Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrum optimisation in wireless communication systems : technology evaluation, system design and practical implementation

Two key technology enablers for next generation networks are examined in this thesis, namely Cognitive Radio (CR) and Spectrally Efficient Frequency Division Multiplexing (SEFDM). The first part proposes the use of traffic prediction in CR systems to improve the Quality of Service (QoS) for CR users. A framework is presented which allows CR users to capture a frequency slot in an idle licensed channel occupied by primary users. This is achieved by using CR to sense and select target spectrum bands combined with traffic prediction to determine the optimum channel-sensing order. The latter part of this thesis considers the design, practical implementation and performance evaluation of SEFDM. The key challenge that arises in SEFDM is the self-created interference which complicates the design of receiver architectures. Previous work has focused on the development of sophisticated detection algorithms, however, these suffer from an impractical computational complexity. Consequently, the aim of this work is two-fold; first, to reduce the complexity of existing algorithms to make them better-suited for application in the real world; second, to develop hardware prototypes to assess the feasibility of employing SEFDM in practical systems. The impact of oversampling and fixed-point effects on the performance of SEFDM is initially determined, followed by the design and implementation of linear detection techniques using Field Programmable Gate Arrays (FPGAs). The performance of these FPGA based linear receivers is evaluated in terms of throughput, resource utilisation and Bit Error Rate (BER). Finally, variants of the Sphere Decoding (SD) algorithm are investigated to ameliorate the error performance of SEFDM systems with targeted reduction in complexity. The Fixed SD (FSD) algorithm is implemented on a Digital Signal Processor (DSP) to measure its computational complexity. Modified sorting and decomposition strategies are then applied to this FSD algorithm offering trade-offs between execution speed and BER.
Basic Statistics Using SAS Enterprise Guide:: A Primer

Now it's easy to perform many of the most common statistical techniques when you use the SAS Enterprise Guide point-and-click interface to access the power of SAS. Emphasizing the practical aspects of the analysis, this example-rich guide shows you how to conduct a wide range of statistical analyses without any SAS programming required. One or more real data sets, a brief introduction of the technique, and a clear explanation of the SAS Enterprise Guide output are provided for each analysis. Exercises at the end of each chapter help you consolidate what has been learned. Topics include: Analysis of variance Dealing with categorical data Logistic regression Regression Significance tests Survival analysis And more! This text is ideal for those who want to use SAS to analyze their data, but do not have the time to undertake the considerable amount of learning involved in the programming approach.
Improved Image Fusion for Context Enhancement

A memory reverses the sequence of samples of selected lines of a composite video input signal without separating the color burst and chrominance components of the lines thereby preserving chroma-burst phase integrity of scrambled lines. A burst inserter adds a second color burst component to the normal and reversed sequence lines to preserve the secrecy of the scramble code. A descrambler includes a memory for restoring the sample sequence and removing the extra color burst component.
Semantic Relations in Yahoo! News Search

In this thesis we propose a novel approach were 3 days of raw Yahoo! News search query logs are analyzed to find semantic relations among queries. The analysis is based on two independent contributions. The first use session data extracted from the query logs. By finding the term best describing each session, we get a vocabulary of queries related to that term. Sessions with similar terms are merged to create larger groups of queries with one common term or phrase. The second contribution is the use of temporal correlation to give a measure of frequency variation similarity. Queries that show a similar variation over time have a high chance of either being semantically related or appear in the same situations. These two contributions are then merged into related term groups, based on their session group label and the most prominent term or phrase of the correlation query. With the use of non strict parameter settings on the contribution calculations, a great number of queries are found. With the intersection of the results this leaves high accuracy groups of related queries with a term or phrase as group label. A prototype search application was developed to use the created term groups in a search environment. The groups of queries were converted into a tree structure with their group label as the main node. This navigation tree structure let the user navigate up and down in the tree or click directly on a tree node to view its results. When a users search match one of the generated groups, he or she is presented with the first search results of the trees main node together with its children.
Temporal Information Extraction and Knowledge Base Population

TEMPORAL INFORMATION EXTRACTION AND KNOWLEDGE BASE POPULATION by TAYLOR CASSIDY Advisor: Professor Heng Ji Temporal Information Extraction (TIE) from text plays an important role in many Natural Language Processing and Database applications. Many features of the world are timedependent, and rich temporal knowledge is required for a more complete and precise understanding of the world. In this thesis we address aspects of two core tasks in TIE. First, we provide a new corpus of labeled temporal relations between events and temporal expressions, dense enough to facilitate a change in research directions from relation classification to identification, and present a system designed to address corresponding new challenges. Second, we implement a novel approach for the discovery and aggregation of temporal information about entity-centric fluent relations. I dedicate this thesis to my son.
Bisecting Document Clustering Using Model-Based Methods

