Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning in der Bilderkennung: Steuerung autonomer mobiler Roboter mit Hilfe neuronaler Netze

This present bachelor thesis deals with the problem of machine learning for orientation and navigation by visual perception, based on a practical example using a robot vehicle. The basis of this thesis are deep learning concepts in artificial neural networks in the field of image recognition and the theoretical and practical comparison of training models for this networks. The usability of those methods in the context of robot navigation in dynamic environments is evaluated, using a specially for this work developed robot vehicle. Finally, the implementation of the theoretical concepts of these deep learning models is demonstrated with the practical use of this robot vehicle.
Annotated suffix tree as a way of text representation for information retrieval in text collections

A method for information retrieval based on annotated suffix trees (AST) is presented. The method is based on a string-to-document relevance score calculated using AST as well as fragment reverse indexing for improving performance. We developed a search engine based on the method. This engine is compared with some other popular text aggregating techniques: probabilistic latent semantic indexing (PLSA) and latent Dirichlet allocation (LDA). We used real data for computation experiments: an online store’s xml-catalogs and collections of web pages (both in Russian) and a real user’s queries from the Yandex. Wordstat service. As quality metrics, we used point quality estimations and graphical representations. Our AST-based method generally leads to results that are similar to those obtained by the other methods. However, in the case of inaccurate queries, AST-based results are superior. The speed of the AST-based method is slightly worse than the speed of the PLSA/LDA-based methods. Due to the observed correlation between the average query performing time and the string lengths at the AST construction phase, one can improve the performance of the algorithm by dividing the texts into smaller fragments at the preprocessing stage. However, the quality of search may suffer if the fragments are too short. Therefore, the applicability of annotated suffix tree techniques for text retrieval problems is demonstrated. Moreover, the AST-based method has significant advantages in the case of fuzzy search.
Implementation and Verification of Dissemination of Tree Structure Data using Signature Scheme for XML Data

With wide spread use of digital data communication on networks, security of data has become an important issue which provides integrity and confidentiality of content that ensures the distribution of information appropriately. While dealing with encoded content in the context of XML, its hierarchical tree structure has different level of confidentiality and integrity for various portion of the same content. Thus it imposes the need of dissemination approach specifically tailored for XML data to address the issues of efficiency and scalability. However these characteristics must be achieved without compromising the security and privacy of contents. The goal of efficient proposed Signature scheme for secure & selective distribution of XML content is to provide uniform platform for different data representation for secure and efficient availability of data. Proposed Signature Scheme is used to detect the change of content at information providers to discover and deliver new content to users. This can be achieved using structural properties of hierarchical tree structure data model with multicast topology approach.
Precoding Designs in Multiuser Multicell Wireless Systems: Competition and Coordination

In a multicell system, universal frequency reuse can be employed in a network of neighboring cells for higher spectral efficiency. However, universal frequency reuse comes at the price of severe inter-cell interference (ICI), especially at cell- edge mobile stations (MS), which may effectively impair the overall system performance. To actively deal with the ICI, the emerging wireless communication standard advocates the concept of interference-aware multicell coordination. Known as coordinated multipoint transmission/reception (CoMP), the new paradigm allows the multicell system to actively control and even take advantage of the ICI. The objective of this research is to study the precoding perspectives in the multiuser multicell system with CoMP. Specifically, this research examines various precoding techniques and develops low-complexity and distributed algorithms in designing optimal precoders that either minimize the transmit power or maximize the sum-rate of the CoMP systems. In addition, this research brings new perspectives and understanding to the CoMP system where the interactions among the coordinated BSs are characterized under two operating modes: interference aware (IA) and interference coordination (IC). Under the IA mode, the multicell system is said to be in competition where each BS selfishly adapts its precoding strategies accordingly to the ICI. Naturally, the IA mode represents a strategic noncooperative game (SNG) with the BSs being the rational players, who try to maximize a certain utility for their connected MSs. This work characterizes the SNG played among the BSs by examining the existence and uniqueness of a stable operating point of the system, which is corresponding to a Nash equilibrium (NE) of the multicell game. The convergence to the NE and its efficiency are then thoroughly analyzed.Under the IC mode, the multicell systems are said to be in coordination where the transmissions from the BSs are coordinated to jointly maximize the performance gain of CoMP. Optimality and distributed implementation are key considerations for the precoding designs under the IC mode. In this work, we propose multicell precoding designs that jointly maximize the weighted sum-rate (WSR) of the coordinated multicell system. Due to the nonconvexity of the WSR optimization problems, we focus on the development of low-complexity convex approximation techniques to decompose them into a sequence of simpler convex problems, which can be solved distributively with local processing at each coordinated cell. Simulation results show significant performance improvements in terms of transmit power and achievable sum-rate by the IC mode over the IA mode. %%%%Dans un systeme multicellulaire, la reutilisation universelle des frequences peut etre utilisee dans un reseau de cellules voisines pour une efficacite spectrale superieure. Cependant, la reutilisation universelle des frequences provoque de l'interference intercellulaire (ICI) severe, qui peuvent nuire a la performance globale du systeme, en particulier dans les…
Frame-based matching algorithms for input-queued switches

