Miracle-dz/UniFAR-FTUs huggingface dataset:
ERP classification using empirical mode decomposition

Empirical Mode Decomposition (EMD) is applied to the problem of ERP classification for BCI. Artificial ERPs are created using a Neural Mass model assuming the additive model of ERP generation at different SNRs. Features are extracted from an EMDbased reconstruction and a Support Vector machine is applied to classify the ERPs. The classification method produced classification accuracies significantly better than chance for SNRs between 0 dB and -20 dB. Further, the EMD-based method produced significantly better classification than the conventional averaging method for SNR of -5 dB, -10 dB and -15 dB.
Bridging the gap between NLP and HCI: A new synergy in the name of the user

When usability became a major concern in system design, a dichotomy among visual and verbal language arose. Even if both interaction modalities were considered adequate to human capability [9], the past decades saw the dominance of the graphical approach. In this paradigm, the primary interaction style is Direct Manipulation (DM); verbal language is just a subordinated modality. Words or plain utterances (in the form of menus, error messages or icon labels) are used only when pictures and actions need to be disambiguated. This primitive form of Natural Language (NL) represents an asymmetric medium of communication, since verbal elements are meaningful only to the user.
Definição de Processos de Software em um Ambiente de Desenvolvimento de Software Baseado em Ontologias

Software process definition is not an easy task. It can be done in several levels, starting by defining a standard software process for the organization, specializing it to consider certain paradigm, software type or domain application, and finally tailoring the specialized standard processes to projects. Since it is a very complex, knowledge-intensive and error prone task, it is useful to provide automated tools to support it. In ODE, an ontology- based process-centered software engineering environment, there is a tool that supports this leveled approach for process definition. This paper presents an evolution of this tool and discusses the design rationale behind this evolution. Resumo. A definicao de processos de software nao e uma tarefa facil. Ela pode ser feita em diversos niveis, comecando pela definicao de um processo padrao para a organizacao, passando pela especializacao deste processo em outros processos padrao especializados para paradigmas, tipos de software ou dominios de aplicacao especificos, ate chegar a instanciacao de um processo para um projeto especifico, a partir de um processo padrao, especializado ou nao. Uma vez que esta e uma tarefa complexa, propensa a erros e que requer muito conhecimento e experiencia, e muito importante prover ferramentas automatizadas para apoia-la . Em ODE, um ambiente de desenvolvimento de software centrado em processo e baseado em ontologias, ha uma ferramenta que apoia essa abordagem em niveis para a definicao de processos. Este artigo apresenta uma evolucao dessa ferramenta e discute as razoes por detras dessa evolucao.
Using hand-held devices and pcs together

The age of ubiquitous computing is at hand with computing devices of different shapes and sizes appearing in offices, homes, classrooms, and in people’s pockets. Many environments contain embedded computers and data projectors, including offices, meeting rooms, classrooms [1], and even homes. One little-studied aspect of these environments is how personal, hand-held computers will interoperate with the desktop and built-in computers. More and more people are carrying around programmable computers in the form of Personal Digital Assistants (PDAs) such as a PalmOS organizer or Pocket PC (also called Windows CE). Cell-phones and even watches also are increasingly able to participate in the user’s computing and information environment. In the Pebbles project, we are researching the question of how the functions and the user interface can be spread across all of the computing and input / output devices that the user has available to form multi-machine user interfaces. In this way, the hand-held devices 1 can be used to augment the other
A Research Taxonomy for Latent Semantic Analysis- Based Educational Applications

