Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Modeling Essentials

Data Modeling Essentials, Third Edition provides expert tutelage for data modelers, business analysts and systems designers at all levels. Beginning with the basics, this book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management.The third edition of this popular book retains its distinctive hallmarks of readability and usefulness, but has been given significantly expanded coverage and reorganized for greater reader comprehension. Authored by two leaders in the field, Data Modeling Essentials, Third Edition is the ideal reference for professionals and students looking for a real-world perspective. Thorough coverage of the fundamentals and relevant theory. Recognition and support for the creative side of the process. Expanded coverage of applied data modeling includes new chapters on logical and physical database design. New material describing a powerful technique for model verification. Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict. Extensive online component including course notes and other teaching aids (www.mkp.com). UML diagrams now available! Visit the companion site for more details.Click here to view a book review by Steve Hoberman!
Supporting the emergence of a shared services organisation: Managing change in complex health ICT projects

• Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. • Authors control the copyright of their thesis. You will recognise the author's right to be identified as the author of this thesis, and due acknowledgement will be made to the author where appropriate. • You will obtain the author's permission before publishing any material from their thesis.
Calibration and simulation of DSGE models

Many interesting macroeconomic models are either sufficiently complex that they must be solved computationally, or the questions being asked are inherently quantitative and so they should be solved computationally. The first group includes almost any empirically relevant version of the neoclassical growth model. The second group includes such basic questions as business cycle fluctuations: How well does the the neoclassical growth model do in producing variation in macroaggregates (like output, consumption, investment and hours worked) that “look like” those seen in the data. These are quantitative questions for which qualitative answers are insufficient. Calibration is an effective tool for imposing discipline on the choice of parameter values that arise in such models, taking what would otherwise be a numerical example into the realm of an empirically relevant exercise with parameters tightly pinned ∗We received helpful comments from Stephane Auray and David Fuller. The research assistance of Saeed Zaman is gratefully acknowledged. Gomme received financial support from Fonds de Recherche Societe et Culture Quebec. Except in very special cases, the neoclassical growth model does not allow for closed-form solutions (that is, ones that can be worked out by hand). Perhaps the best known of these is when utility is logarithmic in consumption, separable between consumption and hours worked, the production function is Cobb-Douglas, and depreciation is 100%. These restrictions are very special, and in the case of depreciation, clearly at odds with the data.
Efficient TCB Reduction and Attestation (CMU-CyLab-09-003)

We develop a special-purpose hypervisor called TrustVisor that facilitates the execution of security-sensitive code in isolation from commodity OSes and applications. TrustVisor provides code and execution integrity as well as data secrecy and integrity for protected code, even in the presence of a compromised OS. These strong properties can be attested to a remote verifier. TrustVisor only adds 5306 lines to the TCB (over half of which is for cryptographic operations). TrustVisor imposes less than 7% overhead in the common case. This overhead is largely the result of today’s x86 hardware virtualization support.
Care 3 model overview and user's guide, first revision

A manual was written to introduce the CARE III (Computer-Aided Reliability Estimation) capability to reliability and design engineers who are interested in predicting the reliability of highly reliable fault-tolerant systems. It was also structured to serve as a quick-look reference manual for more experienced users. The guide covers CARE III modeling and reliability predictions for execution in the CDC CYber 170 series computers, DEC VAX-11/700 series computer, and most machines that compile ANSI Standard FORTRAN 77.
Automated Velocity Measurement Technique for Unconsolidated Marine Sediment

The conventional mercury delay method to measure compressional wave velocity of unconsolidated sediment is inconvenient because the signal must be analyzed on the oscilloscope and the mercury column has to be calibrated between measurements. We developed an automated compressional wave velocity measurement technique by connecting an oscilloscope and a PC with a GPIB (General Purpose Interface Bus) card. The GPIB card buses signals from the oscilloscope to the PC where the signal from a sample is analyzed and compared to the input pulse thereby the compressional wave velocity of the sample is computed and recorded automatically. Differences between the mercury delay method and the automated measurement technique are negligible except the slightly greater velocity in the automated measurement technique. We concluded that the new technique can be used to measure the velocity for unconsolidated marine sediment. It also has an advantage to calculate sediment attenuation through the processing of waveform using the spectral ratio technique.
Learning to Unscrew a Light Bulb from Demonstrations

