Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase-Reconfigurable Shuffle Optimization for Hadoop MapReduce

Hadoop MapReduce is a leading open source framework that supports the realization of the Big Data revolution and serves as a pioneering platform in ultra large amount of information storing and processing. However, tuning a MapReduce system has become a difficult task because a large number of parameters restrict its performance, many of which are related with shuffle, a complicated phase between map and reduce functions, including sorting, grouping, and HTTP transferring. During shuffle phase, a large mount of time is spent on disk I/O due to the low speed of data throughput. In this paper, we build a mathematical model to judge the computing complexity of different operating orders within map-side shuffle, so that a faster execution can be achieved through reconfiguring the order of sorting and grouping. Furthermore, a three-dimensional exploring space of the performance is expanded, with which, some sampled features during shuffle stage, such as key number, spilling file number, and the variances of intermediate results, are collected to support the evaluation of computing complexity of each operating order. Thus, an optimized reconfiguration of map-side shuffle architecture can be achieved within Hadoop without extra disk I/O induced. Comparing with the original Hadoop implementation, the results show that our reconfigurable architecture gains up to <inline-formula><tex-math notation="LaTeX">$2.37\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>2</mml:mn><mml:mo>. </mml:mo><mml:mn>37</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="qiu-ieq1-2459707.gif"/></alternatives></inline-formula> speedup to finish the map-side shuffle work.
Grid Computing: Status of Technology In Current Perspective

Modern computer industry is operating with very large amounts of data which utilizes more processing power and high storage volumes of data. Grid computing is proposed as effective resource management to the organization, since it involves using resources from different spaces, from different ownerships and with different individual performance. It requires a highly complex resource management procedure for effective result. This paper presents an overview of grid computing, basic grid technologies, challenges, emerging trends, Grid Security issues, future prospects and the potential for Computational Grid
IMPROVED EAACK FOR INTRUSION DETECTION SYSTEM

Today Mobile Ad-hoc networks (MANETs) are preferred in many applications because of its self-configuring nature and dynamic topology. Sending node in MANETs rely on intermediate nodes for data transmission to remote nodes. This poses serious security threats. There is a necessity of an intrusion detection system to ensure secure message transmission in MANETs. Many Intrusion Detection Systems (IDS) like Watchdog, TWO ACKnowledgement (TWOACK), Adaptive ACKnowledgement (AACK) and Enhanced Adaptive ACKnowledgement (EAACK) have been proposed for this purpose. Of these IDS, EAACK is found to perform better. EAACK is purely acknowledgement based. Hence there should be a mechanism to validate the acknowledgements. This paper aims at improving performance of EAACK by using hybrid cryptography to validate the sending and receiving nodes in place of Digital Signature Algorithm (DSA) and Rivest Shamir and Adelman algorithm (RSA) that is used in existing EAACK. In hybrid cryptographic key exchange algorithm, a combination of symmetric and asymmetric key cryptographic algorithm (AES and RSA) is used. When compared with its contemporary EAACK, Improved EAACK (IEAACK) achieves smaller network overhead.To simulate the IEAACK environment, NS2 simulator is used. IEAACKovercomes the problems of existing IDS.
Probabilistic Brain FiberTractography on GPUs

Abstract —Diffusion Tensor Magnetic Resonance Imaging(DT-MRI) is an emerging techniquethat explores the structuralconnectivity of the human brain. The probabilistic ﬁber trac-tography based on DT-MRI data behaves more robustly thandeterministic approaches in the presence of ﬁber crossings, butrequires more prohibitive computational time. In this workwe present a GPU-based probabilistic framework for brainﬁber tractography. The framework includes two main steps:1) Markov-Chain Monte-Carlo (MCMC) sampling, and 2)probabilistic streamlining ﬁber tracking. We implement theMetropolis-Hastings sampling for local parameter estimationon GPU. In the probabilistic streamlining ﬁber tracking,we ﬁnd that ﬁber lengths are exponentially distributed, andpropose a novel segmenting strategy to improve the loadbalance. On mid-range GPUs, we achieve performance gainsup to 34x and 50x over CPUs for the two steps respectively. Keywords -GPU; Probabilistic ﬁber tractography; DT-MRI;MCMC; Probabilistic Streamlining
Lighting geometry aware environment matting and 3D reconstruction

