Miracle-dz/UniFAR-FTUs huggingface dataset:
A Structured Approach to Parallel Programming

Parallel programs are more difficult to develop and reason about than sequential programs. There are two broad classes of parallel programs: (1) programs whose specifications describe ongoing behavior and interaction with an environment, and (2) programs whose specifications describe the relation between initial and final states. This thesis presents a simple, structured approach to developing parallel programs of the latter class that allows much of the work of development and reasoning to be done using the same techniques and tools used for sequential programs. In this approach, programs are initially developed in a primary programming model that combines the standard sequential model with a restricted form of parallel composition that is semantically equivalent to sequential composition. Such programs can be reasoned about using sequential techniques and executed sequentially for testing. They are then transformed for execution on typical parallel architectures via a sequence of semantics-preserving transformations, making use of two secondary programming models, both based on parallel composition with barrier synchronization and one incorporating data partitioning. The transformation process for a particular program is typically guided and assisted by a parallel programming archetype, an abstraction that captures the commonality of a class of programs with similar computational features and provides a class-specific strategy for producing efficient parallel programs. Transformations may be applied manually or via a parallelizing compiler. Correctness of transformations within the primary programming model is proved using standard sequential techniques. Correctness of transformations between the programming models and between the models and practical programming languages is proved using a state-transition-based operational model. This thesis presents: (1) the primary and secondary programming models, (2) an operational model that provides a common framework for reasoning about programs in all three models, (3) a collection of example program transformations with arguments for their correctness, and (4) two groups of experiments in which our overall approach was used to develop example applications. The specific contribution of this work is to present a unified theory/practice framework for this approach to parallel program development, tying together the underlying theory, the program transformations, and the program-development methodology.
Sokoban is PSPACE-complete

It is shown that the popular puzzle Sokoban can be used to emulate a linear bounded automata ((nite tape Turing Machine (TM)). In particular, a construction is given that has a solution if and only if the corresponding Turing Machine on its input halts in the accept state. Further, if the TM halts and accepts, then the pusher will make (n + t(n)) moves and pushes, where n is the number of symbols on the input tape, and t(n) is the number of transitions made by the TM during its computation. This construction shows that the puzzles are PSPACE-complete, solving the open problem stated in 1].
Mesoscale observations of an extended heat burst and associated wind storm in Central Oklahoma

On 13 May 2009, 13 surface‐based observing stations within central and western Oklahoma recorded maximum wind speeds in excess of 22.5 m s−1, along with gusts exceeding 28 m s−1 in isolated locations, during a localized wind storm that lasted in excess for over an hour. These wind speeds were associated with an enhanced mesoscale pressure gradient that developed during the late evening of 12 May 2009 and early morning hours of 13 May 2009, which then slowly propagated from west to east. Ultimately, the event produced localized wind damage in northern portions of Oklahoma City. Analysis of the synoptic and mesoscale conditions present at each stage of the event revealed that specific parameters associated with heat bursts occurred during the event, but with the inclusion of varying mesoscale and microscale influences. As such, a close examination of the mesoscale pressure field indicated that a dynamically variable mesoscale convective system (MCS) produced a mesohigh/mesolow couplet that ultimately created the strong pressure gradient. The result was a prolonged period (in excess of 1 h) of enhanced wind speed values across a swath approximately 300 km in length and 50 km in width that were not directly associated with the anomalously warmer and drier conditions that occurred due to the heat burst. Copyright © 2011 Royal Meteorological Society
Italian Reformulation Markers: a study on spoken and written language

This paper tackles the issue of the relationship between the medium of communication and the meaning conveyed by reformulation markers. In particular, we show that spoken and written media select different types of markers, and that the meaning conveyed by single markers changes according to the medium of communication. Eventually, we have a look at reformulation triggers, and we demonstrate that the medium of communication has an impact on the motivations underlying reformulation.
A Two Stage DC-DC Converter with Isolation for Renewable Energy Applications

In this work, the design and development of a DC-DC Converter using a two stage buck-boost operation is discussed. This converter is suitable for low power application such as a matrix LED lighting system. The advantage of this converter is that instead of using two controlled switches as in case of a conventional converter, this circuit uses one MOSFET as a switch. The circuit uses two inductors and two capacitors as energy transferring elements that are able to provide a good quality, high efficiency power supply to the load. The design of TSBB converter is analyzed with closed loop control using a PI controller circuit. Even with smaller values of inductor and capacitor a highly efficient power supply can be made. The main feature of this circuit compared to the other circuits proposed previously is that have a galvanic isolation between the load and the source is provided. Thus, by a suitable controller and galvanic isolation, the ripple magnitude in the output is reduced considerably. A simulation model of the TSBB converter with results is presented.
Introduction to Statistical Methods for Clinical Trials

