Miracle-dz/UniFAR-FTUs huggingface dataset:
Name Origin Recognition in Chinese Texts Based on Conditional Random Fields

Name origin recognition is to identify the origin of a name. In natural language processing, information of name origin is an important feature for name entity translation and question answering. Language identification of the origins of names can help to know what language-specific transliteration approaches to use. While some early work used two main methods, which are based on rules and statistics. In this paper, we use the conditional random fields (CRFs) model and view the task as a labeling problem on a sequence of words, taking advantage of the ability of using arbitrary features as input in CRFs under the character-based framework. Experimental results show that CRFs model is effective in recognizing origins of personal names in Chinese texts.
Innovations in learning technologies for English Language Teaching

Foreword Martin Peacock I remember as a fledgling teacher in the British Council teaching centre in Hong Kong listening to the Director of Studies giving a welcome speech to teachers at the start of the new academic year. The centre had begun investing heavily in computers and had just opened its 'Classroom of the Future' – a classroom with specially adapted furniture which gave students relatively painless access to computers built into desks. The Director of Studies was talking about the role of technology in the future of language learning and rather dramatically made his point by closing with the following epithet: 'The British Council needs teachers who are confident with technology. You are either into technology or you are in the way and had better start looking for a new job. ' Strong words indeed – and at the time quite a wake-up call for a number of teachers in the room who looked nervously around at their colleagues and no doubt made mental notes to get to grips with this new-fangled email malarkey. Times have changed, teachers have evolved, and we now have a new breed of learning technologists. As in Hong Kong, the first changes began in the classroom itself – new technologies such as overhead projectors, interactive whiteboards, laptop computers and wireless internet have opened up the classroom to the outside world. Teachers who spent their lives managing with a textbook, a tape recorder and a blackboard are now adept at using PowerPoint to present grammar, playing podcasts to practise listening skills, pulling texts off the world wide web to introduce reading skills and perhaps most groundbreaking of all – empowering students by giving them access to a wide range of web-based tools that allow them to publish work and engage with live audiences in real contexts. And that is just the beginning – because just as technologies have begun to change the way that English is learned in the classroom, even bigger changes seem to be taking place outside it. In fact, the digital revolution in learning now threatens to undermine the classroom completely as a place of study. Learning English through mobile devices gains credibility every day and the increasing popularity and rapidly diminishing cost of tablet devices reinforce this by providing a format that really is capable of delivering courseware. Factor in the growing interest in Massive Open Online Courses (MOOCs), providing large-scale (and …
Using mLearning and MOOCs to understand chaos, emergence, and complexity in education

In this paper, we look at how the massive open online course (MOOC) format developed by connectivist researchers and enthusiasts can help analyze the complexity, emergence, and chaos at work in the field of education today. We do this through the prism of a MobiMOOC, a six-week course focusing on mLearning that ran from April to May 2011. MobiMOOC embraced the core MOOC components of self-organization, connectedness, openness, complexity, and the resulting chaos, and, as such, serves as an interesting paradigm for new educational orders that are currently emerging in the field. We discuss the nature of participation in MobiMOOC, the use of mobile technology and social media, and how these factors contributed to a chaotic learning environment with emerging phenomena. These emerging phenomena resulted in a transformative educational paradigm.
Automated Metadata Extraction

Abstract : Metadata is data that describes data. There are many computer forensic uses of metadata and being able to extract metadata automatically provides positive forensic implications. This thesis presents a new technique for batch processing disk images and automatically extracting metadata from files and file contents. The technique is embodied in a program called fiwalk that has a plug-in architecture allowing new metadata extractors to be readily incorporated. Output from fiwalk can be provided in multiple formats such as ARFF and text. The plug-ins created for this thesis include one created by Simson Garfinkel for extracting metadata from . jpeg files, two for Microsoft Office documents (one for prior to Office 2007 release and one for Office 2007 release), and a default plug-in for extracting metadata from . gif, . pdf, and . mp3 files. To better understand the metadata available in common file formats such as . doc, . docx, . odt, . pdf, . mp3, . mp4, . jpeg, . tiff, and . gif, an examination of these formats is provided.
Differences in Phonological Recoding in German- and English-Speaking Children.