We focus on input-buffered packet switches, which are traditionally controlled slot-by-slot with heuristic approximations (such as iSLIP) of maximum weight or size matching algorithms. We consider instead a frame-based control strategy, in which f slots are grouped in a frame, and contentions are solved only at frame boundaries. A number of frame-based heuristics is described, and simulation is used to show that our approach provides performance advantages over a slot-by-slot control in a number of traffic scenarios.
Verification-driven design and programming of autonomous robots

This thesis describes a new agent-based architecture called the Limited Instruction Set Agent (LISA). Agent-based systems are a popular approach to the implementation of autonomous behaviour, and they usually consist of a ‘reasoning’ module that commands lower level subsystems that in turn interact with the environment. When an autonomous system is placed in any environment, the correctness of the software must be guaranteed for safety. This is generally done with ‘verification by model checking’ which consists of creating a model, which represents the system and its interaction with the environment, and then proving specifications using the model. Most agent frameworks to date do not contemplate verification as a design feature and they generally share a few drawbacks: the generation of a model that can be verified by a model checking software is either done manually or by executing the agent code recursively and exploring every possible path to list the state space of the system. The LISA system is based on existing agent-based architectures and it is designed to be structurally simpler than its predecessors with the aim of facilitating the verification process. The agent program of LISA is enriched with structures that allow to model the probabilistic nature of environmental events, so that they can be taken into account in the verification process. The LISA program can be automatically translated to a verifiable probabilistic model suitable for verification with existing software tools such as PRISM. Furthermore, the system is structured to minimise the size of its probabilistic model, and ultimately offers a faster verification process. The thesis contains a number of theoretical contributions to the LISA programming system, including run-time verification for prediction of future outcomes of actions, and the new methods are illustrated on the programming and simulation with an example of autonomous surface vehicle for sea mine detection and disposal.
Virtual Small Group Dynamics:a Quantitative Experimental Framework

We present a research framework consisting of a standard chat environment and a set of analytical tools, able to detect some relevant characteristics of the group dynamics of interacting people. The analysis is independent of the semantic content of the exchanged messages, and the standardized interface avoids hard-to-detect non-verbal communications, still providing the expression of emotional contents. This study proposes a quantitative approach to the investigation of the cognitive small group dynamics, considering the personal representation of the others, and communication dynamics. We developed a framework for the analysis that merges the complex network theory with concepts from social psychology and sociophysics. The focus of the framework is a quantitative investigation of how people explore and build their cognitive representation of the social space. Moreover two different experimental tasks have been proposed in order to investigate the role of some ecological constraints on the cognitive heuristics used by the subjects. The results show how people behave differently with respect to the task they are facing. In particular the absolute and the relative frequencies of the messages and their qualitative aspects significantly differ between the two conditions, as so as the cognitive strategies used by subjects to assess the affinity with the others. Keywords-Virtual Dynamics; Small Group; Social Psychology; Complex Systems
Middle History of Logic Programming: Resolution, Planner, Prolog and the Japanese Fifth Generation Project

Logic Programming can be broadly defined as “using logic to infer computational steps from existing propositions” (although this has been opposed by Kowalski; see below). The focus of this article is on the development of this idea. Consequently, it does not treat any other associated topics related to Logic Programming such as constraints, abduction, etc. The idea has a long development that went through many twists in which important questions turned out to have surprising answers including the following:  Is computation reducible to logic?  Did Logic Programming contribute to the failure of the Japanese Fifth Generation Project (ICOT)?  What is Logic Programming?
Alleviating manual feature engineering for part-of-speech tagging of Twitter microposts using distributed word representations

Many algorithms for natural language processing rely on manual feature engineering. In this paper, we show that we can achieve state-of-the-art performance for part-of-speech tagging of Twitter microposts by solely relying on automatically inferred word embeddings as features and a neural network. By pre-training the neural network with large amounts of automatically labeled Twitter microposts to initialize the weights, we achieve a state-of-the-art accuracy of 88.9% when tagging Twitter microposts with Penn Treebank tags.
Self-paced BCI with NIRS based on speech activity

