Miracle-dz/UniFAR-FTUs huggingface dataset:
A traffic sampling model for measurement using packet identification

A new sampling model for measurement using packet identification on IP network is provided under a principle of the PSAMP, a working group of IETF (to be set up), that a good sampling model should work for all purposes of measurement applications at the same time with a simple way. After researching and analyzing huge amounts of packet headers captured randomly on the CERNET backbone, the result shows that 16 bits of identification field in the IP packet header is enough for matching bits of the sampling mask. Randomization and statistical attributes of the sampling are analyzed, and the experiment also reveals that this sampling method can be used not only in traffic measurement but also for network behavior analysis.
Static and dynamic mapping of media assets on a network of distributed multimedia information servers

This paper presents principles and algorithms for the management of a network of media servers. Such a server network allows the online delivery of broadband multimedia data, e.g. audio and video streams, to a large number of widely distributed clients. Thus, the implementation of large scale distributed broadband media information services is possible if such networks can be handled efficiently. In the paper two new combinatorial optimization problems are defined that have to be solved for an efficient management of the distributed media servers connected by a high-bandwidth communication network. The algorithms consider the case of a static mapping of media assets onto the server network as well as the dynamic migration of media assets on such a network. The first scenario is used in the case that all media assets are loaded for the first time onto the server network. The second scenario is applied dynamically during run-time of an information service taking the varying user access pattern and changing media content of the server network into account. In this paper the algorithms are presented and their efficiency is demonstrated using some benchmark instances. The algorithms are part of a larger distributed system that allows the management of a network of distributed media servers. The principles of this system are presented as well as some applications that have been developed and are supported by this distributed server management system (DSMS).
Using AI-based monitoring technologies in management control

The author asserts that alternative monitoring technologies will broaden the scope of contractual choices and thereby increase the likelihood of congruence with the organization's objectives, even in those cases where issues of measurability are ill defined. He reviews agency theory with particular reference to implications for organization theory; links agency theory with the empirical and theoretical literature on the managerial task of environmental scanning; describes an AI (artifical intelligence)-based system for facilitating scanning activities; and presents results of a laboratory test of the system's effect on trust in the scanning manager. He provides evidence for the hypothesis that using machine induction can provide information that increases principal trust in agent behavior. <<ETX>>
Predictive medicine: initial symptoms may determine outcome in clinically treated depressions

Nonlinear mathematical modeling methods were compared in the study of therapeutic outcome prediction for clinically depressed patients. The performance of backpropagation, a nonlinear regression technique, was compared to multiple linear and quadratic regression. The results demonstrated nonlinear methods were useful in studying depression. To look for nonlinear predictive relationships among pre-treatment symptoms, treatment, and outcome, several studies were performed on data from 99 patients. This study investigated whether linear and nonlinear methodologies could reliably predict percent improvement of clinically depressed individuals exposed to fluoxetine, desipramine, or cognitive behavioral therapy. The linear model performed at chance levels with no factor statistically significant. However, both nonlinear models, backpropagation and quadratic regression, predicted outcome at statistically significant levels (p<0.05).
Industrial IT Structures as a Means to Express Context Sensitive Information

Industrial IT, from ABB, is a framework-based solution for integrating and operating many, possibly independent, industrial applications. Industrial IT provides a software architecture (embodied in a platform), along with supported tools, that allow integration both at the hardware and software level. In order to be able to still control and manage an industrial plant, it is essential to model and represent different types of information on the various domain objects through Industrial IT. The concepts of Aspect Objects and Aspects 1 along with their usage inside Structures provide the mechanisms by which one can represent and manipulate context specific information of domain objects inside Industrial IT. In this paper we introduce these concepts and show how they can be used today in Industrial IT applications to model but also operate on multiple views of the same domain objects.
A novel direct back EMF detection for sensorless brushless DC (BLDC) motor drives

A novel back EMF detection method for sensorless BLDC motor drives without the motor neutral point voltage information is presented in this paper. The true phase back EMF signal can be directly obtained from the motor terminal voltage by properly choosing the PWM and sensing strategy. As a result, the method proposed is not sensitive to switching noise, no filtering is required, and good motor performance is achieved over a wide speed range. The detailed circuit model is analyzed and experimental results verify the analysis and demonstrate advantages of the new technique.
Detection of incipient clogging in pulverized coal injection lines