Orthographic consistency in different languages is likely to have an effect on phonological recoding skills, which are basic to the acquisition of reading. To explore this issue, we investigated word and nonword reading in German- and English-speaking 7- to 12-year-old children. Comparability of the stimuli across the 2 languages was strictly controlled: The German and English words used were common to both languages. Nonwords were derived by exchanging consonantal onsets between short words and by recombining syllables in long words. An identical set of CVCVCV nonwords was also presented to both language groups. At ages 7, 8, and 9, English-speaking children made a higher proportion of errors than their German-speaking peers when reading nonwords and words of low frequency. This was the case even when word-recognition ability was equated between the 2 language groups. By age 12, both groups had equally fast nonword-recognition latencies, but English-speaking readers were still less accurate when recoding.
Tomographic processing of spotlight-mode synthetic aperture radar signals with compensation for wavefront curvature

An algorithm is introduced which corrects for problems which arise in spotlight-mode synthetic aperture radar (SAR) when a significant amount of wavefront curvature is present. Wavefront curvature can be problematic when it is desired to reconstruct high-resolution images of ground patches which subtend a large angle at the radar. The proposed, non-Fourier, algorithm uses mappings to modify the convolution-backprojection method of computed tomography, providing reconstructions from circular-arc projections that are of the same high quality as those made from standard straight-line projections using the unmodified algorithm. In addition, other problems in high-resolution SAR imaging are identified which have solutions involving tomographic concepts, including situations which give rise to fan-beam-like projections. The new algorithm can be modified to deal with these problems as well. <<ETX>>
Empirical Analysis Of Open Source System For Predicting Smelly Classes

Software development plays an important role in software organization for high reliability and maintenance of the software. One such solution is refactoring that eases the code readability and maintainability. Refactoring is done by identifying bad smell areas in the code. An empirical model of object oriented software metrics is developed in this paper for prediction of bad smells. A binary statistical analysis presented here between metrics and bad smell which shows a significant relationship. Then a model is generated by using bad smell categorization. The proposed model is validated using dataset collected from jfreechart which shows that proposed model predict bad smell with high accuracy.
Adapted hedging

Exponentials of squared returns in Gaussian densities, with their consequently thin tails, are replaced by the absolute return to form Laplacian and exponentially tilted Laplacian densities at unit time. Scaling provides densities at other maturities. Stochastic processes with these marginals are identified. In addition to a specific local volatility model the densities are consistent with the difference of compound exponential processes taken at log time and scaled by the square root of time. The underlying process has a single parameter, the constant variance rate of the process. Delta hedging using Laplacian and Asymmetric Laplacian implied volatilities are developed and compared with Black Merton Scholes implied volatility hedging.The hedging strategies are implemented for stylized businesses represented by dynamic volatility indexes. The Laplacian hedge is seen to be smoother for the skew trade. It also performs better through the financial crisis for the sale of strangles. The Laplacian and Gaussian models are then synthesized as special cases of a model allowing for other powers between unity and the square. Numerous hedging strategies may be run using different powers and biases in the probability of an up move. Adapted strategies that select the best performer on past quarterly data can dominate fixed strategies. Adapted hedging strategies can effectively reduce drawdowns in the marked to market value of businesses trading options.
OntoUji–Ontology to Evaluate Domain Ontology for Semantic Web Services Description

Ontology evaluation has become an important aspect for selecting suitable ontology to be used within a system. User such as services provider has been proposed with variety of methodology to help in selecting ontology from the Web. Ontology has been used by service providers to describe the semantic part of their web services profile. Evaluating domain ontology for semantic Web services descriptions is currently in its early phase. Moreover the building of domain ontology itself requires greater attention because the ontological element for semantic web services description is not standardized in the current knowledge and thus requiring further refinement. There are studies conducted on transforming Web Services Description Language (WSDL) format into Ontology Web Language for Services (OWL-S) types of ontology to improve the services discovery. But since then, the ontologies were stored and retrieve locally, as well as ranked based on its history of selection or popularity. Criteria for ontology evaluation were then proposed to help users to select the suitable ontology to describe their web services description by achieving certain criteria measurement. By far, the users have problems because the current WSDL description does not signify the services profile. Hence, our study proposes an ontology called OntoUji, which will be used within the process of domain ontology evaluation to suit the required description of semantic web services.
Neuro-fuzzy identification and control of a chain of oscillators

During the last few years a very common question in the field of nonlinear complex systems mainly concerned how their dynamics can be detected, characterised, and particularly controlled. In this paper a fuzzy model of a forced damped nonlinear pendulum, identified by using the innovative soft-computing techniques, is proposed. Soft-computing, an innovative approach to constructing computationally intelligent systems, has just come into the limelight. The quintessence of designing intelligent systems of this kind is neuro-fuzzy computing. In the last section, the behaviour of a linear chain of identical obtained fuzzy systems has been investigated and the use of disorder as a means to control spatio-temporal dynamics has been explored.
The Effects Of Information Technology Innovativeness On Audit Efficiencies

Information technology (IT) has been identified as an important component of a company’s internal control and general business environment (COSO 2009). This paper examines how IT innovativeness can create value in the accounting domain through its role in improving efficiencies associated with the audit process by reducing overall inherent risks and business risks. To test the relationship between IT innovativeness and audit efficiencies, we use a sample of IT firms recognized by the publication InformationWeek as innovative users of IT and compare those firms with a control group. For the dependent variables measuring audit efficiencies, we focus on audit fees and audit delays. Our research suggests that firms recognized as IT innovators pay lower audit fees and receive their audit reports in a timelier manner than the control firms. Our results are consistent with the idea that investments in IT can provide significant benefits for firms in terms of audit efficiencies.
Runtime Evolution as an Aspect

