Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-LingualLexical Triggers in Statistical LanguageModeling

We proposenew methodsto take advantage of text in resource-richlanguages to sharpenstatisticallanguagemodelsin resource-deficient languages.We achieve this throughan extensionof the method of lexical triggers to the cross-language problem,andby developinga likelihoodbasedadaptationschemefor combining a trigger model with an -gram model. We describethe applicationof suchlanguagemodelsfor automaticspeechrecognition. By exploitingaside-corpusof contemporaneousEnglish news articles for adaptinga staticChineselanguagemodel to transcribeMandarinnews stories,we demonstratesignificantreductionsin both perplexity and recognition errors. We alsocompareour cross-lingualadaptation schemeto monolingual languagemodel adaptation, andto analternatemethodfor exploiting cross-lingualcues, via crosslingual informationretrieval andmachine translation,proposedelsewhere. 1 Data Sparsenessin LanguageModeling Statistical techniqueshave been remarkablysuccessfulin automaticspeechrecognition(ASR) and naturallanguageprocessing(NLP) over thelasttwo decades.This success, however, dependscrucially Thisresearchwassupportedby theNationalScienceFoundation(via GrantNo ̄ ITR-0225656andIIS-9982329)andthe Officeof Naval Research(via ContractNo ̄ N00014-01-1-0685). on the availability of accurateand large amounts of suitablyannotatedtrainingdataandit is difficult to build a usablestatisticalmodel in their absence. Most of the success, therefore,hasbeenwitnessed in the so called resour ce-rich languages.More recently, therehasbeenan increasinginterestin languagessuchasMandarinandArabic for ASR and NLP, anddataresourcesarebeingcreatedfor them at considerablecost. The data-resourcebottleneck, however, is likely to remainfor a majority of the world’s languagesin theforeseeablefuture. Methodshave beenproposedto bootstrapacoustic modelsfor ASR in resourcedeficientlanguages by reusingacousticmodelsfrom resource-richlanguages(Schultz and Waibel, 1998; Byrne et al., 2000). Morphologicalanalyzers, noun-phrasechunkers, POStaggers,etc., have also beendeveloped for resourcedeficientlanguagesby exploiting translatedor parallel text (Yarowsky et al., 2001). Khudanpur and Kim (2002) recently proposedusing cross-lingualinformationretrieval (CLIR) andmachinetranslation(MT) to improve a statisticallanguagemodel(LM) in a resource-deficient language by exploiting copiousamountsof text available in resource-richlanguages.Whentranscribinga news story in a resource-deficient language,their core ideais to usethefirst passoutputof a rudimentary ASRsystemasaqueryfor CLIR, identify acontemporaneousEnglishdocumentonthatnewstopic,followedby MT to provide a roughtranslationwhich, evenif not fluent,is adequateto updateestimatesof word frequenciesandtheLM vocabulary. They report up to a 28%reductionin perplexity onChinese text from theHongKongNewscorpus. in Natural Language Processing, pp. 17-24. Proceedings of the 2003 Conference on Emprical Methods
A Functional Central Limit Theorem for a Class of Interacting Markov Chain Monte Carlo Methods

We present a functional central limit theorem for a new class of interacting Markov chain Monte Carlo algorithms. These stochastic algorithms have been recently introduced to solve non-linear measure-valued equations. We provide an original theoretical analysis based on semigroup techniques on distribution spaces and fluctuation theorems for self-interacting random fields. Additionally we also present a series of sharp mean error bounds in terms of the semigroup associated with the first order expansion of the limiting measurevalued process. We illustrate our results in the context of Feynman-Kac semigroups. Key-words: Multivariate and functional central limit theorems, random fields, martingale limit theorems, self-interacting Markov chains, Markov chain Monte Carlo methods, Feynman-Kac semigroups. ∗ Centre INRIA de Bordeaux Sud-Ouest & Institut de Mathématiques de Bordeaux , Université de Bordeaux I, 351 cours de la Libération 33405 Talence cedex, France, Bernard.Bercu@math.u-bordeaux1.fr † Centre INRIA de Bordeaux Sud-Ouest & Institut de Mathématiques de Bordeaux , Université de Bordeaux I, 351 cours de la Libération 33405 Talence cedex, France, Pierre.DelMoral@inria.fr ‡ Department of Statistics, University of British Columbia, 333-6356 Agricultural Road, Vancouver, BC, V6T 1Z2, Canada, arnaud@stat.ubc. ca in ria -0 02 27 53 4, v er si on 5 18 J un 2 00 9 Un Théorème de la Limite Centrale Fonctionnel pour une classe de méthodes de Monte Carlo par Châınes de Markov en Interaction Résumé : Nous présentons un théorème de la limite centrale fonctionnel pour une nouvelle classe d’algorithmes de Monte Carlo par châınes de Markov en interaction. Ces algorithmes stochastiques ont été récemment introduits pour résoudre des équations à valeurs mesures non linéaires. Nous développons une analyse théorique originale fondée sur des techniques de semigroupes sur des espaces de distributions associées à des théorèmes de fluctuations de champs aléatoires en auto-interaction. Outre l’analyse des fluctuations de ces modèles, nous présentons une série d’estimations fines des erreurs moyennes en fonction du semigroupe associé à un développement au premier ordre du semigroupe d’évolution du processus limite. Nous illustrons également nos résultats dans le cadre de semigroupes de Feynman-Kac. Mots-clés : Théorèmes de la limite centrale multidimensionnels, champs aléatoires, théorèmes limites de martingales, processus en auto-interaction, méthodes de Monte Carlo par châınes de Markov, semi-groupes de Feynman-Kac in ria -0 02 27 53 4, v er si on 5 18 J un 2 00 9 Fluctuations of a Class of Interacting Markov Chain Monte Carlo Models 3
Ontology Research and Development Part 1 – A Review of Ontology Generation