This paper deals with the detection of clogging in the coal injection lines of a blast furnace. A physical model is developed and augmented with a signal that represents clogging. A nonlinear observer is proposed and shown to have any predefined convergence rate. An adaptive detection threshold scheme which is robust against time-varying uncertainties is employed. Simulations and experiments with real data are carried out to illustrate the usefulness of the methods.
Finding Critical Values to Control Type I Error for a Biomarker Informed Two-Stage Winner Design

Adaptive clinical trial designs have been getting very popular in recent years. The PhRMA Working Group defines an adaptive design as a clinical study design that uses accumulating data to direct modification of aspects of the study as it continues, without undermining the validity and integrity of the [1]. These designs can assist in potentially accelerating clinical development and improving efficiency. However, the multiple interim looks and adaptive adjustments with the design can lead to inflation of type I error. Over the past decade, several statistical approaches have been proposed to control the inflation, some of which have been widely applied in practice. Some of these approaches include: error spending approach for classical group sequential plans [2-4]; Combination of p-values, such as Fisher’s combination test [5,6], Inverse Normal Method [7], sum of p-values approach [8]; conditional error function [9-11]; fixed weighting method [12]; variance spending method [13,14]; and multiple testing methodology such as closed test procedures [15-17].
Aprendizaje en Agentes con Mecanismos de Selecci´ on de Acci´ on basados en Redes de Comportamiento

The main goal of this work is to introduce plasticity in the autonomous adaptive behavior displayed by agents based on behavior networks. In order to do this, reinforcement learning (RL) is used to learn about the preferences for satisfying selected consummatory behaviors in the competence of the agent. Learnt preferences are then considered by the behavior network to compute the action selection of the agent, approaching in this way a well known problem posed by any learning agent, the trade-off between exploring to learn and exploiting the knowledge previously acquired by learning. ABC-ApR, a resourceful tool designed to study this problem with a choice of eight RL algorithms, was applied to model the foraging and food selection of howler monkeys (alouatta palliata). Different kinds of environments having variable amounts and distributions of labeled food were considered. Plasticity, introduced with RL, enables the simulated agents to achieve food selection sensitive to the variable conditions observed in the environment. Results favorable compare to ethological studies under similar conditions. Este trabajo trata sobre la plasticidad conductual en agentes basados en redes de comportamiento. El aprendizaje por reforzamiento (RL) es usado por estos agentes para establecer preferencias sobre la selección de conductas consumatorias. Estas preferencias son propagadas en las demás conductas que conforman la red de comportamiento, impactando ası́ la selección de acción del agente. Estas ideas se experimentan en el dominio de la conducta de forrajeo del mono aullador alouatta palliata, utilizando ABC-ApR, una herramienta para el estudio de redes de comportamiento que incorpora ocho algoritmos de RL. La plasticidad obtenida con nuestro enfoque, permite a los agentes simulados seleccionar su alimento tomando en cuenta condiciones ambientales, como variabilidad en la cantidad y distribución de los alimentos. Los resultados obtenidos se comparan favorablemente con estudios etológicos bajo condiciones similares, contribuyendo ası́ al área de la etologı́a computacional.
A universal technique for fast and flexible instruction-set architecture simulation

In the last decade, instruction-set simulators have become an essential development tool for the design of new programmable architectures. Consequently, the simulator performance is a key factor for the overall design efficiency. Based on the extremely poor performance of commonly used interpretive simulators, research work on fast compiled instruction-set simulation was started ten years ago. However, due to the restrictiveness of the compiled technique, it has not been able to push through in commercial products. This paper presents a new retargetable simulation technique which combines the performance of traditional compiled simulators with the flexibility of interpretive simulation. This technique is not limited to any class of architectures or applications and can be utilized from architecture exploration up to end-user software development. The work-flow and the applicability of the so-called just-in-time cache compiled simulation (JIT-CCS) technique will be demonstrated by means of state of the art real world architectures.
A universal multi-dimensional lossy compression algorithm

A universal algorithm to compress multi-dimensional data is presented. Besides being able to explore multidimensional correlations of the data, it incorporates two other fundamental innovations when compared to its predecessors, the Lossy Lempel-Ziv (LLZ) and Hierarchical String Matching algorithms: first, instead of building a dictionary of strings to match the data, it builds a dictionary of basis functions in which the data will be decomposed in the spirit of Mallat's matching pursuits; second, any basis function in the dictionary can be dilated or contracted when used to match the data. Simulation results show that it has good coding performance for a large class of image data. With Gaussian sources it has shown good performance, outperforming LLZ algorithms for low data rates, being close to the R(D). With real image data, when LLZ fails at all rates, it has performed even better, showing a great improvement over LLZ.
Mathematica as an educational tool for signal processing