Abstract The paper presents a taxonomy that summarises and highlights the major research into Latent Semantic Analysis (LSA) based educational applications. The taxonomy identifies five main research themes and emphasises the point that even after more than 15 years of research, much is left to be discovered to bring the LSA theory to maturity. The paper provides a framework for LSA researchers to publish their results in a format that is comprehensive, relatively compact, and useful to other researchers. 1 Introduction The major contribution of this paper is a taxonomy resulting from an in-depth, systematic review of the literature concerning latent semantic analysis (LSA) research in the domain of educational applications. The taxonomy presents the key points from a representative sample of the literature. Researchers and developers implementing LSA-based educational applications will benefit by studying the taxonomy because it brings to one place the techniques and evidence reported in the vast LSA literature. We realized the need for a taxonomy while building an LSA-based assessment system for use in computer science courses. Although our original assessment results were encouraging, they were not good enough for the intended task of summative assessment (Thomas, Haley, et al. '04). We conducted a comprehensive, in-depth literature review to find techniques to improve our system. The taxonomy documents our findings and supports the insights gained by studying the literature. There exists a great deal of literature on LSA. Some of it involves educational uses (Steinhart '01), some concentrates on LSA theory (Landauer & Dumais '97), and some of the newer articles
Mashup Ecosystems: Integrating Web Resources on Desktop and Mobile Devices

The Web is increasingly used as an application platform, and recent development of it has introduced software ecosystems where different actors collaborate. This collaboration is international from day one, and it evolves and grows rapidly. In web ecosystems applications are provided as services, and interdependencies between ecosystem parts can vary from very strong and obvious to loose and recondite. Mashups – web application hybrids that combine resources from different services into an integrated system that has increased value from user perspective – are exploiting services of the Web and creating ecosystems where end-users, mashup authors, and service providers collaborate. The term “resources” is used here in a broad sense, and it can refer to user’s local data, infinite content of the Web, and even executable code. This dissertation presents mashups as a new breed of web applications that are intended for parsing the web content into an easily accessed form on both regular desktop computers as well as on mobile devices. Constantly evolving web technologies and new web services open up unforeseen possibilities for mashup development. However, developing mashups with current methods and tools for existing deployment environments is challenging. First, the Web as an application platform faces numerous shortcomings, second, web application development practices in general are still immature, and third, development of mashups has additional requirements that need to be addressed. In addition, mobility sets even more challenges for mashup authoring. This dissertation describes and addresses numerous issues regarding mashup ecosystems and client-side mashup development. To achieve this, we have implemented technical research artifacts including mashup ecosystems and
Project-specific Machine Translation

Abstract : This report details a project-specific method for translating a book-length text. The method used a human-in-the-loop strategy to iteratively and incrementally produce a progressively more accurate statistical machine translation system. The system generated rough-draft translations of chunks of text that were post-edited by an expert translator. The method was used to produce a high-quality translation of the Army Field Manual (FM) 7-8 Infantry Rifle Platoon and Squad from English into the Afghan language Pashto. The results show that through a process of over-fitting, this method leads to systems that are optimized for aiding a single translator.
Predictive gate drive boosts synchronous dcidc power converter efficiency

Predictive Gate Drive is a novel digital control-driven technique that optimizes MOSFET turn-on and turn-off delays in synchronous rectifiers. It uses a closed loop feedback system to detect body-diode conduction, and continuously adjusts dead-time delays to minimize the conduction time interval. Depending upon operating frequency and output voltage, the Predictive Gate Drive control method can improve overall converter efficiency by two to four percent and the synchronous rectifier MOSFET power dissipation by 20 to 40 percent over currently available drive techniques. This paper compares this innovative new control technique to previous and currently existing related technologies. The problem of body-diode conduction is discussed and used to demonstrate efficiency improvements when the Predictive Gate Drive technology is applied.
Structural representations of unstructured knowledge

Knowledge should be represented in a formal, structured manner if we want to process and manage it. Unfortunately a source knowledge presented in many documents has informal, unstructured shape. The goal of these considerations is to present the methods of translation from the textual, unstructured knowledge to the structured knowledge, preserving textual form. Keywords— textual knowledge, knowledge representation languages, ontology.
The Antialiasing Problem in Ray Tracing

