Miracle-dz/UniFAR-FTUs huggingface dataset:
CGAMAS: a post-processing tool for microwave data files

At many businesses, including Allgon Mobile Communications, frequency domain measurements are taken and simulated on a variety of instruments in a variety of formats. There are many different display formats for frequency domain data. Some engineers prefer the Smith Chart, while others want VSWR or S11 and some think in terms of input impedance (separating the real component from the imaginary component). There is a need to plot several files simultaneously to compare data. Engineers want to compare their simulation results with experimental results, usually in several different file formats. An in-house program was developed here at Allgon Mobile Communications. It is written entirely in Matlab 4.2 and runs on a variety of platforms: DOS, UNIX, and Macintosh. The program, titled CGAMAS, can run on small computers-486 with 8 MB RAM and has an adjustable video display to accommodate a range of video monitors.
Grammars, parsers, and memory limitations

Abstract Linguistic competence cannot be adequately characterized by grammatical devices of finite state power. Nevertheless, there are reasons to suspect that the human parsing device cannot adequately deal with languages that fall outside this class. This paper discusses these issues, arguing that restrictions on available parsing memory, and on our ability to operate properly when parsing recursive constructions, mean that there is an interesting sense in which human parsing resources must be characterized as finite state. This means that certain constructions regarded as grammatical according to a (richer than finite state) competence grammar, are not parsable, or are parsed in a way which is not in exact correspondence to their description by this grammar. This raises the further question of how these constructions can nevertheless be understood appropriately, given the assumption that semantic interpretation relies on syntactic structure. The paper goes on to describe an implemented computer program.
A text classification model constructed by Latent Dirichlet Allocation and Deep Learning

In this paper, we proposed a mixed model of text classification constructed by latent dirichlet allocation and deep learning. The model present that a text will be represent as a vector computing by latent dirichlet allocation algorithm, and this vector is probabilistic vector of corresponding topic words space. Then we input these topic vectors into a deep learning framework for computing nonlinear relationship of each vector. Finally, we constructed a text classification system. The proposed model achieves a higher accuracy when compared with other current popular algorithms, such as SVM, KNN and TFIDF.
DESIGN OF A SCALE-MODEL HUMAN-POWERED HELICOPTER

Over the past several decades, several attempts have been made at designing and constructing human-powered helicopters (HPH). The goal of this MQP is to design an 8.25:1 scale model of an HPH that incorporates the most functional aspects of past designs and addresses their shortcomings. The design is based on the rules as defined by the Igor I. Sikorsky Human-Powered Helicopter Competition. Dynamic similarity was used to determine the essential characteristics of the model, such as weight, rotor angular velocity, and power required. A counter-rotating blade design is used to promote stability and minimize structural weight. Rotor blades are designed from a high-lift Epler series airfoil obtained from a low Reynolds number airfoil database. Using a wind tunnel and a custom-designed and built test stand, original lift and drag data has been collected for a Reynolds number of 10,000 on a test wing. This raw data is used to obtain regression curves for lift and drag, from which ideal wing geometries can be determined. A simple blade element theory code was developed using MATLAB. Using this code various planforms are considered, including a linear and elliptic taper on the trailing edge. Geometric twist is also incorporated into the design of the wing sections to provide the most efficient lift and drag distributions along the span of the rotor. An effort was made to construct the model using materials similar to those that likely would be used to build the prototype. Preliminary tests determined that the power required to produce the required lift is below the threshold set by the dynamic similarity analysis. “Certain materials are included under the fair use exemption of the U.S. Copyright Law and have been prepared according to the fair use guidelines and are restricted from further use. ”
A COMPARATIVE STUDY OF COUPLED AND UNCOUPLED ANALYSIS METHODS FOR THERMOHYDRAULIC LOADS IN PIPE SYSTEMS