The authors describe extensions to a symbolic mathematics program that make it an effective educational tool for courses in linear systems theory. These extensions are in the form of packages and notebooks for the Mathematica environment. The new signal processing packages contain rule bases that symbolically compute convolutions and all the transforms common to signal processing: Fourier, Laplace, z, etc. In order to introduce a student to these concepts and to how they are implemented in Mathematica, four tutorials have been written in Mathematica's notebook format. Notebooks, a form of hypertext, allow students to access material randomly, to discover insights at their own pace, and to evaluate code provided in the examples. Students can also use notebooks to solve homework problems in a self-documenting fashion. <<ETX>>
14 Neural Networks for Time-Series Forecasting

Neural networks has become an important method for time series forecasting. There is increasing interest in using neural networks to model and forecast time series. This chapter provides a review of some recent developments in time series forecasting with neural networks, a brief description of neural networks, their advantages over traditional forecasting models, and some recent applications. Several important data and modeling issues for time series forecasting are highlighted. In addition, recent developments in several methodological areas such as seasonal time series modeling, multi-period forecasting, and the ensemble method are reviewed.
Applying the ABC metric to C, C++, and Java

Point::~AbstractPoint(void) { // does nothing } The LOC value for this destructor is three, which suggests the code is actually performing some action. On the other hand, the ABC vector components and magnitude are all zero, signifying that the destructor does not contribute directly to program size. This does not necessarily imply, however, that the destructor is not needed. Perhaps the most important aspect of the ABC metric is that it seems to judge a program’s size the way that most developers do. For research purposes, as set of C++ class methods was ranked by eighteen developers who had little familiarity with LOC and no familiarity with ABC. Their rankings shows a significantly higher correlation to ABC magnitudes than to LOC. The result is not too surprising since LOC is merely a convenient measure, not a well- constructed one. No one is fooled into thinking that there is a greater amount of source code if it is spread out over several lines. Likewise, developers do not normally estimate size by assessing the number of operators and operands as software science would suggest. Conclusion The ABC metric overcomes many of the limitations of the LOC metric. It has a theoretical foundation, is style independent, and has useful mathematical properties. Furthermore, the ABC counting rules for C, C++, and Java are defined to allow accurate cross-language comparisons, thereby enhancing the applicability of the metric. Preliminary research suggests that the ABC metric provides program size measurements similar to those given by professional developers. Because of its consistency, the ABC metric should provide better estimates of project development time and program reliability. Specifically, it should provide more accurate comparisons of projects created by different individuals and businesses. Although the ABC is a promising metric, further research is needed to assess its viability for larger programs. The metric must be compared to LOC and other measures to determine the extent of its benefits. The relationship between the ABC components should be explored further. Finally, the hypothesis regarding size and cohesion should be confirmed and the relationship between the two defined. Because ABC counting is too tedious and error-prone to perform by hand, I am developing programs for Windows 95/NT that will automate the process. When completed, you’ll be able to download them from the website http://www.redmtn. com [26 Jun 2002: these utilities are no longer available]. I encourage you to try ABC instead of LOC. I’d be interested in your results, ideas, and comments. References 1. Halstead, M.H. Elements of Software Science, Elsevier North Holland 1977. 2. Fenton, N. Software Metrics, Chapman & Hall 1991. Copyright 1997 by Jerry Fitzpatrick. All rights reserved. Originally published in C++ Report, June 1997.
Assessment of Using Technology for Teaching Statistics

The list of technologies used in statistics classes today has been expanded from those used in a classroom twenty-five years ago. Today's instructional technologies include Java applets for simulating and visualizing concepts in probability and statistics, free Internet-based analysis tools for calculating test statistics and p-values, multimedia textbooks which show video clips of real world situations that use statistics, and easy access to realistic data sets which can be downloaded and used in one of the many statistical application software packages. With so many options of technologies from which to select, a statistics teacher needs to have a means of assessing the effectiveness of these instructional technologies. This paper presents several general strategies associated with assessing instructional technologies. Specific examples are drawn from concepts and technologies used in teaching statistics. Current efforts of organizations to assist statistics teachers with the assessment of the wide array of materials available on the Internet are also presented.
A Web Server for Computing the Size of DNA/Protein Fragments using a Graphical Method