PREFACE Introduction to Clinical Trials History and Background Ethics of Clinical Research Types of Research Design and Types of Trials The Need for Clinical Trials The Randomization Principle Timing of a Clinical Trial Trial Organization Protocol and Manual of Operations Regulatory Issues Overview of the Book Defining the Question Statistical Framework Elements of Study Question Outcome or Response Measures The Surrogate Outcome Composite Outcomes Summary Problems Study Design Early Phase Trials Phase III/IV Trials Non-Inferiority Designs Screening, Prevention, and Therapeutic Designs Adaptive Designs Conclusions Problems Sample Size Sample Size versus Information A General Setup for Frequentist Designs Loss to Follow-up and Non-Adherence Survival Data Clustered Data Tests for Interaction Equivalence/Non-Inferiority Trials Other Considerations Problems Randomization The Role of Randomization Fixed Randomization Procedures Treatment- and Response-Adaptive Randomization Procedures Covariate-Adaptive Randomization Procedures Summary and Recommendations Problems Data Collection and Quality Control Planning for Collection of Clinical Trial Data Categories of Clinical Data Data Quality Control Conclusions Survival Analysis Background Estimation of Survival Distributions Comparison of Survival Distributions Regression Models Composite Outcomes Summary Problems Longitudinal Data A Clinical Longitudinal Data Example The Subject-Specific Model Two-Stage Estimation The Random-Effects, Subject-Specific Model The Population-Average (Marginal) Model Restricted Maximum Likelihood Estimation (REML) Standard Errors Testing Additional Levels of Clustering Generalized Estimating Equations for Non-Normal Data Missing Data Summary Quality of Life Defining QoL Types of QoL Assessments Selecting a QoL Instrument Developing a QoL Instrument Quality of Life Data Analysis of QoL Data Summary Data Monitoring and Interim Analysis Data and Safety Monitoring Examples The Repeated Testing Problem Group Sequential Tests Triangular Test Curtailment Procedures Inference Following Sequential Tests Discussion Problems Selected Issues in the Analysis Bias in the Analysis of Clinical Trial Data Choice of Analysis Population Missing Data Subgroup Analyses Multiple Testing Procedures Summary Problems Closeout and Reporting Closing out a Trial Reporting Trial Results Problems Appendix: Delta Method, Maximum Likelihood Theory, and Information Delta Method Asymptotic Theory for Likelihood-Based Inference Hypothesis Testing Computing the MLE Information Brownian Motion REFERENCES INDEX
DepthCube solid-state 3D volumetric display

The DepthCube 3D Volumetric Display is a solid state, rear projection, volumetric display that consists of two main components: a high-speed video projector, and a multiplanar optical element composed of a air-spaced stack of liquid crystal scattering shutters. The high-speed video projector projects a sequence of slices of the 3D image into the multiplanar optical element where each slice is halted at the proper depth. Proprietary multiplanar anti-aliasing algorithms smooth the appearance of the resultant stack of image slices to produce a continuous appearing truly three-dimensional image. The resultant 3D image is of exceptional quality and provides all the 3D vision cues found in viewing real object.
Factors affecting the bandwidth efficiency of packet reservation multiple access

The authors have extended a preliminary study of packet reservation multiple access (PRMA) by examining the influence of a large number of system variables on PRMA performance. The measure of efficiency is eta , the maximum number of conversations per channel that PRMA can support within a given packet-dropping probability constraint of P/sub drop/<or=0.01. The number of channels is defined as the ratio of channel rate to source rate. Over the range of conditions examined, many PRMA configurations are found for which eta =1.6 conversations per channel. This represents an efficiency improvement of 60% over conventional time-division multiple access. The overall conclusion is that PRMA shows encouraging potential as a statistical multiplexer of speech packets. <<ETX>>
Unintentional gun injuries, firearm design, and prevention: What we know, what we need to know, and what can be done

The public health community has long recognized unintentional gun injuries as a public health issue. In 1998 in the United States, 866 people died from unintentional gunshot wounds, resulting in a crude death rate of 0.32 per 100,000. Unintentional gun deaths have been declining since at least 1920, yet the reasons for this downward trend are not understood. Possible explanations, such as changes in gun ownership and demography, changes in access to guns among population subgroups, safety practices, and artifactual influences are discussed. Intervention strategies for reducing the risk of unintentional gun injury are also discussed.
PERAN KEMAMPUAN BERPIKIR LATERAL DAN POSITIF TERHADAP PRESTASI BELAJAR EVALUASI PENDIDIKAN