Lighting geometry, which refers to the relationship between lighting conditions, object geometry or appearance and various lighting interaction phenomenons, is a fundamental issue in many computer graphics and computer vision problems. The challenges of lighting geometry related problems lie in the complex interactions between environment lights and objects, the diversity of lighting sources, the high computational cost and so on. This thesis investigates two specific lighting geometry related topics: environment matting and 3D reconstruction, where the former is with controllable lighting conditions and the latter is with general unknown illumination conditions. Our goal is to design and develop some effective and efficient algorithms which exploit lighting geometry property to improve the performance of the existing algorithms. First of all, considering that the state-of-the-art real-time environment matting and compositing method is short of flexibility, in the sense that it has to repeat the entire complex matte acquisition process if the distance between the object and the background is different from that in the acquisition stage, and also lacks accuracy, in the sense that it can only remove noises but not errors, we introduce the concept of refractive vector and propose to use a refractive vector field as a new representation for environment matte. Such refractive vector field provides great flexibility for transparent object environment matting and compositing. Particularly, with only one process of the matte acquisition and the refractive vector field extraction, we are able to composite the transparent object into an arbitrary background at any distance. Furthermore, we introduce novel light vector field fitting algorithms to simultaneously remove both noises and errors contained in the extracted matte data. Experimental results show that our method is less sensitive to artifacts and can generate perceptually good composition results for more general scenarios.
OAuth 2.0 Message Authentication Code (MAC) Tokens

This specification describes how to use MAC Tokens in HTTP requests to access OAuth 2.0 protected resources. An OAuth client willing to access a protected resource needs to demonstrate possession of a cryptographic key by using it with a keyed message digest function to the request. The document also defines a key distribution protocol for obtaining a fresh session key.
Time-Predictable Communication on a Time-Division Multiplexing Network-on-Chip Multicore

Time-Predictable Communication on a Time-Division Multiplexing Network-on-Chip Multicore This thesis presents time-predictable inter-core communication on a multicore platform with a time-division multiplexing (TDM) network-on-chip (NoC) for hard real-time systems. The thesis is structured as a collection of papers that contribute within the areas of: reconfigurable TDM NoCs, static TDM scheduling, and time-predictable inter-core communication. More specifically, the work presented in this thesis investigates the interaction between hardware and software involved in time-predictable inter-core communication on the multicore platform. The thesis presents: a new generation of the Argo NoC network interface (NI) that supports instantaneous reconfiguration, a TDM traffic scheduler that generates virtual circuit (VC) configurations for the Argo NoC, and software functions for two types of intercore communication. The new generation of the Argo NoC adds the capability of instantaneously reconfiguring VCs and it addresses the identified shortcomings of the previous generation. The VCs provide the guaranteed bandwidth and latency required to implement time-predictable inter-core communication on top of the Argo NoC. This new Argo generation is, in terms of hardware, less than half the size of NoCs that provide similar functionalities and it offers a higher degree of flexibility to the application programmer. The developed TDM scheduler supports a generic TDM NoC and custom parameterizable communication patterns. These communication patterns allow the application programmer to generate schedules that provide a set of VCs that efficiently uses the hardware resources. The TDM scheduler also shows better results, in terms of TDM period, compared to previous state-of-the-art TDM schedulers. Furthermore, we provide a description of how a communication pattern can be optimized in terms of shortening the TDM period. The thesis identifies two types of inter-core communication that are commonly used in real-time systems: message passing and state-based communication. We implement message passing as a circular buffer with the data transfer through the NoC. The worst-case execution time (WCET) of the send and receive functions of our implementation is not dependent on the message size. We also implement five algorithms for state-based communication and analyze them in terms of the WCET and worst-case communication delay. The five algorithms each have scenarios where they are better than the others. This thesis shows in detail how time-predictable inter-core communication can be implemented in an efficient way, from the low-level hardware to the high-level software functions.
Control Strategy for Modular Multilevel Converter based on Single-phase Power Factor Correction Converter

This paper proposes a novel control strategy for a step-down rectifier that applies a modular multilevel converter (MMC). This paper first discusses the circuit configuration and the proposed control method. The main part of the control system is based on the control method for the single-phase power factor correction converter (PFC converter), which means that the conventional control techniques of the single-phase PFC converter can be simply applied to the MMC. The control elements which achieve step-down rectification and capacitor voltage balancing are added to the main part. Besides, in capacitor voltage balancing of the proposed control method, it is not necessary to design the control parameters. In addition, the operation of the proposed step-down rectifier is confirmed by the simulation. The simulation results show that the proposed converter achieves step-down rectification from the grid voltage of 6.6 kV to the DC voltage of 400 V. Moreover, the step-down rectifier maintains all capacitor voltages constant. Finally, a fundamental operation is confirmed by experiments using a miniature model. As the results, the step-down rectifier converts from the input grid voltage of 200 V to the output DC voltage of 75 V. Besides, the proposed step-down rectifier maintains the capacitor voltage of each cell to the voltage command of 130 V. The maximum error between the voltage command of the cell capacitor and the measured voltage is less than 2%.
A qualitative study comparing the instruction on vectors between a physics course and a trigonometry course

