Miracle-dz/UniFAR-FTUs huggingface dataset:
Relevanz ist alles: Algorithmen im Intranet

Durch den Einzug elektronischer Verbreitungsmedien in den Alltag spielen einerseits der Ort und die Zeit in der Kommunikation eine kontinuierlich geringere Bedeutung. Mitarbeiter leiden deshalb nicht mehr an Informationsdefiziten, sondern an Informationsüberflutungen. In diesemBeitrag soll dargestellt werden, wie in der Praxis in Intranets durch Algorithmen versucht wird, die Informationsüberflutung einzudämmen. Hierzu wird eine soziologische Herangehensweise gewählt, wobei nicht der Aushandlungsprozess von Algorithmen in den Fokus gerückt wird, sondern die Ideen hinter Algorithmen,und wie diese sich auf organisatorische Strukturen und alltägliche Praktiken auswirken. Die folgenden Bemerkungen basieren auf 27 Experteninterviews, die mit der dokumentarischen Methode ausgewertet wurden. Angereichert werden diese durch eigene Projekterfahrungen der vergangenen 2,5 Jahre, die ich in Unternehmen und öffentlichen Diensteinrichtungen gesammelt habe. Schlagworte: Intranet, Algorithmus, Mitarbeiter, Informationsverhalten, Web 2.0, informelle Kommunikation, Kommunikation, Unternehmen, Komplexität, Personalisierung Publiziert von Hamburg University Press 1 Mai 2017 | Bd. 18 | Nr. 2 doi: 10.15460/kommges.2017. 18.2. 578
Joint equalization and interference suppression for high data rate wireless systems

Enhanced Data Rates for Global Evolution (EDGE) is currently being standardized as an evolution of GSM in Europe and IS-136 in the United States as an air interface for high speed data services for third generation mobile systems. We study space-time processing for EDGE to provide interference suppression. We consider the use of two receive antennas and propose a joint equalization and diversity receiver. This receiver uses front-end filters on each diversity branch to perform minimum mean-square error (MMSE) cochannel interference suppression, while leaving the intersymbol interference to be mitigated by the subsequent equalizer. The equalizer is a delayed decision feedback sequence estimator (DDFSE), consisting of a reduced-state Viterbi processor and a feedback filter. The equalizer provides soft output to the channel decoder after deinterleaving. We describe a novel weight generation algorithm and present simulation results on the link performance of EDGE with interference suppression. These results show a significant improvement in the signal-to-interference ratio (SIR) performance due to both diversity (against fading) and interference suppression. At a 10% block error rate, the proposed receiver provides a 20 dB improvement in SIR for both the typical urban and hilly terrain profiles.
Bayesian inference for structured additive regression models for large-scale problems with applications to medical imaging

In der angewandten Statistik konnen Regressionsmodelle mit hochdimensionalen Koeffizienten auftreten, die sich nicht mit gewohnlichen Computersystemen schatzen lassen. Dies betrifft unter anderem die Analyse digitaler Bilder unter Berucksichtigung raumlich-zeitlicher Abhangigkeiten, wie sie innerhalb der medizinisch-biologischen Forschung haufig vorkommen. In der vorliegenden Arbeit wird ein Verfahren formuliert, das in der Lage ist, Regressionsmodelle mit hochdimensionalen Koeffizienten und nicht-normalverteilten Zielgrosen unter moderaten Anforderungen an die benotigte Hardware zu schatzen. Hierzu wird zunachst im Rahmen strukturiert additiver Regressionsmodelle aufgezeigt, worin die Limitationen aktueller Inferenzansatze bei der Anwendung auf hochdimensionale Problemstellungen liegen, sowie Moglichkeiten diskutiert, diese zu umgehen. Darauf basierend wird ein Algorithmus formuliert, dessen Starken und Schwachen anhand von Simulationsstudien analysiert werden. Daruber hinaus findet das Verfahren Anwendung in drei verschiedenen Bereichen der medizinisch-biologischen Bildgebung und zeigt dadurch, dass es ein vielversprechender Kandidat fur die Beantwortung hochdimensionaler Fragestellungen ist.
A methodology for measuring software development productivity using Eclipse IDE

