Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical Classification and its Application in University Search

Web search engines have been adopted by most universities fo r searching webpages in their own domains. Basically, a user sends keywords to the search e ngine and the search engine returns a flat ranked list of webpages. However, in universit y search, user queries are usually related to topics. Simple keyword queries are often insu fficient to express topics as keywords. On the other hand, most E-commerce sites allow users to brows e and search products in various hierarchies. It would be ideal if hierarchical browsing and keyword search can be seamlessly combined for university search engines. The main di fficulty is to automatically classify and rank a massive number of webpages into the topic hierarchies for universities. In this thesis, we use machine learning and data mining techn iques to build a novel hybrid search engine with integrated hierarchies for universitie s, called SEEU ( SearchEngine with hiErarchy forUniversities). Firstly, we study the problem of e ff ctive hierarchical webpage classification. We develop a parallel webpage classification system based on Support Ve ctor Machines. With extensive experiments on the well-known ODP (Open Directory Project) da aset, we empirically demonstrate that our hierarchical classification system is very e ffective and outperforms the traditional flat classification approaches significantly. Secondly, we study the problem of integrating hierarchical cl ssification into the ranking system of keywords-based search engines. We propose a novel ranking framework, called ERIC (EnhancedRanking by hIerarchicalClassification), for search engines with hierarchies. Experimental results on four large-scale TREC (Text REtrie val Conference) web search datasets show that our ranking system with hierarchical classificati on outperforms the traditional flat keywords-based search methods significantly. Thirdly, we propose a novel active learning framework to imp rove the performance of hierarchical classification, which is important for ranking w ebpages in hierarchies. From our experiments on the benchmark text datasets, we find that our a ctive learning framework can achieve good classification performance yet save a consider able number of labeling e ffort compared with the state-of-the-art active learning methods fo r hierarchical text classification. Fourthly, based on the proposed classification and ranking m ethods, we present a novel hierarchical classification framework for mining academic topics from university webpages. We build an academic topic hierarchy based on the commonly ac cepted Wikipedia academic disciplines. Based on this hierarchy, we train a hierarchic al classifier and apply it to mine academic topics. According to our comprehensive analysis, the academic topics mined by our method are reasonable and consistent with the real-world to pic distribution in universities. Finally, we combine all the proposed techniques together an d implement the SEEU search engine. According to two usability studies conducted in the ECE and the CS departments at
Parallel solution of power system linear equations

At the heart of many power system computations lies the solution of a large sparse set of linear equations. These equations arise from the modelling of the network and are the cause of a computational bottleneck in power system analysis applications. Efficient sequential techniques have been developed to solve these equations but the solution is still too slow for applications such as real-time dynamic simulation and on-line security analysis. Parallel computing techniques have been explored in the attempt to find faster solutions but the methods developed to date have not efficiently exploited the full power of parallel processing. This thesis considers the solution of the linear network equations encountered in power system computations. Based on the insight provided by the elimination tree, it is proposed that a novel matrix structure is adopted to allow the exploitation of parallelism which exists within the cutset of a typical parallel solution. Using this matrix structure it is possible to reduce the size of the sequential part of the problem and to increase the speed and efficiency of typical LU-based parallel solution. A method for transforming the admittance matrix into the required form is presented along with network partitioning and load balancing techniques. Sequential solution techniques are considered and existing parallel methods are surveyed to determine their strengths and weaknesses. Combining the benefits of existing solutions with the new matrix structure allows an improved LU-based parallel solution to be derived. A simulation of the improved LU solution is used to show the improvements in performance over a standard LU-based solution that result from the adoption of the new techniques. The results of a multiprocessor implementation of the method are presented and the new method is shown to have a better performance than existing methods for distributed memory multiprocessors.
L'abri sous roche Cadet 3 (Marie-Galante) : un gisement à accumulations de faune et à vestiges archéologiques