In this paper we show a way of learning how to sequence predefined basic movements in order to reproduce a previously demonstrated skill. Connections between subsequently executed movements are learned and represented in a graph structure. Learning the switching behavior between connected movements is treated as classification problem. Due to the graph, the overall accuracy of the system can be improved by restricting the possible outcomes of the classification to connected movements. We show how the graph representation can be learned from the observations and evaluate Support Vector Machines as classifier. The approach is evaluated with an experiment in which a 7-DOF Barrett WAM robot learns to unscrew a light bulb.
MULTI-CELL WCDMA SIGNAL PROCESSING SIMULATION TESTBED

OF THE THESIS Multi-cell WCDMA Signal Processing Simulation Testbed by Vikram Kaul Thesis Director: Professor Roy D. Yates Third generation (3G) wireless systems are being developed to increase system capacity and support innovative broadband multimedia services. Wideband CDMA (WCDMA) is one such system where the air interfaces need to support services with different bit-error rates, delay, and rates. This thesis describes the Wireless Propagation and Protocols Evaluation Testbed (WiPPETsignal), a virtual testbed for signal processing simulation for the physical layers of CDMA wireless systems. A multi-cell simulation platform implementing user mobility and detailed radio channels has been developed to study the impact of mobile users, fading and propagation effects, and other-cell interference on waveform level processing. The ultimate aim of the study is analyzing and improving algorithms at the link level (interference cancellation) and system level (power control and handoff) for WCDMA systems.
Fault Localization Automation using Code Coverage Data and Diff Utilities

Performing fault localization is one of the most time consuming and expensive aspects of software development today. In large software systems the manual fault localization techniques quickly become unmanageable and as such there is a growing need for automated solutions. In this master’s thesis we propose and evaluate a new method for fault localization based on comparing code coverage and diff utility data. The implemented tool is called FLAC which consists of both a Java application that performs the necessary functionality and a Qlik Sense application designed for visualization purposes. The FLAC prototype is restricted to JavaScripts but the method can be applied to all types of software development projects that employ version control and have the ability to gather code coverage data from test executions. Our method is evaluated by applying it to otherwise stable software that has been injected with faults, analyzing efficiency and performance information and also through interviews. Our results indicate that this method can significantly increase fault localization efficiency.
Regression With Social Data: Modeling Continuous and Limited Response Variables

Preface. 1. Introduction to Regression Modeling. 2. Simple Linear Regression. 3. Introduction to Multiple Regression. 4. Multiple Regression with Categorical Predictors: ANOVA and ANCOVA Models. 5. Modeling Nonlinearity. 6. Advanced Issues in Multiple Regression. 7. Regression with a Binary Response. 8. Advanced Topics in Logistic Regression. 9. Truncated and Censored Regression Models. 10. Regression Models for an Event Count. 11. Introduction to Survival Analysis. 12. Multistate, Multiepisode, and Interval-Censored Models in Survival Analysis. Appendix A: Mathematics Tutorials. Appendix B: Answers to Selected Exercises. References. Index.
Design and analysis of a model based low level slip controller based on a hybrid braking system

In the past decades, car manufacturers have improved the safety of road vehicles significantly. Besides passive safety measures like seat belts and airbags a lot of development has taken place in the field of active safety measures. Since 2011 all new car models being sold in the EU have to be equipped with an Electronic Stability Program (ESP), while since 2007 an Anti-lock Braking System (ABS) was already mandatory. Since the introduction of the Toyota Prius in 1997 car manufacturers invested enormous amounts of resources on the development of hybrid and electric drive trains. Adding an electric motor to the vehicle increases both the complexity as well as the potential to recuperate energy while braking. Although this additional actuator is exploited during nominal driving conditions, in case of emergency braking the potential of the electric motor is often neglected and traditional ABS algorithms are evoked. In this work the effect of incorporating the electric motor into the ABS algorithm will be investigated. For simulation and validation of the slip controller in combination with the control allocator Matlab/Simulink and CarSim will be used. Master of Science Thesis K.H. B. Lubbers
A unified formalism for complex systems architecture

Complex industrial systems are typically artificial objects designed by men, involving a huge number of heterogeneous components (e.g. hardware, software, or human organizations) working together to perform a mission. In this thesis, we are interested in modeling the functional behavior of such systems, and their integration. We will model real systems as functional black boxes (with an internal state), whose structure and behaviors can be described by the recursive integration of heterogeneous smaller subsystems. Our purpose is to give a unified and minimalist semantics for heterogeneous integrated systems and their integration.
Parallel Imaging and MR Motion Correction

where is some similarity between images, here . Thus, the energy would take the form for small displacements ,w here is a function of the coil spatial patterns which is zero when the coils are identical; is the image. We plot here the energy in a simulation where the motion is a 1-parameter ( ) nonrigid radial deformation ( : distance
Artificial intelligence models for large scale buildings energy consumption analysis