Ray tracing is one of the most general and powerful techniques for synthesizing realistic images. Unfortunately, this method suffers from a notoriously difficult problem with aliasing. This survey will consider why the problem is hard, several classes of solutions, and some of the issues that require further study. Before discussing ray tracing in particular, some general concepts of images and signals will be reviewed.
Dagda, a load-balanced middleware to distribute Complex Systems simulations

Resume—Complex systems which are modeled and are simulated in computer science become increasingly sophisticated. The computing power of a single machine becomes insufficient to execute these simulations. Therefore, it needs to exploit computing power of a set of machines. DAGDA, the architecture and the platform which are presented in this paper, offers a layer between simulation of a complex system and the available resources. This layer manages spreading of entities on machines to reduce work-load and network-load of each machine. Index Terms—middleware, dynamic load-balancing, complex systems simulations
Design and implementation of a validating XML parser in Haskell

This thesis introduces the core component of the Haskell XML Toolbox: a validating XML parser that supports almost fully the Extensible Markup Language (XML) 1.0 (Second Edition) W3C Recommendation [WWW01]. The thesis presents how a validating XML parser and XML processing applications can be implemented by using filter functions as a uniform design. The Haskell XML Toolbox is a collection of tools for processing XML with Haskell. It is itself purely written in Haskell. The Toolbox is a project of the University of Applied Sciences Wedel, initialized by Prof. Dr. Uwe Schmidt. The Haskell XML Toolbox bases on the ideas of HaXml [WWW21] and HXML [WWW25], but introduces a more general approach for processing XML with Haskell. It uses a generic data model for representing XML documents, including the DTD subset and the document subset. This data model makes is possible to use filter functions as a uniform design of XML processing applications. Libraries with filters and combinators are provided for processing this data model.
Dynamic bayesian networks for information fusion with applications to human-computer interfaces

Recent advances in various display and virtual technologies coupled with an explosion in available computing power have given rise to a number of novel human{computer interaction (HCI) modalities{ speech, vision-based gesture recognition, eye tracking, EEG, etc. However, despite the abundance of novel interaction devices, the naturalness and e ciency of HCI has remained low. This is due in particular to the lack of robust sensory data interpretation techniques. To deal with the task of interpreting single and multiple interaction modalities this dissertation establishes a novel probabilistic approach based on dynamic Bayesian networks (DBNs). As a generalization of the successful hidden Markov models, DBNs are a natural basis for the general temporal action interpretation task. The problem of interpretation of single or multiple interacting modalities can then be viewed as a Bayesian inference task. In this work three complex DBN models are introduced: mixtures of DBNs, mixed-state DBNs, and coupled HMMs. In-depth study of these models yields e cient approximate inference and parameter learning techniques applicable to a wide variety of problems. Experimental validation of the proposed approaches in the domains of gesture and speech recognition con rms the model's applicability to both unimodal and multimodal interpretation tasks.
Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.
Myphrase: Passwords from your Own Words

To improve manageability and strength of user-chosen passwords, we propose a multi-word password scheme called Myphrase. Contrary to the often-repeated but failed policy of banning common words as passwords, we encourage users to use words that are more personal to them—irrespective of the words being too common or esoteric. In Myphrase, a small dictionary is created from user-authored content such as sent emails and blogs. A master passphrase is constructed by randomly selecting words from the dictionary. We propose two variants as a trade-off between security and memorability; in random sequence, words are chosen uniformly across the dictionary, and in connected discourse, words are tagged using a part-of-speech engine and inserted appropriately into sentence templates. Words in the passphrase are expected to be easily recognizable to users and can be efficiently entered by leveraging the auto-suggest feature. Myphrase is designed to be compatible with both desktop and mobile platforms—a growing requirement for current authentication schemes. We create website-specific passwords from the master passphrase by salting the phrase with the site’s domain. To restrict offline attacks on the master passphrase from exposed site passwords, we require the passphrase to be of sufficient length (e.g., 6 words from a 1024-word dictionary, resulting in 60 bits of entropy in the random sequence variant). Entropy calculation for the connected discourse variant is less straightforward. We analyze Myphrase dictionaries and expected entropy of generated passphrases with two datasets: the Enron email corpus, and several popular books from Project Gutenberg. We also evaluate Myphrase using a recently proposed, slightly modified, framework of usability-deployability-security ratings, and seek feedback on our proof-of-concept prototypes available for both desktop and mobile platforms.
The construction of experience: interface as content