Bisecting Document Clustering Using Model-Based Methods Aaron S. Davis Department of Computer Science Master of Science We all have access to large collections of digital text documents, which are useful only if we can make sense of them all and distill important information from them. Good document clustering algorithms that organize such information automatically in meaningful ways can make a difference in how effective we are at using that information. In this paper we use model-based document clustering algorithms as a base for bisecting methods in order to identify increasingly cohesive clusters from larger, more diverse clusters. We specifically use the EM algorithm and Gibbs Sampling on a mixture of multinomials as the base clustering algorithms on three data sets. Additionally, we apply a refinement step, using EM, to the final output of each clustering technique. Our results show improved agreement with human annotated document classes when compared to the existing base clustering algorithms, with marked improvement in two out of three data sets.
Effects of Alternative Student Performance Graphing Procedures on Achievement.

ABSTRACT This meta-analysis investigates the effects on achievement of type of graphing paper employed in displaying student performance data collected over tivlb. Ongoing curriculum-based measurement syslams employing Data-Based Program Development (DBPD) provide a data source of 16 controlled studies with 17 effect sizes. A total of 3,494 subjects participated in these studies, with 81 percent of the investigations employing handicapped subjects. The average weighted unbiased effect sizes for six-cycle and equal interval paper, respectively, were . 65 and . 46. Hedges' analogue to analysis of variance indicated this difference was not statistically reliable. This study provides a basis for two conclusions: (1) the existing data base concerning methods for displaying student performance data indicates that type of graphing method does not affect student achievement reliably; and (2) this meta-analysis highlights the need for components of DBPD, including graphing conventions, to be contrasted within the context of controlled experimental investigations. Comparisons of DBPD components within controlled experimental studies should provide important knowledge alma critical elements of ongoing monitoring systems for effective development of individualized instructional programs. Implications for special education practice are discussed. in appendix lists the reports included in the meta-analysis. (Maher/PM)
TVPD : un jeu de données pour évaluer les algorithmes d'estimation de points de fuite

Nous presentons a travers cet article un nouveau jeu de donnees comprenant un corpus de photos de scenes dites de Manhattan prises avec un iPad Air 1. Ce jeu de donnees permet d'evaluer des algorithmes d'estimation de points de fuite. A la difference des jeux de donnees existants, des donnees inertielles issues des differents capteurs de l'iPad, synchronisees avec la camera sont egalement presentes. Ces donnees inertielles peuvent etre utilisees pour ameliorer les performances d'un algorithme d'estimation de points de fuite. Enfin, nous presentons un nouvel algorithme d'estimation de regions d'incertitude sur les points de fuite estimes a partir des segments verites-terrain.
XLMS: A Linguistic Memory System,

Abstract : LMS ('Linguistic Memory System') is a knowledge representation formalism particularly designed for representing knowledge that can be straightforwardly expressed in natural language. Fundamentally, it is a semantic network formalism, a formalism for managing interconnected objects in a highly-organized, network-like memory. XLMS is a particular LISP-based implementation of LMS, intended primarily for experimental use. (Author)
Bitki Doku Kültürü Yöntemleri İle Sekonder Metabolitlerin Üretimi

Genis kapsamli kullanim alanina sahip olan sekonder metabolitlerin dogal kosullar altinda bitkilerden elde edilmesi sirasinda cesitli zorluklarla karsilasilmaktadir. Karsilasilan baslica sorunlar; dogal floraki bitkilerin toplanmasinin zor ve pahali olmasi, bitkilerin dogadan surekli toplanmasi sonunda nesillerinin zamanla yok olmasi, sekonder metabolit miktar ve kalitesinin iklimsel kosullardan etkilenmesi, etkili maddelerin bitkilerde belli gelisim evrelerinde ve cok az miktarda sentezlenmeleri, bitkilerin kulture alinmalarinda basarinin dusuk olusu, ekonomik miktarlarda etkili madde uretimi icin genis tarim alanlarina ihtiyac duyulmasi olarak ozetlenebilir. Bu ve benzer nedenlerle sinirli olan uretim, tuketici isteklerinin degismesi ile birlikte dogal maddelerin kullanimindaki talep artisini yeterli duzeyde karsilayamamaktadir. Tum bu problemlerin onune gecmek icin sekonder metabolitlerin uretiminde biyoteknolojik yontemler, ozellikle bitki hucre ve doku kulturleri alternatif bir yontem olarak gorulmektedir. Farkli in vitro uygulamalar, sekonder metabolitlerin biyosentez ve birikiminin artirilmasi icin kullanilmaktadir. Bu derlemede, bitki hucre ve doku kulturleri yoluyla sekonder metabolitlerin uretiminde kullanilan sistemler ve uretimin artirilmasini saglayan uygulamalar hakkinda bilgi verilmistir.
Statistical Concepts: A Second Course for Education and the Behavioral Sciences