Ce petit abri sous-roche, immediatement voisin de la Grotte Cadet 2, a fait l’objet en 2004 d’un sondage de reconnaissance de 2 m2. L’investigation a revele un remplissage sedimentaire d’une epaisseur de 1,20 m. Les sediments sont pieges dans le site apres qu’une serie de blocs accumules au sommet du prisme de depots de pente ait barre l’entree de la cavite. Les colluvions se sont ainsi accumulees depuis la fin du Pleistocene et au cours de l’Holocene. La stratigraphie est constituee, dans sa partie inferieure, par des depots phosphates riches en restes de faune vertebree, de gasteropodes pulmones et de crustaces terrestres. La base de ce niveau a ete datee autour de 13 800 av. J.-C. La partie superieure de la serie a livre les traces d’une occupation du Neoindien recent datee autour de 980 ap. J.-C. puis des vestiges d’epoque historique. Ce gisement a thanatocenoses en cavite constitue, grâce a son etude pluri-disciplinaire, un premier referentiel en Guadeloupe. L’ensemble des niveaux a livre pres d’une cinquantaine de taxons dont certains sont absents aujourd’hui de l’archipel guadeloupeen. La sequence stratigraphique revele donc l’Histoire de ce peuplement et de l’anthropisation des milieux. En effet, les couches profondes ont fourni une grande diversite de petite faune mammalienne (uniquement Chiropteres), aviaire, sauriennne et amphibienne. Cette faune a ete remplacee au cours des temps precolombiens par des especes de plus grande taille (rats des rizieres, agoutis et iguanes, par exemple) et les especes natives de Vertebres vont diminuer, ce qui est probablement du a une anthropisation des milieux, alors que les Crustaces et les Gasteropodes prendront une part de plus en plus consequente. Enfin, les couches superficielles, correspondant a des niveaux post-colombiens illustrent une disparition presque brutale de l’utilisation de la cavite par les petites faunes natives de l’ile et une chute drastique de la biodiversite des Vertebres. En revanche, les taxons domestiques (cochons, caprines et rats de l’ancien monde) ont alors constitue l’essentiel de la taphocenose de l’abri.
The Cambridge CAP computer and its operating system (Operating and programming systems series)

The need for hardware memory protection was first met when operating systems which permitted the running of users’ programs written in a variety of languages, including assembly language, came into use. One early system, the CTSS, had a separate memory to hold the supervisor and this memory could be accessed only when the computer was in privileged mode. More flexibility in the use of available memory space is required and it is now common for computers to be provided with a number of base-limit registers, each of which, when appropriately loaded, points to and delimits a segment of memory; when the computer is operating in normal mode only those parts of the memory that lie within segments pointed to by base-limit registers are accessible. Associated with each base-limit register are a few extra bits which define the type of access permitted, for example, read-only, read-write, execute-only, etc. If an attempt is made to access memory outside the permitted limits or to make an access of a forbidden type, the hardware switches the computer to privileged mode and sends control to a place in memory determined by the nature of the violation that has occurred. This type of organisation is illustrated in Figure 1.1, taken from Wilkes (1975), where a fuller discussion of such memory protection systems will be found.
Temporal coherence in the perception of tone sequences [doctoral dissertation

A direct reduction apparatus having a means for briquetting oxide ores of iron, manganese, chrome, and copper, with a powdered coal tar pitch, means for caramelizing (hardening) the briquettes for ease of handling, subjecting the caramelized briquettes to a first temperature source until said briquettes are partially reduced to conductivity, their dimensions are substantially reduced and subsequently reducing said briquettes by subjecting them to a frequency electric induction induced heat source.
The Effects of Computer Graphic Organizers on the Persuasive Writing of Hispanic Middle School Students with Specific Learning Disabilities

A multiple baseline design investigated the effects of computer graphic organizers on the persuasive composition writing skills of four Hispanic students with specific learning disabilities. Participants reviewed the elements of persuasive writing and then developed compositions using a word processing program. Baseline planning was done with a paper and pencil, while intervention planning was done using a computer graphic organizer program. With variation, the use of computer graphic organizers during planning resulted in an increase in the total number of words written, time spent planning, number of supporting details planned, percentage of planned supporting details transferred to the composition, and syntactical maturity as measured by the number of T-units. Also observed was an improvement in the overall organization of the compositions as measured by an analytical scoring guide or rubric.
Beyond Methods: Macrostrategies for Language Teaching

In this work, B. Kumaravadivelu presents a macrostrategic framework designed to help both beginning and experienced language teachers develop a systematic, coherent and personal theory of practice. His book offers to provide the tools a teacher needs in order to self-observe, self-analyze, and self-evaluate his or her own teaching acts. The framework consists of ten macrostrategies based on current theoretical, empirical and experiential knowledge of second language and foreign language teaching. These strategies enable teachers to evaluate classroom practices and to generate techniques and activities for realizing teaching goals. With checklists, surveys, projects and reflective tasks to encourage critical thinking, the book is designed to be both practical and accessible.
Applications of nonuniform sampling in wideband multichannel communication systems