Abstrak: Penelitian ini bertujuan untuk menganalisis peran kemampuan berpikir terhadap prestasi belajar mata kuliah evaluasi pendidikan. Penelitian ini adalah penelitian survei korelasional, dengan populasi mahasiswa pendidikan matematika UNINDRA. Sampel diambil dengan teknik multistage random sampling sejumlah 60 orang. Instrumen yang digunakan adalah angket dan tes. Analisis data menggunakan regresi berganda. Dari pengolahan data diperoleh hasil: (1) terdapat pengaruh kemampuan berpikir lateral terhadap prestasi belajar evaluasi pendidikan; (2) terdapat pengaruh kemampuan berpikir positif terhadap prestasi belajar evaluasi pendidikan; dan (3) terdapat pengaruh kemampuan berpikir lateral dan kemampuan berpikir positif secara bersama-sama terhadap prestasi belajar evaluasi pendidikan. Kata Kunci: berpikir lateral, berpikir positif, prestasi belajar, evaluasi pendidikan THE ROLE OF LATERAL AND POSITIVE THINKING ON LEARNING ACHIEVEMENT OF EDUCATIONAL COURSES Abstract: This research aimed at analyzing the role of the thinking ability on learning achievement. The study applied a correlational survey research design. The population was the UNINDRA Mathematics education students. The sample, taken by a multistage random sampling technique, involved 60 students. The instruments were in the forms of questionnaires and tests. The data were analyzed using multiple regression. The findings showed that (1) lateral thinking ability had a positive and significant impact on learning achievement; (2) positive thinking ability had a positive and significant impact on learning achievement; (3) lateral thinking and positive thinking abilities had positive and significant simultaneous impact on learning achievement. Keywords: lateral thinking, positive thinking, learning achievement
Practical Chemical Thermodynamics for Geoscientists

"Practical Chemical Thermodynamics for Geoscientists" covers classical chemical thermodynamics and focuses on applications to practical problems in the geosciences, environmental sciences, and planetary sciences. This book will provide a strong theoretical foundation for students, while also proving beneficial for earth and planetary scientists seeking a review of thermodynamic principles and their application to a specific problem. This title provides strong theoretical foundation and emphasis on applications; numerous worked examples in each chapter; brief historical summaries and biographies of key thermodynamicists - including their fundamental research and discoveries; and, extensive references to relevant literature.
An ATM/CDMA-based satellite access scheme

This paper presents a new access scheme for an ATM-based satellite communication network. The up-link channel is shared by all users in the system. Access to the up-link channel is done using a direct sequence (DS) code division multiple access (CDMA) technique combined with quadrature phase shift keying (QPSK) modulation to reduce the spectral bandwidth. It is shown that by using forward error control (FEC) the probability of bit error, which is directly affected by the number of users that simultaneously transmit on the up-link channel, can be dramatically reduced. The probability of bit error, the cell success probability and the network efficiency are computed and plotted vs. the number of simultaneous users.
Catalogue of Cataclysmic Binaries, Low-Mass X-Ray Binaries and Related Objects

This catalogue lists coordinates, apparent magnitudes, orbital parameters, stellar parameters of the components and other characteristic properties of cataclysmic binaries, low-mass X-ray binaries and related objects with known or suspected orbital periods, together with a comprehensive selection of the relevant recent literature. In addition, the catalogue contains a list of references to published finding charts for a subset of the objects, and a cross-reference list of alias object designations. This is a no-frills catalogue website, focusing on content and simplicity for both user and data provider. We publish updated data regularly about every six months; updates will be announced on the "What's new? " page. There will be no detailed differential list specifying the changes. Instead, we archive the main data tables (for CVs, LMXBs, related objects) before each update. Archived tables will be accessible for at least five years. For the current edition (7.14), literature published before 30 June 2010 has, as far as possible, been taken into account. This edition has entries for 849 CVs, 95 LMXBs, and 266 related objects.
High-performance multiprocessor architecture for a 3-D lattice gas model

The lattice gas method has recently emerged as a promising discrete particle simulation method in areas such as fluid dynamics. We present a very high-performance scalable multiprocessor architecture, called ALGE, proposed for the simulation of a realistic 3-D lattice gas model, Henon's 24-bit FCHC isometric model. Each of these VLSI processors is as powerful as a CRAY-2 for this application. ALGE is scalable in the sense that it achieves linear speedup for both fixed and increasing problem sizes with more processors. The core computation of a lattice gas model consists of many repetitions of two alternating phases: particle collision and propagation. Functional decomposition by symmetry group and virtual move are the respective keys to efficient implementation of collision and propagation.
Appositive Relative Clauses and their Prosodic Realization in Spoken Discourse: a Corpus Study of Phonetic Aspects in British English.

