costs and expected abandonment penalties by selecting an appropriate staffing level for each server pool. We propose a simple and computationally tractable method for solving this problem that requires as input only a few system parameters and historical call arrival data for each customer class; in this sense the method is said to be data-driven. The efficacy of the proposed method is illustrated via numerical examples. An asymptotic analysis establishes that the prescribed staffing levels achieve near-optimal performance and characterizes the magnitude of the optimality gap.
Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme
Authors: Malcolm McPhee, Jim Oltjen, James Fadel, David Mayer, Roberto Sainz
Venue: Mathematics and Computers in Simulation (2009)

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting for energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.
Further Evidence for the Deep-Level Reasoning Question Effect
Authors: Brent Morgan, Roby Coles, Josh Brittingham, Barry Gholson
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

This experiment sought to generalize to middle-and high-school students the learning gains observed through deep-level reasoning questions among college students in vicarious environments. 342 eighth through eleventh graders were presented with either content alone, content preceded by deep-level reasoning questions, or an interactive session with a virtual tutor. Students exposed to the deep-level reasoning questions outperformed the interactive and content-only groups, suggesting that deep-level reasoning questions do indeed aid in knowledge representation amongst middle-and high-school students.
Can RDB2RDF Tools Feasibily Expose Large Science Archives for Data Integration?
Authors: Alasdair J. Gray, Norman Gray, Iadh Ounis
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Many science archive centres publish very large volumes of image, simulation, and experiment data. In order to integrate and analyse the available data, scientists need to be able to (i) identify and locate all the data relevant to their work; (ii) understand the multiple heterogeneous data models in which the data is published; and (iii) interpret and process the data they retrieve. rdf has been shown to be a generally successful framework within which to perform such data integration work. It can be equally successful in the context of scientific data, if it is demonstrably practical to expose that data as rdf.In this paper we investigate the capabilities of rdf to enable the integration of scientific data sources. Specifically, we discuss the suitability of sparql for expressing scientific queries, and the performance of several triple stores and rdbrdf tools for executing queries over a moderately sized sample of a large astronomical data set. We found that more research and improvements are required into sparql and rdbrdf tools to efficiently expose existing science archives for data integration.
Aero-pilot concentration monitoring and alert system using correlation and ZIGBEE
Authors: S. Rajasekar, A. H. Syed Sulthan Alaudeen
Venue: Proceedings of the 8th WSEAS international conference on Electronics, hardware, wireless and optical communication (2009)

Accidents caused by aero pilot concentration deviations have a high fatality rate due to the decline of pilot abilities in perception, recognition, and vehicle control abilities while deviation. Preventing such an accident requires a technique for detecting, estimating, and predicting the level of alertness of a pilot and a mechanism to maintain the pilots's maximum performance of riding. Preventing deviation during driving requires a method for accurately detecting a decline in pilot alertness and a method for alerting and refreshing the driver. This paper suggests a new way to alert the aero pilot with the real time monitoring of bio brain waves. Yet by processing of instant bio signals with a mathematical tool correlation and by communicating with ZigBee the pilots and can be alerted during decline of driving concentration. Here the wireless zigBee play a vital role in the design of monitoring and alerting structure.
Bounds on Mincut for Cayley Graphs over Abelian Groups
Authors: Vladimir Lipets
Venue: Theory of Computing Systems (2009)

In this paper we find upper bounds for the mincut value of Cayley graphs over abelian groups. These results provide a significant improvement of those in Annextein and Baumslag (Math. Syst. Theory 26(3):271&#x2013;291, [1993]).
Synthesizing intensional behavior models by graph transformation
Authors: Carlo Ghezzi, Andrea Mocci, Mattia Monga
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

This paper describes an approach (SPY) to recovering the specification of a software component from the observation of its run-time behavior. It focuses on components that behave as data abstractions. Components are assumed to be black boxes that do not allow any implementation inspection. The inferred description may help understand what the component does when no formal specification is available. SPY works in two main stages. First, it builds a deterministic finite-state machine that models the partial behavior of instances of the data abstraction. This is then generalized via graph transformation rules. The rules can generate a possibly infinite number of behavior models, which generalize the description of the data abstraction under an assumption of “regularity” with respect to the observed behavior. The rules can be viewed as a likely specification of the data abstraction. We illustrate how SPY works on relevant examples and we compare it with competing methods.
Tools for cryptographic protocols analysis: A technical and experimental comparison
Authors: Manuel Cheminod, Ivan Cibrario Bertolotti, Luca Durante, Riccardo Sisto, Adriano Valenzano
Venue: Computer Standards Interfaces (2009)

The tools for cryptographic protocols analysis based on state exploration are designed to be completely automatic and should carry out their job with a reasonable amount of computing and storage resources, even when run by users having a limited amount of expertise in the field. This paper compares four tools of this kind to highlight their features and ability to detect bugs under the same experimental conditions. To this purpose, the ability of each tool to detect known flaws in a uniform set of well-known cryptographic protocols has been checked. Results are also given on the relative performance of the tools when analysing several known-good protocols with an increasing number of parallel sessions.