This research is an investigation into utilising randomised sampling in communication systems to ease the sampling rate requirements of digitally processing narrowband signals residing within a wide range of overseen frequencies. By harnessing the aliasing suppression capabilities of such sampling schemes, it is shown that certain processing tasks, namely spectrum sensing, can be performed at significantly low sampling rates compared to those demanded by uniform-sampling-based digital signal processing. The latter imposes sampling frequencies of at least twice the monitored bandwidth regardless of the spectral activity within. Aliasing can otherwise result in irresolvable processing problems, as the spectral support of the present signal is a priori unknown. Lower sampling rates exploit the processing module(s) resources (such as power) more efficiently and avoid the possible need for premium specialised high-cost DSP, especially if the handled bandwidth is considerably wide. A number of randomised sampling schemes are examined and appropriate spectral analysis tools are used to furnish their salient features. The adopted periodogram-type estimators are tailored to each of the schemes and their statistical characteristics are assessed for stationary, and cyclostationary signals. Their ability to alleviate the bandwidth limitation of uniform sampling is demonstrated and the smeared-aliasing defect that accompanies randomised sampling is also quantified. In employing the aforementioned analysis tools a novel wideband spectrum sensing approach is introduced. It permits the simultaneous sensing of a number of nonoverlapping spectral subbands constituting a wide range of monitored frequencies. The operational sampling rates of the sensing procedure are not limited or dictated by the overseen bandwidth antithetical to uniform-sampling-based techniques. Prescriptive guidelines are developed to ensure that the proposed technique satisfies certain detection probabilities predefined by the user. These recommendations address the trade-off between the required sampling rate and the length of the signal observation window (sensing time) in a given scenario. Various aspects of the introduced multiband spectrum sensing approach are investigated and its applicability highlighted.
Rencontre : an experimental tool for electronic literature

For several years, the Paragraph Laboratory, University of Paris 8, has explored new avenues in the field of digital art and literature. In that context, a project is currently ongoing in this lab, in collaboration with the University of Technology of Compiegne and the University of Geneva, supported by the Maison des Sciences de l’Homme Paris Nord. The goal of this project is to design a computer tool for the writing of nonlinear fictions for interactive media and to investigate its impact on both the writing and reading processes.
A Comparative Study of Exact versus Propensity Matching Techniques Using Monte Carlo Simulation.

Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized designs. In such situations, subject matching provides an alternative design approach for conducting causal inference studies. This study examined various design conditions hypothesized to affect matching procedures’ bias recovery ability. The study examined three common social science research scenarios for case matching where discrete, continuous, or both types of covariates are employed. For each scenario, the following hypothesized factors were arranged experimentally in a factorial design: (a) bias amount, (b) effect size (ES), (c) covariance among the covariates (CV), and (d) correlation (CR) between the bias amount and the covariate group. Within these between group factors, six matching methods (MM) (random sampling, exact matching, propensity score matching, nearest neighbor matching, radius matching, and Mahalanobis metric matching) were examined in terms of their ability to minimize the difference
Estimation and Inference in High Dimensional Networks, with Applications to Biological Systems.

This dissertation discusses several aspects of estimation and inference for high dimensional networks, and is divided into three main parts. First, to assess the significance of arbitrary subnetworks (e.g. pathways), I propose a latent variable model that directly incorporates the network information. By formulating the problem as a (generalized) mixed linear model, I introduce a general inference procedure for testing the significance of subnetworks, that can be used to test for changes in both expression levels of the corresponding nodes (e.g. genes), as well as the structure of the network. The framework is then extended for analysis of data obtained from complex experimental designs. We also study the effect of noise in the network information, both theoretically and empirically, and show that the proposed inference procedure is robust to the presence of random noise. In the second part, we consider the problem of estimating directed graphs from observed data. The general problem of estimation of directed graphs is computationally NP-hard and direction of interactions may not be distinguishable from observations. I consider a special case of this problem, where the nodes (i.e. variables) inherit a natural ordering, and propose efficient penalized likelihood methods for estimating the underlying network structure. Consistency of the estimators in the high dimensional setting (more variables than observations) is established. I also propose an extension of the lasso penalty that results in improved estimation of graphical
A two-scale computational strategy including homogenization for highly heterogeneous structures