A web server has been developed for computing the size of DNA/protein fragments from their electrophoretic mobilities using a graphical method. This server is based on the computer program DNASIZE (Raghava 1994). It uses DNA marker data and selects the semilogarithmic linear range (slrange), i.e., linear portion of the semilogarithmic curve (mobility vs. log of DNA fragment length). Over this range, a least-squares interpolation is derived for calculating the size of DNA fragments whose mobility falls in sl-range. The program derives hyperbolic interpolation formula over the entire range for determining the size of DNA fragments whose mobility is beyond the semilogarithmic linear range. This server can also be used to compute the size of proteins or polypeptides from SDSPAGE. This web server utilizes a CGI program written in Perl and Javascript, which makes the server live and interactive (imtech.res.in/raghava/dnasize/).
Artistic Method in Research as a Flexible Architecture for Theory-Building

This paper lays out some working tenets for an artistic method of research, one that arguably predates the scientific method and yields multiple strategies for the improvisatory address of researchable ideas and problems. Four overlapping domains of arts-based knowledge, creative practice, and teaching will be outlined along with derivative research methodologies that can be alternately framed as critical-activist, synthetic, analytic, and/or improvisatory. In this writing, the author lays out the basic framework for an Arts-Based Research Primer (2013), an introductory research textbook that aims to reveal how the arts lend themselves to blended spaces of naturalistic inquiry, aiding artists and scientists alike in their conduct of research.
A new motion estimation algorithm based on adaptive hybrid genetic search and selective vector tracing

This paper describes a new motion estimation search strategy that exploits spatio-temporal correlation of a motion vector field to estimate any kind of sequences containing low/high spatial details and slow/fast moving objects. The proposed algorithm dynamically changes its searching strategy between a modified genetic search and an N-step search accordingly to the scene motion complexity and the specified processing power budget. An adaptive subsampled motion vector tracing among B-frames mechanism is provided that drastically improves the coding quality for a relative additional complexity (less than 25%) which gives better results than exhaustive search over large searching range in all CCIR601 sequences tested.
Novel reduced-order small-signal model of three-phase PWM rectifiers and its application in control design and system analysis

A reduced-order small signal model of three-phase PWM rectifiers is proposed. By combining the PWM switch model and equivalent multi-module model techniques in DC-DC power converters, a three-phase rectifier can be modeled as a DC-DC power converter with equivalent power capability and small-signal characteristics. This model reduces the system order to two, and greatly simplifies the control design and system analysis of three-phase power converters. In this paper, the proposed model is also used for control design and for system interaction analysis on the three-phase interface of a boost rectifier. The reduced-order model is verified with the d-q model, switching-model simulation and experimental results.
Image Sensing Technology. A Level-Conversion Method for Wide-Dynamic-Range Camera System.

A level-conversion method for wide-dynamic-range camera system called advanced contrast enhancement (ACE) has been developed. The wide-dynamic-range data is separated from the image's illumination and texture components, then the components are processed accordingly. Component separation is based on the human-vision mechanism and is done using hierarchical non-linear filtering. Experiments showed that ACE generates images with higher contrast and wider dynamic-range. Implementation of ACE in a general purpose camera system confirmed its effectiveness.
Films as graphical comments in the source code of programs

The author suggests using animated pictures (films) as graphical comments in the source code of programs. Such pictures can be played forwards and backwards in steps under the control of the user. They can have multiple branches, which lead to different pictures. Animation effects can be applied to show how a picture changes over time. This can be useful for visualizing the dynamic behavior of programs. He shows how to extend an object-oriented graphics editor so that it can be used for creating and viewing films. He also explains how such films can be embedded into the source code of programs using a text framework.
Improvements in real-time correlation-based stereo vision

A stereo vision system that is required to support high-level object based tasks in a tele-operated environment is described. Stereo vision is computationally expensive, due to having to find corresponding pixels. Correlation is a fast, standard way to solve the correspondence problem. This paper analyses the behaviour of correlation based stereo to find ways to improve its quality while maintaining its realtime suitability. Three methods are suggested. Two of them aim to improve the disparity image especially at depth discontinuities, while one targets the identification of possible errors in general. Results are given on real stereo images with ground truth. A comparison with five standard correlation methods shows that improvements of simple stereo correlation are possible in real-time on current computer hardware.
S-TFT: an analytical model of polysilicon thin-film transistors for circuit simulation

This paper describes the S-TFT model developed for poly-Si TFT which improves the accuracy dramatically. The proposed model emphasis is on deriving the large parasitic resistance characteristics at low Vds by adding the junction current to the on-current. The physical-based subthreshold and off-state current model are also considered. The model guarantees the continuities of the current and the derivatives. Compared to the RPI model, known to be the best model, the proposed model improved overall simulation speed by 40-50% due to the better convergence characteristics.