Recent research on discourse has shown that Appositive Relative Clauses (ARCs) can be defined positively in spite of a long tradition in which they are defined asymmetrically with respect to Determinative Relative Clauses (DRCs). Particularly, Loock (2007) has shown that ARCs fulfill specific discourse functions, and distinguishes three categories: Relevance, Subjectivity and Continuative ARCs. This paper aims to show that, for the same syntactic structure, different functions in discourse correspond not only to specific morphosyntactic and semantic criteria, but also to different prosodic realisations. Using attested examples taken from electronic corpora and analysed using semi-automatic procedures within Praat, this paper suggests that a distinction can be made between ARC types such as defined in Loock's study, with for instance higher onset values for subjectivity ARCs, a cue of stronger discourse discontinuity. This paper also addresses the prosodic realization of ARCs as opposed to the general category of parentheticals, which generally include ARCs.
A novel subgridding algorithm for the FDTD method combined with an adaptively adjusted time‐stepping scheme

In a finite‐difference time‐domain (FDTD) calculation, relatively fine spatial gridding is required to resolve regions containing fine structural features. To reduce computation time, subgridding algorithms can be used to efficiently handle configurations that feature multiscale dimensions: Such algorithms can maintain the desired accuracy while avoiding the computation of the entire FDTD space at a finer mesh resolution. A novel FDTD subgridding algorithm with adaptively adjusted time‐steps is proposed in this article. The separated temporal and spatial interfaces for the proposed FDTD subgridding algorithm with a typical 1:3 mesh ratio are described in detail. Higher mesh ratios were achieved using the adaptively adjusted time‐stepping procedure. Accuracy of the proposed method was verified by comparing the results with those of the conventional FDTD method involving a fine mesh resolution. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:613–616, 2015
Hull vector-based incremental learning of hyperspectral remote sensing images

Abstract. To overcome the inefficiency of incremental learning for hyperspectral remote sensing images, we propose a binary detection theory-sequential minimal optimization (BDT-SMO) nonclass-incremental learning algorithm based on hull vectors and Karush-Kuhn-Tucker conditions (called HK-BDT-SMO). This method can improve the accuracy and efficiency of BDT-SMO nonclass-incremental learning for fused hyperspectral images. But HK-BDT-SMO cannot effectively solve class-incremental learning problems (an increase in the number of classes in the newly added sample sets). Therefore, an improved version of HK-BDT-SMO based on hypersphere support vector machine (called HSP-BDT-SMO) is proposed. HSP-BDT-SMO can substantially improve the accuracy, scalability, and stability of HK-BDT-SMO class-incremental learning. Ultimately, HK-BDT-SMO and HSP-BDT-SMO are applied to the classification of land uses with fused hyperspectral images, and the classification results are compared with other incremental learning algorithms to verify their performance. In nonclass-incremental learning, the accuracy of HSP-BDT-SMO and HK-BDT-SMO is approximately the same and is higher than the others, and the former has the best learning speed; while in class-incremental learning, HSP-BDT-SMO has a better accuracy and more continuous stability than the others and the second highest learning speed next to HK-BDT-SMO. Therefore, HK-BDT-SMO and HSP-BDT-SMO are excellent algorithms which are respectively suitable to nonclass and class-incremental learning for fused hyperspectral images.
Implementation of a Stress-dependent Strength Material Model in PLAXIS 3D

To perform tests on bucket foundations, full-scale testing is rarely used since it is rather expensive. Instead small-scale testing is done to examine the static and dynamic behaviour of such structures. In the laboratory at Aalborg University, small-scale testing of offshore support structures can be performed in a pressure tank, where a pressure can be applied in order to simulate deep water situations. Since the test set-up is downscaled 15 to 30 times compared to real-life structures, stresses and strains will be downscaled too. For soils, normally a Mohr-Coulomb failure criterion is used, and in the region of small stresses, a non-linear behaviour is observed unlike the linear behaviour normally assumed in Mohr-Coulomb. To better model this non-linearity, a stress-dependent model for the strength of the soil material is sought to be implemented in PLAXIS 3D through FORTRAN to improve the computational accuracy of small-scale tests.
APPLICATION OF KALMAN FILTER TO ARTIFICIAL NEURAL NETWORKS PREDICTION FOR FOREIGN EXCHANGE RATES

In recent years, artificial neural networks have received increasing attention as a decision making tool when prediction of financial time series is concerned. Modeling issues associated with artificial neural network model like the size of sample data and the general architecture of the model affect the performance of the model. For this reason, artificial neural networks outputs are prone to over-fitting or under-learning resulting to large mean squared errors which affect the accuracy of the prediction. In this paper, we investigate if the application Kalman filter algorithm to artificial neural networks model output can improve the model accuracy through the reduction of the mean squared error. Performance measures for prediction accuracy were used to compare the two models over the datasets for dollar, Euro and Pound exchange rates in Kenya Shilling for a period of five years. In the entire cases artificial neural networks model performed better than artificial neural networks with Kalman filter model. Keywords : Artificial Neural Networks, Currency, Exchange Rates, Kalman Filter, Multi-Layer Perceptron