A Review of Simple Linear Regression Multiple Regression One-Factor Analysis of Variance - Fixed-Effects Model Multiple Comparison Procedures Factorial Analysis of Variance - Fixed-Effects Model Random- and Mixed-Effects Analysis of Variance Models Hierarchical and Randomized Block Analysis of Variance Models Introduction to Analysis of Covariance - the One-Factor Fixed-Effects Model With a Single Covariate Introduction to Multivariate Analysis. Appendix: Statistical Tables.
Applied Iterative Methods

Applied Iterative Methods is a self-contained treatise suitable as both a reference and a graduate-level textbook in the area of iterative algorithms. It is the first book to combine subjects such as optimization, convex analysis, and approximation theory and organize them around a detailed and mathematically sound treatment of iterative algorithms. Such algorithms are used in solving problems in a diverse area of applications, most notably in medical imaging such as emission and transmission tomography and magnetic-resonance imaging, as well as in intensity-modulated radiation therapy. Other applications, which lie outside of medicine, are remote sensing and hyperspectral imaging. This book details a great number of different iterative algorithms that are universally applicable.
Spreading of aqueous liquids in unsized papers is by film flow

Nous utilisons le cryo-microscope electronique a balayage pour visualiser la penetration des fluides mouillants dans divers papiers kraft blanchis de resineux. Les resultats indiquent que le mouvement du fluide est attribuable principalement au fluide mouillant sous forme de pellicule liquide le long des canaux formes par le chevauchement des fibres, ce qui vient a l'encontre de la description courante de la penetration du fluide, ou le mecanisme de debit primaire est base sur le remplissage global des pores. Les canaux formes par le chevauchement des fibres forment un reseau dense et interconnecte de voies de circulation transportant efficacement le fluide mouillant. Nous calculons le debit associe a la penetration le long d'un certain nombre de canaux unidirectionnels potentiels dans la feuille fibreuse. Le taux de penetration observe en laboratoire est conforme au debit d'une pellicule dans des canaux interfibres qui est significativement inferieur a un processus de penetration domine par un menisque unidirectionnel dans les pores.
A Mono- and Multi-objective Approach for Recommending Software Refactoring

Software systems have become prevalent and important in our society. There is a constant need for high-quality software. Hence, to improve software quality, one of the most-used techniques is the refactoring which improves design structure while preserving the external behavior. Refactoring has promised, if applied well, to improve software readability, maintainability and extendibility while increasing the speed at which programmers can write and maintain their code. In general, refactoring can be performed in various levels such as the requirement, design, or code level. In this thesis, we mainly focus on the source code level where automated refactoring recommendation can be performed through two main steps: 1) detection of code fragments that need to be improved/fixed (e.g., codesmells), and 2) identification of refactoring solutions to achieve this goal. For the code-smells identification step, we translate regularities that can be found in such code-smell examples into detection rules. To this end, we use genetic programming to automatically generate detection rules from examples of code-smells. For the refactoring identification step, a search-based approach is used. The process aims at finding the optimal sequence of refactoring operations that improve software quality by minimizing the number of detected code-smells while prioritizing the most critical ones. In addition, we explore other objectives to optimize using a multi-objective approach: the code changes needed to apply refactorings, semantics preservation, and the consistency with development change history. Hence, reducing code changes allows us to keep as much as possible the initial design. On the other hand, semantics preservation insures that the refactored program is semantically coherent, and that it models correctly the domain-semantics. Indeed, we use knowledge from historical code change to suggest new refactorings in similar contexts. Furthermore, we introduce a novel multi-objective approach to improve software quality attributes (i.e., flexibility, maintainability, etc.), fix “bad” design practices (i.e., code-smells) while promoting “good” design practices (i.e., design patterns).
On-Campus E-Mail for Communicative Writing

This paper documents some pilot projects using on-campus e-mail to teach communicative English writing to Japanese junior college students. The purpose of this case study is to find how on-campus e-mail can be effectively implemented in order to motivate students to write more communicatively in English. The projects have been carried out in three stages; (1) a preparation period, (2) a pilot project with a small group of students, and (3) writing activities in two courses in larger classrooms with two formats, one with e-mail format, and another with the combination of paper and e-mail formats. This study will report what kind of activities can be provided and which media can be utilized in order to teach communicative writing effectively to various groups of students. The paper will also discuss the benefits of using e-mail for the language teacher, such as obtaining necessary data on student writing, and giving instructive feedback to the students more promptly.
Analysis and Visualization of metabolic syndrome trends using SOM