The structural integrity of the Swedish nuclear power plants continuously needs to be verified according to the standards decided by the Swedish Radiation Safety Authority. One part of the standard is to compute the stress response in the pipe systems and to verify them according to the current codes for the industry, such as the ASME code for boiler and pressure vessels. One method of performing these verifications is to use a 1-D fluid simulation software to calculate the forces within the pipe and then apply those forces on a pipe system stress calculation software where the pipes are regarded as beams. In this Master’s dissertation, results from performing an evaluation according to the method above, using the 1-D fluid simulation software Relap5 and the pipe system stress calculation tool Pipestress, will be compared to performing the same evaluation using more refined simulation methods. The purpose is to evaluate whether or not a more refined simulation method will generate a lower stress response and to show if the Relap5 and Pipestress simulation method is conservative. New forces will be calculated using a CFD-simulation software, ADINA CFD. More refined FEM-calculations, using ADINA FEM, will be performed using both the Relap5 and the ADINA CFD forces. Lastly, a Fluid Structure Interaction (FSI) simulation will be performed, connecting the ADINA CFD with the ADINA FEM code to run simultaneously and to interact with each other. The pipe system examined in this Master’s dissertation is a fictive setup, total of five meters long, running between two tanks. The pipe system is supported at five points along the pipe. A pressure wave propagation will be examined within the pipe system. The pressure wave will be initiated by a fast closing valve. The simulations will be performed at such a high pressure that cavitation will be avoided. In this Master’s dissertation it is shown that a more refined simulation method gives a lower stress response in two out of three evaluation points along the pipe system. However, the FSI simulation does not yield lower stress responses, this is because of how the pressure within the system is accounted for in the different methods. It is clear that the Relap5 and Pipestress simulation method is conservative. It is also observed that the frequency of the pressure waves and the forces are increased using the more refined simulation methods.
Coupling‐Isomerization‐Stetter and Coupling‐Isomerization‐Stetter—Paal—Knorr Sequences — A Multicomponent Approach to Furans and Pyrroles.

SYNTHESIS 2004, No. 14, pp 2391–2406xx.xx. 2004 Advanced online publication: 23.08. 2004 DOI: 10.1055/s-2004-831192; Art ID: Z05304SS © Georg Thieme Verlag Stuttgart · New York Abstract: 2,3,5-Trisubstituted furans 6 and 1,2,3,5-tetrasubstituted pyrroles 8 can be synthesized in good yields in a one-pot three-step threeor four-component process by a coupling-isomerization-Stetter–Paal–Knorr sequence of an electron-poor (hetero)aryl halide 1, a terminal propargyl alcohol 2, an aldehyde 3, and, in the case of pyrroles, a primary amine 7. All novel furans and pyrroles exhibit a strong blue fluorescence with considerable Stokes shifts.
Statistics Education: Steadfast or Stubborn

This paper claims (1) that the introductory statistics course is essentially the same in content as it was 50 years ago, (2) that statistical education has ignored many - if not most - of the content changes proposed by leaders in statistical education, and (3) that the introductory statistics course is essentially a math-stat (research-methods) course. One explanation is that statistics education is being steadfast in upholding random varia- tion as the central idea and ultimate goal of the introductory course. Examples of how context (confounding, assumptions and bias) can influence statistical significance are shown using confidence intervals as a test of statistical significance. Statistics educators seem unwilling to adopt this into introductory statistics. An alternate explanation is that statistics educators want the introductory course to be maintained as a research methods course dedicated to upholding the purity and rigor of deductive mathematics. If so, then any attempt to introduce context may require that statistical educators actively support a separate course in statistical literacy.
Accurate hidden Markov models for non-audible murmur (NAM) recognition based on iterative supervised adaptation

In previous works, we introduced a special device (Non-Audible Murmur (NATM) microphone) able to detect very quietly uttered speech (murmur), which cannot be heard by listeners near the talker. Experimental results showed the efficiency of the device in NAM recognition. Using normal-speech monophone hidden Markov models (HMM) retrained with NAM data from a specific speaker, we could recognize NAM with high accuracy. Although the results were very promising, a serious problem is the HMM retraining, which requires a large amount of training data. In this paper, we introduce a new method for NAM recognition, which requires only a small amount of NAM data for training. The proposed method is based on supervised adaptation. The main difference from other adaptation approaches lies in the fact that instead of single-iteration adaptation, we use iterative adaptation (iterative supervised MLLR). Experiments prove the efficiency of the proposed method. Using normal-speech clean initial models and only 350 adaptation NAM utterances, we achieved a recognition accuracy of 88.62%, which is a very promising result. Therefore, with a small amount of adaptation data, we were able to create accurate individual HMM. We also introduce results of experiments, which show the effects of the number of iterations, the amount of adaptation data, and the regression tree classes.
Statistics and experimental design for toxicologists

Assuming only basic mathematical skills as a starting point, Statistics and Experimental Design for Toxicologists provides a thorough and exhaustive introduction to the statistical methods available to and used in the field. Written from a toxicologist's perspective, it provides both the methodological tools necessary to analyze experimental toxicology data and the insight to know when to use them. A worked, practical example is provided for each technique presented, and the text includes information on using SAS for solving statistical problems in toxicology.
Integrated Cooperative Localization for Connected Vehicles in Urban Canyons