To enable Brain Computer Interfaces (BCIs) to be used intuitively, they should use an input paradigm which is as natural as possible, while the usage of the device is as convenient as possible. In this study, we show that functional near infrared spectroscopy (fNIRS) signals can be used to automatically detect the user’s intent to use the system by detecting asynchronous speech activity, which is a very natural form of communication. Thereby, we take a first step towards self-paced BCIs with fNIRS based on speech activity.
Vibrométrie holographique multipoint. Dimensionnement, limites et applications

In the vibro-acoustics field, Laser Doppler Velocimetry (LDV) is the most used tool for investigating dynamic measurements. The main drawback of LDV is that it can provide dynamic data at only a particular location of the inspected surface. Scanning techniques are an alternative approach to get full -fi ed measurement, but the object of interest has to be under a perfectly controlled excitation. In order to simultaneously obtain a collection of data points at the surface of the vibrating object, we propose an approach relater to m ultipoint vibrometry, which is based on very high -speed digital holography. The measurement system was designed according to a simulation based design, and this establishes rules for the experimental optimization. The method is experimentally validated and provides 5916 simultaneous measurement points at 50 kHz, which is the best performance of the curre nt state of the art. Application of the method to the int raction between an acoustic wave and a two-dimensional acoustic black hole is described. MOTS-CLÉS : holographie numérique, mesure de phase, bruit dans les systèmes d’imagerie, image interférometrique, technique de reconstruction d’image, analyse vibr atoire.
MATHEMATICS TEACHER'S SPECIALIZED KNOWLEDGE. REFLECTIONS BASED ON SPECIFIC DESCRIPTORS OF KNOWLEDGE

We present some reflections on mathematical knowledge for teaching arising from the descriptors proposed by Sosa (2010) and linked to the model of mathematics teachers’ knowledge constructed by Ball, Thames and Phelps (2008). The former leads us to reflect on the model and to adopt the proposal of Mathematics Teacher's Specialized Knowledge so as to make progress in describing the mathematical knowledge brought into play when teaching. This suggests the need to scrutinise the model carefully and to refine its characterisation. To do so, we embark on a search for evidence which allows the incorporation, integration and interconnection of aspects of knowledge apparently unrelated in the model of Mathematical Knowledge for Teaching (MKT).
Perbandingan Learning Management System Edmodo dan Moodle Dalam Pembelajaran Online

n Abstrak: E-learning adalah proses belajar yang difasilitasi dan didukung melalui pemanfaatan Teknologi Informasi dan Komunikasi. E-learning dapat mengakomodasi sistem pembelajaran yang mengatur peran pengajar, siswa, pemanfaatan sumber belajar, pengelolaan pembelajaran, sistem evaluasi dan monitoring pembelajaran.n Suatu sistem pengelolaan pembelajaran online terintegrasi yaitu Learning Management System (LMS). Dengan Edmodo akan lebih mudah memonitor interkasi siswa dalam Edmodo Learning Environtment. Edmodo dirancang untuk membuat siswa bersemangat belajar dilingkungan yang lebih akrab. Moodle adalah sebuah program aplikasi yang dapat merubah sebuah media pembelajaran kedalam bentuk web. Aplikasi ini memungkinkan siswa untuk masuk kedalam "ruang kelas" digital untuk mengakses materi-materi pembelajaran. Edmodo dan Moodle merupakan pilihan yang sangat tepat untuk digunakan sebagai media pembelajaran online karena terdapat banyak fitur-fitur yang ditawarkan dalam hal mengoptimalkan pembelajaran juga mempermudah kegiatan belajar mengajar antara pengajar dan siswa. n Kata kunci: edmodo, e-learning, learning management system, moodle n Abstract:nE-learning is a learning process that is facilitated and supported through the utilization of Information and Communication Technology. E-learning can accommodate learning systems that regulate the roles of teachers, students, use of learning resources, learning management, evaluation systems and monitoring of learning. Learning Management System (LMS). With Edmodo it will be easier to monitor student interactions in Edmodo Learning Environtment. Edmodo is designed to make students eager to learn in a more familiar environment. Moodle is an application program that can transform a learning medium in web form. This application allows students to enter digital "classroom" to access learning materials. Edmodo and Moodle is an excellent choice to use as an online learning medium because there are many features offered in terms of optimizing learning as well as teaching and learning activities between teachers and students. n Keywords: edmodo,e-learning, learning management system, moodle
Symmetric switched diode multilevel inverter structure with minimised switch count