During software development processes many methodologies and technologies are used which can be examined and compared by many points of view. One of the important aspects is the development productivity which aects development time and costs significantly. It is the composition of many factors but actually not all relevant and aecting factors and their relationships are known. Measuring the development productivity can be very useful if we would like to see that: • How much of the total development time takes the real development? • How long is the real development time of specific software components and layers? • How much time does a bug fix or the implementation of a new feature take in specific components or layers during software evolution? Beside the development time it is also worth to examine the quality of the software using various software metrics. Therefore a special tool is needed which can perform real time productivity measurements during the development but at present there are only a few tools for this task with limited measurement capabilities. The goal of this paper is to introduce a methodology for measuring productivity (even for specific software units) with defining a list of relevant factors and events to be observe (e.g. file and user interface events). Besides, this paper presents a measurement tool for monitoring development productivity in the Eclipse IDE (Integrated Development Environment). We have successfully measured a former project using this Eclipse-based tool and evaluated the measurement results to examine the development time of specific application layers.
Sense And Avoid (SAA) & Traffic Alert and Collision Avoidance System (TCAS) Integration for Unmanned Aerial Systems (UAS)

The emerging role of Unmanned Aerial Systems (UAS) for both military and civil operations hinges on the ability to gain unrestricted access to national airspace. One of the key issues that must be resolved to open up the skies to UAS is coexisting safely and effectively with current manned operations in Federal Aviation Administration (FAA)controlled airspace. This includes the ability to perform Sense and Avoid (SAA) functions at an “equivalent level of safety” (ELOS) to manned aircraft while not negatively impacting the existing infrastructure and manned Traffic Alert and Collision Avoidance System (TCAS) that create today’s safe airspace. An SAA system consisting of multiple dissimilar passive and active sensors can be designed to provide a robust and safety-critical autonomous collision avoidance solution to protect against midair collisions with both cooperative (transponding) and non-cooperative (non-transponding) intruder vehicles. In this paper, the authors investigate the feasibility of using data from multiple sensors to drive a collision avoidance algorithm that is compatible with current manned TCAS II-equipped aircraft. Furthermore, the authors investigate the effects of integrating TCAS II on UAS.
DERIVATIVE-FREE KALMAN FILTER-BASED CONTROL OF NONLINEAR SYSTEMS WITH APPLICATION TO TRANSFEMORAL PROSTHESES

Derivative-free Kalman filtering (DKF) for estimation-based control of a special class of nonlinear systems is presented. The method includes a standard Kalman filter for the estimation of both states and unknown inputs, and a nonlinear system that is transformed to controllable canonical state space form through feedback linearization (FL). A direct current (DC) motor with an input torque that is a nonlinear function of the state is considered as a case study for a nonlinear single-input-single-output (SISO) system. A three degreeof-freedom (DOF) robot / prosthesis system, which includes a robot that emulates human hip and thigh motion and a powered (active) transfemoral prosthesis disturbed by ground reaction force (GRF), is considered as a case study for a nonlinear multi-input-multi-output (MIMO) system. A PD/PI control term is used to compensate for the unknown GRF. Simulation results show that FL can compensate for the system’s nonlinearities through a virtual control term, in contrast to Taylor series linearization, which is only a first-order linearization method. FL improves estimation performance relative to the extended Kalman filter, and in some cases improves the initial condition region of attraction as well. A stability analysis of the DKF-based control method, considering both estimation and unknown input compensation, is also presented. The error dynamics are studied in both frequency and time domains. The derivative of the unknown input plays a key role in the error dynamics and is the primary limiting factor of the closed-loop estimation-based control system stability. It is shown that in realistic systems the derivative of the unknown input is the primary determinant of the region of convergence. It is shown that the tracking error asymptotically converges to the derivative of the unknown input.
MODEL CHECKING REVEALS HIDDEN ERRORS IN SAFETY-CRITICAL I&C SOFTWARE

Function blocks are a common programming language for safety-classified instrumentation and control (IC as an example, we have been consulting the Finnish Radiation and Nuclear Safety Authority (STUK) on evaluating NPP I&C system designs using model checking since 2008. In this paper, we present a method for model checking of function block based systems. Since model checking also requires the formal specification of system requirements, we also present a method for requirement specification based on requirement templates.
Using $1 UNISTROKE Recognizer Algorithm in Gesture Recognition of Hijaiyah Malaysian Hand-Code