The goal to achieve accurate and ubiquitous localization is the driving force for location based services in vehicular ad hoc networks (VANETs). In urban areas, global positioning system (GPS) and in-vehicle navigation sensors (e.g. odometers) suffer from prolonged outages and unsustainable error accumulation, respectively. The need for precise vehicle localization remains paramount, and cooperative vehicle localization based on ranging techniques are being exploited to this end. This paper presents a novel cooperative localization scheme that utilizes round trip time (RTT) for inter-vehicle distance calculation, integrated with inertial sensor measurements to update the position of not only the vehicle to be localized, but its neighbors as well. We adopted the extended Kalman filter (EKF), to limit the effect of errors in both the sensors and the neighbors' positions, in computing the new location. In comparison to the existing cooperative localization techniques, our proposed cooperative scheme does not depend on GPS updates for the neighbors' positions thus making it far more suitable in urban canyons and tunnels. In addition, our scheme considers updating the neighbors' positions using their current inertial sensor measurements resulting in; better position estimation. The scheme is implemented and tested using the network simulator 3 (ns-3), vehicle traces are generated using SUMO and error models are introduced to the sensors and initial positions for different velocities and densities. Results show that our scheme outperforms the inertial navigation systems (INS) technology typically used in environments where GPS fails.
Extraction of cutaneous primitives from tactile sensor images

Tactile array sensors give images of contact. Different approaches are possible to analyze these images. In this paper the authors present a new approach to tactile data analysis based on the extraction of tactile primitives. The technique consisting of the extraction of primitives was initially developed for visual images processing, but tactile data are quite different from a camera image. Tactile sensors have low resolution and are not affected by perspective; on the other hand tactile data present high distortion. (due to the sensor protective layer) and a tensorial nature. Moreover, tactile sensors can usually "see" only one primitive, while cameras see more. For this reason they need a different, and still largely unexplored, type of analysis. The system described here uses a set of concurrent neural nets, in order to determine the tactile primitive (and its features) that better describe the contact area between an object and a tactile sensor. Input data are a scalar combination of the normal stress components inside the sensor. Simulations show that the neural system learns and has a high noise immunity. <<ETX>>
A cartographic approach to visualizing conference abstracts

A cartographic approach to mapping nongeographic information helps to manage graphic complexity in visualizations. It aids domain comprehension by forcing us to use the same cognitive skills we use when viewing geographic maps. The author presents a distinctly cartographic approach to mapping nongeographic information. Focusing on the text content of a set of conference abstracts, we can derive 2D visualizations of information spaces that address complexity and automation.
Framework for Better Efficiency of Automated Testing

The paper introduces our design of a framework for test automation, which utilizes both recording and scripting approaches to help quality-assurance engineers with their test automation efforts. Characteristic problems of test automation are a low efficiency and/or high maintenance costs. The framework cuts down those drawbacks using a technique of abstraction, a clever structure of test cases, and reusable common test case retrieval from recorded tests. Finally, the approach is robust to a test script ageing and is technologyindependent as well as testing-tools independent. Keywords-automated testing; functional tests; quality assurance; test efficiency; test recording
A Mild Synthesis of Coumaryl, Coniferyl, Sinapyl Aldehydes and Alcohols

Acetylconiferyl aldehyde is obtained from acetylvanillin by a Wittig reaction under phase-transfer conditions; basic hydrolysis gives coniferyl aldehyde, or after reduction with sodium borohydride affords coniferyl alcohol. This method is extended to the sinapyl and coumaryl series
The complete guide to software testing

From the Publisher: Presents a new perspective on software testing as a life cycle activity. Develops the concepts and principles of testing, offering detailed discussions of testing techniques, methodologies and management viewpoints. This completely revised edition features new chapters on testing methodologies such as ANSI standard-based testing and a survey of testing practices. Includes numerous examples, checklists and case studies.
Sampling Combinatorial Spaces Using Biased Random Walks

This paper addresses the problem of learning control policies in very high dimensional state spaces. We propose a linear dimensionality reduction algorithm that discovers predictive projections: projections in which accurate predictions of future states can be made using simple nearest neighbor style learning. The goal of this work is to extend the reach of existing reinforcement learning algorithms to domains where they would otherwise be inapplicable without extensive engineering of features. The approach is demonstrated on a synthetic pendulum balancing domain, as well as on a robot domain requiring visually guided control.
Structural studies of highly strained hydrocarbons. III. The T–C–C stereoisomer of perhydrotriptycene