We propose viewing the ability to update a system at runtime as an aspect, since it is a crosscutting concern. To show that the runtime evolution aspect can be developed separately from application development we have developed an implementation of such aspect using the language AspectJ. We describe our implementation of the aspect and limitations of the implementation.
Ensemble approach for clustering of interval-valued symbolic data

Ensemble approach has been applied with a success to regression and discrimination tasks [see for example Gatnar 2008]. Nevertheless, the idea of ensemble approach, that is combining (aggregating) the results of many base models, can be applied to cluster analysis of symbolic data. The aim of the article is to present suitable ensemble clustering based on symbolic data. The empirical part of the paper presents results simulation studies (based on artificial data sets with known cluster structure) of ensemble clustering based on co-occurrence matrix for symbolic interval-valued data, compared with single clustering method. The results are compared according to corrected Rand index.
Reliable Communication in Wireless Networks

Wireless communication systems are increasingly being used in industries and infrastructures since they offer significant advantages such as cost effectiveness and scalability with respect to wired communication system. However, the broadcast feature and the unreliable links in the wireless communication system may cause more communication collisions and redundant transmissions. Consequently, guaranteeing reliable and efficient transmission in wireless communication systems has become a big challenging issue. In particular, analysis and evaluation of reliable transmission protocols in wireless sensor networks (WSNs) and radio frequency identification system (RFID) are strongly required. This thesis proposes to model, analyze and evaluate self-configuration algorithms in wireless communication systems. The objective is to propose innovative solutions for communication protocols in WSNs and RFID systems, aiming at optimizing the performance of the algorithms in terms of throughput, reliability and power consumption. The first activity focuses on communication protocols in WSNs, which have been investigated, evaluated and optimized, in order to ensure fast and reliable data transmission between sensor nodes. The second research topic addresses the interference problem in RFID systems. The target is to evaluate and develop precise models for accurately describing the interference among readers. Based on these models, new solutions for reducing collision in RFID systems have been investigated
Performing Bayesian analysis in Stata using WinBUGS

WinBUGS is a program for Bayesian model fitting by Gibbs sampling. WinBUGS has limited facilities for data handling, whereas Stata has excellent data handling but no routines for Bayesian analysis; therefore, much can be gained by running Stata and WinBUGS together. This talk explains the use of the winbugsfromstata package, described in Thompson et al. (2006), a set of programs that enable data to be processed in Stata and then passed to WinBUGS for model fitting. Finally, the results can be read back into Stata for further processing. Examples will be chosen to illustrate the range of models that can be fitted within WinBUGS and where possible the results will be compared with frequentist analyses in Stata. Issues to consider when fitting models under Markov Chain Monte Carlo methods will be discussed including assessment of convergence, length of burn-in and the form and impact of prior distributions. J. Thompson, T. Palmer, and S. Moreno, 2006, Bayesian analysis in Stata with WinBUGS, The Stata Journal, 6(4), p530–549.
Wideband Gapfiller Satellite system support for the Global Hawk mission

The main purpose of this paper is to document the findings of a study tasked by the joint staff regarding the potential supportability of the Global Hawk (GH) high data rate requirements using the Wideband Gapfiller Satellite (WGS). The joint staff tasking was based upon an intelligence program decision memorandum (IPDM) tasking investigating options for the support of the Global Hawk unmanned aerial vehicle beyond line of sight requirements. DISA conducted the study with support from the Space and Missile Systems Center MILSATCOM Joint Program Office (SMC/MJPO) and from ARMYSpace the WGSSATCOM System Expert (SSE). SMC/MJPO provided the WGS payload specification as proposed by Boeing and ARMYSpace provided operational and technical input into the study. WGS will provide up to nineteen 125-MHz digital transponders to meet tactical user requirements. These segments can be flexibly connected between Ka and X-band and can route subsegments of these 125-MHz band segments between X- and Ka-band coverages. Analyses are based on Ka-band connectivity between the satellite and the Global Hawk platform, with hub to satellite connectivity at either Ka-band or X-band. In addition to bandwidth considerations, the analysis examines required power budgets and coverages expected to serve the Global Hawk mission.
An empirical study on the effectiveness of the greedy MUTP strategy

We propose the use of a greedy heuristic in finding a subset of test cases from the set of all unique true points so that it satisfies the multiple unique true points (or MUTP) strategy. Moreover we report an empirical study on the effectiveness of the greedy heuristic in finding a set of test cases that satisfies the MUTP strategy.
Local Feature Based Face Recognition