The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, occupancy and their behaviors, the operation of sub-level components like Heating, Ventilation and Air-Conditioning (HVAC) system. This complex property makes the prediction, analysis, or fault detection/diagnosis of building energy consumption very difficult to accurately and quickly perform. This thesis mainly focuses on up-to-date artificial intelligence models with the applications to solve these problems. First, we review recently developed models for solving these problems, including detailed and simplified engineering methods, statistical methods and artificial intelligence methods. Then we simulate energy consumption profiles for single and multiple buildings, and based on these datasets, support vector machine models are trained and tested to do the prediction. The results from extensive experiments demonstrate high prediction accuracy and robustness of these models. Second, Recursive Deterministic Perceptron (RDP) neural network model is used to detect and diagnose faulty building energy consumption. The abnormal consumption is simulated by manually introducing performance degradation to electric devices. In the experiment, RDP model shows very high detection ability. A new approach is proposed to diagnose faults. It is based on the evaluation of RDP models, each of which is able to detect an equipment fault.Third, we investigate how the selection of subsets of features influences the model performance. The optimal features are selected based on the feasibility of obtaining them and on the scores they provide under the evaluation of two filter methods. Experimental results confirm the validity of the selected subset and show that the proposed feature selection method can guarantee the model accuracy and reduces the computational time.One challenge of predicting building energy consumption is to accelerate model training when the dataset is very large. This thesis proposes an efficient parallel implementation of support vector machines based on decomposition method for solving such problems. The parallelization is performed on the most time-consuming work of training, i.e., to update the gradient vector f. The inner problems are dealt by sequential minimal optimization solver. The underlying parallelism is conducted by the shared memory version of Map-Reduce paradigm, making the system particularly suitable to be applied to multi-core and multiprocessor systems. Experimental results show that our implementation offers a high speed increase compared to Libsvm, and it is superior to the state-of-the-art MPI implementation Pisvm in both speed and storage requirement.
Teorización sobre la construcción de corpus orales en la adquisición del lenguaje: una propuesta metodológica para el procesamiento de lenguas con soporte tecnológico

espanolHay una preocupacion cada vez mayor por las condiciones de obtencion y manipulacion de los datos en la linguistica de corpus. Este trabajo analiza las facetas metodologicas en la constitucion de corpus orales para investigar la adquisicion del lenguaje, y valora las consecuencias de las decisiones que atanen a las tecnicas de registro de muestras, y al tratamiento y codificacion de los datos. EnglishThere is a growing concern because of the conditions of obtaining and handling the collected corpus data in the linguistics of corpus. This paper discusses the methodological facets applied in the constitution of oral corpus in the investigation of the acquisition of the language, with the aim of assessing the consequences of the decisions pertaining to techniques for registration of samples and the treatment and coding of data.
Standardized Volume Rendering Protocols for Magnetic Resonance Imaging using Maximum-Likelihood Modeling

Volume rendering (VRT) has been used with great success in studies of patients using computed tomography (CT), much because of the possibility of standardizing the rendering protocols. When using magnetic resonance imaging (MRI), this procedure is considerably more difficult, since the signal from a given tissue can vary dramatically, even for the same patient. This thesis work focuses on how to improve the presentation of MRI data by using VRT protocols including standardized transfer functions. The study is limited to exclusively examining data from patients with suspected renal artery stenosis. A total number of 11 patients are examined.A statistical approach is used to standardize the volume rendering protocols. The histogram of the image volume is modeled as the sum of two gamma distributions, corresponding to vessel and background voxels. Parameters describing the gamma distributions are estimated with a Maximum-likelihood technique, so that expectation (E1 and E2) and standard deviation of the two voxel distributions can be calculated from the histogram. These values are used to generate the transfer function.Different combinations of the values from the expectation and standard deviation were studied in a material of 11 MR angiography datasets, and the visual result was graded by a radiologist. By comparing the grades, it turned out that using only the expectation of the background distribution (E1) and vessel distribution (E2) gave the best result. The opacity is then defined with a value of 0 up to a signal threshold of E1, then increasing linearly up to 50 % at a second threshold E2, and after that a constant opacity of 50 %. The brightness curve follows the opacity curve to E2, after which it continues to increase linearly up to 100%. A graphical user interface was created to facilitate the user-control of the volumes and transfer functions. The result from the statistical calculations is displayed in the interface and is used to view and manipulate the transfer function directly in the volume histogram.A transfer function generated with the Maximum-likelihood VRT method (ML-VRT) gave a better visual result in 10 of the 11 cases than when using a transfer function not adapting to signal intensity variations.
Satellite and Missile Data Generation for AIS.