Science and engineering instructors often observe that students have difficulty using or applying prerequisite mathematics knowledge in their courses. This qualitative project uses a case-study method to investigate the instruction in a trigonometry course and a physics course based on a different methodology and set of assumptions about student learning and the nature of mathematics than traditionally used when investigating students‘ difficulty using or applying prerequisite mathematics knowledge. Transfer theory examined within a positivist or post-positivist paradigm is often used to investigate students‘ issue applying their knowledge; in contrast, this qualitative casestudy is positioned using constructionism as an epistemology to understand and describe mathematical practices concerning vectors in a trigonometry and a physics course. Instructor interviews, observations of course lectures, and textbooks served as the qualitative data for in-depth study and comparison, and Saussure‘s (1959) concept of signifier and signified provided a lens for examining the data during analysis. Multiple recursions of within-case comparisons and across-case comparison were analyzed for differences in what the instructors and textbooks explicitly stated and later performed as their practices. While the trigonometry and physics instruction differed slightly, the two main differences occurred in the nature and use of vectors in the physics course. First, the ―what‖ that is signified in notation and diagrams differs between contextualized and context-free situations, and second, physics instruction taught vectors very similar to trigonometry instruction when teaching the mathematics for doing physics, but once instruction focused on physics, the manner in which vector notation and diagrams are used differed different from what is explicitly stated during mathematics instruction.
Predicting and Controlling Complex Networks

The research on the topology and dynamics of complex networks is one of the most focused area in complex system science. The goals are to structure our understanding of the real-world social, economical, technological, and biological systems in the aspect of networks consisting a large number of interacting units and to develop corresponding detection, prediction, and control strategies. In this highly interdisciplinary field, my research mainly concentrates on universal estimation schemes, physical controllability, as well as mechanisms behind extreme events and cascading failure for complex networked systems. Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks. One of the most challenging problems in complex dynamical systems is to control complex networks. Upon finding that the energy required to approach a target state with reasonable precision is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural “short boards” that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy. Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dy-
Skip cycle modulation in switching DC-DC converter

A novel control mode named SCM (skip cycle modulation) in switching DC-DC converter is developed and analyzed in this paper. The principles and the characteristics of SCM are described. Compared with PWM and PFM control modes, the response speed of DC-DC converter under SCM control mode is faster, the efficiency of the system with low loads is higher, and the harmonics smaller. All of these indicate that SCM is a better control mode in high frequency switching DC-DC converter.
Implementation of Immunological Algorithms in Solving Optimization Problems

This paper gives a global review of artificial immune systems in computer science and their implementation. The performance of the immunological algorithm in solving optimization problems is analysed using the Optimization Algorithm Toolkit, with emphasis on determining the impact of parameter values. It is shown that these types of algorithms are particularly sensitive to the choice of parameters that affect the functioning of the algorithm.
Multi-level SLIC superpixels segmentation method based on edge detection operator

Simple linear iterative clustering (SLIC) super-pixel algorithm for its excellent performance and efficient border holding computational efficiency is widely used in image processing. But with the increase of the number of super-pixels, there will be a lot of redundancy in the image merging process. In this paper, we propose a multi-level super-pixels method based SLIC algorithm, which focuses on the target area to set up edge detection operator for generating multi-level super-pixels. Simulation results show that the proposed method ensures the accuracy of extraction and improves the computational efficiency.
The Time Series Properties of the Real Exchange Rates Between the Member States of the European Monetary Union

Abstract The article “The Time Series Properties of the Real Exchange Rates Between the Member States of the European Monetary Union” analyses the time series behavior of the components of the real exchange rates between the founding member states of the EMU before and after the start of the EMU. Various panel and univariate country-specific tests show that the levels of these components are typically random walks. The resulting real exchange rates are also random walks and their components are not cointegrated. It is argued that these results question the operability of the EMU under the current policy regime in the long-run. One possibility to deal with this problem could be the suspension of the principle of a “single monetary policy”. Die Zeitreiheneigenschaften der realen Wechselkurse der Mitgliedsländer der Europäischen Währungsunion Zusammenfassung Der Artikel „Die Zeitreiheneigenschaften der realen Wechselkurse der Mitgliedsländer der Europäischen Währungsunion“ untersucht das Zeitreihenverhalten der Komponenten der realen Wechselkurse zwischen den Gründerstaaten der EWU vor und nach dem Beginn der EWU. Verschiedene Panel- und univariate länderspezifische Test zeigen, dass die Niveaus dieser Komponenten typischerweise Zufallspfaden folgen. Die resultierenden realen Wechselkurse folgen ebenfalls Zufallspfaden und ihre Komponenten sind nicht kointegriert. Diese Ergebnisse, so schließt der Artikel, stellen die langfristige Funktionsfähigkeit der EWU unter dem gegenwärtigen geldpolitischen Regime in Frage. Eine Möglichkeit, dieses Problem zu adressieren, könnte in der Preisgabe des Prinzips der einheitlichen Geldpolitik bestehen. JEL Classification: E50, E31, C12
CoAP Management Interface