How people communicate with each other depends on one’s ability to hear, see, lip-reading skills, body language, sign language or speaking abilities. What if one person is deaf or speech impaired and the other does not understand sign language or body language used by the deaf in communicating. Conventional sign language is not effective and is not applicable when it comes to recitation of al-Quran. To overcome the difficulty in using conventional sign languages to teach Quran for deaf people, a method called FAKIH was introduced in deaf school for Muslim deaf pupil in Malaysia. However, it is difficult to evaluate and to interpret the gestures performed by deaf or speech impaired when they master these signs. This is one of many reasons why a technology like gesture recognition could help. Researchers have conducted numerous researches on gesture recognition within the last 2 decades. Although these techniques have been used in gaming and providing control mechanism for virtual environment for users, there is some variation within the tools and environments used between implementations. Recognition of gesture by a person, especially deaf or speech impaired should be easily perceived without going through complex procedures. However, technology has evolved and advanced devices and techniques have been introduced to simplify recognition of gestures. These techniques and technologies can be used to help people with special needs. A simplified gesture recognition platform specially focused on detecting the methods described in FAKIH is crucial for the speech impaired or deaf community to practice and recite al-Quran. This research involves evaluation of algorithms name $1 UNISTROKE Recognizer and identify the gestures in accordance to FAKIH method.
Transport Layer Security (TLS) Extensions: Extension Definitions

This document provides specifications for existing TLS extensions. It is a companion document for the TLS 1.2 specification [RFC5246]. The extensions specified are server_name, max_fragment_length, client_certificate_url, trusted_ca_keys, truncated_hmac, and status_request. INTERNET-DRAFT TLS Extension Definitions
A computational approach for processing diatopic verbal fixed expressions

One of the main problems in the task of a translator are the fixed expressions or phraseological units (UFs), is not possible to establish a meaning from its constituents, in addition to a grammatical structure which can move away from the language rules. Other problems associated with fixed expressions are their low representation in thesaurus and dictionaries, also fixed expressions have problems with indexing, search and management of their variants. In this paper an alternative method of processing and translate of verbal locutions and verbal syntagms into a diatopic system of the Spanish language is presented. The proposed approach incorporates computational techniques and tools such as a relational model, expansion and variation of the expressions using key-words and regular expressions to show of examples of use of these expressions in an electronic corpus.
Detection of Seam Carved Image Based on Additional Seam Carving Behavior

Seam carving is a kind of content aware image retargeting algorithm and can be applied to resize and deliberately remove objects from digital images. Based on the observation that after applying an additional seam carving operation, the similarity, the energy relative error, and the difference of seam distance of original image are quite different from those of the seam-carved image, we propose and develop a new method for detecting seam carving or seam insertion of natural images without knowledge of the original image. First, we apply an additional seam carving operation to the testing image, then calculate similarity, energy relative error, and difference of seam distance between the testing image and its seam carved version. Last, we extract 11 dimensional features to detect seam carving operation to train a support vector machine classifier for recognizing whether an image is an original or it has been modified using seam-carving. Our experimental results demonstrate that our proposed forensic method achieves not only better detection rate but also lower dimensional features compared with other existing seam carved detection methods.
Impacts of Channel Switching Overhead on the Performance of Multicast in Wireless Mesh Networks

Wireless mesh networks (WMNs) have emerged as a promising technology for nextgeneration wireless networking. A WMN extends network coverage using wireless mesh routers that communicate with each other via multi-hop wireless communications. One technique to increase the network capacity of WMNs is to use routers equipped with multiple radios capable of transmitting and receiving on multiple channels. In a Multi-Channel Multi-Radio wireless mesh network (MCMR WMN), nodes are capable of transmitting and receiving data simultaneously through different radios and at least theoretically doubling the average throughput. On the other hand, the use of multi-radio and multi-channel technology in many cases requires routers to switch channels for each transmission and/or reception. Channel switching incurs additional costs and delay. In this thesis, we present a simulation-based study of the impacts of channel switching overheads on the performance of multicast in MCMR WMNs. We study how channel switching overheads affect the performance metrics such as packet delivery ratio, throughput, end-to-end delay, and delay jitter of a multicast session. In particular, we examine:
Factors affecting timely completion of a PhD: a complex systems approach

Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim. Focusing on a single research group in Mathematical Sciences, we develop a conceptual model to describe the factors considered to be important to students and then quantify the network based on five individual perspectives: the students, a supervisor and a university research students centre manager. The resultant network comprised 37 factors and 40 connections, with an overall probability of timely completion of between 0.6 and 0.8. Across all participants, the four factors that were considered to most directly influence timely completion were personal aspects, the research environment, the research project, and incoming skills. Timely completion of a PhD is an important outcome for the student, the host university and the economy. However, completion of this programme in the required timeframe is dependent on many interacting factors. In this study, we develop a statistical complex systems approach to identify and quantify the important factors and their interactions that are perceived to impact on timely completion of a PhD in Statistics in an Australian university. We define timely completion to be within 3.5 years. We construct a Bayesian Network (BN) to describe these inter-relationships (Pearl, 1985); the construction and interpretation of a BN is described in more detail below. The conceptual model for the BN was developed collectively and then quantified by five candidates: three students, a supervisor and a university research students centre
Anomaly-Based Detection of Malicious Activity in In-Vehicle Networks

Modern automobiles have been proven vulnerable to hacking by security researchers. By exploiting vulnerabilities in the car’s external interfaces, attackers can access a car’s controller area network (CAN) bus and cause malicious effects. We seek to detect these attacks on the bus as a last line of defence against automotive cyber attacks. The CAN bus standard defines a low-level message structure, upon which manufacturers layer their own proprietary command protocols; attacks must similarly be tailored for their target. This variability makes intrusion detection methods difficult to apply to the automotive CAN bus. Nevertheless, the bus traffic is generated by machines; thus we hypothesize that it can be characterized with machine learning, and that attacks produce anomalous traffic. Our goals are to show that anomaly detection trained without understanding of the message contents can detect attacks, and to create a framework for understanding how the characteristics of a novel attack can be used to predict its detectability. We developed a model that describes attacks based on their effect on bus traffic, informed by a review of published material on car hacking in combination with analysis of CAN traffic from a 2012 Subaru Impreza. The model specifies three high-level categories of effects: attacks that insert foreign packets, attacks that affect packet timing, and attacks that only modify data within packets. Foreign packet attacks are trivially detectable. For timing-based anomalies, we developed features suitable for one-class classification methods. For packet stream data word anomalies, we adapted recurrent neural networks and multivariate Markov model methods to sequence anomaly detection and compared their performance. We conducted experiments to evaluate our
Black Cats and Yellow Birds - What do Viewpoint Correspondences Do?

The ODP Reference Model is one of a number of specification frameworks which are based on the definition of a set of viewpoints that are coupled together by the definition of correspondences between terms. Wherever a correspondence is declared, any real world entity that is represented by a term in one viewpoint must also satisfy the requirements placed by the occurrence of the corresponding term in the other viewpoint. Although this idea represents an intuitively simple and satisfying way of talking about the design of complex systems, the idea of a correspondence is not as simple as it might, at first sight, appear. This paper uses simple examples to illustrate some of the complexities resulting from the coupling of object models and examines the consequences for claims of conformance to the complete system of specifications.
Proving Floating-Point Numerical Programs by Analysis of their Assembly Code

We present an approach for proving behavioral properties of numerical programs by analyzing their compiled assembly code. We focus on the issues and traps that may arise on floating-point computations. Direct analysis of the assembly code allows to accurately take into account architecture- or compiler-dependent features such as the possible use of extended precision registers. The approach is implemented on top of the generic \Why platform for deductive verification, which allows us to perform experiments where proofs are discharged by combining several back-end automatic provers.
Multi-Transition Systems: A theory for neural spatial navigation

Spatial navigation is considered fundamental for animals and is attributed primarily to place and grid cells in the rodent brain. Commonly believed to either perform path integration or localization, the true objective of grid cells, their hexagonal grid fields, and especially their discrete scales remain puzzling. Here it is proposed that grid cells efficiently encode transitions in sequences. A biologically plausible model for dendritic computation in grid cells is presented. A network of competitive cells shows positive gridness scores early in simulations and realigns the orientation of all cells over time. Then, a scale-space model of grid cells is introduced. It improves behaviorally questionable run-times of a single scale significantly by look-ahead in multiple scales, and it is shown that the optimal scale-increment between consecutive scales is √2. Finally, a formal theory for sequences and transitions is stated. It is demonstrated that hexagonal transition encoders are optimal to encode transitions in Euclidean space and emerge due to the sampling theorem. The paper concludes with a discussion about the suggested purpose, makes testable predictions, and highlights relevant connections to computational neuroscience as well as computer science and robotics.