Ontology is an important emerging discipline that has the huge potential to improve information organization, management and understanding. It has a crucial role to play in enabling content-based access, interoperability, communications, and providing qualitatively new levels of services on the next generation of Web transformation in the form of the Semantic Web. The issues pertaining to ontology generation, mapping and maintenance are critical key areas that need to be understood and addressed. This timely survey is presented in two parts. This first part reviews the state-of-the-art techniques and work done on semiautomatic and automatic ontology generation, as well as the problems facing these researches. The second complimentary survey is dedicated to ontology mapping and ontology evolving. Through this survey, we identified that shallow information extraction and natural language processing techniques are deployed to extract concepts or classes from free-text or semi-structured data. However, relation extraction is a very complex and difficult issue to resolve and it has turned out to be the main impedance to ontology learning and applicability. Further researches are encouraged to find appropriate and efficient ways to detect or identify relations through semi-automatic automatic means.
Considering Student ’ s Emotions in Computer-Mediated Learning Environments

This text aims to present the current state of the art of the e-learning systems that consider the student’s affect. It presents the perspectives adopted by the researchers for the solution of the problems (for example, which kind of tools we might use to recognize users emotions) and also some better-known works in order to exemplify. It a lso describes the necessary background to understand these studies that involves some concept s on Artificial Intelligence, Computer in Education, and Human-Computer Interaction research fields, as also a brief introduction on the main theories about emotion. The authors conclude t he chapter by presenting challenges and the main difficulties of the research in affectivity in e-learning systems and ideas on some new work on the matter.
ExSIDE Working Paper Series

We construct, estimate and explore the monetary policy consequences of a New Keynesian (NK) behavioural model with bounded-rationality and heterogeneous agents. We radically depart from most existing models of this genre in our treatment of bounded rationality and learning. Instead of the usual Euler learning approach, we assume that agents are internally rational (IR) given their beliefs of aggregate states and prices. The model is inhabited by fully rational (RE) and IR agents where the latter use simple heuristic rules to forecast aggregate variables exogenous to their micro-environment. We find that IR results in an NK model with more persistence and a smaller policy space for rule parameters that induce stability and determinacy. In the most general form of the model, agents learn from their forecasting errors by observing and comparing them with those under RE making the composition of the two types endogenous. In a Bayesian estimation with fixed proportions of RE and IR agents and a general heuristic forecasting rule we find that a pure IR model fits the data better than the pure RE case. However, the latter with imperfect rather than the standard perfect information assumption outperforms IR (easily) and RE-IR composites (slightly), but second moment comparisons suggest that the RE-IR composite can match data better. Our findings suggest that Kalman-filtering learning with RE can match bounded-rationality in matching persistence seen in the data. JEL Classification: E03, E12, E32.
SAND 2006-5000 Unlimited Release Printed October 2006 QCS : A System for Querying , Clustering and Summarizing Documents

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system—the Query, Cluster, Summarize (QCS) system—which is portable, modular, and permits experimentation with different instantiations of each of the constituent text
Triaxial test simulation on Erksak sand using hardening soil model

Hardening Soil model (HS) available in numerical computer program Plaxis is widely used in geotechnical practice for modeling both cohesive and noncohesive soils. The basic characteristics of the model are stress dependent stiffness according to a power law, plastic straining due to primary deviatoric loading, plastic straining due to primary compression, elastic unloading/reloading and failure according to the Mohr-Columb model. In this paper parameters of HS model are evaluated for Erksak sand. The triaxial tests database used consists of 15 drained and 31 undrained tests and it covers wide range of sand density and isotropic consolidation pressure. Results of simulations show that relative density has to be accounted for to be able to simulate the sand behavior for different states. Some relationships to relative density are proposed for reference secant stiffness, effective angle of internal friction and angle of dilatancy. Great advantages of HS model, but also some limitations are presented in this paper, both for drained and undrained conditions.
Tracking the Role of Adversaries in Measuring Unwanted Traffic Mark Allman ICSI