This document describes a network management interface for constrained devices and networks, called CoAP Management Interface (CoMI). The Constrained Application Protocol (CoAP) is used to access datastore and data node resources specified in YANG, or SMIv2 converted to YANG. CoMI uses the YANG to CBOR mapping and converts YANG identifier strings to numeric identifiers for payload size reduction. The complete solution composed of CoMI, x and [I-D.ietf-core-sid] is called CORECONF. CORECONF extends the set of YANG based protocols, NETCONF and RESTCONF, with the capability to manage constrained devices and networks.
Generalized 3D Co-occurrence Matrix for Visual Information Retrieval *

A novel feature set based on generalized co-occurrence matrix is proposed for Content-based Image Retrieval (CBIR). Texture features provide important cue for the visual information retrieval and discrimination of image content, therefore a set of 3D co-occurrence matrix based texture features is proposed. The preliminary results based on the novel features are much better than traditional ones. Experiments are implemented on an image database including 25000 images.
Berufliche Interessen, kognitive und fachgebundene Kompetenzen: Ihre Bedeutung für die Studienfachwahl und die Bewährung im Studium

0\. Inhaltsverzeichnis 1\. Einleitung 1 2\. Fahigkeiten und Interessen: Determinanten und Folge differenzieller Schullaufbahnen 6 3\. Fahigkeiten und berufliche Interessen als Determinanten von Studienfachwahlen 29 4\. Berufliche Interessen und kognitive und fachbezogene Fahigkeiten als Determinanten des Studienerfolgs 55 5\. Forschungsanliegen der vorliegenden Arbeit 78 6\. Studie 1: Die Struktur der beruflichen Interessen 85 7\. Studie 2: Korrelate beruflicher Interessen 137 8\. Studie 3: Determinanten der Studienfachwahlen 175 9\. Studie 4: Berufliche Interessen, kognitive und fachliche Kompetenzen und Studienerfolg 206 10\. Gesamtdiskussion 255 11\. Literatur 277 12\. Anhang 300
Bayesian projection of the acquired immune deficiency syndrome epidemic

Short‐term projections of the acquired immune deficiency syndrome (AIDS) epidemic in England and Wales have been regularly updated since the publication of the Cox report in 1988. The key approach for those updates has been the back‐calculation method, which has been informally adapted to acknowledge various sources of uncertainty as well as to incorporate increasingly available information on the spread of the human immunodeficiency virus (HIV) in the population. We propose a Bayesian formulation of the back‐calculation method which allows a formal treatment of uncertainty and the inclusion of extra information, within a single coherent composite model. Estimation of the variably dimensioned model is carried out by using reversible‐jump Markov chain Monte Carlo methods. Application of the model to data for homosexual and bisexual males in England and Wales is presented, and the role of the various sources of information and model assumptions is appraised. Our results show a massive peak in HIV infections around 1983 and suggest that the incidence of AIDS has now reached a plateau, although there is still substantial uncertainty about the future.
Method of Trajectory Generation of a Generic Robot using Bresenham’s Circle Algorithm

Objectives: This paper characteristic the proposed method of trajectory generator of designing the mechanical type manipulator configuration as called the robot model after validating the kinematic analysis and software simulation of the mechanism. Methods/Statistical Analysis: The robot manipulator has utilized in this paper used for welding operation. In the mechanical configuration the successful utilization of newly designed universal joints and also the use of screw jack mechanisms at the robot manipulator base give the higher flexibility and degrees of freedom (dof) in the arms of the robot. This paper also describes the path planning of the robot based on the computer graphics concept of Bresenham’s line and circle algorithm for trajectory generation. This paper also describes the path planning of the robot based on the Bresenham’s line and circle algorithm concepts. Findings: This type of algorithm proved to generate the trajectory is very much effective, accurate and fast manner. From the trajectory points the new way of finding the joint angles was found using the inverse kinematics relationship were explained in this paper. Application/Improvements: This work is an essential parameter for robot trajectory formation with the given diameter of the cylinder to be going to be welded.