C20H32 is monoclinic, space group P21/c with a = 8.904 (3), b = 15.226 (3), c = 12.410 (2) A, fl = 106.03 (2) °, Z = 4, Dr, = 1-03 (2), D x = 1.043 gcm -3. The structure was refined to R = 5.9% for 2961 observed reflections. The bond and torsion angles of the central bicyclooctane nucleus reveal a high degree of strain imposed by the attached cyclohexane rings. The two rings cis-bonded and the one trans-bonded to the central nucleus show different conformations, the former being in the boat and the latter in a chair conformation. All bond lengths and angles agree well with the values obtained by force-field calculations.
Modelling Functional Neuroscience Data

This thesis focus on classification of functional magnetic resonance imaging (fMRI) data using spatio-temporal pattern recognition methods based on probabilistic Bayesian principles. Materials/methods: The principles behind fMRI, fMRI pre-processing methods, hemodynamic response (HR) modelling are reviewed, as are the foundations of kernel methods (KMs), sparse kernel based classifiers, and relevant kernel functions. In-depth descriptions of the relevance vector machine (RVM) and spatio-temporal pattern recognition techniques are given. The 'fast' sequential sparse Bayesian learning (SBL) algorithm for RVM training is described, and a direct search method for adaptation of the Gaussian kernel width parameter is modified for use with the fast training algorithm. Additionally, a novel spatio-temporal kernel function is presented, in which the scans within the temporal range of the HR response elicited from the current neuronal activation, are considered for classifying the current brain state. Results: It is shown that the RVM, using Gaussian kernel basis functions, is able to classify linearly non-separable data with low error rate. The generalisability and sparsity of the resulting statistical models are very good when a reasonable value is selected for the Gaussian kernel width. HR optimisation using the suggested spatio-temporal kernel function effectively reduced the error rate, and prevented abrupt fluctuations in the estimated posterior probability. The kernel width adaptation scheme made the RVM virtually non-parametric, when initialising the width parameter within a sensible range. Conclusion: For the fMRI data sets used in this thesis, employing RVM classification, resulted in very sparse models with low classification error rates. Compared to the support vector machine (SVM), which is the current state-of-the art sparse classifier, the RVM provides a usable posterior probability output. Use of the HR optimised spatio-temporal kernel showed promising results.
System and method for wireless communications

本发明提供一种用于无线通信的方法和系统。 一种在通信网络中操作的方法包括接收码簿(405)，所述码簿包括若干码字；确定所述码簿是否满足恒定模数性质(410)。 该方法还包括当确定所述码簿不满足所述恒定模数性质，将所述码簿转换为满足所述恒定模数性质的码簿(415)，以及存储满足所述恒定模数性质的码簿(420)。 该方法进一步包括当确定所述码簿满足所述恒定模数性质，存储所述码簿(420)，以及将传输信号发射到通信装置，其中所述传输信号使用所述所存储码簿中的码字编码。
FiSH: MATLAB Tools to Turn Fault Data into Seismic‐Hazard Models

Faults have been increasingly integrated into seismic‐hazard assessments. We have developed a package of MATLAB ( , last accessed January 2016) tools (called FiSH ), designed to help seismic‐hazard modelers analyze fault data. These tools enable the derivation of expected earthquake rates, given common fault data, and allow researchers to test the consistency between the magnitude–frequency distributions (MFDs) assigned to a fault and some available observations. The basic assumption of FiSH is that the geometric and kinematic features of a fault are the expression of its seismogenic potential. Three tools have been designed to integrate the variable levels of information available: (1) the first tool allows users to convert fault geometry and slip rates into a global budget of the seismic moment released in a given time frame, taking uncertainties into account; (2) the second tool computes the recurrence parameters and associated uncertainties from historical and/or paleoseismological data; and (3) the third tool outputs time‐independent or time‐dependent earthquake rates for different MFD models. We present a test case to illustrate the capabilities of FiSH , on the Paganica normal fault in central Italy that ruptured during the 2009 L’Aquila earthquake sequence (mainshock M w 6.3). The source codes are open, and we encourage users to handle the scripts, communicate with us regarding bugs, and/or suggest further improvements. Our intent is to distribute these tools in order to help researchers to pinpoint potential inconsistencies and obtain reliable fault‐based seismic‐hazard evaluations.
The Theory of Abstraction

A report for CS9244 on the UltraSPARC T1 processor. Firstly a history and overview of the SPARC architecture is given, focusing on some important features such as instruction set architecture and register windowing. Subsequently we examine the latest implementation of the SPARC architecture, Sun’s UltraSPARC T1. A massively parallel processor implementing Sun’s concepts of “throughput computing”, we detail the unique features of the implementation.