Measurements related to security are being carried out on many sites on the Internet at network ingress points, between specific points on the Internet, and across the wide area Internet. The goals range from identifying sources of and possibly filtering unwanted traffic, to characterizing and coming up with new mechanisms for deterring attacks. Most of the measurements do not systematically consider adversarial traffic aimed at their measurement system. We explore the role adversaries can play and present a taxonomy on the potential impact of unwanted traffic on measurement systems. Our goal is to both enhance the robustness of such systems and spur development of tools that can alter the playing field by increasing the cost to adversaries.
Shaping Sectors, Changing Architectures, Constructing Ecosystems

Over the last few years, there has been a growing appreciation that sectors and their structure should not be taken from granted. There has also been a keen interest in the emergence and prominence of particular architectures- ecosystems, often based on platforms, which have come to transform sectors. But, how do ecosystems emerge? And, more broadly, what drives the process of sector-wide transformation and the change in sector architecture, including, though not limited to, the emergence of ecosystems? This panel consists of presentations of cutting-edge research that looks at the drivers of industry-level change, including ecosystem formation attempts, and considers the mechanisms, drivers and modalities of this process of change in a number of different settings. Some of the leading scholars in their field, and two discussants that offer both depth and breadth will discuss not only four studies, but also the broader research agenda, and the theoretical, phenomenological, and methodological issues that .
The role of formal controls in facilitating information system diffusion

Information systems (IS) studies highlight that IS usage, a pre-requisite for IS diffusion, may be difficult to attain when usage is voluntary because users can resist using the system. User resistance may be overcome through the application of organizational controls. Control theory explains how users’ actions and practices are shaped in line with organizational guidelines and procedures. This paper reports on a qualitative case study and shows how formal control mechanisms (behavior and outcome controls) can have a positive and conclusive impact on IS diffusion. The paper makes three contributions to knowledge. First, it explains how the application of outcome control mechanisms can lead to IS diffusion despite user resistance. Second, it suggests that IS diffusion paths are iterative, rather than smooth and linear. Finally, the paper demonstrates that in some contexts, despite a lack of reward expectancy, sanction expectancy can be an effective force during the IS diffusion process.
The evolution of a transaction processing system

The Arjuna Transaction Service (ATS) began life in the mid 1980s as an academic project (called Arjuna) to examine the use of object-oriented techniques in the development of fault-tolerant systems [1]. It provides a set of tools for the construction of fault-tolerant distributed applications using (nested) transactions controlling operations on persistent objects. A version of the system written in C++ to run on networked UNIX systems was operational in the early nineties. The arrival of the Web and industrial acceptance of CORBA and Java technologies for distributed object computing during this period encouraged the productization of Arjuna. Through a series of acquisitions Arjuna became part of HP’s middleware product lines and was used in creating customised transactional services for new application areas, such as Web Services [2] and mobile computing. In 2002, we span out of HP to continue to evolve ATS, where it supports traditional ACID transactions and “relaxed” transaction models (e.g., compensation transactions). In this paper we shall give an overview its evolution, concentrating particularly on those changes concerned with improved performance and availability.
Multi-Stage Programming: Its Theory and Applications

MetaML is a statically typed functional programming language with special support for programgeneration. In addition to providing the standard features of contemporary programminglanguages such as Standard ML, MetaML provides three staging annotations. These staging annotationsallow the construction, combination, and execution of object-programs.Our thesis is that MetaML's three staging annotations provide a useful, theoretically soundbasis for building program generators. This dissertation reports on our study of MetaML's stagingconstructs, their use, their implementation, and their formal semantics. Our results include anextended example of where MetaML allows us to produce ecient programs, an explanation ofwhy implementing these constructs in traditional ways can be challenging, two formulations ofMetaML's semantics, a type system for MetaML, and a proposal for extending MetaML with atype construct for closedness.The dissertation consolidates a number of previous publications by the author, includingMetaML's type systems and big-step semantics. The presentation is new. The proposed solutionto an implementation problem and the reduction semantics for MetaML's three staging constructsare also new.
Computational Intelligence in Time Series Forecasting: Theory and Engineering Applications (Advances in Industrial Control)

Part I: Introduction Computational Intelligence: An Introduction Traditional Problem Definition Part II: Basic Intelligent Computational Technologies Neural Networks Approach Fuzzy Logic Approach Evolutionary Computation Part III: Hybrid Computational Technologies Neuro-fuzzy Approach Transparent Fuzzy/Neuro-fuzzy Modeling Evolving Neural and Fuzzy Systems Adaptive Genetic Algorithms Part IV: Recent Developments The State of the Art and Development Trends
Security and Privacy via Optimised Blockchain