A new symmetric switched diode multilevel inverter with reduced power switches for medium-voltage applications is presented. The proposed topology consists of several double-source units to produce the synthesised stepped output voltage waveform with reduced total harmonic distortion. The required number of insulated bipolar junction transistors, power diode, and total power losses are compared between conventional and recent topologies. The seven-level output voltage is simulated by using simulation software MATLAB/Simulink, and hardware prototype model has been developed to prove the superiority of the proposed topology. Finally, the advantage of the proposed topology is highlighted, and the topology for high-voltage applications is suggested.
MAXIMIZING AND MATCHING ON CONCURRENT RATIO SCHEDULES1

Pigeons on concurrent variable-ratio variable-ratio schedules usually, though not always, maximize reinforcements per response. When the ratios are equal, maximization implies no particular distribution of responses to the two alternatives. When the ratios are unequal, maximization calls for exclusive preference for the smaller ratio. Responding conformed to these requirements for maximizing, which are further shown to be consistent with the conception of reinforcement implicit in the matching law governing relative responding in concurrent interval schedules.
Modelling the structure and dynamics of network-based social systems

The development of policy interventions to enhance the sustainability of our future often depends on the capacity to understand and model relevant social systems and to predict the consequences of policy change. To this end, we describe in this paper a suite of statistical models for the structure and dynamics of network-based social systems. In these models, global network structure is hypothesised to arise as the outcome of dynamic, interactive processes occurring within local neighbourhoods of a network. A hierarchy of such processes and model specifications are described. Models can be estimated from a number of possible data structures, including single or panel observations, and partial data structures obtained through certain types of network sampling schemes. Using several illustrative applications, we describe how the models can be used to extend our understanding of social systems and build theoretically plausible and empirically-grounded simulation models. Advantages of the approach include a capacity to quantify uncertainty and its implications, and the facility to assess the extent to which a model captures features of the social system not parameterized in the model. We conclude with a sketch of future work designed to improve our understanding of ways to enhance sustainability within network-based social systems.
An extended-life sensor networking prototype system

Microsensor networks will be important tools in the creation of the information force, providing remote sensing for operations such as area denial, search and rescue, and MOUT. Many efforts have focused on single elements of the intelligent microsensor network, but this paper presents an approach for complete system development. This approach includes algorithm, protocol, hardware, and prototype development stages leading toward the creation of extended-life sensor network nodes suitable for forward battlefield deployment. The resulting ad-hoc network will provide an intelligent radio communications system that can automatically self-configure into a network upon deployment in the field and which can support a variety of sensors. Finally we discuss some of the algorithms necessary to implement a complete system, including distributed discovery, routing and network configuration.
The Role of Salience in Second Language Acquisition

iii CHAPTER 1: INTRODUCTION.1 The Competition Model. 1 Cue Conflict Resolution. 5 The Shallow Structure Hypothesis (SSH). 6 Summary of Models and Implications for Language Learning. 7 Implicit Learning and Language Acquisition.7 The Competition Model as a Framework for Language Learning. 8 The Present Study. 9 CHAPTER 2: EXPERIMENT 1. 12 Method. 12 Results. 18 Discussion. 33 CHAPTER 3: EXPERIMENT 2. 35 Method. 36 Results. 36 Discussion. 48 Cross-Experimental Comparison. 48 CHAPTER 4: GENERAL DISCUSSION.52 The Competition Model Versus The Shallow Structure Hypothesis. 55 Applications of VIE. 57 Conclusion. 58 REFERENCES. 59 VITA.62
Consistency model for collaborative software development on cloud

Consistency preservation is an important problem in collaborative system that is activated in both traditional distributed systems a nd cloud based systems for availability and performance. Especially, cloud sto rage services still need to improve the consistency guarantees in client centri c approach. This paper describes a consistency model for constructing coll ab rative software development on cloud that intends to evaluate the e ffectiveness of the system by using Monotonic Write Consistency and Vector clock timestamp algorithm are applied to control the collaborative work on cloud in order to provide the time management. We discuss the effectiveness of our app o ches compared to normal process and process with consistency model.
Optimizing Flow Rule Installations on SDN based Switches

Traditional network monitoring involving packet capturing or flow sampling has many challenges such as scalability, accuracy and availability of processing resource when networks become large-scale, high-speed and heterogeneous. SDN is a promising approach to address these challenges, in which highly granular flow rule installations can provide us with fine-grained flow based statistic. But each SDN switch has its own capacity limitation, such as its cache memory called TCAM, which can get exhausted with a large number of highly granular flow rule installations. Thus, network nodes need coordination of resources with other network nodes to monitor the network in a scalable manner. This thesis introduces an intelligent framework, called lite-flow, which divides flow rule installations into two parts, monitoring and forwarding flow rules. The proposed system distributes the load of monitoring flows among SDN switches, and makes the scalability and accuracy of network monitoring manageable. Also, we introduce a forwarding mechanism which uses a more abundant L2 cache in SDN switches based on MAC labels.