A reliable automatic face recognition (AFR) system is a need of time because in today's networked world, maintaining the security of private information or physical property is becoming increasingly important and difficult as well. Most of the time criminals have been taking the advantage of fundamental flaws in the conventional access control systems i.e. the systems operating on credit card, ATM etc. do not grant access by "who we are", but by "what we have”. The biometric based access control systems have a potential to overcome most of the deficiencies of conventional access control systems and has been gaining the importance in recent years. These systems can be designed with biometric traits such as fingerprint, face, iris, signature, hand geometry etc. But comparison of different biometric traits shows that face is very attractive biometric because of its non-intrusiveness and social acceptability. It provides automated methods of verifying or recognizing the identity of a living person based on its facial characteristics. In last decade, major advances occurred in face recognition, with many systems capable of achieving recognition rates greater than 90%. However real-world scenarios remain a challenge, because face acquisition process can undergo to a wide range of variations. Hence the AFR can be thought as a very complex object recognition problem, where the object to be recognized is the face. This problem becomes even more difficult because the search is done among objects belonging to the same class and very few images of each class are available to train the system. Moreover different problems arise when images are acquired under uncontrolled conditions such as illumination variations, pose changes, occlusion, person appearance at different ages, expression changes and face deformations. The numbers of approaches has been proposed by various researchers to deal with these problems but still reported results cannot suffice the need of the reliable AFR system in presence of all facial image variations. A recent survey paper (Abate et al., 2007) states that the sensibility of the AFR systems to illumination and pose variations are the main problems researchers have been facing up till.
Object-oriented programming in Eiffel

(Most chapters begin with an Introduction.) Introduction. Analysis. Types in Programming Languages. Specification. Modularisation. Using and Building Types. Building Types with Inheritance. Polymorphism. Exceptions. Programming by Contract. Language Requirements. Beginning Eiffel. How to Create Instances of a Data Type. How to Manipulate Objects. Initialization and the Basic Data Types. Classes. Executing Eiffel Programs. Practical Work. The Specification Of Abstract Data Types. Specifying Abstract Data Types. Classes And Features. Routines and Attributes. Classes and Data Hiding. Scope. Basic Input and Output. Practical Work. Eiffel Instructions. Assignment. Conditional Instructions. Loops. Practical Work. Storage Structures. The Class ARRAY. Linked Representation. Library Classes. Files. Practical Work. Expressions And Calls. Expressions. Calls. Practical Work. Semantics Of Abstract Data Types. The Constructive Approach. The Axiomatic Approach. The Client-Supplier Relationship. Correctness: The Client-Supplier Relationship. Correctness. The Client-Supplier Relationship. Verifying Program Correctness. Run-Time Monitoring of Assertions. Practical Work. Correctness: Programming By Contract. Categories of Program Error. The Client-Supplier Contract. Other Program Testing Facilities in Eiffel. Practical Work. Building Types As Subtypes. The Subtype Relationship. Implementing Subtypes in Eiffel Using Inheritance. Inheritance and Generic ADTs. Inheritance Issues. Practical Work. Adapting Inherited Features. Renaming. Changing the Export Status. Redefinition. Deferred (Abstract Classes). Joining. Undefining: Making Non-Effective. Repeated Inheritance and Adaptation. Practical Work. Polymorphism And Dynamic Building. Polymorphism. Polymorphism and Feature Redefinition. Dynamic Binding and Repeated Inheritance. Checking the Dynamic Type: The Reverse Assignment Attempt. Conformance. Type Problems with Polymorphism and Dynamic Binding. Practical Work. The Exception Mechanism. Trapping Exceptions. Principles Governing What the Rescue Clause Can Do. Information about exceptions: The Class EXCEPTION. Handling Exceptions. User-Defined Exceptions. Program Correctness. Practical Work. Client-Supplier Vs. Inheritance. Review of the Client-Supplier Relationship and Inheritance. Choosing Between Client-Supplier Relationship and Inheritance. Additional Features Of Eiffel. Expanded Types. Once Routines. Frozen Features. Building Libraries. Practical Work. A Case Study. The Application. The Database. the Commands. The User Interface. 0201593874T04062001
Real-time Caption Detection and Localization in TV Programs via Stroke Width Transform and Morphological Transform

Captions in TV programs are important clues for video content analysis, indexing, and retrieval. However, it is difficult to extract due to complex background, unknown caption color, etc. Nevertheless, caption detection and localization on its own is a hard task, let alone real time realization. In this paper, we propose a novel algorithm to extract caption from TV channel videos. Our proposed algorithm is composed of three steps: canny edge detection and binarization, simple stroke width transform, and histogram projection analysis. The experimental results show that the proposed method mentioned above is effective in real time TV caption detection and localization.