Security of IoT devices and applications can be improved by using the emerging Blockchain Technology which uses decentralised interaction and scalable architectures with security and distributed trust. In this work a review of Lightweight scalable Blockchain is proposed for security and privacy of IoT devices. An IoT scenario of smart home is used for illustrative purposes but this proposed architecture is well-suited for diverse IoT applications. Effectiveness of this architecture is analysed using common threat models which provides an appropriate assessment for security and privacy implementation for smart home.
Biased Random Key Genetic Algorithm and Local Search To solve Overlapping Correlation Clustering

In Overlapping Correlation Clustering (OCC), a number of objects are assigned to clusters. Two objects in the same cluster have correlated characteristics. As opposed to traditional clustering where objects are assigned to a single cluster, in OCC objects may be assigned to one or more clusters. since an object can have characteristics that are correlated with objects in more than one cluster. In this paper, we present Biased RandomKey Genetic Algorithms for OCC. Computational experiments are presented.
Analysis of E-Commerce Backend Operations Data

Data analysis is the process of finding the analyzing data to find useful results for decision-making, understanding fundamental the data, discovering the significant pattern in the data. Analysis of e-commerce data (which includes guidelines details, record details, stuffing details, delivery details, etc.) involves scanning through the database and extracting data and probing pattern that can be helpful to the company in classify to get better their competence in the backend behavior like selection, superiority checks, packing and shipping. Such information obtained from analysis can provide insight into the various operations and can help the company to make informed decisions to speed up activities and ensure delivery in shortest possible time. The raw data from the various sources needs to be extracted, transformed and loaded into the data warehousebefore beginning the proper analysis on the data. This consolidated data is availableto run a series of patterns for knowledge discovery. In this paper, ETL process, architecture of a system involving Pentaho ETL tool for analysis of large e-commerce data sets and the final visualization of the analysis are discussed.
Technology Adoption by Groups: A Test of Twin Predictions based on Social Structure and Technological Characteristics

While the study of technology adoption by individuals and organizations has received considerable attention from researchers in the information systems discipline, little is known about how groups (an important social entity within organizations) adopt technologies. Drawing on past research in groups and technology adoption, this study proposes an “additive model” of technology adoption by groups, surrounding the “twin predictions” of the key social and technological factors. Specifically, the study examines the effect of the group’s social structure (e.g., influence of the majority and the high-status member), and the features of the technology (e.g., the technology’s complexity, transferability, and group supportability), on the group’s adoption of the technology. Further, the model also outlines the effect of the group’s adoption of the technology on the group’s performance. A laboratory experiment, where groups were given the choice of selecting one of two different technologies for performing a flowcharting task was conducted to test the model. Even though the empirical examination highlights the dominant effect of the technology characteristics, the study illustrates that this dominance is not an indication of the support of the “technological imperative” perspective, but is actually a testimony to the fact that “technology characteristics” is in fact a sociotechnical construct.
Using Conndence Interval to Summarize the Evaluation Results: a Case Study

Distributed Shared Memory(DSM) has gained popular acceptance by combining the scalability and low cost of distributed system with the ease of use of single address space. Many new hardware DSM and software DSM systems were proposed in recent years. In general, benchmarking is widely used to demonstrate the performance advantages of new systems. However, the common method used to summarize the measured results is the arithmetic mean of ratios, which is incorrect in some cases. Furthermore, many published papers showed a lot of data only, and did not summarize them eeectively, which confused users greatly. In fact, many users want to get a single number as conclusion, which was not provided in old evaluation methods. Therefore, a new data summarizing technique based on conndence interval is proposed in this paper. The new technique includes two data summarizing methods: (1) paired conndence interval method; (2) unpaired conndence interval method. With this new technique, we can say at some conndence that one system is better than others. On the other hand, with the help of conndence level, we propose to standardize the benchmarks used for evaluating DSM systems so that we can get a convincible result. Moreover, our new summarizing technique ts not only for evaluating DSM systems, but also for evaluating other systems, such as memory system and communication systems.
Shape-based Retrieval on a Fish Database of Taiwan

“Digital Museum/Library” is an ongoing project sponsored by the National Science Council of Taiwan. The content of this paper is partial result of one of its subprojects called `` Image content-based retrieval on a fish database of Taiwan. '' The objective of this project is to develop an image content-based search engine which can perform identity check of a fish. It is well known that conventional fish databases can only be retrieved by text-based query. In this study we shall use shape, color, and other features extracted from a fish to search the fish database of Taiwan. The developed technique is able to perform scale, translation, and rotation invariant matching between two fishes. Currently, the database contains several hundreds of fishes. In the future, we shall enhance the capability of the search engine to deal with more than 2,000 fish species, which is the total amount of fish species along the coast of Taiwan.