: Recently metabotic s.vndeome has becon? e a mcu'or concern to health. Mday ofthe youth have fallen vic'tim qf' these s. )'ncb'ome or retated consequences. Sle4f! onganizing mops (SOop can be vieived as a visttalization tool that peiJ12)rms a sort oj' cotnpromise henveen a high-dimensional dutaset and a nvo-dimensionaiplane. T7iis paper giL,es an oveivievv', analysis and visualization of'the ,sp,ndrome using SOMwith a view to understanding its trendg and inter-re/ating other risk.factors that have no retation with the syndrome . vet having a very big c'ontribution to the syndrome and hence overall health risk.
Hardware/Firmware Interface Design: Best Practices for Improving Embedded Systems Development

Why care about hardware/firmware interaction? These interfaces are critical, a solid hardware design married with adaptive firmware can access all the capabilities of an application and overcome limitations caused by poor communication. For the first time, a book has come along that will help hardware engineers and firmware engineers work together to mitigate or eliminate problems that occur when hardware and firmware are not optimally compatible. Solving these issues will save time and money, getting products to market sooner to create more revenue.The principles and best practices presented in this book will prove to be a valuable resource for both hardware and firmware engineers. Topics include register layout, interrupts, timing and performance, aborts, and errors. Real world cases studies will help to solidify the principles and best practicies with an aim towards cleaner designs, shorter schedules, and better implementation! Reduce product development delays with the best practices in this bookConcepts apply to ASICs, ASSPs, SoCs, and FPGAsReal-world examples and case studies highlight the good and bad of design processes
A comparison of ontology servers

Recently, an ontology is increasingly becoming an essential tool for solving problems in many research areas. The ontology is a complex information object. It is used in practice and can contain millions of concepts in complex relationship. When we want to manage complex information objects, we generally turn to information systems technology. There are many tens of millions of information systems in use around the world doing many things ranging from helping a business manage its billing to keeping track of the design and parts inventory of large aircraft. An information system intended to manage ontology is called an ontology server. The ontology server technology is at the time of writing quite immature. Therefore, in this paper, we necessarily try to remain somewhat speculative in nature by reviewing several ontology servers in mainstream literatures. As a result, we point out some important opportunities that would trigger several research questions related to the server technology.
Train delay evolution as a stochastic process

In this paper we present a method for modelling uncertainty of train delays based on a Markov stochastic process. The dynamics of a train delay over time and space is presented as a stochastic process that describes the evolution of the time-dependent random variable. Probability distribution of an arrival delay in a station changes over time in discrete steps as more information becomes available. We consider and compare the results and computational requirements of two discrete state space formulations. Moreover, we test the applicability of modelling train delays as a non-stationary Markov chain, meaning that the probability of a state change depends on the moment of transition. The model is applied on a set of historical traffic realisation data from the part of the high-speed corridor between Beijing and Shanghai. We analyse the accuracy of predictions as well as the evolution of probability distributions of all events over time. The presented method is important for making better predictions for train traffic, that are not only based on static, offline collected data, but are able to positively include the dynamic characteristics of the ever-changing delays, thus increasing the reliability of prediction by 71%.
Synthesis and characterization of π-extended porphyrins as potential precursors for the formation of columnar mesophases: Design principles for columnar mesophases need revision?

A series of meso-β bridged extended porphyrins substituted with long aliphatic chains were synthesized and fully characterized. Two different synthetic strategies were tested to obtain the target structures. The synthetic steps were optimized in order to obtain scalable routes for the production of sufficient quantities of π-extended porphyrins for material science studies. The porphyrins were obtained either as free bases or complexed with Ni II or Cu II . UV-Vis spectroscopy and polarized light microscopy was used for the analysis of the material properties of the π-extended porphyrins. The results obtained with our compounds are not compatible with the results reported in the literature.
Computer Vision Classification of Leaves from Swedish Trees

The aim of this master thesis is to classify the tree class from an image of a leaf with a computer vision classiffication system. We compare different descriptors that will describe the leaves different features. We will also look at different classiffication models and combine them with the descriptors to build a system hat could classify the different tree classes.
A Simple, Intuitive Hypermedia Synchronization Model and its Realization in the Browser/Java Environment

This paper presents a simple and intuitive hypermedia synchronization model – the Media Relation Graph (MRG), and an alternative implementation of the Hypermedia Presentation and Authoring System (HPAS), which is the testbed for MRG. Our model combines the power of both interval-based and point-based synchronization mechanisms. The new implementation exploits many rich features of commercial web browsers and reuses existing browser components, such as plugins and Java applets. (An overview of HPAS and its original Unix/C implementation can be found elsewhere [18].)