Abstract : The effort described specifically addressed the problem of deriving indicator and descriptor data from the narrative text portions of a class of intelligence messages dealing with events related to missile and satellite launchings used for input to the Advanced Indicator System (AIS) data base. The introductory section briefly discusses the intelligence problem which OSI's event processing technology intends to solve, summarizes the technology developed under this contract, and presents the conclusions drawn on the basis of the results obtained. Section 2 offers a summary of OSI's methodological approach to the analysis and description of event reports. This methodology, initially developed on the basis of messages dealing with air activities, was, under this contract, extended to cover reports of events involving missile and satellite launchings and related events. Section 3 describes the Missile and Satellite domains, and presents the results of their analysis in terms of a domain definition. The discussion includes a characterization of the event report in terms of its component messages; a list of the message types encountered in the domains under consideration; a list of the event types identified together with their descriptor system, and a definition of the sublanguage in terms of its vocabulary and syntax. Section 4 focuses on the implementation of OSI's message text analysis system, MATRES II. It briefly reviews the principles underlying OSI's event processing technology and offers an overview of MATRES II.
Adding Statistical Machine Translation Adaptation to Computer-Assisted Translation

Abstract : Statistical machine translation (SMT) has proven effective for general purpose language translation but not for highly specialized domains like medicine, military operations, and law enforcement, which have their own technical jargon. We present a novel approach for iteratively incorporating a human translator in the loop to adapt SMT models to a particular domain. We show how these models can be made accessible via Web services and integrated with computer-assisted translation (CAT) tools. In this report, we describe a novel human-in-the-loop post-editing domain adaptation algorithm for refining SMT models using the Joshua decoder and integrate it with a CAT tool called OmegaT.
Cyclic Contention Free Access Scheme for IEEE802.15.4 WPAN

The GTS(Guaranteed Time Slot) of IEEE802.15. 4 standard, which is the contention free access mechanism, has some problems such as the limited number of deployed devices, the low channel utilization and the service confirm delay. The proposed Cyclic-CFA(Contention Free Access) scheme is a modified polling algorithm that allows a large number of devices to be served Contention Free Access without polling packets. The Cyclic-CFA scheme improves the channel utilization dramatically and also reduces service delay time.
Software defined network monitoring scheme using spectral graph theory and phantom nodes

Abstract : In this thesis, we propose a new software defined network monitoring scheme that provides the controller with a method to determine network states for the purpose of updating flow rules for network control and management. Network centrality and nodal influence metrics derived from the dual basis concept of the graph theory are used to monitor changes in a network. The proposed scheme uses a phantom node and the concept of a reference node to determine changes in these metrics in order to identify disconnected, congested, underutilized, and attacked nodes. The phantom node establishes a congestion threshold in the dual basis that is used to determine changes in node health and capacity due to network traffic. Multiple phantom nodes are used to produce multiple congestion thresholds for network monitoring. A congestion estimation method is proposed to estimate a node's capacity used when it crosses the congestion threshold. Simulations are used to validate the concept of reference node, identification of node disconnections, congestion, and attacks, and the congestion estimation method.
Middleware for Managing QoS Adaptation of SOA Applications

The paper describes an improvement over our previous work: the concept of an Adaptive SOA Solution Stack (based on the IBM S3 model) which applies an AS3 element pattern to S3 layers where the need for adaptation arises. The presented improvement, called the adaptation strategy management process, represents a solution that enables an Adaptation Architect to model Quality of Service (QoS) adaptation in a declarative manner, automatically deploy it into a running system and then monitor its execution. Its main objective is to allow the Adaptation Architects to view the adaptation process on a higher level of abstraction and employ adaptivity mechanisms in working applications in an easy way. This is accomplished by incorporating the adaptive application metamodel developed in the DiVA EU project and adjusting it to the SOA context. This paper explains the challenges involved in adaptation strategy management and proposes extensions to the DiVA metamodel. Subsequently, it presents a method by which the Adaptive Manager (a component of the AS3 adaptation loop responsible for making decisions about adaptation) can execute adaptation strategies in accordance with the adaptation model. The presented approach is evaluated in a case study, creating an adaptation strategy and monitoring its impact on an application prototype.