A new two-scale computational strategy is proposed for the analysis of struc- tures which are described up to the micro level, such as composite structures. The de- scription of micro and macro quantities is performed on the interface, arising from the decomposition of the structure into an assembly of substructures and interfaces. The strategy can be interpreted as a two-level mixed domain decomposition method and then is well-suited to parallel architecture computers. Several numerical examples for composite structures illustrate the possibilities of this method. Comparisons with other computational methods are given.
Replication and Knowledge Production in Empirical Software Engineering Research

Replication and Knowledge Production in Empirical Software Engineering Research Jonathan L. Krein Department of Computer Science, BYU Doctor of Philosophy Although replication is considered an indispensable part of the scientific method in software engineering, few replication studies are published each year. The rate of replication, however, is not surprising given that replication theory in software engineering is immature. Not only are replication taxonomies varied and difficult to reconcile, but opinions on the role of replication contradict. In general, we have no clear sense of how to build knowledge via replication, particularly given the practical realities of our research field. Consequently, most replications in software engineering yield little useful information. In particular, the vast majority of external replications (i.e., replications performed by researchers unaffiliated with the original study) not only fail to reproduce the original results, but defy explanation. The net effect is that, as a research field, we consistently fail to produce usable (i.e., transferable) knowledge, and thus, our research results have little if any impact on industry. In this dissertation, we dissect the problem of replication into four primary concerns: 1) rate and explicitness of replication; 2) theoretical foundations of replication; 3) tractability of methods for context analysis; and 4) effectiveness of inter-study communication. We address each of the four concerns via a two-part research strategy involving both a theoretical and a practical component. The theoretical component consists of a grounded theory study in which we integrate and then apply external replication theory to problems of replication in empirical software engineering. The theoretical component makes three key contributions to the literature: first, it clarifies the role of replication with respect to the overall process of science; second, it presents a flexible framework for reconciling disparate replication terminology; and third, it informs a broad range of practical replication concerns. The practical component involves a series of replication studies, through which we explore a variety of replication concepts and empirical methods, ultimately culminating in the development of a tractable method for context analysis (TCA). TCA enables the quantitative evaluation of context variables in greater detail, with greater statistical power, and via considerably smaller datasets than previously possible. As we show (via a complex, real-world example), the method ultimately enables the empirically and statistically-grounded reconciliation and generalization of otherwise contradictory results across dissimilar replications—which problem has previously remained unsolved in software engineering.
Causal and Topological Aspects in Special and General Theory of Relativity

In this article we present a review of a geometric and algebraic approach to causal cones and describe cone preserving transformations and their relationship with the causal structure related to special and general relativity. We describe Lie groups, especially matrix Lie groups, homogeneous and symmetric spaces and causal cones and certain implications of these concepts in special and general relativity, related to causal structure and topology of space-time. We compare and contrast the results on causal relations with those in the literature for general space-times and compare these relations with K-causal maps. We also describe causal orientations and their implications for space-time topology and discuss some more topologies on space-time which arise as an application of domain theory. For the sake of completeness, we reproduce proofs of certain theorems which we proved in our earlier work.
Temporal dynamics of early brain activity explored using EEG and computational models

This thesis considers the temporal structure of burst dynamics in early brain activity through the analysis of human very preterm electroencephalograph (EEG) recordings and computational neural network models. A novel algorithm for the detection of the discontinuous bursts of activity in the preterm EEG is developed and the temporal structure of burst occurrence, size and duration are assessed. The dynamics are shown to exhibit long-range temporal correlations (LRTCs) indicating a temporal complexity within early brain activity not previously appreciated. This result is replicated in a larger population of preterm children and the effect of gestational age and postnatal age on the degree of LRTCs is examined. A possible mechanism underlying the generation of burst activity that exhibits LRTCs is investigated in a stochastic excitatory neural network model. It is shown that burst dynamics occur in the model when there is a balance between the activity of an individual neuron and the number of neurons it in turn activates. Furthermore, it is shown that correlations in the temporal statistics of these bursts exist over a wide range and extend across an infinite range in the limit of system size. The behaviour of the model with respect to different network topologies is also investigated. In summary, it is shown that complex temporal dynamics exist even in early brain activity and such dynamics can be observed in a simple model. In light of this, the evidence that the brain exhibits self-organised criticality - a theoretical framework suggested by previous authors as an explanation for LRTCs in a systems dynamics - is discussed. Overall, the observation of complex temporal structure of activity in the early developing brain suggests that the temporal organisation of this activity may play an important developmental role. This thesis therefore provides strong motivation for future work in this area.