INTRODUCTION I’m an interactive artist; I construct experiences. Since the early 80’s I’ve been exhibiting my installations in galleries, trade shows, science museums, and public and private spaces. These exhibitions serve as a public research laboratory where my ideas about interaction and experience are tested, affirmed, or shot down. This is a condensation of the results of my free-form research.
A Tool-Suite for Simulating, Composing and Editing Timed Automata (LUSCETA: Users Manual Release 1.0)

In this paper, we present a tool for creating, edit ing, composing and simulating timed automata. The editor provides a means for creating different components, which are then composed together into an overall system. The mode l of the system can then be explored using our simulator, which gives fast results with a wide range of options available.
Predictive power conservation

In the case of a hard disk in a laptop, the restart cost is considerable: the disk has to be spun up to speed again, recalibratedl and made ready to execute commands. This takes between 2.5 and 6 seconds for typical 2.5" hard disk drives. During this time, the system is locked up waiting for the I/O to complete. The power costs are also high: on a representative Quantum 2.5" drive, spinningup the drive requires 5Wfor 1 second, followed by 1.5W for a 1 second calibration pass.
Gay L.A.: A History of Sexual Outlaws, Power Politics, And Lipstick Lesbians

The exhortation to 'Go West! ' has always sparked the American imagination. But for gays, lesbians, and transgendered people, the City of Angels provided a special home and gave rise to one of the most influential gay cultures in the world. Drawing on rare archives and photographs as well as more than three hundred interviews, Lillian Faderman and Stuart Timmons chart L.A. 's unique gay history, from the first missionary encounters with Native American cross-gendered 'two spirits' to cross-dressing frontier women in search of their fortunes; from the bohemian freedom of early Hollywood to the explosion of gay life during World War II to the underground radicalism set off by the 1950s blacklist; and, from the 1960s gay liberation movement to the creation of gay marketing in the 1990s.
Experiences in Implementing Measurement Programs

Abstract : Despite significant improvements in implementing measurement programs for software development in industry, data collected by Rubin Systems show that a large percentage of metrics programs fail. This technical note describes some useful lessons learned at a number of organizations that have implemented measurement programs using the Goal-Driven Software Measurement methodology. It includes a description of the methodology, a discussion of the challenges, obstacles, and their solutions, an initial set of indicators and measures, as well as some artifacts (such as templates and checklists) that we have found to enable successful implementations. The main motivation of this technical note is to provide some practical advice and guidelines for planning and implementing measurement programs.
IMPROVING DOCUMENT ACCESSIBILITY THROUGH ONTOLOGY-BASED INFORMATION SHARING

Information plays a crucial role in the entire life cycle of a product, i.e. from conceptual design through use and maintenance to eventual disposal. Once key personnel move on from a company, vital know-how may only exist in archived product documents, leading to great interest in ways of extracting readily sharable information from them. Studies have shown that knowledge workers spend appreciable amounts of their productive time searching for information online, and that those searches often prove unsuccessful. In addition, most engineers have difficulty in formulating effective query terms and current keyword-based searches are inefficient for helping them to select better queries. It is commonly argued that this problem can be solved by giving explicit definitions to the information through an ontology. Ontology-based information sharing has the potential to reduce the effort expended by engineers on retrieval and reuse of existing information. This paper presents an approach that extracts domain concepts from the documents based on an ontology definition. In particular, the applications of information extraction and document enrichment through engineers’ comments are discussed. The EDIT engineering ontology is described, and its role in improving document enrichment is presented.